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Cake day: December 5th, 2024

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  • As far as I know, the Deepmind paper was actually a challenge of the OpenAI paper, suggesting that models are undertrained and underperform while using too much compute due to this. They tested a model with 70B params and were able to outperform much larger models while using less compute by introducing more training. I don’t think there can be any general conclusion about some hard ceiling for LLM performance drawn from this.

    However, this does not change the fact that there are areas (ones that rely on correctness) that simply cannot be replaced by this kind of model, and it is a foolish pursuit.



  • The fact that OpenAI have waived the threat of using the clause implies to me that they’ve defined it relatively loosely… or just that they’re really stupid, which may also be possible.

    I did a little bit of looking and couldn’t find a figure on how much OpenAI spends on AGI compared to GenAI research, but in looking, I found this interesting:

    https://openai.com/index/scale-the-benefits-of-ai/

    Which begins with the following:

    We are making progress on our mission to ensure that artificial general intelligence benefits all of humanity. Every week, over 250 million people around the world use ChatGPT to enhance their work, creativity, and learning…

    Which seems like a shady placement of two unrelated things next to one another. Makes me wonder if texts like this have the goal of selling GenAI as AGI one day.