Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
An in-depth look into the proposed tax on Bitcoin’s electricity input. This article was featured on Medium’s ILLUMINATION. Full article on Medium. -By Stephen Perrenod
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Inspired by the TOP500 list, biannual list of the most powerful cryptocurrency mining pools tracks compute power and economic value
Press Release
Menlo Park, Calif. – June 30, 2021 – PRLog — OrionX Research today released the sixth edition of its CryptoSuper500 list. The list recognizes cryptocurrency mining as a new form of supercomputing and tracks the top mining pools. Cryptocurrency technologies include blockchains, consensus algorithms, digital wallets, in addition to utility and security tokens. Cryptocurrency mining is a specialized domain of decentralized high performance computing (HPC). This dynamic, highly competitive, and rapidly growing industry has reached nearly $40 billion in annual economic value.
As of May 29th 2021, almost all the produced value is in three coins: Ethereum’s ETH coin, Bitcoin, and Dogecoin. While Bitcoin continues to represent the top spot in mining power, ETH produced the most mining revenue, aided by emerging applications that offer Decentralized Finance (DeFi) or manage Non-Fungible Tokens (NFTs).
“We present an overview of market forces and details of the top 45 pools for Ethereum, Bitcoin, and Dogecoin,” said Dr. Stephen Perrenod, OrionX Partner and Analyst and the developer of the CryptoSuper500. “Trends to watch include advances in ASIC-based and GPU-based mining rigs, the end of Ethereum mining, the trend of increasing electricity usage offset by increases in the green fraction of mining, and bans in certain countries that cause hash rate to move elsewhere.”
Cryptocurrency Supercomputing refers to large-scale cryptocurrency mining operations which are typically powered by accelerator technologies such as GPUs, FPGAs, or custom ASICs. Bitcoin is the most notable of such currencies. Cryptocurrency mining via Proof of Work is important since it represents the most effective consensus algorithm to maximize security in a decentralized manner.
The full list with additional explanation is available at OrionX.net/research.
About OrionX
OrionX is a Silicon Valley consulting firm offering Technology Research, Market Execution, and Customer Engagement services to high tech companies. More than 70 financial institutions and technology leaders in virtually every technology segment have trusted OrionX to provide advice, help set new break-away strategies, ignite brands, and grow market share. Visit us at OrionX.net.
* Note: This effort is an analysis of the technologies and trends surrounding blockchain and cryptocurrencies. It is not, and must not be considered as, financial, investment, or legal advice.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
One well known Macro guru says his hedge fund friends are pivoting to Ethereum from Bitcoin. Maybe it’s a trade, but what about for the longer term investor? Full article on Substack. -By Stephen Perrenod
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Has Dark Matter been converted to X-rays in Neutron Star magnetic fields? Many people have heard of neutrinos (little ‘neutral ones’). But there is another dark matter candidate, never observed in the laboratory, which would have a mass much less than even the three known neutrinos. And is less well known than neutrinos. Full article on Medium. -By Stephen Perrenod
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Money is a universal intermediate good used as a form of wealth. People use it as the connector between other goods and services, and as a way to resolve debts. The first well-documented money was accounted for in Babylonian temples in the form of barley. You see already from this, that money has aspects of virtuality, and it has a definition as an accounting unit as well as serving as a medium of exchange and a store of value for delayed usage. Full article on Medium. -By Stephen Perrenod
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Bitcoin has survived many errors, shocks, and even splits from the main branch of its evolutionary tree. It has been declared dead by journalists and fiat economy wise men and women some 380 times. But these events, concerns, or self-interested attacks have not stopped Bitcoin. It keeps getting stronger, and every 10 minutes the security of all prior transactions is enhanced. Bitcoin is now functionally eternal, certainly positioned to survive beyond the year 2100. Full article on Medium. -By Stephen Perrenod
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Today is Block Year 12, and within the year it is Block Month 5, Block Day 137
Bitcoin Generates Its Own Calendar
Our Gregorian calendar is based on the Solar year, the Lunar month, and the Terrene (Earthly) day. Bitcoin has its own natural calendar that can be constructed to approximate our human calendar of years, months, and days.
But the details are a bit different, and since Bitcoin is a dynamic process built around the construction of blocks, block count, not regular calendar time, is the most relevant and precise way of looking at the passage of time in the Bitcoin context.
Bitcoin’s fundamental process driver is the construction of a chain of blocks. Blocks are created one at a time and chained together in a time chain, or blockchain. That process and the ever-growing chain drives Bitcoin’s security and its value. The value comes both from security and scarcity, and the money supply is created on a per-block basis, via a block reward for the winning miner.
The block count is the clock. It is the system’s heartbeat. Bitcoin has its own clock that has a rough correspondence with wall clock time. Yet it has its own cycles, years, months and days of somewhat different and varying duration from regular time but with an approximate correspondence.
I now describe a natural Bitcoin calendar system, based on the block length at the short end, the difficulty adjustment in the mid-range, and the Halving cycle at the long end.
We designate block height or block number by variable B.
The first year is designated Year 1, Anno Satoshi, 1 A.S. and it originated with the first block B = 1 that was completed on 9 January 2009.
Block Year, Block Month, Block Day And More
So now let’s look at the Block Era, Block Year, Block Quarter, Block Month, Block Fortnight, Block Week, Block Day, Block Hour, and Block Minute. They are roughly equal to our familiar calendar and time intervals, but not precisely.
Bitcoin is a dynamic process creating blocks approximately, but not exactly, every 10 minutes. So BlockTime will deviate from wall clock time. There is a self-correcting process within the Nakamoto consensus algorithm that is called the difficulty adjustment, and which occurs every 2016 blocks; this is approximately every two weeks of wall clock time. Increasing or decreasing the difficulty regulates the block interval back toward 10 minutes’ duration.
The block duration and the difficulty adjustment are two of our pegs for the Bitcoin calendar system.
The most important aspect of Bitcoin’s monetary policy are the Halvings, which occur every 210,000 blocks. The block subsidy (mining reward) is cut in half after each 210,000 blocks, which also roughly equals a four-year period.
The formula for Bitcoin supply creation and Halvings, denominated in Satoshis (each Bitcoin contains 100 million Satoshis). The original reward was 50 Bitcoins with Blocks 1 through 209,999 and then cut to 25 Bitcoins from Block 210,000 through 419,999 and so forth.
No need to memorize the formula!
Formula for Bitcoin supply, with 32 Halvings at each 210,000 blocks
No need to memorize the formula!
Block, Difficulty, Halvings Define The Calendar
So these three pegs of a block (Earthly: around 10 minutes), difficulty adjustment (Lunar: around two weeks), and Halvings (Solar: around four years) allow us to define a Bitcoin calendar system.
The calendar begins with B=1 on January 9, 2009, and that initiates the Age of Satoshi. Years are rendered as A.S. (Anno Satoshi), counting begins at year one. We are now in the 12th BlockYear, the last year of the third Reward Era.
Months and weeks are numbered from 1 to 12 and from 1 to 52, respectively, within a year. Like the Gregorian calendar, there are precisely 12 months, but the calendar has slightly more than 52 weeks.
It is easy to determine the natural rhythm of the Bitcoin calendar. Rows in italics are the three pegs we build the system around.
Solar
Block Century = 5,250,000 blocks (25 Eras, 100 Block years)
Block Era (Cycle, Reward Era) = 210,000 blocks
Block Year = 52,500 blocks (one-quarter of a Block Era)
Block Quarter = 13,125 blocks (one quarter of a Block Year, or three Block Months)
Lunar
Block Month = 4375 blocks (1/12 of a Block Year, and unlike Gregorian calendar, all of the equal length)
Block Fortnight = 2016 blocks (the difficulty adjustment period, and two Block Weeks)
Block Week = 1008 blocks (52 weeks plus a bit in a year, not unlike the Gregorian calendar)
Terrene
Block Day = 144 blocks (1/7 of a Block Week, 24 Block Hours)
Block Hour = 6 blocks (nominal block time is 10 ordinary minutes)
Block Minute = 0.1 blocks
We can refer to these either as BitYear, BitMonth, BitWeek, BitDay, BitHour, etc.,
We will see what the community gravitates toward. And in either case the abbreviations can be:
Solar: BCentury, BEra, BYr, BQ
Lunar: BMo, BFort, BWk
Terrene: BDay, BHr, BMin
Here are the formulae for the longer intervals
BCentury = int(B/5,250,000)+1
BEra = int(B/210,000)+1
BYr = int(B/52,500)+1
Within a given year, the quarter and month number are given by:
BQ = 1 + int (B/13125) — 4 * (BYr — 1)
BMo = 1 + int (B/4375) — 12 * ( Byr — 1)
One good thing is that we have no leap years, although there are definitely parties at each 4 BlockYear intervals for Halving Day.
The BlockYear has 52 weeks plus an extra short day of 84 blocks (14 BlockHours). It also has exactly 12 BlockMonths. The BlockMonth has 30.382 days, or 30 days plus a short day of 55 blocks (9 BlockHours and 1 additional block).
Example: Block #596323 on 24 Sep 2019–09–23 07:53:57 UTC
and the block corresponds to the 10th fortnight, the 19th week, and 131st day of Byr 12.
A More Accurate Basis For Analysis
I suggest that it is much more natural, appropriate, and accurate to do price, market cap, hashrate, transaction value and other studies on a Bitcoin Calendar basis, in order to examine correlations and co-integrations of these quantities with a time-related variable.
The results can then be converted to regular Gregorian calendar time after the analysis for presentation purposes.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Today, June 14, 2019, we released the second biannual list of Top 50 cryptocurrency mining pools.
We do this in conjunction with the Top 500 supercomputing list that is released twice a year, in June and November. That list has been a matter of national pride for the US, Japan, China, and many other countries.
Cryptocurrency mining is a specialized form of supercomputing, producing billions of dollars of economic value per year.
In the Information Age, money has become information. Bitcoin is energy converted to information and encapsulated as secure immutable transactions on a time chain. This is money in the Internet, that we call Money 3.0. Currently it is primarily a store of value, a sort of digital gold, but it continues to grow use cases as a medium of exchange, and unit of account.
Cryptocurrency mining operations are large-scale, run on clusters, but also consist of highly decentralized pools that anyone can join and contribute their equipment to the effort, for proportionate rewards. Most mining is done on custom ASIC computing rigs, highly optimized for the relevant crypto consensus algorithm.
Using statistics readily available on the hashing rates and block production rates for the large mining pools, we can tabulate the economic value produced by these pools.
We consider only mined coins, that is, those that use some type of Proof of Work algorithm such as Bitcoin’s Nakamoto consensus.
We do not consider coins created with other types of consensus mechanisms, since they require no significant supercomputer-class computation. This includes coins produced through premining, Proof of Stake, distributed Byzantine Fault Tolerance and the like since supercomputing resources are not involved.
While there are a number of lists that provide hash rates and block production rates for pools mining a single coin, our lists are the first aggregation of which we are aware.
This raises the question as to how to compare mined coins that have radically different hashing rates and whose consensus algorithms, although often similar to Bitcoin conceptually, differ in the details.
We settled on the economic value of the mined coins that are produced. This enables us to make comparisons across coins when rank ordering the list of mining pools.
We compare the dollar value of a day’s mining from a given pool, with that of other pools, across the top eight mined cryptocurrencies.
The top 10 mined coins have market caps above $0.5 billion dollars, and the #1 coin, Bitcoin, as of our snapshot taken on May 30, 2019, had a market cap of $154 billion.
When we rank order the top 50 mining pools we find that the top eight mined coins in economic value are: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Bitcoin Cash (BCH), Zcash (ZEC), Bitcoin SV (BSV), Dash (DASH), and Monero (XMR). All of these except Monero are ASIC-friendly, and production is dominated by ASIC miners and clusters. Monero relies on GPUs.
For Bitcoin, Ethereum, and Litecoin we have used 30 day averages as of May 30, 2019 for block production and hash rates; for the other coins 7 day average data was available.
Table 1: Top 8 Mined Coins (all mining pools, not just Top 50)
Coin
Hardware class
Algorithm
New coins / day
Hash Rate
Hash units
Price 5/30/2019 US$
Economic Production per Day, Million $
Extrapolated Annual Production Million $
Bitcoin
ASIC
SHA256
1800
47.1
Exa
8701
15.662
5,717
Ethereum
ASIC
Ethash
13,600
172
Tera
284
3.862
1,410
Litecoin
ASIC
Scrypt
14,825
352
Tera
117.6
1.743
636
Bitcoin Cash
ASIC
SHA256
1800
1.36
Exa
469
0.844
308
Zcash
ASIC
Equihash
7200
4
Giga
86.9
0.626
228
Bitcoin SV
ASIC
SHA256
1800
2.03
Peta
222
0.400
146
Dash
ASIC
X11
1693
1.68
Peta
172.2
0.292
107
Monero
GPU
CryptoNight
1934
329
Mega
95.1
0.184
67
Totals
23.61
8,619
From Table 1above, which is across all pools, not just the Top 50, we see that total annual economic value run rate (extrapolated from the recent average daily values) is about $8.6 billion. About 2/3 of the economic value created is from Bitcoin production alone, with about $15 million produced per day recently. Ethereum amounts to around one-quarter of that at almost $4 million per day. The next six coins add another $4 million daily. Overall around $24 million per day is currently being mined from all pools.
The locations of top mining pools can be multi-country. The next Table summarizes the major host countries for the Top 50 pools; China, the US, and Hong Kong account for 70% of the top 50 pools and almost all of the top 10 operators. China alone is responsible for nearly half of the annual value produced by the Top 50 pools. The Mixed category includes various combinations of US, China, the EU, Russia, or other Asian or European countries. This category has grown as Chinese operators begin to move to other geographies, as a result of pressure from the government to constrain cryptocurrency mining in China.
Table 2: Host Countries, Top 50 Pools
Country
# Top Pools
Daily M$
Annual M$
China
18
10.717
3911.7
US
11
4.77
1742.5
Hong Kong
6
2.77
1009.6
Mixed
12
2.69
980.4
Other
3
1.18
430.0
Totals
50
22.12
8,074
Table 3: Top 10 Pool Operators (aggregated across coins)
MultiPools
Coins
Number
Daily M$
Annualized M$
Country
BTC(dot)com
BTC, BCH
2
3.06
1115
China
F2Pool
BTC, ETH, ZEC, BSV, LTC
5
2.76
1007
China
Antpool
BTC, LTC, ZEC, BCH, DASH
5
2.38
868
Hong Kong
Poolin
BTC, ZEC, LTC, BSV
4
2.26
825
China
SlushPool
BTC, ZEC
2
1.62
592
US
BTC.Top
BTC, LTC, BCH
3
1.47
537
China
ViaBTC
BTC, LTC,BCH
3
1.34
488
US
Huobi.Pool
BTC, ETH
2
0.69
251
China
NanoPool
ETH, XMR
2
0.50
182
US, EU, Asia
Bitcoin(dot)com
BTC, BCH
2
0.34
124
US
Totals
30
16.41
5,990
We have aggregated, for the top 10 operators, their results across all of the top eight coins, and summarized in Table 3 above. Some operators mine two different coins, others mine as many as five of the top eight. These pools account for, when broken out by coin, 30 of the entries in our Top 50 list.
The #1 operator is BTC.com based in China, and it produces $3 million a day of economic value. F2Pool, Antpool, and Poolin each produce over $2 million of cryptocurrency per day. Theselarge operators are responsible for $6 billion of the $8 billion annual production by the top 50 pools. Three of the five largest operators are in China, one is in Hong Kong, and one is in the US.
The winners in this race, for this second list, are Bitcoin, naturally, with BTC.com again as the top pool, and China as the host country for the most top mining pools, including both #1 and #2 positions. Hong Kong has the #3 pool. The US has the second largest number of mining pools.
The economic value of mining has increased substantially. In the first list of November, 2018 we looked at the Top 30 pools, responsible for some $5.5 billion of annual run rate of mining. This new list of Top 50 pools indicates $8.1 billion of annual cryptocurrency creation (even the Top 30 for this list amounts to well over $7 billion).
We intend to update this list again in November, 2019. Suggestions and comments may be sent to: stephen.perrenod@orionx.net
A presentation with the full Top 50 list is available at SlideShare.net:
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
An article in Barron’s written by Ben Walsh on Valentine’s Day is titled “JPMorgan Just Killed the Bitcoin Dream”.
JPMorgan Chase has announced an altcoin, a stable coin, for use by institutional customers. It will be tethered to the US dollar.
This development is the first such stable coin issued by a US bank. So that is noteworthy. And no doubt it will be useful in expediting transactions for corporate clients. But this is no Valentine’s Day Massacre of cryptocurrencies, no murder of Bitcoin, with its $63 billion market cap.
The major use cases envisioned are (1) securities settlement, (2) international payments processing, and (3) cash management for corporate subsidiaries. It is designed to increase speed and efficiency for these cases, and add flexibility in the cash management case.
Bitcoin does not put faith and trust in JPMorgan, the trust comes from the mining process. In that process, hashing algorithms encapsulate value and security, as transactions in validated blocks. These blocks are widely decentralized and replicated across the Internet.
Bitcoin already allows anyone, retail users as well as corporate clients, to send value across the globe in an hour or less, with fees less than a dollar. The Lightning Network second layer to Bitcoin allows even the tiniest transactions at extremely low cost.
So why use or trust JPMorgan’s coin? After all they have paid over $29 billion in fines and penalties for banking violations since 2000. It seems unlikely that the JPM coin would ever reach even that total valuation, since it is created and then destroyed after transactions have completed.
Retail users won’t have access to the JPMcoin. Actually if they want a dollar-tethered stable coin, there are already a slew of alternative coins for that, today. Perhaps in some distant future, JPMorgan would consider entering the retail stablecoin space.
Certainly for some corporate customers there will be a degree of convenience and familiarity with their existing banking relationship. And banking is ultimately all about trust.
In the immediate term, this coin might be a significant competitor to Ripple and its XRP, another centralized altcoin that has found traction in the international banking payments market. XRP is the third most valuable by market cap, after Bitcoin and Ethereum.
Bitcoin will be around at least until 2140, when the new coins issued as mining rewards have stopped, and after that it will be solely supported by transaction fees in what is already a trillion dollar economy, and growing. We cannot be as certain about the longevity of JPM’s new coin.
A privately issued stablecoin is nothing like Bitcoin. Let’s check in on Valentine’s Day 2020.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Suppose Bitcoin could scale. Many altcoins were created in the promise of handling more transactions, and with lower fees.
But Bitcoin can scale, and it will, thanks to the Lightning Network which went live in 2018. While small, it is growing rapidly.
Bitcoin is often criticized for lack of scalability, relative to traditional credit card, debit card, and mobile-based payment solutions. Currently it is capable of about 7 transactions per second onto the blockchain, whereas the Visa network can handle tens of thousands of transactions per second.
The implementation of Segwit, separating signature information, has allowed additional transactions to fit within a single block of the blockchain. Segwit was implemented as a soft fork in 2017 and nearly half of transactions currently use Segwit.
Other proposed solutions have included larger block sizes, but these have required hard forks leading to new coins. The overwhelming majority of hash power and of market cap have remained with original Bitcoin.
Bitcoin is in fact worth more than all 2000 plus altcoins combined.
There are many other approaches to scaling implemented by other cryptocurrencies desiring to address the scaling problem. These include non-ASIC friendly mining algorithms, and a variety of consensus algorithms that eschew mining, such as Proof of Stake, and Byzantine Fault Tolerant protocols more generally.
The second most egregious method is the airdrop, the “helicopter money” of the cryptocurrency world. This tends to be worth, in the long run, close to what you paid for it. The most egregious of all is premining, where insiders reward themselves first, while selling a ‘utility token’ that currently has no utility, and may never have, to others in an ICO.
The problem with these easy money solutions is that they can push up transaction rates greatly, but at an enormous sacrifice in security. You want fast transactions, just lower hash difficulty in mining, or eliminate it. Lower difficulty means lower security. And thus, it sacrifices the store of value aspect of their currency. (Think Venezuela or Zimbabwe).
If you want to conduct large numbers of low value transactions, that may be fine. If you lose your Starbucks card, do you worry about replacing it? Probably not. With a credit card, it’s different entirely.
The solutions described above, such as block sizes and different forms of mining or consensus algorithms, are on-chain solutions. The transactions are all on some “original” chain (which may have been a hard fork from Bitcoin).
An alternative way is to keep the Blockchain very secure, but then add off-chain scaling.
What: Payment Channels
Lightning is such an approach with Bitcoin, building payment channels that can handle many transactions within that channel. At some future date, the consolidated transfer of value for the channel is committed as a blockchain transaction.
Back to our Starbucks card. The card accepts fiat currency of a given amount and then is used as a payment channel until the funds are exhausted over some number of days as a result of your mild coffee addiction. The card, or payment channel, can then be topped up with funds added back into the channel.
Wikipedia has a good definition for the Lightning Network as a second layer payment protocol: “It features a peer-to-peer system for making micropayments of digital cryptocurrency through a network of bidirectional payment channels without delegating custody of funds.”
One opens a channel with another party and each makes a funding transaction on the blockchain to establish the channel. The channel can then be used for a series of ‘micropayments’ (not necessarily small, but smaller than the funding amount in the channel) that are handled within the payment channel.
After a few, or very many transactions, the channel may be closed out by either party and the net aggregate balance transferred is recorded onto the blockchain.
For example if I put in 0.3 Bitcoin initially, and you put in 0.2, the channel was opened with 0.5 Bitcoin total. You and I make a series of Lightning-based transactions, possibly all in one direction. (We’ve been betting on the price of Bitcoin at the end of each month, say).
Let’s also say we agreed to close the channel at the end of the year. And suppose, netted out overall, I sent you 0.2 Bitcoin over a number of transactions. In closing the channel we would commit the final balance in a blockchain transaction showing that you now have 0.4 Bitcoin of the original 0.5, and I now have just 0.1 Bitcoin. That closing transaction gets recorded on-chain.
If we wanted to continue to exchange, we would open and fund a new payment channel.
There is fraud protection; each party can monitor transactions over a chosen time interval. The party in error can lose (to the counterparty) their funding transaction or more.
The Bitcoin blockchain is highly innovative triple entry accounting (you, me, and the blockchain keep records) whereas the Lightning Network uses good old-fashioned double entry accounting (you, me).
How: It’s not just Channels, it’s a Network of Channels
The Lightning Network is more than just a set of disconnected bidirectional payment channels, it is a network of richly connected payment channels. Suppose Lionel wants to send a payment to Linda, but they have no direct channel established.
If they each have a channel established with Lee, they can route the payment through him as an intermediary and he may collect a small fee.
Or they can route through several unknown intermediaries. The network will tend to develop hubs with many connections and larger funding amounts, including commercial enterprises.
Representation of current Lightning Network early January 2019
Rapid Progress
As of early January 2019, the Lightning Network looks like the above image. There are 15,000 channels and almost 500 nodes. The carrying capacity is modest at $2 million presently, but the growth is exponential. The node count grew a factor of 4 in the month of November alone!
Who: Enabling software and Payment processors
Applications built on the Lightning Network are referred to as LAPPs.
There are several payment processors that merchants can use to enable receipt of Bitcoin payments via Lightning. These include BTCPayServer, CoinGate, GloBee, OpenNode, and Strike.
Implementations of Lightning Network Software include Lit from MIT Media Labs, LND and Neutrino from Lightning Labs, and Blockstream’s c-lightning.
The Future
The Lightning Network has the ability to go places that Visa, MasterCard, and PayPal cannot reach by enabling micro-transactions across the globe with extremely small fees. It is fraud resistant and has rapid verifiable transfer of the most secure cryptocurrency on the network layer, with eventual settlement onto the blockchain.
As a proof point, a work of art known as Black Swan was recently sold at auction to the < Low > Bidder for only 0.001 Satoshi or 4 millionths of a cent. (A Bitcoin is divisible into 100,000,000 Satoshis).
Another, more typical transaction and proof point was established at an Australian car wash with a transfer of over 1,000,000 Satoshis or about $40 US.
You wanted to buy coffee with Bitcoin? Now you can.
(The gory details: “The Bitcoin Lightning Network: Scalable Off-Chain Instant Payments” J. Poon and T. Dryja, 2016 https://lightning.network/lightning-network-paper.pdf)
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Recently the International Monetary Fund produced a research report on Central Bank Digital Currencies, titled “Casting Light on Central Bank Digital Currency”, and available here:
Even the title is interesting in its omission of the terms cryptocurrency and blockchain.
The basic concept they were evaluating was that of central bank controlled digital currency issued for the benefit of retail users (individuals and non-banking businesses). These would exist alongside existing fiat currencies and be intended for domestic use primarily. Their value would have to be tethered to the related fiat.
The study reached several initial conclusions:
* CBDC could be the next milestone in the evolution of money.
* It is a digital form of fiat money, issued by the central bank.
* The ability to meet policy goals is one major issue.
* The demand for CBDC depends on the attractiveness of alternatives (cash, e-money).
* The case for adoption could vary from country to country.
* Appropriate design and policies should help mitigate risks.
* Cross-border usage would raise a host of questions.
Many Central Banks are Studying
A number of central banks around the world are studying CBDCs. This table from the IMF report indicates their publicly stated rationales, which include diminishing use of cash as other payment channels e.g. mobile become popular, efficiency gains for payment and settlement, and greater access for the unbanked or lightly banked to financial services.
But the key point is that CBDCs are quite antithetical to Bitcoin and mined cryptocurrencies in general (we exclude in this comparison airdrops, premined, and other largely centralized, but private, forms of cryptocurrency). CBDCs are closest to the tethered cryptos, but maintained by the fiat issuing authority itself.
Cryptocurrency
CBDC
Created by ‘miners’ running hashing protocols
Created by central bank
Predefined monetary policy
Variable monetary policy set by central bank committee
Transnational usage
Domestic usage primarily
Open triple entry ledger
Central bank permissioned ledger
Validation by private computer nodes
Validation by central bank
There is very little in common between Bitcoin and mined cryptocurrencies in general, and hypothetical CBDCs. Most existing fiat is already digital; a small portion is cash.
Disintermediation of Banking Balances
The main new alternative, besides existing fiat cash, for CBDCs are private payment channels (private e-money) such as PayPal and M-Pesa in Africa. These are similar to stored value cards with prepaid fiat balances, but with mobile interfaces. Here the account balances are managed by private companies, usually with a known partner, and a user needs to trust the company holding the balance.
Both new private money channels and CBDCs threaten to disintermediate balances held in bank checking and savings accounts. So do cryptocurrencies, of course.
These balances are used as reserves for banks to issue loans, so if they were moved to a cryptocurrency or a central bank ledger they are no longer available for lending (fractional reserve banking).
A fundamental difference is that cryptocurrencies are assets whereas fiat money is debt-based, created when banks issue loans. CBDCs in their basic form are not available as reserves for bank lending.
CBDCs would in essence just be a different form of fiat, tethered to fiat, and with the same accounting unit and value.
Cryptocurrency represents a challenge to the banking system and to central banks. It seems that the IMF may be encouraging central banks to sacrifice the interests of banks in order to maintain, and even increase, their own power.
Central Banks could Consolidate Power
The CBDC framework, like cryptocurrency, would move deposits away from the banks. Unlike cryptocurrency, which holds balances on an open ledger, accessed by private keys, CBDC balances would be held for individuals and businesses at the central bank. This means the central banks would be able to restrict access to funds owned by individuals. One can assume they would do this during crises or under court order.
Central banks could even apply interest to CBDC deposits, possibly even with negative interest rates during times of slackened growth.
Fractional reserve banking and the economy as a whole are based on the provision of credit by commercial banks, backed only by a small percentage of reserve balances held with the central bank. If deposits move in large amounts to CBDCs or cryptocurrencies, both of which are assets in the name of the depositor, the system of credit provision in the economy will have to be significantly transformed.
Or a system that allows banks to participate and hold reserves based in CBDC would have to be developed.
CBDCs of the simplest type discussed in this IMF paper seem like a way to protect the prerogatives and increase the power of central banks, and co-opt cryptocurrency. The losers would be traditional banks because their lending power would be decreased.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
The idea that bitcoin will consume an enormous fraction of the world’s electricity is hysteria.
In a recent article in the Communications of the Association for Computing Machinery, June 2018 issue, Nicholas Weaver (a lecturer in computer science at UC Berkeley) raised this issue, in what was otherwise a good article on the security issues around bitcoin.
Weaver quotes a statistic that cryptomining consumes more electricity than Ireland. This may be based on digiconomist.net, which runs toward the high end. Other estimates are only half as large.
He states “If there is profit in mining, the miners will keep using more and more power until there is no more excess profit available”.
This is true, but he overstates things. He evidences a lack of basic understanding of economics and how businesses operate, ignoring all the complexities that go into cryptomining.
Mining costs are a combination of fixed, and variable costs. The variable cost is primarily the electricity consumed. The fixed costs consist of facilities costs, equipment costs, and people and administrative costs. Equipment costs can run over 1/4 of the total.
Total global Hash rate over the past 12 months has grown from 5 to 38 Exahashes, a factor of 7.5.
Difficulty in the Nakamoto consensus protocol has grown by a factor of 7.
Revenue per Terahash per day grew from $1 to $3+ at the peak half a year ago and with the price collapse is down to $0.30. That is before electricity.
According to cryptocompare.com, with the current BTC price of $6500 and at $.10 per kWh for electricity the profit is just $0.06 per Terahash-day currently, but that is before any of the fixed costs are recovered.
If you are not covering your fixed costs plus variable costs you will not stay in business to consume electricity.
Here’s where Weaver really gets it wrong. He states “a 10x reduction in power consumption per hash for Bitcoin mining would have little real effect on Bitcoin’s power consumption. Instead, there would just be 10x as many hash computations needed to produce a block.”
Difficulty rates depend on the total cost burden.
His statement above completely ignores fixed costs. Whether it is an individual mining rig or a huge mining farm, the fixed costs of location, equipment and labor will generally be of order half the total cost.
Do-it-yourself miners in Mom’s basement or my friend Dan might ignore their location costs and equipment burden on their cooling and they might give away their labor for free. But their rigs aren’t as efficiently operated and their electric costs may be higher. They still have to amortize their equipment costs, at least for added ASICs and GPUs.
Suppose the gross revenue is $0.30 per THash-day and the fixed costs can be held to $0.10 and the electricity cost is $0.2. This is a breakeven business example with a large electricity burden.
Now reduce the power consumption per hash by 10x, in which case the total costs drop from $0.30 to $0.12. There would be incentive to increase total hash power by up to 2.5x not 10x. A factor of 4 overestimate.
In practice, it takes time to ramp up hash power. Supplies of equipment are tight. Data center spaces are limited. System administrators are not always available. There are both practical and regulatory restrictions on power available to mining farms.
Furthermore, ASICs and GPUs for Bitcoin and cryptocurrency mining are in particularly tight supply. As demand goes up, there is a bidding war with equipment going for premium prices. This drives up the fixed cost component of Bitcoin mining.
Doubling capacity takes many months, and is subject to financial planning scenarios about future crypto prices, equipment delivery time lags, and electricity prices and availability.
According to digiconomist.net on July 5th, Bitcoin is just 1/3 of 1% of global energy usage (1 part in 300). Global GDP is some $80 Trillion and annual transaction flows of Bitcoin are over $1 trillion. So for over 1% of the proportional GDP the related energy requirement is proportionally 3 times lower.
According to an article in ZeroHedge, gold mining is much more energy costly. Per $ of value produced bitcoin and gold are roughly comparable, but there is a lot more gold mined.
Spillway of Robert-Bourassa generating station, author: fargomeD, CC BY-SA 3.0
They state that per bitcoin the energy consumption is 6.6 million barrels of oil equivalent per year while the consumption for gold mining is 123 million barrels per year.
There are about 88 million ounces of gold produced per year, with a value of around $109 billion, versus 2/3 of a million Bitcoins, value around $4.3 billion. That’s a factor of 25 in value since bitcoin is 5 times more valuable comparing one coin to one ounce.
It seems that the total energy consumed in gold mining globally is around 19 times that of Bitcoin mining. And the number of bitcoins produced per year is dropping due to the halving every 4 years coded into the Nakamoto consensus.
The whole concept is designed to shift miners’ revenue toward transaction fees as the economy develops over time.
If you want to save the environment, focus on gold mining energy efficiency. Improve it by 5% and you can cover the entire Bitcoin mining energy budget.
For a variety of reasons, other cryptocurrencies are less energy intensive than bitcoin. They are also less secure, less battle hardened.
Bitcoin is a digital gold alternative that has the advantages of very low cost portability, and lower costs to secure and store.
It is a valid alternative to gold ownership as a store of value, and is a greener solution. There is a great deal of work (pun intended) on alternatives to Proof of Work mining, including Proof of Stake protocols and delegated Byzantine Fault Tolerant protocols. Also the growth of second layer solutions such as Lightning will support a larger economy and shift miners’ revenue more toward transaction fees.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
No, not asking if you own any Bitcoin. Or the IP address.
This blog is prompted by the Nicholas Weaver article “Risks of Cryptocurrencies” in the June 2018 Communications of the ACM.
He writes, rather misleadingly in our opinion:
“This was not because our Bitcoin was stolen from a honeypot, rather the graduate student who created the wallet maintained a copy and his account was compromised. If security experts can’t safely keep cryptocurrencies on an Internet-connected computer, nobody can. If Bitcoin is the ‘Internet of money’, what does it say that it cannot be safely stored on an Internet connected computer?”
Would you leave a gold coin lying around in the open? Lock that thing up in a safe or safety deposit box.
Bitcoin is not really the ‘Internet of Money’ so much as ‘Money in the Internet’. And the cryptocurrency was not on an Internet-connected computer. Those were the keys.
Your wallet holds one or more private keys, not cryptocurrency itself.
Key distinction (pun intended). The money doesn’t move off the distributed ledger. When it moves from one wallet to another what happens is the send process (that you initiate) changes which private key can access it. Namely the designated receiver’s key becomes the only one that works.
The graduate student’s indiscretion was in making a copy of the key that allowed the safe or safety deposit box to be opened by an unauthorized person. And then not properly securing it.
Where is the Bitcoin stored? Why in the distributed ledger, the blockchain, that is simultaneously existing in many places, but has a single verified history from the Nakamoto consensus protocol that committed it into the blockchain.
That is effectively the bank where all the safety deposit boxes are.
How do you get to your coin? With a key stored in a wallet, the private key. Visit your bank.
That key must be stored in a safe place. It can be in a hardware wallet (USB device typically) which is stored in a home safe. And then it has the same level of security as the gold coins in your safe.
Better, since you can keep another copy in another secure location (safety deposit box, for example).
The next best alternative is a pass phrase on a piece of paper again stored in a safe or safety deposit box. Or a paper wallet that can use a QR code.
There is no need for your private key to be sitting on the Internet.
If you use an exchange you can use their vault, or cold storage, option for most of your holdings. Then you are relying on their assurances that they are storing in offline devices.
When you do visit your Money in the Internet bank, do so from the privacy of your home, not from some insecure wifi in a cafe.
You go to the bank and take some gold coins out from your box and they are already less secure, but that is why they have guards at banks. And when you go out to your car with a couple of the coins, they and you are even less secure.
But we are used to doing that. We understand the procedures.
It’s just that there are new procedures that we have to get used to, with digital gold like Bitcoin. It’s rare to be physically mugged for Bitcoin.
Keep only moderate amounts of cryptocurrencies in exchanges with established security reputations, and modest amounts in mobile wallets.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
National Security considerations are often intimately intertwined with the adoption of new technologies.
Last year Tokyo hosted a meeting of the International Standards Organization, including a session on blockchain technology to examine ideas around standards for blockchain and distributed ledgers.
A member of the Russian delegation, who is part of their intelligence apparatus at the FSB, apparently said “the Internet belonged to the US, the Blockchain will belong to Russia.” In fact three of the four Russian delegates were FSB agents! By contrast, Chinese attendees were from the Finance Ministry, and American attendees were representing major technology companies, reportedly IBM and Microsoft among others.
Let’s unpack this a bit. The Internet grew out of a US military funded program, Arpanet, and the US has been the dominant player in Internet technology due to the strength of its research community and its technology companies in particular.
Blockchain and the first cryptocurrency, Bitcoin, were developed by an unknown person or persons, with pen name Satoshi Nakamoto. Based on email timestamps, the location may have been New York or London, so American or British citizenship for Bitcoin’s inventor seem likely, but that is speculation.
More to the point, the US is the center of blockchain funding and development activity, while China in particular has been playing a major role in mining and cryptocurrency development.
There are many Russian and Eastern European developers and ICO promoters in the community as well. The Baltic nations bordering Russia and the Russian diaspora community have been particularly active.
The second most valuable cryptocurrency after Bitcoin is Ethereum, which was invented by a Russian-Canadian, Vitalik Buterin. Buterin famously met with Russian President Vladimir Butin in 2017. Putin is himself of course a former intelligence agent.
The Growing Interest of Governments
The Russians reportedly want to influence the cryptographic standards around blockchain. This immediately raises fears of a backdoor accessible to Russian intelligence. Russia is also considering the idea of a cryptocurrency as a way to get around sanctions imposed by the American and European governments.
The Russian government has a number of blockchain projects. The government-run Sberbank had initial implementation of a document storage blockchain late last year. There is draft regulation around cryptocurrency working its way through the Russian parliament. President Putin has said that Russia cannot afford to fall behind in blockchain technology.
Given the broad array of applications being developed for cryptocurrencies, including money transfer, asset registration, identity, voting, data security, and supply chain management among others, national governments have critical interests in the technology.
China has been cracking down on ICOs and mining, but it is clear they think blockchain is important and they want to be in control. Most of their government concerns and interest appear to be centered around the potential in finance, such as examining the possibility of a national cryptocurrency (cryptoYuan).
China would like to wriggle free from the dollar standard that dominates trade and their currency reserves. They have joined the SDR (foreign reserve assets of the IMF) and have been building their stocks of gold as two alternatives to the dollar.
China’s biggest international initiative is around a new ‘Silk Road’, the One Belt, One Road initiative for infrastructure development across EurAsia and into the Middle East and Africa. One could imagine a trading currency in conjunction with this, a “SilkRoadCoin”. In fact, the government-run Belt and Development Center has just announced an agreement with Matrix AI as blockchain partner. Matrix AI is developing a blockchain that will support AI-based consensus mechanisms and intelligent contracts.
China’s One Belt One Road Initiative actually has six land corridors and a maritime corridor.
(Image credit: CC 4.0, author: Lommes)
The American military is taking interest in blockchain technology. DARPA believes that blockchain may be useful as a cybersecurity shield. The US Navy has a manufacturing related application around the concept of Digital Thread for secure registration of data across the supply chain.
In fact the latest National Defense Authorization Act requires the Pentagon to assess the potential of blockchain for military deployment and to report to Congress their findings, beginning this month for an initial report.
National Security
What is clear, is that blockchain and distributed ledger technology have the potential to be of major significance in national security and development for the world’s leading nations.
A range of efforts are underway by government, industry, and academia to understand blockchain technology and cryptocurrencies, to enhance the technology, and plan for the future. In that context, we see potential in the technology to impact many facets of society and global dynamics. That potential is now sufficiently developed for us to advocate a more visible presence by government agencies in helping shape the policy and academic research.
We encourage the US government to increase engagement with blockchain and distributed ledger technology. This can include funding research in universities, pilot projects with industry across various government agencies including the military and intelligence communities, the Federal Reserve, and the Department of Energy, NOAA and NASA, in particular.
Also the federal government should pursue standards development under the auspices of the NIST and together with ISO. Individual state governments are also promising laboratories for projects around identity, voting, and title registration.
Information has always been key to warfare. But there is little doubt that warfare is increasingly moving toward a battlefield within the information sphere itself. These are wars directed against the civilian population; these are wars for peoples’ minds. Blockchain technologies could play a significant role in these present and future battles, both defensively and offensively.
America was founded and grew rapidly largely in the context of the Industrial Revolution. The Information Age provides a similar opportunity and responsibility to set the course for the next century and beyond. As before, getting it right will not only assure the country’s continued success and leadership. It also arms the nation to solve problems that affect all of humanity.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Web 3.0 has been around as a meme since early in the century. This writer was formerly with the Sun Microsystems Education business and recalls meetings we sponsored over a decade ago, that were attended by academic computer scientists promoting the concept.
And yet it has been slow to take off, and it remains a somewhat fuzzy catch-all concept. So much so that there is no Wikipedia entry! Some people claim Wikipedia has deliberately censored the term “Web 3.0”.
Wikipedia does have a section within the Semantic Web article. And this notes: “Web 3.0 has started to emerge as a movement away from the centralization of services like search, social media and chat applications that are dependent on a single organization to function.”
To my ear, this matches the desires of many in the cryptocurrency community for decentralized services built on blockchain that challenge the centralization of Facebook and others.
Web 3.0 was initially discussed in conjunction with Semantic Web and with agents. John Markoff of the New York Times supposedly coined the phrase.
Tim Berners-Lee has promoted the Semantic Web, where context and meaning are attached to data, and data structures have rich linkages in support of better data integration.
Cambridge Analytica has famously exploited these kinds of linkages in the Facebook environment to influence the U.S. presidential election and the Brexit referendum.
The general idea around Web 3.0 has been the semantic web, along with data mining, AI, and natural language providing a more productive web environment for users, with greater inferencing and intelligence.
Here’s a very simple view of how it relates to Web 1.0 and 2.0:
Web 1.0: Read-oriented, static
Web 2.0: Read and write, dynamic, interactive
Web 3.0: Read and write and execute, composite services, integration, meaning and agency, and greater decentralization
Now we see that blockchain and cryptocurrency are beginning to have an impact on the definition of Web 3.0.
Why? Well let us consider some major issues:
Net neutrality is dead in the U.S. thanks to the state-corporatist position of the FCC
The web is increasingly centralized on platforms such as Facebook, Google, Twitter who derive almost all of the financial benefit from data that users provide
Cryptocurrencies and blockchain are proving that decentralization can work in a secure fashion, at least for some significant applications
Cryptocurrencies and blockchains provide the opportunity to restore the Web toward its original vision of a decentralized resource. They provide the opportunity to return control and monetization of data to users, instead of it being concentrated in relatively few large corporations.
Note that the Semantic Web stack shown at right includes trust, proof, and cryptography as major attributes. Well blockchains and cryptocurrencies are built on cryptography and are all about distributed trust. (Sometimes they are called ‘trustless’ but in fact trust resides in the protocols and in the network of blockchain miners, and the developer and user communities more generally).
You can find a presentation here by Ben Gardner on Semantic Blockchains:
Blockchains add trust and proof of work to the Semantic Web’s unambiguous data with connections. Ricardian contracts or smart contracts can be implemented.
The Semantic Web template is linked data plus directed graphs built with RDF triples.
The author writes “Linked Data is proclaimed as the Semantic Web done right…an incomplete dream so far, but a homogeneous revolutionary platform as a network of Blockchains could be the solution..designed to interconnect data and meaning, thus allow (sic) reasoning.”
The Semantic Web is all about linked data with defined attributes and relationships, e.g. graph structures such as with RDF triples as the data model. One can adapt blockchains, including linked blockchains, to this purpose and add smart contracts to provide reasoning.
A Semantic Blockchain is defined in his paper as “the use of Semantic web standards on Blockchain-based systems. The standards promote common data formats and exchange protocols on the Blockchain…Semantic Blockchain is the representation of data stored on the distributed ledger using Linked Data.”
More broadly, Blockchains allow the ability to build a new Web from the ground up, with name services more fully decentralized and file and compute services layered on top. Identity and services can also be fully decentralized. Security is inherently provided by the blockchain’s peer-to-peer decentralized mechanism.
We believe that blockchain and cryptocurrencies will accelerate the development of Web 3.0 while also helping to refine its definition.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
We often hear that we live in an Information Economy. We have an information-based economy, but we don’t have a pure form of “money as information”. Instead we have a hybrid of digital money and paper money with encoded information such as denomination and serial numbers and engraving details.
Money (Money 2.0, ‘paper’ fiat money) today is mostly information, but the modern monetary system was designed long before the Information Economy. Even so, money is mostly held in digital form, on the ledgers of banks, and as monetary reserves at central banks. Physical currency in circulation is a small fraction of the money supply. So today it is a hybrid. One can argue it is not fully suited to our rapidly evolving information economy.
Steven Mnuchin, Treasury Secretary, and Wife Posing as Bond Villains, while Enjoying Dollar Bills at the Bureau of Engraving
Bitcoin and cryptocurrencies collectively are Money 3.0, a form of money that is entirely digital, entirely information. Even if you have a physical bitcoin wallet or paper wallet, the money does not reside in the wallet, only the keys! The keys release bitcoin money held on the blockchain.
Trying to separate the blockchain from bitcoin or cryptocurrency is like trying to separate the economy from information in the information economy. The blockchain holds the ledger information, the cryptocurrency powers the economy. The term ‘blockchain’ does not appear even once in Satoshi Nakamoto’s seminal paper for bitcoin and cryptocurrency. See this OrionX.net podcast discussing Nakamoto’s vision and the Nakamoto consensus algorithm: https://youtu.be/ZLS5P7SYcyI
Today, market participants mostly look at the market cap of bitcoin and other cryptocurrencies, as if they were some sort of equity shares. But actually, they are currencies, or perhaps digital gold, and what is somewhat strangely called ‘market cap’ is actually the money supply for that currency. It is simply the price of bitcoin, times the aggregate number of bitcoins in circulation. Here, in circulation means securely committed to the blockchain through a cryptographic hashing algorithm.
The size of the economy for bitcoin is related not only to the money supply, but also how rapidly that turns over. In macroeconomics this is called monetary velocity. In fact GDP = M2*V where the GDP is equal to the M2 money supply and V is the velocity of that money. It reflects how fast money moves through the system per year.
In the US the GDP is about $19.5 Trillion, the M2 money supply is about $13.7 Trillion and the velocity is about V = 1.42. That is, on average, the money supply turns over 1.42 times per year. In fact the Federal Reserve has been worried that the velocity is too low. It has been dropping steadily, which is a symptom of stagnation.
Velocity of M2 Money: Federal Reserve of St. Louis
For bitcoin the velocity is much higher. It turns over about 20 times a year, V = 20. Today the money supply or market cap for bitcoin is about $158 billion. With a velocity of 20, that translates to a bitcoin economy that is over $3 trillion. That amounts to around 16% of US GDP (roughly equal to annual health care expenditures) and more than the GDP of The Netherlands. Bitcoin is not usually described in such terms, but this is a measure of the vibrancy of the economy for the cryptocurrency.
Many cryptocurrencies have even higher velocities. Bitcoin Cash, which has only been in existence a few months, has a velocity of 28 and a total economy of over $700 billion, similar to the GDP of Switzerland. The world economy of cryptocurrencies exceeds about $9 trillion. This is about twice the GDP of Japan.
While cryptoeconomies are much less developed and have high levels of speculation, the overall size is indicative of the great potential they provide utilizing “Money in the Internet”.
Bitcoin and other cryptocurrencies are enabling the Information Economy 2.0, where whole new forms of efficient exchange of value can be implemented with fewer or even no middlemen and at lower cost.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Well there are 20 flowers in the Bitcoin ecosystem. And over 1400 in the cryptocurrency ecosystem at present.
Salad forks, dinner forks, shrimp forks, dessert forks, tuning forks, pitchforks… so many kinds of forks..
Image credit: Ellen Levy Finch, CC BY-SA 4.0
Why fork a new cryptocoin? One can fork for technological improvements, one can fork to make money, and one can fork for ego, for the pride of “ownership”.
There were several software forks that occurred mainly in the 2015-2016 timeframe and known as XT, Classic, and Unlimited. Including Unlimited, they have had limited impact to say the least.
But let us look at hard forks, or coin splits, that have been so prevalent since August of last year.
Technology enhancements promoted in these forks are across several main categories:
Bigger blocks for scaling, shorter block times
Off chain or side chain transactions (Segwit for signature, more generally Lightning, etc.) for scaling
Different hashing algorithms for easier mining
More anonymity, security
Enhanced programmability, smart contracts
Increased money supply
How many hard forks and coin splits has Bitcoin had so far? In total there have been 20 such forks to date.
August 2017 – 2
October – 1
November – 1 and Segwit2x proposed, withdrawn
December – 14
January 2018 – 2 so far
This Cambrian Explosion of bitcoin forks is in large part a result of the increased transaction costs and delayed confirmation times with original BTC, Bitcoin Core. But it is also a sign of a healthy and growing blockchain universe. If cryptocurrencies were not seeing increased success, the rate of innovation, and the number of forks, would be smaller.
Here is a list of the most significant ones, all in the second half of 2017, and with current pricing, key features, and URL:
August – Bitcoin Cash, BCH, $2413, 8 MB blocks, bitcoincash.org
October – Bitcoin Gold, BTG, $323, equihash, bitcoingold.org
November – Bitcoin Diamond, BTCD, $22, 10 times number coins , X13 hash, btcd.io
December – Super Bitcoin, SBTP, $108, lightning and zero knowledge proofs and smart contracts, supersmartbitcoin.com
If you owned bitcoin prior to block 478558, you in principle own all 20 of the forked coins, including the most valuable one Bitcoin Cash, and mostly in a one-one ratio. Putting your hands on them is trickier.
That is a question as to what support particular private wallets or public exchanges provide. There are guides on the internet and YouTube as to how to retrieve although it seems more trouble and risk than justified in most cases. (This writer has managed to get some BCH and BTG separated out, but it is a somewhat nerve-wracking experience.)
For now it seems we have reached a point of exhaustion for the principal good ideas and the newest forks are more likely to be dodgy, or frauds, or duplicating others, or of limited potential.
Here is an important consideration: while increasing the transaction rate and lowering fees will bring greater utility to users, this does not contribute to the store of value or digital gold aspect. Bitcoin, the original Bitcoin core, is most valuable today for its store of value attribute, much more so than for its medium of exchange attribute.
Now it will be a race between development teams and marketing teams to see which of these forks/coins other than BCH and maybe BTG will have relevance and value going forward, and what value any of them can sustain.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Recent News: Segwit2x fork has been postponed indefinitely
Some say bitcoin acts more as digital gold then as a currency, more as a store of value than as a medium of exchange. It is very interesting to look at the various bitcoin forks with this question in mind.
Everything in life and in finance is a tradeoff. Gold works well as a long term store of value, but not so well as a medium of exchange. The US dollar works very well as a medium of exchange, but not well as a store of value in the long term. Even the Federal Reserve and other central banks hold gold as a reserve asset. It represents the bottom of the inverted money pyramid.
Now bitcoin is from its beginning more like gold in the sense that it is an asset with limited, predetermined supply. Dollars and other fiat currencies are debt-based since they come into existence when new loans are made, and their continual supply growth is rather assured; usually inflation occurs to varying degrees. See the Money 3.0 article for a longer discussion of this point.
Image: Silver ice cream fork, De Young Museum
There are 4 versions of bitcoin, 3 currently, and one possible fork. That was scheduled for mid-November as Bitcoin 2x (or B2X) a possible fork due to partial adoption of Segwit 2x, but it has now been indefinitely postponed due to lack of support.
As of today, approximate values for the 3 existing forks are:
Bitcoin BTC $11,530
Bitcoin Cash BCH $1560
Bitcoin Gold BTG $330
And Bitcoin 2x B2X had future values around $1600 before plunging on the announcement that it is now postponed. That value seems to have migrated to BCH.
All these cryptocurrencies have a supply of around 16.7 million accounting units, and all are limited to 21 million as the ultimate supply. And yet their prices are very different. Bitcoin has a first mover advantage but is that the whole story? How does one value BCH and BTG relative to BTC? In principle the various versions have both asset and currency characteristics.
Each of the alternatives to the original bitcoin is designed to facilitate faster, less expensive transactions. And this makes it more like a currency than a reserve asset.
BTC can be looked at like a large denomination bill, not as easily spent, although it is much easier to break into change than large bills are. Bitcoin Cash differs from BTC because it has a much larger blocksize, 8 MB. Bitcoin Gold differs in adopting a GPU-friendly mining algorithm, Equihash, rather than SHA-256 used by the others, which requires custom ASICs.
Bitcoin 2x adopts Segwit2x with a larger 2 MB block size.
Each of these three alternative coins is designed so that the system can process transactions more quickly and at lower cost, and so, along the spectrum of digital gold to currency, each is closer to a currency than the original BTC.
And that, somewhat counter-intuitively, is why original BTC retains a higher value.
In particular, the Bitcoin Gold is actually least like gold of all of these, since it will have the most accessible and thus fastest mining algorithm, and presumably could end up with the lowest transaction fees.
Image credit: bitcoingold.org
The respective values of the 3 or 4 types of bitcoin reflect this view. Bitcoin is the “slowest” and has the lowest velocity (slowest turnover) and highest value. Bitcoin Gold appears to be the most rapid and with lowest transaction fees, and thus has the lowest value.
Bitcoin Cash and a possible future Bitcoin 2x are between the two extremes. Since Bitcoin Cash has much larger blocks it has substantial miner support. Bitcoin 2x is favored by the user community that wants to facilitate more efficient transactions.
If you have a gold coin and some fiat currency, which do you spend first? You bought the gold coin in expectation that it would preserve its value and increase in terms of the number of currency units per coin.
So HODL (hold on for dear life) BTC, and spend or convert BTG and BCH seems the way to go for now. As always one should monitor how the different cryptocurrencies are developing in comparison to each other, in this very dynamic and volatile marketplace.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
It is early days in evolutionary terms for cryptocurrency. Bitcoin has not been around even a decade. Ethereum has only been here for a few years. The respective economies of these and other cryptocurrencies have been growing at triple digit percentage rates.
A given blockchain can be thought of as a continuing line of a particular species. A new blockchain, e.g. Ethereum with new attributes, is a new species of cryptocurrency. A fork in a blockchain, such as the recent Bitcoin Cash, is also a new species, but perhaps one can say that it belongs to the same genus.
Mayr’s concept of species is that of representatives of the same breeding population. They are in some sense on the same continual chain.
A fork is an evolutionary branch in response to environmental pressure. The pressure arises due to the developing needs of the ecosystem for cryptocurrencies overall and for individual cryptocurrencies.
Pressure
The pressure that gives rise to evolution in the cryptocurrency ecosystem arises from the need to scale cryptocurrency to higher transaction rates and to more diverse use cases. For example, there is the very general use case of smart contracts, that led to the creation of Ethereum.
How new currencies are created or are forked results from the technological requirements and how those are interpreted and implemented by particular members of the development community. This is a political arena since miners, developers, exchanges, merchants, and other groups have different interests.
We have just had the Bitcoin Cash fork a few months ago and the Bitcoin Gold fork more recently. The Segwit2x fork scheduled for November was postponed indefinitely due to lack of support.
It is difficult to determine which fork or species will be the most successful in the long run; but the original or main branch can have an advantage. Overall forks can be seen as strengthening the ecosystem as a whole since total value seems to rise after forks. After the Bitcoin Cash (BCH) fork the original Bitcoin (BTC) increased in value, and one could also collect the BCH on a one per one BTC held basis as a dividend.
More generally, this has been borne out by the continually increasing market capitalization of the set of cryptocurrencies, currently having reached around $300 billion (more than Buffet, Bezos, and Gates rolled together).
For investors in cryptocurrency one can view forks as special dividends. Those who held Bitcoin through the Bitcoin Cash fork received a dividend of several hundred dollars per BTC. Sometimes numbered prints or copies are valuable as well.
Above is not our view, but that of @BitcoinWrld
What you do (hold, sell all, sell half) with your dividends is up to you and your views on individual forks; we make no recommendations here. But the dividends are there to receive, along with possible capital appreciation as the cryptocurrency economy continues to grow rapidly.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Ethereum is described in Wikipedia as an “an open-source, public, blockchain-based distributed computing platform featuring smart contract functionality“.
How does it differ from Bitcoin? Well Bitcoin is open-source, public, distributed, and block-chain based. The difference is principally found in the terms “computing platform” and “smart contract functionality”. And there are other differences as well.
Ethereum is only two years old. It was the brainchild of wunderkind Vitalik Buterin, a Bitcoin developer, and while initial funds for the project were raised in mid-2014, the network went live in mid-2015. A foundation under Swiss law manages Ethereum.
The motivation was to have better scaling than Bitcoin, both horizontally, in terms of transaction speed, and vertically, in terms of use cases supported (implemented via smart contracts). It also has a better specified development plan, with 0, 1, and 2 versions of the software having been implemented, and version 3 (Metropolis) currently in testing.
It has been a great success, and Ether, the coin of Ethereum, now has the number two market cap among all cryptocurrencies at around $29 billion. Its value has risen dramatically during 2017, rising from $8 to well over $300.
Ethereum logo CC-BY-3.0
Contracts
There are two types of accounts in Etherland. One can have a regular cryptocurrency account, or an account can represent a smart contract. There is a virtual machine (EVM) that is said to be “Turing complete” and that supports multiple scripting languages in which contract rules can be specified.
The idea of smart contracts has been around for over two decades; blockchain with broad programmability on the chain provides a very useful technology for their implementation.
Smart contracts allow value to be exchanged between agents without existing trusted relationships. Sort of like escrow, but much more streamlined. The basic idea is to cut out the expense and complications associated with middlemen.
Use cases being explored for such smart contracts include:
Real estate leases or purchases
Securities settlement
Supply chain management
Governance, including voting
Intellectual property protection
The number of currently existing use cases is few at present, however, and they tend to be simple and related to the Ether coin itself. Some have argued that smart contracts are much harder to implement in practice than many imagine. A recent interesting one is Prism Exchange, which allows you to hold a variety of altcoins across multiple exchanges from a single application.
Mining
Ether is much quicker to mine than Bitcoin, and can process 25 transactions per second. Transaction fees are also much lower than Bitcoin, around 8 times lower currently. Blocks are generated every 12 seconds, as opposed to the 10 minute target with Bitcoin.
Like Bitcoin, Ether is mined via Proof of Work, but the intent is to move to Proof of Stake (some measure of ownership) over time. A different cryptographic hash problem, Ethash, is solved, and with this hash Ether does not benefit greatly from mining with ASICs and is therefore accessible to CPU and especially to GPU mining. “Ethash PoW is memory hard, making it basically ASIC resistant.”
Basically the algorithm is designed to consume memory bandwidth and to be GPU-friendly. So it is good news for Nvidia and AMD and Intel.
Enterprise Ethereum Alliance
The Enterprise Ethereum Alliance has grown to over 150 organizations as members and includes some of the most important technology companies and largest banks. Its purpose is to address enterprise requirements for smart contracts and blockchains. The founding members are shown in the graphic below. Mastercard and Cisco are two major companies who have also joined recently.
Banks, in particular, have interest in permissioned blockchains, so that they can retain control of their customer relationships. There is a natural tension between open distributed trust of the blockchain and centralized trust that banks provide today.
It is an exciting time. How blockchain will be deployed by the financial industry, and how it will disrupt the industry are open questions. Smart contracts allow blockchain to be even more disruptive because they provide the tools for disintermediation. Jamie Dimon may not want his traders to trade Bitcoin, but he sure wants a seat at the Ethereum “smart contracts” table.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Warren Buffett is the most famous name in stock investing, the second richest person in the world, and a leading expert in valuing companies and securities. He also is a big investor in banks, including Wells Fargo, Goldman Sachs, and Bank of America. So he has a lot of vested interest in the current monetary and financial system.
He recently said that bitcoin is in a bubble, which may well be true. He also said “You can’t value bitcoin because it’s not a value-producing asset”.
And yet, as of today, bitcoin has a market cap which is over $120 billion, substantially more than Buffet’s net worth. Bitcoin can be valued, but not like a security or a company, which is what Buffet does so well.
As we have written elsewhere, bitcoin is a currency, money, a cryptocurrency. Some will say it is a digital asset, like a digital gold. We say it is Money 3.0 (fiat is Money 2.0, gold and silver coins were Money 1.0).
Do these have value? Although none has intrinsic value and each costs a nominal amount to make the one on the right is worth quite a bit more than the one in the center, and the one on the left, more still.
Yes, money is designed as a store of value, a medium of exchange, a unit of account. Cryptocurrencies have the same design goals.
Bitcoin is a unit of account in a secure, distributed ledger. It has been a much better store of value than fiat currency in recent years.
In fact in 2014, Buffet said “It’s a mirage”. And yet, the value of a single bitcoin has increased 20 times since late October, 2014 to about $5800 today.
Money is valued by what you can exchange it for in the economy, by its utility. It is valued against other currencies. Bitcoin can be valued the same way, and thus by the vitality of the bitcoin economy.
Within the cryptocurrency world, bitcoin is the reference benchmark, just as the US dollar is globally. Bitcoin gets valued every single day, every minute of the day, against all major fiat currencies and against hundreds of cryptocurrencies. Like those currencies it has an economy and a turnover (or velocity) of the currency.
One thing we don’t normally think of with respect to cryptocurrencies is interest, or dividends. It is possible to lend out bitcoin for interest, as one can do with dollars, euros, or even gold. But bitcoin has effectively thrown off two special dividends this year, in the form of forks of the bitcoin blockchain. These are known as Bitcoin Cash (forked in August) and Bitcoin Gold (forked in October). Collectively, those two are worth close to $700, representing over 9% dividend rate to date during 2017, based on the current bitcoin price.
And for someone who bought at the beginning of the year, when bitcoin was under $1000, the dividend is around 70%. Not shabby, and a very reasonable reward for accepting the volatility.
Bitcoin is a technology for internet money, network money that is independent of any government, and it can be hard to fathom for the newcomer. Buffett has always said he does not understand technology. He was late getting into Apple, for example. He has not examined the technology and potential of bitcoin and other cryptocurrencies sufficiently to have an informed opinion.
Bitcoin’s future value? It all depends on how the economy around bitcoin develops, but it will be quite an adventure. And bitcoin to bagels it will increase in value over the next several years.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Bitcoin, and cryptocurrencies more generally, can be a bridge to a better monetary future for the globe. In almost every nation today, fiat currency managed by a central bank is the norm. This is money that is inherently inflationary by design. Since central banks are controlled by national governments, and governments routinely run substantial deficits, the banks promote inflation in order to benefit their governments.
In our current low growth environment, the Federal Reserve has grown the money supply (M2 money stock) 4.9% during the past year when inflation is running at 2% or less. They are operating on an equation of around 2% inflation plus 2% to 3% GDP real growth for about 5% monetary growth.
Bitcoin has a very controlled and low absolute inflation, much less than 1%. There are currently 16.6 million bitcoins available, and there will never be more than 21 million, and that does not occur until over 100 years from now. In practice, Bitcoin is currently deflationary since the economy around Bitcoin is at present increasing very rapidly, at triple digit rates. It has been gaining value against fiat currencies quickly, albeit with very high volatility.
Bitcoin meets the attributes of currency, see our Money 3.0 article. It is not debt-based, as are all currently circulating fiat moneys, paper and digital money backed by nothing but debt (Money 2.0).
Akashi Kaikyo bridge is the world’s longest suspension bridge. GFDL license.
The entire financial system was at risk of collapse in 2008 due to accumulated debts and risky and fraudulent derivatives built on top of those debts. Trillions of dollars of wealth were destroyed, with Americans losing 40% of their net worth during a 3 year period.
In addition, the system is well-designed for the money center banking elites to pull more and more wealth into their own hands, through financial techniques that create no real wealth. Those who get to create the money lend it out and accrue the highest benefits.
A more stable system is required, and Bitcoin could play an important role, as an asset-based, not debt-based, currency. Dollars and Euros come into creation as new loans are issued by commercial banks. Central banks manage the reserve and equity requirements of those banks, but a large amount of leverage is inherent in the fractional reserve system.
Bitcoin comes into creation as a result of the mining process, that occurs as new transactions are forged into the blockchain. Bitcoin creation is a direct result of the operation of the economy around the cryptocurrency. Bitcoins are ‘minted’, not ‘printed’. Like fiat currency they have value due to scarcity and utility, and dependent on the growth of their economy.
Bitcoin and other cryptocurrencies can be the basis for more honest money, as well as for decreased transaction costs, and higher efficiency. Banking will change forever. Like fiat currency, bitcoin can be borrowed and it can be lent.
Those who are involved in Bitcoin today, a “peer-to-peer cash” are pioneering a future that could be a more stable, more honest monetary system. Today Bitcoin is young, has plenty of growing pains, and volatility, but it is now 8 years old and maturing rapidly.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
One of the largest banks in Japan, Mizuho, along with other Japanese banks, is looking to get into the blockchain game. CNBC reports “Japanese banks are thinking of making their own cryptocurrency”.
Except they are not, based on the information released so far. This will be mobile Yen, a use of blockchain to allow mobile users to spend Yen and send Yen. Mobile money. Not that there is anything wrong with mobile money, an electronic wallet, it can be quite useful.
This is not Nakamoto consenus, this is not mining of currency. It is a tethered currency. This is not an open source, globally distributed ledger with trust resident in the algorithm, the ledger, and the community.
I was married to a Japanese lady for over a quarter century, and have lived and worked in Japan. I know the Japanese mindset. This will be a highly constrained ‘currency’.
No doubt with all the constraints, and as a complete tether to the Yen, and with large banks behind it, they will be able to gain Japanese government approval.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
First they ignore you, then they ridicule you, then they fight you, goes the saying.
JP Morgan (not Jamie Dimon)
Jamie Dimon is CEO of JP Morgan Chase, arguably the most important money center bank. He recently called Bitcoin a “fraud”, heaping ridicule upon, and fighting with Bitcoin as well, with a single phrase. Because he is “afraid”.
It certainly is not a fraud. It is in fact a more advanced form of money our fiat currency; it is Money 3.0.
JP Morgan Chase, the combined bank, has been around since 1799 (Chase portion), over 200 years, and has a market cap of around $331 billion. Bitcoin and other cryptocurrencies have been around for less than 9 years and have a market cap of around $150 billion. That is over 1/2 of Visa’s market cap.
It would not be a surprise to see the total cryptocurrency market cap exceed that of JPM by the end of the decade.
Why did Jamie call Bitcoin a “fraud”? Because he knows he has to fight it. Cryptocurrency, or the Internet of Money as Andreas Antonopoulos likes to call it, is a steamroller that will severely disrupt banking as practiced today.
Who is really happy with their bank? You think it is your money you have in your bank, right? No, you have lent your money to the bank so they can lend it to others and make hefty profits on the spread. Why don’t you lend directly? You can use Bitcoin to do that, or dollars as well, through direct lending sites.
Try taking all of your savings and checking funds out of your bank tomorrow in cash. They probably won’t let you if you have more than $10,000. They have know-your-customer regulations and anti-money laundering regulations and many other restrictions. They don’t keep much cash on hand. You might hear “we can give you $2500 today, then come back next week”.
In his book Internet of Money, Antonopoulos tells a story about how he gave a talk at the Deutsche Bank. This is the equivalent of the Federal Reserve, for Germany, their national bank. He asked to be paid in Bitcoin; they couldn’t do it. Ok, could they send him dollars to his US bank. Okay SWIFT code, etc. Without going through all the gory details, the whole transaction took 16 days! His bank in the U.S. said, who is the Deutsche Bank?
You can easily transfer a few thousand dollars or more via Bitcoin in an hour or so. If you haven’t used Bitcoin yet, now is the time to learn about it, it will only grow in importance.
The real frauds here? JP Morgan and Jamie Dimon. They have paid over $30 billion in fines for multiple financial crimes since the Great Recession. Around 10% of their company market cap. But that huge sum is less than half the market cap of Bitcoin today.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Why are cryptocurrencies like Bitcoin and Ethereum Money 3.0? And what are Money 1.0 and Money 2.0?
Recently, Jamie Dimon called Bitcoin a ‘fraud’. This coming from the CEO of JP Morgan, the bank that has been fined more than any other, save one, for financial crimes since the Great Recession of 2008. His statement reeks of hypocrisy since JPM is a member of the Enterprise Ethereum Alliance, his traders have been trading Bitcoin related ETN securities, and his firm has applied for patents using blockchain technology.
By the way the Enterprise Ethereum Alliance has well over 100 members including Microsoft and Mastercard. Serious players understand that cryptocurrencies are a big deal. The market cap of all cryptocurrencies is currently in the neighborhood of $150 billion, around 2/3 the market cap of Visa. And this has all happened in only eight years’ time.
First, what is Money?
It is amazing how few people can give a definition, other than pulling out a bill from their wallet, or referring to the numbers in their checking account statement. And how does money get created in our modern economy? Very few actually understand the process. Most people say government creates it. Governments can, and do, but most money is not created directly by the government. What the government does is validate money, they define a single type of money for their nation. They print currency, but most money today is digital, residing in bank balance sheets, and most money creation occurs as banks issue new loans.
Throughout history there have been many forms of money, but two forms have dominated. The first form, Money 1.0, was the dominant form for millennia. It was coins made of precious metals, in particular gold and silver, and ‘base’ metals such as copper and bronze. According to the St. Louis Federal Reserve, money must have six properties: durability, portability, divisibility, uniformity, limited supply, and acceptability.
They sound a bit like goldbugs when they write it that way. These are all useful attributes of the thing that is used for money, be it gold or paper. But it doesn’t quite get to the most essential three properties of money. It must serve as:
A unit of account
A store of value, and
A medium of exchange
Money is whatever can be used as a socially agreed upon unit of account and medium of exchange. It also should retain its value, not depreciate quickly, so that it can be used next month and next year as well. Notice I say socially. Societies agree upon what is used as money, and nation states in recent centuries have taken the lead in that definition. In order to be conveniently exchanged, then the six properties above come into play. Durability and limited supply allow the retention of value. Portability and divisibility make it easier to exchange. Uniformity makes it a useful unit of account, as does acceptability.
We all have to more or less agree on what the accounting unit is. That is actually the starting point for money, agreeing on the standard measure. The government can decree the accounting unit, and can demand taxes be paid in that unit. That is government fiat, and can apply for either coined money of precious or base metals (Money 1.0) or paper money (Money 2.0).
Image: Roman gold Solidus coin. York Museums Trust. CC-BY-SA 4.0
The US dollar was originally defined to contain a certain weight of silver, and aligned to the Spanish dollar (originally Austrian thaler) or ‘pieces of eight’ that was widely used in New World trade. The US dollar has also been defined against gold, with an official act in 1900 following nearly 3 decades of defacto gold standard following the Civil War. Of course the gold standard is now entirely gone after being discarded in two phases, under Roosevelt in 1933 and Nixon in 1971. The remnants of the bimetallic standard of the late 19th century remain in present-day dimes and quarters that used to contain silver even until 1965, retain the color, but have been entirely debased.
No nation remains on a Money 1.0 standard of precious metals, all have moved to Money 2.0, fiat paper money. If they did they would lose their gold, and they prefer to melt it into bars and store it in central bank vaults as a reserve. So as Warren Buffet says, we dig it up in mines, melt it down into bars, and bury it again in vaults.
With paper money, there must be fiat, as nobody wants pieces of paper that have no value. The days of gold certificates and silver certificates as circulating currency are long gone, although I remember silver certificate dollar bills from my youth. The value comes from the legal tender requirements that the paper be accepted by businesses, be used for taxes, and from the government’s printing process to make counterfeiting difficult plus the government’s overall management of the money supply (usually through interest rate policies) to limit loss of value due to inflation.
The technology of high quality paper engraving, augmented with serial numbers, threads and holograms, and the technology of central banks, allow fiat money to work. The vast majority of nations have central banks to lend to the commercial banks in times of crisis and to manage the banking system and money supply indirectly.
So those are Money 1.0 and Money 2.0. In summary:
Money 1.0 – Public or private, asset-based, intrinsic value, coins or bars of precious metal
Image of $2 Federal Reserve Note, Bureau of Engraving and Printing, U.S. Dept. of Treasury
Money 2.0 – Public and sovereign, debt-based, no intrinsic value, paper and digital.
Most Money 2.0 is digital, with the circulating currency representing a small percentage. Money mostly comes into circulation not through the printing press, but when banks make new loans. If a bank creates an auto loan, it credits the checking account of its customer digitally. Banks are allowed to make new loans within the limits of their central bank authority determined reserves and equity capital requirements.
Note as an aside that Money 1.0 and Money 2.0 can coexist. We mostly have Money 2.0 in the United States, but there was a small amount of silver coinage money circulating alongside up until the 1960s. This is an important principle, since we are beginning to see the coexistence of Money 2.0 and Money 3.0.
What about Money 3.0?
Cryptocurrencies are purely digital, whereas Money 2.0, fiat and debt-based money, is mostly digital.
Why Money 3.0? Technologists and advocates of non-fiat money were concerned about the risks of centralized monetary systems dominated by central banks and by money center banks engaged in fraudulent activities around mortgages and other lending with derivatives including CDOs, CDSs and more. The corrupt system lead to the Great Recession of 2008. Everyone in the society suffered, but the banks were bailed out by enormous government loans.
There were more than 50 attempts at creating a digital crypotcurrency prior to the year 2000. None succeeded. One was gold-based and known as e-gold. It was shut down in 2009 by the US government, because it ran afoul of stricter money laundering regulations. It was also subject to repeated thefts of accounts from Russian and other criminal hackers.
A successful non-fiat cryptocurrency must provide a single secure ledger of entries to protect against counterfeiting and double spending. It must have a method of commiting a single instance of a transaction to this secure ledger that is publicly shared, and is known as the blockchain. It must have a built-in automated “central banking” function that determines the money supply.
Satoshi Nakamoto’s brilliance was to combine a number of existing ideas around public/private key cryptography, distributed ledgers, and a mining algorithm with “proof of work” that rewarded miners for solving a difficult cryptographic hash problem. Transactions are signed with private keys. All bitcoins reside in the distributed ledger. The owner has a wallet with the key that allows them to transfer bitcoin in arbitrary amounts to someone else and thus confers ownership.
The supply is limited with a maximum at 21 million bitcoins that will not be reached until well into the 22nd century. New bitcoin comes into existence in conjunction with the mining of blocks of transactions. The successful miner is rewarded with an allocation of new coins, presently 12.5 coins per block of approximately 2000 transactions. So here we have the central banking function and a digital minting or mining process for the ‘coins’ which are really just ledger entries.
We describe this Nakamoto consensus algorithm and the mining process in more detail at orionx.net/podcast.
Now we have not just Bitcoin, but Ethereum, Bitcoin Cash (which is a recent fork of Bitcoin with large block size), Ripple, Litecoin and hundreds more cryptocurrencies. We have new coins being created rapidly in conjunction with new applications and ICOs – initial coin offerings.
The largest of these, those with market caps in the billions of dollars, meet the three requirements for money. Unit of account. Medium of Exchange. Store of value. Their limitations at present relate to the latter two attributes. They are accepted as medium of exchange in some environments, but relatively few compared to existing fiat currencies. And as a result of that their value is less stable and determined more by investment and speculative demand. Their ultimate value will be determined by the cryptocurrency economy as uses cases, applications, and acceptance grow.
They are child currencies, developing and growing, but far from the maturity of an existing national fiat currency. The value should continue to grow for the long term, however since transaction volumes are increasing very rapidly.
So now we have in the world:
Money 3.0 – Private and globally distributed, asset-based, digital only.
Money 3.0 holds much promise. It can remove a lot of cost and friction from the financial system. Trying sending a check or ACH transfer to your sister and having the transaction complete on the weekend. Send her some bitcoin? She will get it even on Sunday at 3 am around an hour or so after you send it. Bitcoin is 24 by 7 by 365. And with very limited fees within the Bitcoin economy. Most of the cost is in moving Bitcoin to fiat or vice versa.
It is not based on debt, so does not have the instability of debt or counterparty risk. The only real risk is security, which holds as well for your banking balances. The other risk is to the value as governments and politicians feel threatened. But at the end of the day, they can only regulate it, but not eliminate it. The technology is too widely available to anyone.
Money 3.0 is not poised to replace Money 2.0 anytime soon, although in a number of ways it is superior. They will coexist. At some point a small country will convert their currency to Money 3.0, by building a blockchain-based peso or some such. A number of central banks, large and small, are already studying this issue.
Many have talked about global currencies in the past. The US dollar has global impact for trade and the price of key commodities, but you have to exchange it when you cross borders. The Euro has been a boon for commerce, trade, and travel in many countries within Europe. Gold historically had a global role but was difficult to move and verify as to weight and purity.
Bitcoin has no weight and purity issues. It transcends borders. It, Ether, and the other cryptocurrencies are indeed the first global currencies.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
What does a Spanish silver dollar have to do with Deep Learning? It’s a question of standards and required precision.The widely used Spanish coin was introduced at the end of the 16th century as Spain exploited the vast riches of New World silver. It was denominated as 8 Reales. Because of its standard characteristics it served as a global currency.
Ferdinand VI Silver peso (8 Reales, or Spanish silver dollar)
The American colonies in the 18th century suffered from a shortage of British coinage and used the Spanish dollar widely; it entered circulation through trade with the West Indies. The Spanish dollar was also known as “pieces of eight” and in fact was often cut into pieces known as “bits” with 8 bits comprising a dollar. This is where the expression “two bits” referring to a quarter dollar comes from. The original US dollar coin was essentially based on the Spanish dollar.
For Deep Learning, the question arises – what is the requisite precision for robust performance of a multilayer neural network. Most neural net applications are implemented with 32 bit floating point precision, but is this really necessary?
It seems that many neural net applications could be successfully deployed with integer or fixed point arithmetic rather than floating point, and with only 8 to 16 bits of precision. Training may require higher precision, but not necessarily.
A team of researchers from IBM’s Watson Labs and Almaden Research Center find that:
“deep networks can be trained using only 16-bit wide fixed-point number representation when using stochastic rounding, and incur little to no degradation in the classification accuracy”.
“As long as you accumulate to 32 bits when you’re doing the long dot products that are the heart of the fully-connected and convolution operations (and that take up the vast majority of the time) you don’t need float though, you can keep all your inputs and output as eight bit. I’ve even seen evidence that you can drop a bit or two below eight without too much loss! The pooling layers are fine at eight bits too, I’ve generally seen the bias addition and activation functions (other than the trivial relu) done at higher precision, but 16 bits seems fine even for those.”
He goes on to say that “training can also be done at low precision. Knowing that you’re aiming at a lower-precision deployment can make life easier too, even if you train in float, since you can do things like place limits on the ranges of the activation layers.”
Moussa and co-researchers have found 12 times greater speed using a fixed-point representation when compared to floating point on the same Xilinx FPGA hardware. If one can relax the precision of neural nets when deployed and/or during training, then higher performance may be realizable at lower cost and with a lower memory footprint and lower power consumption. The use of heterogeneous architectures employing GPUs, FPGAs or other special purpose hardware becomes even more feasible.
This is such an interesting area, with manycore chips such as Intel’s Xeon Phi, nVidia’s GPUs and various FPGAs jockeying for position in the very hot Deep Learning marketplace.
OrionX will continue to monitor AI and Deep Learning developments closely.
References:
Gupta, S., Agrawal, A., Gopalakrishnan, K., Narayanan, P. 2015,https://arxiv.org/pdf/1502.02551.pdf “Deep Learning with Limited Numerical Precision”
Jin, L. et al. 2014, “Training Large Scale Deep Neural Networks on the Intel Xeon Phi Many-Core Processor”, proceedings, Parallel & Distributed Processing Symposium Workshops, May 2014
Moussa, M., Areibi, S., and Nichols, K. 2006 “Arithmetic Precision for Implementing BP Networks on FPGA: A case study”, Chapter 2 in FPGA Implementations of Neural Networks, ed. Omondi, A. and Rajapakse, J.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Competitive analysis (competitive intelligence) is critically important for strategy, planning, and sales support. But it should also permeate an organization’s DNA, preserve high ethical standards, and deliver high quality content. Competitive awareness is like security awareness or commitment to quality – it’s the duty of everyone in the organization. This is what we call a “Competitive Culture”.
A competitive culture means everyone in the organization is tuned in to the competitive realities the company and its products and services face. It is not a one-time activity, but an essential ongoing requirement. It must evolve continuously as competitors strengthen and fade, new competitors enter the market, and as you introduce new offerings or pursue new strategies.
Jesse Owens, 4 gold medals, 1936 Olympics
The competitive function takes input from and supports various stakeholders, including sales, marketing, executive management, and engineering. As it matures within the organization, it evolves into both a back-office function, with its own processes and roadmap, as well as a collective effort for the organization at large.
Everyone in the company can contribute to intelligence about the competition and can use it to enhance their work performance. And everyone must protect information that, if known by competitors, would decrease the company’s competitiveness.
OrionX has a history of excellence in developing best practices and tools across the competitive intelligence discipline and we offer a range of packages. The starter package provides:
* Target market / solutions / product roadmap review
* Program objectives, elements, timelines, calendar, dashboard
* Competitive SWOT, playbook, head-to-head comparisons, beat sheets, and more
“A very critical requirement for every company and every organization is competitive analysis. It is something that needs to be done with high integrity but also with high quality. And it requires the development of processes and the ability to look at your competition and understand why customers might be buying [from] them, and how they evaluate you based on the competition. We have developed best practices and have effectively worked with clients to arrive at a competitive intelligence function that you can be proud of.”
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
In our 2016 predictions blog, we said “If you missed the boat on cloud, you can’t miss it on IoT too”, and “IoT is where Big Data Analytics, Cognitive Computing, and Machine Learning come together for entirely new ways of managing business processes.”
IoT represents the ultimate convergence theme in the marketplace today. IoT includes fixed and mobile edge devices (fog computing), cloud computing, big data, analytics and machine learning, and in many instances can include social and mobile computing as well.
Composition VIII, Wassily Kandinsky, 1923, Shared via #WikiArtApp http://bit.ly/18GCSaj
Because of the very large number of devices being incorporated in IoT solutions and because of the high data rates that must be supported at the very edge of a network, IoT also requires embedded computing with low-power processors for preliminary data ingestion and filtering. Data processing at the edge accomplishes two things: firstly, it allows elimination of data that does not need to be transmitted to the central cloud-based data lake. Secondly, it supports preliminary real-time processing of acquired data that can be used for device monitoring and control with immediate feedback and very low latency. Additionally, computing at the edge should be a prerequisite for enabling security of devices and the data at the time of acquisition.
IOT and cloud computing fit together like a hand in a glove. This is only natural with the highly distributed and very dynamic nature of IoT devices and IoT data. Cloud infrastructure provides the most versatile, flexible and adaptable platform for an IoT repository and processing system. Cloud vendors including Amazon (AWS), Microsoft (Azure), IBM (SoftLayer) and Alphabet (Google Compute Engine) are racing to implement IoT capabilities, APIs, and advanced analytics and machine learning solutions in their public cloud environments. For reasons of control and to meet privacy and regulatory requirements, many companies will choose to implement private cloud services as well. Hybrid cloud services will play an important role in IoT.
When it comes to infrastructure within IoT clouds and at the edge, one can imagine every type of processor, network and protocol, servers and storage playing a role – both in distributed and centralized fashions – for IoT environments. Shared APIs and protocols are critical to promote interoperability. End-to-end security is as well an imperative; security is needed within every device and at each and every layer and sub-layer of the solution.
If anything deserves the term Big Data it is IoT. Billions and billions of devices are becoming Internet-enabled and the number of devices engaged in IoT applications will soon exceed the number of people on Earth. Because there are now many Big Data solutions available in public clouds this reinforces the cloud as a natural repository for IoT-generated Big Data lakes.
Analytics and machine learning will be heavily used to extract maximum value from the large amount of data acquired. A very wide range of business intelligence, analytics and machine learning techniques will be required. We foresee that IoT will be a big driver for machine learning advances. Analytics and machine learning will support everything from better operations of the connected devices to better information on how devices are utilized and new value-added services enabled by the device manufacturers.
There is a wide array of potential IoT applications covering every industry: Transportation, Retail, Manufacturing, Energy, Finance, Smart Cities, Healthcare, Agriculture, Government and other areas. Consumer apps are found in areas such as wearables, fitness, smart homes, electronics, and gaming.
Benefits from IoT applications will include improved operational efficiency and reliability, insight into usage patterns, and opportunities for increased revenue and better product design for manufacturers. Just as today we cannot imagine life without the Internet, we will not be able to imagine life without IoT by the beginning of the next decade.
It’s difficult to think of an area that requires a more holistic and converged view than IoT and that is not already a natural subset or example of IoT. Robotics? Drones? 3D printing? …. Every device of value should benefit from being plugged into the Internet, if only for maintenance and monitoring purposes, and these IoT-enabled devices will become available to participate in other IoT apps. At the other end of the data flow, big value comes from analytics services that are applied to a pool of devices and the streaming data they provide.
IT and IoT will become inseparable. IoT requires, incorporates, and benefits from all of the other major themes in IT today and thus we see it as representing the Ultimate Convergence at present.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Last week, in Part 1 of this two-part blog, we looked at trends in Big Data and analytics, and started to touch on the relationship with HPC (High Performance Computing). In this week’s blog we take a look at the usage of Big Data in HPC and what commercial and HPC Big Data environments have in common, as well as their differences.
High Performance Computing has been the breeding ground for many important mainstream computing and IT developments, including:
The Web
Cluster computing
Cloud computing
Hi-quality visualization and animation
Parallel computing
and arguably, Big Data itself
Big Data has indeed been a reality in many HPC disciplines for decades, including:
Particle physics
Genomics
Astronomy
Weather and climate modeling
Petroleum seismic processing
Horseshoe Falls (portion of Niagara Falls on Canadian side)
All of these fields and others generate massive amounts of data, which must be cleaned, calibrated, reduced and analyzed in great depth in order to extract knowledge. This might be a new genetic sequence, the identification of a new particle such as the Higgs Boson, the location and characteristics of an oil reservoir, or a more accurate weather forecast. And naturally the data volumes and velocity are growing continually as scientific and engineering instrumentation becomes more advanced.
A recent article, published in the July 2015 issue of the Communications of the ACM, is titled “Exascale computing and Big Data”. Authors Daniel A. Reed and Jack Dongarra note that “scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics”.
(n.b. Exascale is 1000 x Petascale, which in turn is 1000 x Terascale. HPC and Big Data are already well into the Petascale era. Europe, Japan, China and the U.S. have all announced Exascale HPC initiatives spanning the next several years.)
What’s in common between Big Data environments and HPC environments? Both are characterized by racks and racks of commodity x86 systems configured as compute clusters. Both environments have compute system management challenges in terms of power, cooling, reliability and administration, scaling to as many as hundreds of thousands of cores and many Petabytes of data. Both are characterized by large amounts of local node storage, increasing use of flash memory for fast data access and high-bandwidth switches between compute nodes. And both are characterized by use of Linux OS operating systems or flavors of Unix. Open source software is generally favored up through the middleware level.
What’s different? Big Data and analytics uses VMs above the OS, SANs as well as local storage, the Hadoop (parallel) file system, key-value store methods, and a different middleware environment including Map-Reduce, Hive and the like. Higher-level languages (R, Python, Pig Latin) are preferred for development purposes.
HPC uses C, C++, and Fortran traditional compiler development environments, numerical and parallel libraries, batch schedulers and the Lustre parallel file system. And in some cases HPC systems employ accelerator chips such as Nvidia GPUs or Intel Xeon Phi processors, to enhance floating point performance. (Prediction: we’ll start seeing more and more of these used in Big Data analytics as well – http://www.nvidia.com/object/data-science-analytics-database.html).
But in both cases the pipeline is essentially:
Data acquisition -> Data processing -> Model / Simulation -> Analytics -> Results
The analytics must be based on and informed by a model that is attempting to capture the essence of the phenomena being measured and analyzed. There is always a model — it may be simple or complex; it may be implicit or explicit.
Human behavior is highly complex, and every user, every customer, every patient, is unique. As applications become more complex in search of higher accuracy and greater insight, and as compute clusters and data management capabilities become more powerful, the models or assumptions behind the analytics will in turn become more complex and more capable. This will result in more predictive and prescriptive power.
Our general conclusion is that while there are some distinct differences between Big Data and HPC, there are significant commonalities. Big Data is more the province of social sciences and HPC more the province of physical sciences and engineering, but they overlap, and especially so when it comes to the life sciences. Is bioinformatics HPC or Big Data? Yes, both. How about the analysis of clinical trials for new pharmaceuticals? Arguably, both again.
So cross-fertilization and areas of convergence will continue, while each of Big Data and HPC continue to develop new methods appropriate to their specific disciplines. And many of these new methods will crossover to the other area when appropriate.
The National Science Foundation believes in the convergence of Big Data and HPC and is putting $2.4 million of their money into this at the University of Michigan, in support of various applications including climate science, cardiovascular disease and dark matter and dark energy. See:
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Data volumes, velocity, and variety are increasing as consumer devices become more powerful. PCs, smart phones and tablets are the instrumentation, along with the business applications that continually capture user input, usage patterns and transactions. As devices become more powerful each year (each few months!) the generated volumes of data and the speed of data flow both increase concomitantly. And the variety of available applications and usage models for consumer devices is rapidly increasing as well.
Are the Big Data and HPC disciplines converging or diverging?
Holding more and more data in-memory, via in-memory databases and in-memory computing, is becoming increasingly important in Big Data and data management more broadly. HPC has always required very large memories due to both large data volumes and the complexity of the simulation models.
Igauzu Falls: By Mario Roberto Duran Ortiz Mariordo (Own work) CC BY 3.0, via Wikimedia Commons
Volume and Velocity and Variety
As is often pointed out in the Big Data field, it is the analytics that matters. Collecting, classifying and sorting data is a necessary prerequisite. But until a proper analysis is done, one has only expended time, energy and money. Analytics is where the value extraction happens, and that must justify the collection effort.
Applications for Big Data include customer retention, fraud detection, cross-selling, direct marketing, portfolio management, risk management, underwriting, decision support, and algorithmic trading. Industries deploying Big Data applications include telecommunications, retail, finance, insurance, health care, and the pharmaceutical industry.
There are a wide variety of statistical methods and techniques employed in the analytical phase. These can include higher-level AI or machine learning techniques e.g. neural networks, support vector machines, radial basis functions, and nearest neighbor methods. These imply a significant requirement for a large number of floating point operations, which is characteristic of most of HPC.
For one view on this, here is a recent report on InsideHPC.com and video on “Why HPC is so important to AI”
If one has the right back-end applications and systems then it is possible to keep up with the growth in data and perform the deep analytics necessary to extract new insights about customers, their wants and desires, and their behavior and buying patterns. These back-end systems increasingly need to be of the scale of HPC systems in order to stay on top of all of the ever more rapidly incoming data, and to meet the requirement to extract maximum value.
In Part 2 of this blog series, we’ll look at how Big Data and HPC environments differ, and at what they have in common.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Long-term planning is an art. But it might take a real scientist to tackle a hundred-year planning horizon!
Frank Wilczek is a Nobel Prize winner in theoretical physics, awarded for his work in quantum chromodynamics (quarks, to you and me). He is currently the Herman Feshbach Professor of Physics at M.I.T.
FRANK WILCZEK, Professor of Physics at MIT and 2004 Nobel Laureate, at a conference
Professor Wilczek was invited to speak at Brown University’s 250th anniversary last year, and was asked to make predictions about the future of physics and technology 250 years from now. Considering that a much too difficult assignment, he modified (re-normalized in physics terms) the assignment to looking forward into the next century.
We won’t look here at his predictions for advancement in physics, many of which have to do with further unification of the laws of physics, such as supersymmetry, but instead focus on long-term planning for technology and his predictions in that area. His paper “Physics in 100 Years” is available here: http://arxiv.org/pdf/1503.07735.pdf and includes both the physics and technology predictions and other speculations about the future of humanity.
Here are some of his technology predictions (quotes from the paper are shown in italics) along with our elaboration, interpretation and reflections.
Microscale
Calculation will increasingly replace experimentation in design of useful materials, catalysts, and drugs, leading to much greater efficiency and new opportunities for creativity.
Computation is key to the nanoscale revolution for developing super-strong yet highly flexible and lightweight materials that can be 3-D printed for a wide variety of applications. And rapid computation is key to developing new drugs specific to individuals’ genetic makeup (targeted gene therapies).
Calculation of many nuclear properties from fundamentals will reach < 1% accuracy, allowing much more accurate modeling of supernovae and of neutron stars. Physicists will learn to manipulate atomic nuclei dexterously, as they now manipulate atoms, enabling (for example) ultra-dense energy storage and ultra-high energy lasers.
Currently, all we are really able to do at the nuclear level is build fission reactors and fission or fusion bombs. As one example, hydrogen fusion will become economically viable during this century, liberating tremendous amounts of energy from deuterium and tritium (heavy hydrogen nuclei) extracted from water, but with lower associated risks as compared to nuclear reactors using uranium.
Mesoscale
Capable three-dimensional, fault-tolerant, self-repairing computers will be developed. In engineering those features, we will learn lessons relevant to neurobiology.
The human brain is a 3-D construct with an extremely complex network and employing high degrees of parallelism, which is key to its processing speed and thus intelligence. Computers as systems are today packaged to some extent in 3-D, but are intrinsically based around 2-dimensional CPU chips and 2-D memory chips. These chips are connected one to the other with simple networks. In the future CPUs, together with their associated memory, will be designed with 3-D architectures, allowing for much faster speeds, much higher connectivity and very much greater memory bandwidth. Quantum computing technology based on more robust qubits, rather than bits, will be well-established, allowing for tremendous speedups for certain classes of algorithms. The image below is of the CPU chip from the first line of commercially available quantum computers. One of these DWave systems is operated jointly by Google and the NASA Advanced Supercomputing Facility in Mountain View, California.
DWave_128chip”DWave 128chip” by D-Wave Systems, Inc. – D-Wave Systems, Inc.. Licensed under CC BY 3.0 via Wikimedia Commons
Self-assembling, self-reproducing, and autonomously creative machines will be developed. Their design will adapt both ideas and physical modules from the biological world.
We’re talking intelligent robots, here, folks! And other autonomous, intelligent, and yes, self-reproducing machines, some very tiny (able to enter the bloodstream for medical purposes), others very large (see macroscale). Artificial organs. Asteroid mining machines. Robot armies (war without human casualties?). The possibilities are endless. Asimov’s 3 laws of robotics will be enforced.
Macroscale
Bootstrap engineering projects wherein machines, starting from crude raw materials, and with minimal human supervision, build other sophisticated machines – notably including titanic computers – will be underway.
Future supercomputers will self-assemble, with limited human oversight in the assembly process. Programming will have much higher levels of machine assistance, with problem statements represented at a very high level. Machinery and vehicle production will be almost entirely automated.
A substantial fraction of the Sun’s energy impinging on Earth will be captured for human use.
The deserts will bloom with advanced solar cells and superconducting transmission lines. Humankind will have settled and begun working in the inner solar system, including the Moon,Mars, one or more major asteroids, and one or more of Jupiter’s moons (e.g. Europa, Callisto).
Imagine how much has changed in the past 100 years. No one had flown on a commercial aircraft. Very few people had telephones or automobiles or radios. And consider that the pace of discovery, knowledge acquisition and technological development is today much higher, and still accelerating. A 100 years from now, average human lifetimes should exceed a century, based on revolutionary medical advances and ever safer transportation.
We’d be interested to hear from you, what are your thoughts on the state of technology a century from now? Please comment.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
This is the final entry of a three-part blog series on Growing in the the Asia-Pacific (APAC) marketplace. In the first entry we discussed the market dynamics for 14 major countries, and presented statistics that indicate that the major share, over 60%, of American exports are sent to developed countries such as Japan, Australia and Singapore. The exports to developed countries handily exceed the share exported to developing countries in Asia such as China and India. This is something that small and medium-sized companies in North American and Europe should consider as they plot their expansion plans for APAC.
In the second entry we addressed the issues of cultural factors, which differ considerably across the region – just think a moment about the differences between Korea, Australia, and India. I suggested it is important to consider each country in its own right as you put together business plans.
In this third blog entry I look more specifically at an important consideration for business in the region – the unfortunate fact of corruption. There is an extremely wide variation in the level of corruption across the region. I tie together the business transparency score with the market potential as addressed in the first blog entry to arrive an an overall opportunity score for each of 14 nations. This is based not simply on population or GDP, but rather on openness and transparency of doing business combined with today’s potential market size, with US exports to each nation as a proxy for the latter.
Let’s look at the important consideration of transparency and openness of business practices. A large portion of business in the region is with governments or government-owned or influenced companies. This is even more so the case in developing nations. To get a feeling for this we take a look at the Corruption Perceptions Index as formulated and rated by Transparency International. The 6 nations in APAC with the highest scores, meaning least corrupt, are New Zealand, Singapore, Australia, Hong Kong, Japan and Taiwan. In fact, all of these have better scores than the US, with the exception of Taiwan. These are easier places to do business, and one can expect better margins in these locations, both because they are more developed economies, and because they are more ethical.
A Go Smart strategy would consider both the import market potential and the ease of doing business in a given location. In the Table we have created an Orion Figure of Merit indicator that combines the volume of imports from the US with the transparency score, as a way to pull these two major criteria together. Using this Orion Figure of Merit, the top 6 countries rank ordered are: Japan, next Singapore, and then China, Korea, Australia, and Hong Kong. In addition to being markets in their own right, Hong Kong and Singapore serve as gateways to business in China in the case of Hong Kong, and to Southeast Asia and India in the case of Singapore.
Table: APAC Import Statistics and Ease of Doing Business
With a Go Smart strategy we look first to focus on more developed markets, and affinity markets, where foreign companies have the opportunity to obtain higher operating margins and where the receptivity to, and experience of, importing US technology are greater.
Orion Marketing would be pleased to work with you to assist in your development of an insightful, Go Smart, business strategy as you seek to enter the Asia-Pacific market or successfully grow your existing business in the APAC theater.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
In the first entry of this 3-part series we discussed a Go Big strategy versus a Go Smart strategy, and looked at some rather surprising statistics on imports from the U.S. into various countries in the region. Yes, China and India have impressive growth rates and great potential, but if we look at 2009 import statistics into the 14 most important countries in the Asia Pacific region, we find that the major share at 63% ($247 billion) of the American exports to APAC went to developed nations such as Japan, Korea and Singapore and 37% ($148 billion) went to the developing nations.
Based on my experiences over the past quarter century of promoting American IT hardware, software, and services into 11 major country markets within APAC, during which time I have been based in Japan, Singapore and Thailand, I would suggest that growing in the APAC market provides a more complex and nuanced set of challenges than do the European or Latin American markets. This is probably the most diverse region on the planet. Cultures are even more diverse and more distinct, as are languages. Even the writing systems vary greatly, ranging from Chinese characters to Roman characters to a wide range of alphabetic scripts in India and Southeast Asia. English proficiency varies widely among countries, and among individuals within a country. While the APAC region is the world’s most dynamic economically, it has a rich mix of highly developed markets, markets in transition to the developed category, and developing markets.
It is important to consider each country on its own as one formulates and implements a go to market strategy. Success has to be built one country at a time. Relationships are exceptionally important in this part of the world. Asians have long lasting cultural, national, ethnic and religious identities and to succeed here, building relationships over time is essential. We need to do our homework and become as familiar as possible with the countries and cultures in which we do business. It is especially useful to become familiar with the etiquette in different countries so that you don’t cause offense or embarrass yourself. They typically won’t tell you what you did wrong! Most of you have Asians or Asian Americans in your companies; don’t forget to take advantage of their cultural knowledge of their particular nations and their contacts in the region.
One of the most difficult areas is determining with whom to partner and whom to hire. Because of the perceived difficulty, few Americans bother learning Chinese, Japanese, or other languages, and thus one can tend to feel comfortable hiring and partnering with those who have the best English skills. We may have well-honed evaluation skills for partners and personnel in the Western context, but may not be able to ‘read’ Asians as well. We continually need to be a better job of communicating from our side, so that we’re surprised less often when a deal doesn’t go through. Asians generally adopt a subtle, less direct approach, in delivering messages, and are often reticent to deliver a message at all!
Americans can be perceived as being in a rush to do business before the customer or partner is comfortable with you. In the US we are often more transaction oriented; in Asia they want to determine if they will have a reliable long-term partner. It takes time to build these relationships, but once they are built your follow-on business opportunities are on a more solid footing.
For small to mid-size American companies entering and growing in the Asian market the biggest challenges are, of course, building name and brand recognition, then getting the strategy right as to which geographies to focus on in which order, finding the right partners, and understanding and appreciating cultural and communication and business style issues.
As my Chinese American associate, Henry Fong, counsels in regard to approaching the market in China, “Do your homework up front, have the attitude that you are making a long-term investment, search carefully for the few partners that will be the right match for your company, and be patient, patient, patient.” I would suggest these words are good counsel across the markets in Asia.
Orion Marketing would be pleased to work with you to assist in your development of an insightful, Go Smart, business strategy as you seek to enter the Asia-Pacific market or successfully grow your existing business in the APAC theater.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
We are all aware that China and India are the two most populous nations on the planet, and that their economies boast impressive growth rates in the range of 8 to 10% per year. In the Asia-Pacific (APAC) region these two nations alone have about 2/3 of the area’s population. Most of us are also aware that China has just recently surpassed Japan to become the world’s second largest economy.
As we seek to grow our business in this most dynamic region of the world, what strategy should we pursue? A Go Big strategy might argue that we should focus on the two largest nations, and look to reap rewards primarily in those two. An alternative strategy, which we dub Go Smart, would look at issues beyond the population size and the size of the economies concerned. One way to refine our strategy is to understand the propensity of the major countries in the region to import high technology from US or other Western suppliers.
With a Go Smart strategy we might look first to focus on more developed markets, where foreign companies have the opportunity to obtain higher operating margins and where the receptivity to, and experience of, importing US technology are greater. These developed countries within APAC spend proportionately more of their GDP on imports from the US and Europe. Also, a number of these countries are not just markets in and of themselves, they are also gateways to doing business in China, India, and in Southeast Asia for cultural and historic reasons.
Let’s look at some statistics in Table 1 below for 14 of the most important countries in APAC. By population the 6 largest countries are China, India, Indonesia, Japan, the Philippines and Vietnam. Only one of these (Japan) is considered a developed country today; the others are in the developing category. By GDP the rank order for the top 6 is China, Japan, India, Australia, Korea (South) and Indonesia.
Table 1: APAC Population, GDP, and Import Statistics
But is GDP the most relevant statistic, or is it more insightful for an IT technology supplier to look at import numbers? For imports the ranking becomes China, Japan, India, Korea, Hong Kong and Singapore. And, if we further refine our analysis to look at imports from the US, the top 6 are China, Japan, Singapore, Korea, Taiwan and then India – a quite different ordering from both the population ranking and the GDP rank ordering. North Asia (China, Japan, Korea, Taiwan) generally dominates in imports from the US, but Singapore, the gateway to Southeast Asia, is found at number 3, well ahead of India.
Orion Marketing would be pleased to work with you to assist in your development of an insightful, Go Smart, business strategy as you seek to enter the Asia-Pacific market or successfully grow your existing business in the APAC theater. In part two of this three part blog series, we will look at some personal experiences in the Asia-Pacific marketplace.
Stephen Perrenod has lived and worked in Asia, the US, and Europe and possesses business experience across all major geographies in the Asia-Pacific region. He specializes in corporate strategy for market expansion, and cryptocurrency/blockchain on a deep foundation of high performance computing (HPC), cloud computing and big data. He is a prolific blogger and author of a book on cosmology.
Jesse Owens, 4 gold medals, 1936 Olympics
