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Simon Willison

Here's my end-of-year review of things we learned about LLMs in 2024 - we learned a LOT of things simonwillison.net/2024/Dec/31/

Table of contents:

The GPT-4 barrier was comprehensively broken Some of those GPT-4 models run on my laptop LLM prices crashed, thanks to competition and increased efficiency Multimodal vision is common, audio and video are starting to emerge Voice and live camera mode are science fiction come to life Prompt driven app generation is a commodity already Universal access to the best models lasted for just a few short months “Agents” still haven’t really happened yet Evals really matter Apple Intelligence is bad, Apple’s MLX library is excellent The rise of inference-scaling “reasoning” models Was the best currently available LLM trained in China for less than $6m? The environmental impact got better The environmental impact got much, much worse The year of slop Synthetic training data works great LLMs somehow got even harder to use Knowledge is incredibly unevenly distributed LLMs need better criticism Everything tagged “llms” on my blog in 2024
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iveyline

@simon Interesting but what's the point in human terms - to ultimately make us all irrelevant?

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Simon Willison

@iveyline I really hope not. I like LLMs that augment human abilities - that give us new tools. That's one of the reasons I'm unexcited about the idea of "AGI" - that sounds like a human-replacement play to me, which doesn't interest me at all.

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lainy
@simon @iveyline every day hundreds of thousands of AGIs are born, so I wouldn't worry too much.
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Qadse Sanur Qut ibn Quaadibz :catsader:
@lain @simon @iveyline AGIs are also not a huge concern due to the absurd amount of energy they would need, while you can have a human going in just 2000kcal and 2 liters of water a day
iveyline

@nerthos Good point. So maybe we humans are not only intelligent but also more energy and resource efficient!

Jan 02, 2025, 11:33 PM·Public
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