So much work being done right now. Jump in and swim or be left behind.

Wow, Arthur Mensch is brilliant 💡

Great interview

very interesting and great humble personality

that was cool 🎶

Amazing talk :) Excited to see Mistral in action in Taskade's next Multi-Agent update! 🌈

@Pankomentator

12 күн бұрын

Bro compare avg salary vs avg home cost in USA 20 years ago with current situation. What do you see?

Wow, Grok is too large for them to deploy. Interesting how large is Au Large then.

Moderator need to remember the best questions can come from.the audience. Open up at half point

Open weights isn’t open source unless they provide full access to their training set and source code. In all respect to the capabilities of Mistral’s models, it is an extreme stretch to call company that’s dropping torrents of weight binary, an OPEN SOURCE. What’s the benefit of this abuse of semantics? Marketing tactic?

@seventyfive7597

Ай бұрын

It's even worse, the illusion that they're open source may give them leniency against future regulation of AI, and even tax breaks. I consider this a dangerous fraudulent precedent.

@AhmedKachkach

Ай бұрын

Open weights is by far the most important part. It allows people to fine tune the model for their own applications (commercial or not), and allows anyone to run it locally rather than have to pay for a handful of private models. Open source would only benefit major researchers that can afford to train similarly sized LLMs

@quantum_encrypt

Ай бұрын

@@AhmedKachkach I suppose that in the ideal case, open source would include open weights. Furthermore, fine-tuning with the weights only isn't always the best methodology. The model can 'forget' (I use that term loosely), ideally what you want to do is have a mix of old data that the model was initially trained on + new data to ensure the model doesn't lose anything previously learnt etc.

@clray123

Ай бұрын

@@quantum_encrypt Correct, you can mess up Mistral with just ~10 epochs of fine-tuning on a single example. It will "transfer" into examples not in the training set in an undesired manner. As a concrete case, consider training on "Q: What is your favorite fruit? A: Tomato." After a few rounds of training it will also start replying that 1. The favorite ANIMAL/PERSON/whatever is tomato and 2. The least liked fruit is tomato. It will also kill the ability to provide longer answers to similar questions. Etc. This highlights how having an unbalanced training set destroys the model. Rather than just incorporate the new information, as some may naively think, it also overwrites and erases the old information along.

@quantum_encrypt

Ай бұрын

@@clray123 Thank you! Great example 😊

Releasing the weights and the necessary code for inference is not open source in the traditional sense, not sure why they are using that term.

@3ico592

Ай бұрын

Because they get the benefits of saying that it is open source with out being open source

he is high? ) Mistral is best .

@VJ-lt9uk

Ай бұрын

No, he is French.

@socialexperiment8267

Ай бұрын

@@VJ-lt9uk that's cool. I'm EU the same )) I love Mistral 4x70

This French dude is hot... now that Elon is old, decrepit and looks more and more like his dad.... this Arthur is the new young musk.

Google deep mind should investigate on this guy.

Has that microphone been dropped on its head?