elcomet

That's not my experience, the model is adding tons of unnecessary details, that make it much harder to find the important information for an expert that already knows all those details.

I don't want ELI5, I just want the model to go straight to the point, like a colleague human expert would do.

Why do you assume this order? I would assume the AI starts with lean (that's what it was RL'd on at least) then tried to translate the proof for us humans, which is quite hard.

I'm not sure about it but it seems plausible given the potential error.

Edit: they explicite say that your order is correct in the post

Why not using a cheap LLM with thinking completely disabled ? I don't think it will be much more expensive than jev.

Strange they don't mention the Pink Floyd album in the article!

Hallucinations were defined in the context of text generation models so your question does not really make sense.

IMO your system can make mistakes that are similar in spirit to hallucination (i.e. answering with a false answer instead of abstaining to answer).

The technology and the results are very handwavy. What is RLCD exactly ? What are scores on benchmarks compared to LLMs ?

This website does not inspire confidence at all, it all sounds like a marketing piece. I wish it was true, some kind of text-prompted classifier with LLM performance would be cool, but I can't trust it with what we are given.

We didn't have the compute required (GPUs powerful enough to parallelize forward and backward pass). This compute is what allows us to train from human knowledge or distillation.

UUID as key is useful when you have a distributed system where multiple workers create items independently

Could you share your config?

The heat pump will pull heat from inside the house? This sounds terrible for efficiency in winter, as you will need to reheat the room

Yeah this sounds disingenuous. I can also see my heater to 70C if I want, that does not increase its size...

I don't understand all the hype for generating SVG with LLM. The task is not really useful, doesn't seem that interesting in single shot as it's really hard, and no human could do it (it would be more useful if the model has visual feedback and could correct the result).

And also, since it becomes a popular task, companies will add the examples in their training set, so you're just benchmarking who has the better text to SVG training set, not the overall quality of the model.

I'd say that thoughts and reasoning are two different things, you're moving the goalpost.

But what makes the computer hardware fundamentally incompatible with thinking? Compared to a brain

How can you know?