This violates the ToS, but I don't think it's distillation. Distillation requires knowing the logits, which current API does not provide. This is just synthetic data generation. Anthropic definitely knows the difference.
Yes, it is annoying that companies keep calling it “distillation” when it’s really imitation learning. In fact the closest analogy is probably more like “scraping” which is pretty ironic.
Google has gigantic power over its users. Consider that for some reason, Google banned your gmail account, which you are using for large number of logins for different essential services.
Great article. To me, this highlights a key question in the era of rapidly advancing machine intelligence: if we know machine intelligence is progressing, what is more valuable to build for? As humans, we still find many tools useful even when doing knowledge work. For instance, a calculator. Sure, a smart person can perform calculations in their head, but it’s much easier to teach everyone how to use a calculator, which is 100% reliable in its intended domain.
In this era, we should build these kinds of tools for problems we know are straightforward ones you can’t get smarter than, even as intelligence continues to advance. Using tools like "bash" or command-line interfaces originally designed for humans is a good initial approach, since we can essentially reuse much of what was built for human use. Later, we can optimize specifically for machines, either accounting for their different cognitive structures (e.g., the ability to memorize extremely long contexts compared to humans) or adapting to the stream-based input/output patterns of current autoregressive token generators.
Eventually, I believe machine intelligence will build their own tools based on these foundations, likely a similar kind of milestone to when humans first began using tools.
Can you give an example of smartness where Gemini is better than the other 2? I have found Gemini 3 pro the opposite of smartness on the tasks I gave him (evaluation, extraction, copy writing, judging, synthesising ) with gpt 5.2 xhigh first and opus 4.5/4.6 second. Not to mention it likes to hallucinate quite a bit .
I use it for classic engineering a lot, it beats out chatgpt and opus (I haven't tried as much with opus as chagpt though). Flash is also way stronger than it should be
OpenAI has a former NSA director on its board. [1] This connection makes the dilution of the term "PRISM" in search results a potential benefit to NSA interests.
A market maker needs a premium to provide liquidity. If all else is equal, why would they take on execution time risk? This is a universal feature of continuous-trading Central Limit Order Books (CLOBs), not something unique to prediction markets.
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