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Interesting developments in use of AI in mathematics and writing
{Math}International Mathematical Olympiad is an international competion for high schoolers around the world. They compete in solving problems related to inequalities, number theory and geometry. It is the last category in which Google's AlphaGeometry leapfrogged the previous SOTA, reaching almost Chinese-team level of success.
It's method is intuitively attractive: it uses both unbiased but blind pattern finding skills associated with LLM today, and rigourous symbolic math honed by millenia of human efforts to find the greatest amount of pure truth. That the latter was included speaks to the fact that we are still at the centaur stage of AI, in that sometimes augmenting AI with what humans already know, allows it to perform better than not doing so.
In the future all AI will be unconstrained by human traditions and biases, thus it will be able to search a wider space, enabling it to beat humans at games humans invented. Such is already the case with AlphaGo. Euclidean geometry has more difficult rules, so some handholding is still needed.
{Writing}Akutagawa Prize is a literary prize expected to awarded twice each year. It is considered one of most prestigous such prizes in Japan. Previous winners include: 石原 慎太郎, 安部 公房, 遠藤 周作, and 大江 健三郎.
The latest winner, 九段 理江, won it for 東京都同情塔, a novel about a high-rise prison tower in futuristic Tokyo and its architect's intolerance of criminals, AI being a recurring theme. In the acceptance speech 九段さま admitted that 5% of the novel was copied verbatim from ChatGPT. Again centaur approach wins out against pure AI.
Had the author attempted to write the 144 pages by asking AI to do it instead, the result would be incoherent, as currently techology isn't there yet to hold in memory so great amounts of data. 九段さま judicious and moderate use of AI to augment, rather than replace, human writing seems to have served them well, beating out works written by only humans.
For once in my life, I will contend that a particular example of AI reaching competence comparable to peak humans is not that big of a deal.
Here's Paul Christiano claiming this could happen, and soon, and quite easily, in the primordial times of 2022:
https://www.lesswrong.com/posts/sWLLdG6DWJEy3CH7n/imo-challenge-bet-with-eliezer?commentId=jSnfYKAv3hxAPwWhH
So while I agree with the general thesis that AI is going to overtake humans, even our best, and quite soon (3-10 years for ASI is about my 95% CI, 50:50 by 2028, as in any an AGI that is better than the set of all humans at all cognitive tasks), this shouldn't make you update particularly hard in either direction.
The arrival of GPT-4 prompted me to dust off my urge, present for a while, to write a novel. Not because it is as good a writer as me (it isn't), but I could see the writing on the cards since the GPT-3 days, and right now I give maybe 30% odds that GPT-5 will write a better novel on any topic I would wish to, including emulating my voice, and according to the majority of readers, do a better job at it.
It does, however, write better than the average human on any topic, if only because of how incompetent the average human is. GPT-2 was semi-convincingly replicating entire subreddits, even if the outputs were hilariously incoherent, and I think most of the default subs like /r/aww or /r/WorldNews would be improved if every human redditor commenting was replaced by an instance of GPT-4 (hopefully one not prompted to act like the average user there, and even then it's only pretending to be retarded). Have you seen the average email or high school essay? For most people, outsourcing that to GPT-4 is an unqualified improvement.
But yes, the strong expectation that I will one day be obsolete as a writer was a driving force for me knocking out a couple while I'm still relevant. Maybe it'll give me street cred in the posthuman future, like Usain Bolt has today even though a car from the 1930s could leave him in the dust. I was good at my passions, before AI replaced everyone.
Yeah, Christiano is absolutely right here. There are some sorts of problems which have significant components that are comparatively much simpler for machines than humans, for example:
This is not to say that it's trivial to make a computer be superhuman at these problems. Despite there being aspects that are very machine-friendly, there's still a lot of difficult work to be done to actually get a machine do them. But it shouldn't make you update particularly much; this is not an "AI is now smarter than IMO medalists" moment.
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