> Related to this, I will not be commenting on any self-reported AI competition performance results for which the methodology was not disclosed in advance of the competition.
Great set of observations, and indeed it's worth remembering that the specific details of assistance and setup make a difference of several orders of magnitude. And ha, he edited the last post in the thread to add this comment:
> Related to this, I will not be commenting on any self-reported AI competition performance results for which the methodology was not disclosed in advance of the competition. (3/3)
(This wasn't there when I first read the thread yesterday 18 hours ago; it was edited in 15 hours ago i.e. 3 hours later.)
It's one of the things to admire about Terence Tao: he's always insightful even when he comments about stuff outside mathematics, while always having the mathematician's discipline of not drawing confident conclusions when data is missing.
I was reminded of this because of a recent thread where some HN commenter expected him to make predictions about the future (https://news.ycombinator.com/item?id=44356367). Also reminded of Sherlock Holmes (from A Scandal in Bohemia):
> “This is indeed a mystery,” I remarked. “What do you imagine that it means?”
> “I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
Edit: BTW, seeing some other commentary (here and elsewhere) about these posts is very disappointing — even when Tao explicitly says he's not commenting about any specific claim (like that of OpenAI), many people seem to be eager to interpret his comments as being about that claim: people's tendency for tribalism / taking “sides” is so great that they want to read this as Tao caring about the same things they care about, rather than him using the just-concluded IMO as an illustration for the point he's actually making (that results are sensitive to details). In fact his previous post (https://mathstodon.xyz/@tao/114877789298562646) was about “There was not an official controlled competition set up for AI models for this year’s IMO […] Hopefully by next year we will have a controlled environment to get some scientific comparisons and evaluations” — he's specifically saying we cannot compare across different AI models so it's hard to say anything specific, yet people think he's saying something specific!
This does a great job illustrating the challenges with arguing over these results. Those in the agi camp will argue that the alterations are mostly what makes the ai so powerful.
Multiple days worth of processing, cross communication, picking only the best result? That’s just the power of parallel processing and how they reason so well. Altering to a more standard prompt? Communicating with a more strict natural language helps reduce confusion. Calculator access and the vast knowledge of humanity built in? That’s the whole point.
I tend to side with Tao on this one but the point is less who’s right and more why there’s so much arguing past each other. The basic fundamentals of how to judge these tools aren’t agreed upon.
I feel like everyone who treats AGI as "the goal" is wasting energy that could be applied towards real problems right now.
AI in general has given humans great leverage in processing information, more than we have ever had before. Do we need AGI to start applying this wonderful leverage toward our problems as a species?
As a graduate student I was actually given tests that more closely resembled the second scenario the auther described. Difficult problems in GR, a whole weekend to work on them, no limits as to who or what references I consulted.
This sounds great until you realize there are only a handful of people on earth that could offer any help, also the proofs you will write are not available in print anywhere.
I asked one of those questions of Grok 4 and its response was to issue "an error". AFAIK, in many results quoted for AI performance, filling the answer box yields full marks but I would have recieved a big fat zero had I done the same.
I like this approach in general for understanding AI tools.
There are lots of things computers can do that humans can't, like spawn N threads to complete a calculation. You can fill a room with N human calculators and combine their results.
If your goal is to just understand the raw performance of the AI as a tool, then this distinction doesn't really matter. But if you want to compare the performance of the AI on a task against the performance of an individual human you have to control the relevant variables.
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[ 3.0 ms ] story [ 26.7 ms ] threadwhat a badass
> Related to this, I will not be commenting on any self-reported AI competition performance results for which the methodology was not disclosed in advance of the competition. (3/3)
(This wasn't there when I first read the thread yesterday 18 hours ago; it was edited in 15 hours ago i.e. 3 hours later.)
It's one of the things to admire about Terence Tao: he's always insightful even when he comments about stuff outside mathematics, while always having the mathematician's discipline of not drawing confident conclusions when data is missing.
I was reminded of this because of a recent thread where some HN commenter expected him to make predictions about the future (https://news.ycombinator.com/item?id=44356367). Also reminded of Sherlock Holmes (from A Scandal in Bohemia):
> “This is indeed a mystery,” I remarked. “What do you imagine that it means?”
> “I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
Edit: BTW, seeing some other commentary (here and elsewhere) about these posts is very disappointing — even when Tao explicitly says he's not commenting about any specific claim (like that of OpenAI), many people seem to be eager to interpret his comments as being about that claim: people's tendency for tribalism / taking “sides” is so great that they want to read this as Tao caring about the same things they care about, rather than him using the just-concluded IMO as an illustration for the point he's actually making (that results are sensitive to details). In fact his previous post (https://mathstodon.xyz/@tao/114877789298562646) was about “There was not an official controlled competition set up for AI models for this year’s IMO […] Hopefully by next year we will have a controlled environment to get some scientific comparisons and evaluations” — he's specifically saying we cannot compare across different AI models so it's hard to say anything specific, yet people think he's saying something specific!
Multiple days worth of processing, cross communication, picking only the best result? That’s just the power of parallel processing and how they reason so well. Altering to a more standard prompt? Communicating with a more strict natural language helps reduce confusion. Calculator access and the vast knowledge of humanity built in? That’s the whole point.
I tend to side with Tao on this one but the point is less who’s right and more why there’s so much arguing past each other. The basic fundamentals of how to judge these tools aren’t agreed upon.
AI in general has given humans great leverage in processing information, more than we have ever had before. Do we need AGI to start applying this wonderful leverage toward our problems as a species?
This sounds great until you realize there are only a handful of people on earth that could offer any help, also the proofs you will write are not available in print anywhere.
I asked one of those questions of Grok 4 and its response was to issue "an error". AFAIK, in many results quoted for AI performance, filling the answer box yields full marks but I would have recieved a big fat zero had I done the same.
There are lots of things computers can do that humans can't, like spawn N threads to complete a calculation. You can fill a room with N human calculators and combine their results.
If your goal is to just understand the raw performance of the AI as a tool, then this distinction doesn't really matter. But if you want to compare the performance of the AI on a task against the performance of an individual human you have to control the relevant variables.