This is clearly less high profile than the Scarlett Johanssen vs OpenAI one. Still this shows it has the potential to become a widespread (even though shady) practice. This might need some regulation fairly soon.

This is indeed important to be able to run such models locally. Will still require more optimization but it's slowly getting there. The reproducibility it brings is especially necessary for science.

This is a very harsh and bleak view on the current generative AI craze. Clearly it survives on some sort of weird faith that things will magically improve. Some decision makers clearly run fully on said faith and lost all kind of realistic view of the situation. They are just very disconnected from the user's needs.

There's even a funny quote in there: "Generative AI must seem kind of magical when your entire life is either being in a meeting or reading an email".

When this bubble bursts, it's hard to predict what the fallout will be on the tech industry... for sure it won't be pretty. It also begs the question: what is this industry going to do next? There's clearly no plan after generative AI.

Need to illustrate how much the current AI arm race is an ecological and social problem? Here is a very pathological case. This is what you get when you let the tycoons behind this completely unchecked.

This is bad. There was no way to know the book was AI generated and clearly it contained errors and lies.

Does a good job listing the main myths the marketing around generative AI is built on. Don't fall for the marketing, exert critical thinking and rely on real properties of those systems.

An excellent essay about generative AI and art. Goes deep in the topic and explains very well how you can hardly make art with those tools. It's just too remote from how they work. I also particularly like the distinction between skill and intelligence. Indeed, we can make highly skilled but not intelligent systems using this technology.

Interesting musing. The predictability in tone doesn't make for very funny content indeed. Also as a side-effect this might help people remember that Markov chain are a thing and much less expensive.

Exciting new type of neural networks. There are limits to use them at large scale for now. Still, they have very interesting properties like the interpretability. And also, they tend to give similar performance to traditional neural networks for a smaller size.

If you're wondering what people do with chat bots, there are some clues here.

This ought to be easier, this should help a bit.

Interesting finding. Looks like the trust is not very high in the general public towards products with AI.

More discussion about models collapse. The provenance of data will become a crucial factor to our ability to train further models.

Still not perfect, but that's an interesting development.

Content creators are clearly annoyed at the lack of consent. The more technical ones are trying to take the matter in their own hands.

Or examples of the collapse of a shared reality. This has nothing to do with "social" media anymore. Very nice investigation in any case.

I'm rarely on the side of a Goldman Sachs... Still this paper seems to be spot on. The equation between the costs (financial and ecological) and the value we get out of generative AI isn't balanced at all. Also, since it is stuck on trying to improve mostly on model scale and amount of data it is doomed to plateau in its current form.

Those brand new models keep failing at surprisingly simple tasks.

A new era of spam is on us... this is going to be annoying to filter out.

This arm race should be stopped... This is becoming an ecological disaster, so much wasted energy.