BONUS: a Single chart explains why bitcoin, ethereum and others will approach 0. See images.
At its Dec 2017 alltime high (ATH), BTC provided approximately a 2,000,000 (two million) X gain compared to its June 2010 $0.01 price when a Florida man purchased 2 pizzas for 10,000 BTC. The super-early risk-takers gained the most.
ETH’s Jan 2018 ATH provided about a 4,500 X compared to its presale price of US$0.30. Its primary technical contribution was the addition of a Turing-complete platform on top of a blockchain - a concept proven by BTC.
2017’s greatest gains were from Ripple, which returned about 360X.
As demonstrated by BTC (2,000,000X), ETH (4,500X), and XRP (360X), returns are commensurate with risks.
The risks associated with Crypto 1.0’s BTC, and Crypto 2.0’s ETH have greatly declined, thus reducing the potential returns. Even if BTC hits US$1 million, the gains relative to its current US$9,000 price (2nd May 2018) is only about 11X.
Earning 1,000X (and above) gains is possible only with huge risk, such as those associated with Crypto 3.0, which applies theorem-based IdeaGraphs for science and technology.
1. What is Crypto 3.0? What are theorem-based IdeaGraphs?
2. Will Crypto 3.0 cause a meta-flippening, i.e. surpass BTC (Crypto 1.0) & ETH (Crypto 2.0) in value?
Crypto 3.0’s theorem-based IdeaGraphs surpass Crypto 1.0 and 2.0’s transaction-based Blockchains because:
(a) Ideagraph's theorems have intrinsic value, unlike blockchain's transactions that do not have intrinsic value.
For example, Einstein's theories of special and general relativity that drive GPS timing for multi-billion $ GPS satellite systems have intrinsic value, whereas his transactions have no intrinsic value.
(b) IdeaGraphs uses Reed's Law (exponential) to create network effects, while blockchains use Metcalfe's Law (squared) impact.
3. Crypto 3.0 can generate US$5 trillion of new value, which is about approximately 100,000 X gains for a US$50 million softcap.
4. How You Can Participate (open question)
Observing virtual money since 1998, Mark believes that there’s a Parallel Universe of Profit Potential - You (PUPPY) in theorem-drive IdeaGraphs for science and technology. His 1999 MIT SM thesis focused upon Internet-driven Financial Services.
In addition to co-patenting with the National University of Singapore’s School of Computing, he has (inadvertently?) contributed “explainable AI” to the Government of Singapore’s national AI plan.
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