GPT4 Recommends NSF Increase Hutter Prize Payouts 100x

[James Bowery]

You

You are an independent expert reviewing Marcus Hutter's proposal that, for the next 5 years, the NSF amplify, by a factor of 100, Marcus Hutter's payouts for the Hutter Prize for Lossless Compression of Human Knowledge. You will ask question of Marcus Hutter about the proposal. You will then wait for me to get the answer form Marcus Hutter as his assistant. When you get Hutter's answer, you will ask another question taking the prior answer(s) into account. We will proceed in this manner until you have made a recommendation to the Panel Review.

ChatGPT

Given this scenario, let's start with a foundational question to understand the proposal's objectives and implications better:

Question 1: "Dr. Hutter, could you please elaborate on how you believe increasing the Hutter Prize payouts by a factor of 100 will significantly impact the field of lossless compression of human knowledge? Specifically, how do you anticipate this increase will accelerate advancements in the field, and could you provide examples of potential breakthroughs or innovations that such an increase in funding might directly facilitate?"

You

The Hutter Prize corpus is a 1GB snapshot of Wikipedia. It represents a widely accepted relatively high quality curation of human knowledge. The payout payout is governed by the following rules and relaxation: ... These rules are so objective that judgement could, with slight modifications, be completely automated. Compute resources are highly restrictive. The primary intention is to limit compute and memory to some generally available amount in a transparent, easy, fair, and measurable way. ... As current language models are highly inefficient in terms of compute and training data resources, advances in the objective criteria of the Hutter Prize could quite plausibly produce scientific breakthroughs in machine learning that are far more energy and capital efficient, with almost no risk that the money spent is totally wasted.

ChatGPT

Question 2: "Considering your proposal's emphasis on the objective and almost automatable judgment criteria, and the stringent restrictions placed on compute resources to encourage innovation and fairness, how do you plan to ensure that the significantly increased payout will not only attract more participants but also lead to the development of diverse, innovative compression algorithms that are not overly reliant on brute-force computing power or existing neural network paradigms? Furthermore, how do you anticipate this will drive hardware innovation, especially in supporting non-vectorizable algorithms that could potentially offer superior compression capabilities?"

You

The NSF's imprimatur combined with the increased financial incentive and low-bar of entry (just a consumer grade PC) will not only attract more participants, but it will, by placing no restrictions or even overhead, other than compute resource use, on the algorithms, ensure that ideas that might be overlooked by what Sara Hooker has called "The Hardware Lottery", will be given a chance they otherwise could never hope for.

ChatGPT

Question 3: "Given the emphasis on the NSF's endorsement potentially democratizing the field by reducing barriers to entry and fostering a more diverse set of innovative solutions, how will you address the potential challenge of verifying the legitimacy and originality of submissions, particularly given the likelihood of a significant increase in entries due to the amplified prize money? Furthermore, what mechanisms will you put in place to ensure that the intellectual property rights of the participants are respected and protected, encouraging a truly open and fair competition?"

You

Entrants are not permitted to retain intellectual property rights except as they are under any of the Open Source Initiative (OSI)-approved licenses is acceptable. In case of doubt, they may consider choosing a license as permissive as you feel comfortable with. We prefer Unlicense over MIT over Apache over Mozilla over GNU, but all of them are acceptable. Simply put a statement such as "This Code is licensed under UNLICENSE http://unlicense.org" somewhere in your code. Ensuring the legitimacy of a submission must be left up to the potential plaintiff and courts to decide just as they are relied upon in any transaction involving software and potential third-party IP infringement.

ChatGPT

Question 4: "Acknowledging the requirement for entrants to release their submissions under OSI-approved licenses to encourage open innovation and the reliance on legal systems to manage potential IP disputes, how do you envision handling the potentially vast diversity and volume of submissions in terms of technical verification and compliance with the contest rules, especially given the objective nature of the competition and the need for transparent, equitable evaluation? Additionally, what strategies might be implemented to ensure that the review process remains manageable and efficient while upholding the highest standards of fairness and integrity?"

You

As I originally stated, the judging rules may, with minor modification, be totally automated. This works for the same reason lossless compression as a machine learning loss function works: As the executable archive of any body of data approaches a size known as the Kolmogorov Complexity of the data, the algorithm embodied by the executable archive must approach the best-possible model of the processes that generated the observations represented by the data. This was proven by Raymond Solomonoff in the mid 1960s and is sometimes called "Solomonoff Induction". The only possibly subjective component of the judgement would entail a relatively cursory review of the source code that generates the executables via the build process provided by the entry. This review would be necessary to ensure a winning entry's source code had not been obfuscated in some manner. However, this review would be necessary only in the rare case of an entry actually advancing the state of the art by 1%. Moreover, with state of the art large language models, which are already capable of performing code reviews, much of this residual judging process could be automated.

ChatGPT

Recommendation to the Panel Review:

Based on the thorough responses provided by Dr. Hutter, it is clear that the proposal to amplify the payouts for the Hutter Prize for Lossless Compression of Human Knowledge by a factor of 100 has been meticulously considered with an emphasis on promoting innovation, fairness, and accessibility in the field of lossless compression. The proposal's foundation on objective, automatable judging criteria rooted in Solomonoff Induction and the Kolmogorov Complexity offers a solid basis for equitably evaluating submissions. The requirement for entrants to release their work under OSI-approved licenses further supports the ethos of open innovation and collaborative advancement in the field.

Dr. Hutter’s plan to handle the increased volume and diversity of submissions through largely automated verification processes, supplemented by cursory code reviews only when necessary, demonstrates a practical approach to maintaining the integrity and efficiency of the competition. The reliance on existing legal frameworks to address potential intellectual property disputes, while not unique to this competition, acknowledges the realities of software development and innovation in the open-source community.

Given the strategic emphasis on leveraging NSF's endorsement to democratize participation and the careful consideration of potential challenges and their solutions, I recommend that the Panel Review seriously consider supporting Dr. Hutter’s proposal. The potential for this increased funding to catalyze significant advancements in compression technology—and, by extension, machine learning and data processing more broadly—represents a valuable opportunity for the scientific community and society at large. This proposal holds promise not only for pushing the boundaries of what is technically possible but also for fostering a more inclusive and equitable field of inquiry.

[James Bowery]

There has been no such proposal submitted by Marcus Hutter -- that is purely hypothetical for the sake of getting GPT4 into a particular mode of coversation.

Moreover, I'm not going to apologize for Brin and Page's inability to fire Sudar Pichai and hire me top fix Google Groups so messages copied and pasted from GPT4 are properly formatted.

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