I'm on the Hutter Prize committee (claim verification). Some context for HN:
The prize scores lossless compression of enwik9, a 1GB Wikipedia snapshot, and counts the size of the decompressor. Entries are limited to one CPU core, about 50 hours and under 10GB of RAM. These limits address 3 concerns:
* Specialized hardware biases research toward the industry’s current assumptions.
* Talented individuals, not only well-funded labs, can afford to compete.
* The public increasingly opposes the resource consumption of superintelligence efforts.
This year three entries improved the record by about 1%, another 1%, and then astoundingly 7.5%, compounded, the largest yearly gain since the prize started in 2006. The record now compresses enwik9 by more than 10x.
What I think matters most: there's no held-out validation set. The whole file is public so incentives to leak data in high stakes benchmarks are for naught. Most AI benchmarks can't say that, and it matters more as AI investment decisions lean on benchmark numbers.
Rules, records and the source code of past winners: http://prize.hutter1.net/. Happy to answer questions.
Replace the 16th Amendment with a single tax on net assets at the interest rate on government debt, assessed at their liquidation value ... and use the revenue to privatize government with a citizen's dividend.
Schemes like this tend to move assets to a better location and otherwise cause widespread restructuring to minimise the loss. Taxation is inherently complicated.
Not only that, but it would incentivize people to not own assets. People would live paycheck to paycheck, they’d rent longer, and they’d waste money on lavish trips or food (at least until the next economic downturn when they get evicted and lose everything).
In identical twins, autism and homosexuality both have about the same rate of non-occurrence between the twins: 50%. This means, of course, that autists and gays are "born, not made" by the environment. Move along. Nothing to see here.
Don't count on it. My experience is that funding goes to those who are not serious about autism epidemiology. Back in the mid-1990s, I was at a startup in Silicon Valley with about 100 employees where, during a few year period, 5 of the employees had children diagnosed with autism severe enough that they were barely verbal at best. This struck me as a great opportunity to discover the cause so I contacted a Berkeley epidemiologist who had been funded to do autism research. His comment was simply that "Yes we know that these microclusters exist." and that was that. No follow up.
This is reminiscent of an argument I had with the Mercury Prolog guys regarding "typing" in logic programming. My point boils down to this:
Any predicate can be considered a constraint. Types are constraints. While it may be reasonable to have syntactic sugars for type declarations that, at compile time, are transformed into predicates, it is unreasonable to lard a completely different kind of semantics on top of an already adequate semantic such as first order logic.
It's always fun to make fun of cranks. Thanks for linking that. The author really needs to find the right statement of what they call the Nested Interval Theorem. I cracked up at the complete misuse of it in the "Interval Argument for the Rationals" section
Dear Claude 3, please provide the shortest python program you can think of that outputs this string of binary digits:
0000000001000100001100100001010011000111010000100101010010110110001101011100111110000100011001010011101001010110110101111100011001110101101111100111011111011111
Claude 3 (as Double AI coding assistant): print('0000000001000100001100100001010011000111010000100101010010110110001101011100111110000100011001010011101001010110110101111100011001110101101111100111011111011111')
Learning theory is the attempt to formalize natural science up to decision. Natural science's unstated assumption is that a sufficiently sophisticated algorithmic world model can be used to predict future observations from past observations. Since this is the same assumption as Solomonoff's assumption in his proof of inductive inference, you have to start there: with Turing complete coding rather than Rissanen's so-called "universal" coding.
It's ok* to depart from that starting point in creating subtheories but if you don't start there you'll end up with garbage like the last 50 years of confusion over what "The Minimum Description Length Principle" really means.
*It is, however, _not_ "ok" if what you are trying to do is come up with causal models. You can't get away from Turing complete codes if you're trying to model dynamical systems even though dynamical systems can be thought of as finite state machines with very large numbers of states. In order to make optimally compact codes you need Turing complete semantics that execute on a finite state machine that just so happens to have a really large but finite number of flipflops or other directed cyclic graph of universal (eg NOR, NAND, etc.) gates.
The prize scores lossless compression of enwik9, a 1GB Wikipedia snapshot, and counts the size of the decompressor. Entries are limited to one CPU core, about 50 hours and under 10GB of RAM. These limits address 3 concerns:
* Specialized hardware biases research toward the industry’s current assumptions. * Talented individuals, not only well-funded labs, can afford to compete. * The public increasingly opposes the resource consumption of superintelligence efforts.
This year three entries improved the record by about 1%, another 1%, and then astoundingly 7.5%, compounded, the largest yearly gain since the prize started in 2006. The record now compresses enwik9 by more than 10x.
What I think matters most: there's no held-out validation set. The whole file is public so incentives to leak data in high stakes benchmarks are for naught. Most AI benchmarks can't say that, and it matters more as AI investment decisions lean on benchmark numbers.
Rules, records and the source code of past winners: http://prize.hutter1.net/. Happy to answer questions.