321–330 of 722 posts
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I think it is because of the Chinese new year. The Chinese labs like to publish their models arround the Chinese new year, and the US labs do not want to let a DeepSeek R1 (20 January 2025) impact event happen again, so i guess they publish models that are more capable then what they imagine Chinese labs are yet capable of producing.
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Earlier quoted context omitted.
I think it is because of the Chinese new year. The Chinese labs like to publish their models arround the Chinese new year, and the US labs do not want to let a DeepSeek R1 (20 January 2025) impact event happen again, so i guess they publish models that are more capable then what they imagine Chinese labs are yet capable of producing.
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Have you ever had a Polish Sausage? Did it make you Polish?
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Speak for yourself. Five years is a long time to wait for my plans of world domination.
This concerns me actually. With enough people (n>=2) wanting to achieve world domination, we have a problem.
I'm pretty certain that DeepMind (and all other labs) will try their frontier (and even private) models on First Proof [1]. And I wonder how Gemini Deep Think will fare. My guess is that it will get half the way on some problems. But we will have to take an absence as a failure, because nobody wants to publish a negative result, even though it's so important for scientific research. [1] https://1stproof.org/
https://hn.algolia.com/?q=1stproof
This is exactly the kind of challenge I would want to judge AI systems based on. It required ten bleeding-edge-research mathematicians to publish a problem they've solved but hold back the answer. I appreciate the huge amount of social capital and coordination that must have taken.
I'm really glad they did it.
Is it me or is the rate of model release is accelerating to an absurd degree? Today we have Gemini 3 Deep Think and GPT 5.3 Codex Spark. Yesterday we had GLM5 and MiniMax M2.5. Five days before that we had Opus 4.6 and GPT 5.3. Then maybe two weeks I think before that we had Kimi K2.5.
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https://arcprize.org/leaderboard $13.62 per task - so we need another 5-10 years for the price to run this to become reasonable? But the real question is if they just fit the model to the benchmark.
A grad student hour is probably more expensive…
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I think it is because of the Chinese new year. The Chinese labs like to publish their models arround the Chinese new year, and the US labs do not want to let a DeepSeek R1 (20 January 2025) impact event happen again, so i guess they publish models that are more capable then what they imagine Chinese labs are yet capable of producing.
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That said, "Lunar New Year" is probably as good a compromise as any, since we have other names for the Hebrew and Islamic New Years.
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> His definition of reaching AGI, as I understand it, is when it becomes impossible to construct the next version of ARC-AGI because we can no longer find tasks that are feasible for normal humans but unsolved by AI. That is the best definition I've yet to read. If something claims to be conscious and we can't prove it's not, we have no choice but to believe it. Thats said, I'm reminded of the impossible voting tests…
> The average human tested scores 60%. So the machines are already smarter on an individual basis than the average human. Maybe it's testing the wrong things then. Even those of use who are merely average can do lots of things that machines don't seem to be very good at. I think ability to learn should be a core part of any AGI. Take a toddler who has never seen anybody doing laundry before and you can teach them in…
Not trained for agentic workflows yet unfortunately - this looks like it will be fantastic when they have an agent friendly one. Super exciting.
Its really weird how you all are begging to be replaced by llms, you think if agentic workflows get good enough you're going to keep your job? Or not have your salary reduced by 50%? If Agents get good enough it's not going to build some profitable startup for you (or whatever people think they're doing with the llm slot machines) because that implies that anyone else with access to that agent can just copy you, its…
Put another way, I’m on the capital side of the conversation.
The good news for labor that has experience and creativity is that it just started costing 1/100,000 what it used to to get on that side of the equation.