It doesn't matter why a liter of milk costs $1 - what matters is that it costs $1 now, it'll cost roughly $1 a year from now and in the interim, it'll still also cost $1. Predictability and consistency is a critical aspect of currency.
The actual numerical value is irrelevant.
You can't assign a fundamental value to the purchasing power of a bitcoin when treating it as a currency because there's nowhere in the world that bitcoin is used to denominate the sticker price of goods. If there was you could regress its value based on how much one bitcoin would buy you in terms of goods priced in it.
However, without that, you can only treat it as a purely speculative asset as jstolfi did. If that ever changes, our model will have to change. It has not, and IMO will not, even with El Salvador because its wildly fluctuating notional value determined predominantly by global speculators precludes it from being used to actually price things in a meaningful and consistent way.
[edit] Either way, the title of the write-up was 'Bitcoin as an investment' - currencies aren't an investment, so the analysis models it as an asset.
"what matters is that it costs $1 now, it'll cost roughly $1 a year from now and in the interim, it'll still also cost $1. Predictability and consistency is a critical aspect of currency."
Are the just reformulating the principles of evolution in digital terms, and essentially not providing any new insights at all?
Yes, intelligence has been created by evolution. That doesn't imply that any system that is subject to evolutionary forces will lead to the creation of intelligence (and not within a reasonable timeframe, either). The challenge is to create a system that is capable of evolving intelligence.
Afaik some biologists even think that the evolution of intelligence was rather unlikely and would not necessarily happen again under the same circumstances as on earth.
As a biologist and longtime dabbler machine learning and Bayesian methods, I tend to see intelligence as a manifestation of evolution. In the case of an organism, the improvement of the model (the genome) occurs through processes that are very similar to what we see in any kind of learning (real, brain based or "artificial", computer based).
Evolution and intelligence are inextricably linked. They are practically the same thing. This means that intelligence is probably a natural result of any system similar to those that support biologics. If you flow the right amount of energy through a substrate with complex enough building blocks, you'll eventually get life ~ which is just something smart enough to survive and feed off the available energy flows. In the world, this flow is radiation from the sun, while in a computer, it is governed by a more abstract loss or fitness function.
> Afaik some biologists even think that the evolution of intelligence was rather unlikely and would not necessarily happen again under the same circumstances as on earth.
Hmm. Can you provide a pointer to those biologists?
AFAIK, high intelligence has arisen more than once on Earth (Hominoids, Cetaceans, Octopuses), so I'm somewhat skeptical of that claim, but perhaps they're construing intelligence more narrowly (ie. only Homo Sapiens qualifies).
Jared Diamond talks about it in his books (don't remember which ones specifically). OK, granted, he is not officially a biologist, I guess, but at least a prominent writer on Evolution Theory.
> Well that has a prior on life even existing in the first place
True, the question of intelligent life evolving can be construed as either:
"Given that life exists, what is the probability of intelligence evolving?"
Or:
"Given that the universe exists, what is the probability of life arising and evolving intelligence?"
Both are actually interesting and important questions (cf. the Drake Equation and Fermi Paradox), but I am pretty comfortable asserting that in the context of this conversation the former interpretation is more apropos.
I'd say it's even less than that. They seem to be summarizing the ways the problem of teaching an agent to do anything (including be generally intelligent) can be formulated as a problem of maximizing a reward (hence the title).
Another way to look at it is, if we had a good enough function (e.g. a universal approximator) it can be made to model any behavior using numerical optimization. Which I think isn't very surprising, but apparently there is some arguments about it.
In fact, "if we had a good enough function" == "if we had sufficient funding". This refrain will resonate mightily in the willing ears of US congressfolk who want re-election and would rather talk about something other than Trump.
So welcome back to the future, and the $trillions the US spent on 20 years of space race and 50 years of cold war. The catchphrase that motivates the next 50 years of government/corporate funding will be...
Evolutionary algorithms are tricky, just like deep learning. It's not "just reformulating the principles of evolution in digital terms, and essentially not providing any new insights".
I switched from Vivaldi to Edge because unfortunately Vivaldi become unusably slow for me beyond a certain amount of open tabs (hopefully just a bug they'll fix eventually).
I miss the little search bar for tabs that Vivaldi shows in the vertical tabs view.
