I feel like we've just crossed a threshold in AI development.
OpenAI and Google have shown with their gold medals at the IMO that general models can now solve the most difficult mathematical problems in native language, even problems that are difficult to verify. Researchers even say that we may develop new mathematical theorems as early as next year.
Open source models are getting better and better. So good that they can easily keep up with closed source and are sufficient for everyday use. What's more, Kimi-K2, the new Qwen, and numerous smaller models show how powerful open source is. And everyone is eagerly awaiting DeepSeek r2.
At the same time, distilled models are becoming increasingly efficient. Small models are becoming so efficient and inexpensive that the costs for small models such as Google Gemini Flash or the Phi models are hardly significant anymore. And costs continue to fall rapidly thanks to improvements in hardware, algorithms, and models.
Text2speech, speech2speech, GenAI videos such as Veo3 (TikTok and Instagram are full of these videos), AI music generation, and so much more are also advancing rapidly.
In short: things are really taking off everywhere. There is still no end in sight. What's more, it's very difficult to keep up with the developments and go along with them. It's the craziest time of our lives. And there's no turning back.
I don’t have the evidence or math to back this up, but it appears to me that we are seeing emerging logarithmic diminishing returns on artificial intelligence vs compute. While Moore’s law says compute exponentially increases over time.
Combined, we should expect to see relatively linear growth of artificial intelligence over time.
No hard takeoff. Just hard work and persistence.
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@GaryMarcus@sama@growing_daniel Anyone who says AGI is around the corner is just pushing hype. It’s becoming painfully clear there’s diminishing returns across the AI the industry.
AGI = Algorithms, Grounding, and Integrations
Compute, LLMs, and scale alone aren’t going to get us there.
I’ve learned more in the past two years thanks to AI tools than in any other comparable period in my life. Mostly because they let me rapidly explore, cross-reference, and test ideas.
The assumption that AI makes people “dumb” seems to conflate misuse with inherent limitation. People who approach it uncritically would likely do the same with any tool. Perhaps the real issue isn’t AI, but the cognitive habits we bring to it.
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unlike past tools that only improve productivity, these agents fully handle entire jobs.
the value is clear — people will pay much more for full job automation than for small productivity boosts
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