Gary Marcus盘点Astra数学8大误区，冷静看待OpenAI新模型，别被'数学已解决'带偏
Gary Marcus在X上列出外界对OpenAI Astra数学结果的八种误解。他认为数学领域擅长验证与合成数据，因此Astra的数学能力不代表通用智能，并援引IBM Watson从问答转向医疗失败的例子。Astra的证明写作水平不及证明本身，也未必能可靠处理PDF提取或写视频脚本。Marcus还驳斥了Astra即奇点的说法，并称一次Fable运行不足以证明数学史被改写。
Don’t think I have seen more misconceptions around one model (I count 8) since the fantasies people ...
Don’t think I have seen more misconceptions around one model (I count 8) since the fantasies people had before GPT-5 was released. That turned out to be a letdown; so will Astra, for people who are dreaming that it is imminent ASI. Bookmark this. Gary Marcus @GaryMarcus Top eight misconceptions about OpenAI’s amazing new Astra math results. 1. Expertise in one domain does not at all guarantee expertise in all or even most domains. There is an important, principled reason to think that success on math is a special case which will not generalize as much people might hope. Math lends itself to two things: verification (using symbolic tools), and massive amounts of cheaply produced synthetic data where you can guarantee that the answers are correct. The same applies to coding — but it is not true in general. You can generate as many math facts as you want; you can’t simulate the open-ended world. You can verify math; you can’t verify a military strategy in the same way. OpenAI can do what Astra does in math because math allows for external tools to do verification and to create synthetic data. That doesn’t make Astra less impressive, but as we learned a decade ago from IBM’s shambolic and ultimately failed attempt to turn Jeopardy-winning Watson into a cancer-fighting machine, success in one domain does not guarantee success in all. 2. Yesterday's tweet and blog were marketing, not science. Neither of those nor the 249-page math article that went with them give any information about how this was accomplished. 3. Astra is good at some math but it is very doubtful that math is “solved” (as a lot of people on X seemed to believe). It seems to be good at certain kinds of math but quite possibly not all. In the newsletter version of this I give lots of examples where it might actually faill 4. Consistent with my general prediction that facility in math doesn’t guarantee universality, it appears that Astra’s proofwriting is not on par with the proofs themselves 5. I seriously doubt that Astra will magically solve all the things that don’t work reliably in current models. Will it be able to reliably extract numbers from arbitrary PDFs? Doubt it. Will it solve Sabine Hossenfelder’s desire to have AI write scripts for her YouTube series? Doubt it. 6. Astra is not (as Musk suggested) the Singularity. Enough said. (But see my recent essay on the topic; nothing has really changed). 7. It is absurd to claim that the Astra debut is “plausibly the most significant day in the history of mathematics” as a bunch of people went around saying, based on a quote from one run of Fable (which might give different answers if asked twice). There was no new theory, no new techniques, and as impressive as it is, it is not on remotely on par with the development of calculus, algebra, logarithms, probability, the decimal system, information theory, the concept of zero I doubt it will lead directly to a cure for cancer, or enormous advances in “materials research, energy production, drug discovery, Everything”, as some excitable AI “influencers” envision. 8. Nor does this mean we just entered “the era of automated scientific discovery”, as multiple recent papers have shown. More detailed essay with links at garymarcus.substack.com (over 110k subscribers). 🔗 View Quoted Tweet 💬 4 🔄 3 ❤️ 19 👀 2675 📊 5 ⚡