> cmix has surpassed the winning entry of the Hutter Prize (but exceeds the memory limits of the contest)...cmix uses a similar neural network architecture to p

> cmix has surpassed the winning entry of the Hutter Prize (but exceeds the memory limits of the contest)...cmix uses a similar neural network architecture to paq8l. cmix uses a four layer feedforward network with 414,273 neurons (paq8l uses a three layer network with 3,633 neurons). This is something I've suspected for a while: the Hutter Prize has become obsolete. I agree with the 'prediction is intelligence' paradigm, but the Hutter Prize cannot show any meaningful progress in AI for the simple reason that the corpus is too small and the resource limits are too stringent. 4 layers with 414k neurons is nowhere near what deep learning researchers use to create intelligent systems. You couldn't fit char-rnn into the Hutter Prize constraints! At this point, all the prize incentivizes is finding an algorithm which fits into the allotted resources, no matter how dumb and inferior that algorithm is to the state of the art which requires more resources to run. Bit-twiddling to optimize the current approaches may be fun for a certain kind of people, but it's hard to see how the contest has contributed at all to progress in AI in the past decade, which was the original purpose. Perhaps what is necessary is a Hutter Prize 2: expand the corpus to the modern English Wikipedia (not one from a decade ago), perhaps add in other language corpuses to increase it further to get a multi-gigabyte corpus, and then increase the resource limits drastically (32GB RAM for starters so cmix can get in), and shut down the old one for diminishing returns. A desktop machine these days can certainly support a decent amount of RAM and computation (on Newegg, you can get a desktop tower refurb with 32GB Ram for <$1000), so there's no cost excuse if one can afford to offer thousands of euros as a prize...