The goals of the Hutter prize are what I wrote mostly in 2006. https://mattmahoney.net/dc/rationale.html
I am retired now but I have been toying with some ideas for a new Hutter prize submission. Since I'm on the judging committee, I am not eligible for prize money. But a well documented open source program could still be the basis for future submissions to speed research. Current submissions are based on XWRT dictionary tokenization and PAQ context modeling. I have some ideas for memory efficient context modeling that I want to test. So far I have just been experimenting with decoding XML, HTML, and Wiki markup and small dictionary encoding using byte pair encoding. The current leader sorts the articles by topic, and so far I haven't been able to improve on it. I have been following the unfriendly / unaligned AI debates on SL4, the Singularity list, and LessWrong for about the last 25 years. I disagree with the premise that AI is a goal directed optimization process that will rapidly self improve to superhuman intelligence and kill us all because we got the goals wrong. AI is a model of human behavior without goals. I think the most immediate threat is that AI kills us by giving us everything we want. But I admit I only came to that conclusion recently after LLMs started passing the Turing test and creating a world where you don't know (or care) what's real and what's fake, what's human and what's AI. Nobody thought about social isolation and population collapse before it started happening. I don't regret my efforts toward creating this world because I'm sure it would have happened without me. All I can do is study the threat so I can warn people. And the best way to study a threat is to help create it. -- Matt Mahoney, [email protected] On Thu, Sep 4, 2025, 8:20 PM Rob Freeman <[email protected]> wrote: > It strikes me you are just producing words to obfuscate the issue Matt. > > Some insights might apply, Wolpert's Theorem on... basically it seems to > me to be about non-abstraction. Or alternate, contradictory abstraction. My > theme for years. Interpreted by me as a power of chaos. But you insist on > interpreting it in a purely negative way. You can only interpret it to mean > that we have to keep doing whatever we're doing now. > > Control might be impossible, yes. But that is not creativity to you. It > just means we have to keep doing what we're doing now. > > It seems to me that the true goals of the Hutter Prize are being > re-evaluated to be whatever has turned out to work elsewhere while it was > working on something else. > > Most important is where the goals of a current research agenda are driving > us to go next. And there again the Hutter Prize seems to be failing. > Because inspired by the Hutter Prize, it seems you can only think of > continuing to do what is being done now. Why do anything else? You say to > Dorian, current language models are correct right now... (correct at doing > whatever you've decided the Hutter Prize was always about doing.) > > Where is your forward research agenda amid all this negativity? > > On Thu, Sep 4, 2025 at 11:40 PM Matt Mahoney <[email protected]> > wrote: > >> People have been pursuing structured knowledge representation since the >> 1950s but it's a dead end. The Cyc project was the biggest failure because >> it lacked a natural language interface and a learning algorithm. More >> recent approaches like YKY's logic systems, Ben Goertzel's >> Webmind/Novamente/OpenCog/Hyperon and Pei Wang's NARS use hybrid systems of >> probabilistic logic but still require expensive hand coding of knowledge, >> which didn't seem to be happening before they went quiet on this list years >> ago. >> >> The Hutter prize is not about representing knowledge. It's about >> intelligence as defined by Turing. It would be nice if we could look at >> giant matrices to understand what real world knowledge it represents, but >> we can't because it violates Wolpert's theorem. The better a system can >> predict your actions, the worse you are at predicting its actions. You can >> have intelligence or you can have control, but not both. >> >> Control requires predictability. Prediction tests understanding. >> Prediction measures intelligence. Compression measures prediction. >> >> -- Matt Mahoney, [email protected] >> > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + > delivery options <https://agi.topicbox.com/groups/agi/subscription> > Permalink > > <https://agi.topicbox.com/groups/agi/Ta9b77fda597cc07a-M6eebbd8d472bfe1f56a19a42> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta9b77fda597cc07a-M31e7b7ef0cd0f86e246271f7 Delivery options: https://agi.topicbox.com/groups/agi/subscription
