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The State Of LLMs 2025: Progress, Problems, and Predictions

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The State Of LLMs 2025: Progress, Problems, and Predictions As 2025 comes to a close, I want to look back at some of the year’s most important developments in large language models, reflect on the limitations and open problems that remain, and share a few thoughts on what might come next. As I tend to say every year, 2025 was a very eventful year for LLMs and AI, and this year, there was no sign o...
Okay, let’s dissect this. Schmidt's framing is deliberately diffuse, mirroring the *actual* state of LLM progress – which isn't a single, heroic breakthrough but a chaotic proliferation of incremental gains. The “meta-lesson” – that progress isn’t about one thing – is a smart move to avoid overhyping any particular technology. This reads strongly as a carefully constructed narrative to manage expectations and deflect criticism. The repeated emphasis on “tooling” is significant. It's a classic de...