ehhhh, we're not really there. Not saying it's impossible to reach in the future but large tasks like this are still out of scope for LLM's beyond demoing toy applications. Impressive nonetheless, but I can't tell an LLM to reproduce microsoft word and have it give me a useful enough tool that doesn't contain an immense amount of bugs and require a human in the loop to replace it.

Between corporate FOMO and the rapidly decreasing costs of actually running LLM's I'm interested to see at which side of the spectrum these two meet

Inference is affordable, and you don't need a SOTA proprietary model to get a lot of use out of this technology. While you likely will still need a human engineer for quite a while longer, I don't agree that some number of humans + an LLM is going to be (or will ever remain) more expensive than just hiring more humans.

If you don't actually believe in your product's capabilities, why sell it?

The other important detail is that LinkedIn already has processed this data that definitely pertains to you, whether you paid for it or not, and are trying to sell it to you. In fact, to quote the article, LinkedIn's argument for not giving it to the user is "on the grounds that protecting that data took precedence". LinkedIn isn't withholding viewer data to protect viewer privacy. We know this because they sell it. If the viewer's privacy interest were so compelling that it overrides your Article 15 right (which is what Noyb is referring to), it would also be compelling enough to prevent LinkedIn from selling that same data to Premium subscribers.

The argument being made for this specific feature (not the ones you added) is that you can't simultaneously claim the data is too privacy-sensitive to disclose under GDPR and then sell it as a product feature

Where did you read this? From what I read in the paper it appears to explicitly state that they used NVIDIA GPU's and their MegaMOE code, which is written in CUDA.

From a conventional perspective Iran is by all means "losing" the war. However, the United States and the majority of the world desperately want the strait to be opened and have so far been unsuccessful in preventing Iran from blocking it. The US is also greatly interested in regime change, which has also been unsuccessful.

"Thinking" is just a term to describe a process in generative AI where you generate additional tokens in a manner similar to thinking a problem through. It's kind of a tired point to argue against the verb since it's meaning is well understood at this point

Your work seems more targeted at tracking the real world impact of the bill rather than the changes it makes to the legal code, but a feature on my roadmap is having bill data also be easily linkable to the votes of politicians so you can track the effect politicians have on the legal code per member. Do you plan to build a member tracker on top of this as well? I think it would be super cool to be able to tie news events to a track record of votes by member of congress.

I'm interested in your cubecl-wgpu patches. I've been struggling to get lower than FP32 safetensor models working on burn, did you write the patches to cubecl-wgpu to get around this restriction, to add support for GGUF files, or both?

I've been working on something similar, but for whisper and as a library for other projects: https://github.com/Scronkfinkle/quiet-crab