I think your last point is the main point. They're going hard at reenforcement learning to improve how good the models are at coding and such, but RL will make models cheat unless you're super careful. But being careful…
Sure, but you can say that about most things. Even for inventions from humans, usually it requires other people having already done a lot of work (hence why there's often inventions by different people at around the…
But it's interesting that the initial things that caused the board weren't even security evals, just normal office tasks. The actual hacking of Hugging Face happened during a security eval, but not all of the stuff…
Though one thing I've heard is that the base model is the one with the various possibilities for patterns, and then the reasoning takes advantage of those vs necessarily creating something new in that additional…
I'm not sure if the context limit on the $25/m, and model-size limit on the $100/m would make it not work well enough for OpenCode, but Featherless AI seems a bit unique in terms of how they handle their inference plans.
Besides what the other person mentioned about being more useful for enterprise, I also heard mentioned on a podcast that gpt-image-2 uses the same general architecture as the LLM models, while Sora was a very different…
While that is cool in principal, I'm not sure how well it'd actually work in reality. First, there is the technical challenge. My understanding is the weights can have a lot of fluctuation, especially early on. How do…
There's been some work on memory lately like Transformer² and Titans. But that may not be necessary for decent agents. Even the "context in a loop" is getting better as general reliability of tasks increases, and as…
It is confusing, but they have diff calls for pdfs vs images. In their example google colab: https://colab.research.google.com/drive/11NdqWVwC_TtJyKT6cmu... The first couple of sections are for pdfs and you need to skip…
I think your last point is the main point. They're going hard at reenforcement learning to improve how good the models are at coding and such, but RL will make models cheat unless you're super careful. But being careful…
Sure, but you can say that about most things. Even for inventions from humans, usually it requires other people having already done a lot of work (hence why there's often inventions by different people at around the…
But it's interesting that the initial things that caused the board weren't even security evals, just normal office tasks. The actual hacking of Hugging Face happened during a security eval, but not all of the stuff…
Though one thing I've heard is that the base model is the one with the various possibilities for patterns, and then the reasoning takes advantage of those vs necessarily creating something new in that additional…
I'm not sure if the context limit on the $25/m, and model-size limit on the $100/m would make it not work well enough for OpenCode, but Featherless AI seems a bit unique in terms of how they handle their inference plans.
Besides what the other person mentioned about being more useful for enterprise, I also heard mentioned on a podcast that gpt-image-2 uses the same general architecture as the LLM models, while Sora was a very different…
While that is cool in principal, I'm not sure how well it'd actually work in reality. First, there is the technical challenge. My understanding is the weights can have a lot of fluctuation, especially early on. How do…
There's been some work on memory lately like Transformer² and Titans. But that may not be necessary for decent agents. Even the "context in a loop" is getting better as general reliability of tasks increases, and as…
It is confusing, but they have diff calls for pdfs vs images. In their example google colab: https://colab.research.google.com/drive/11NdqWVwC_TtJyKT6cmu... The first couple of sections are for pdfs and you need to skip…