Mistral AI
Artificial intelligence companywww.mistral.ai
1.5k
MENTIONS
458
EPISODES
314
PODCASTS
Search complete. 1474 mentions across 458 episodes found for "Mistral AI".
Oct 26, 2026
SwyxHOST
I mean, obviously there's the US labs and you're here in the US.
SwyxHOST
Do the other labs have significant partnerships? What are they like? Mistral, Cohere, the Chinese labs? I don't know if...
SwyxHOST
Not so much.
SwyxHOST
Well, they might
Sergio GagoGUEST
And from bare metal to a Spark job, it could take you two months and 15 to 20 people.
Sergio GagoGUEST
The last customer that we had with a similar environment, we went from bare metal to running a Mistral model.
Sergio GagoGUEST
in their data center with GPU within an hour.
Sergio GagoGUEST
And that is obviously thanks to the technology that we have today that the community builds, right? That's what you get by having open source blood and then creating enterprise solutions around that.
DanHOST
It's like trying to talk French into the computer when you really want to do English, right?
LeoHOST
Apparently, the Mistral models are really good.
DanHOST
I know a few words, but I'm not fluent in them.
LeoHOST
Right, right, exactly.
JoeHOST
But on the other hand, look at the geopolitical reality.
JoeHOST
While our tech companies here in the U.S. are building massive, world-changing AI models, and while China is pushing incredibly hard into autonomous driving and scaling their supply chains, European startups are just
SunnyHOST
Trapped in endless meetings.
JoeHOST
Yes.
JoeHOST
They're sitting with their compliance lawyers trying to decipher the GDPR and the new AI Act.
JoeHOST
And their brilliant talent is just fleeing to Silicon Valley.
JoeHOST
So today we are going to really unpack this.
SunnyHOST
Exactly.
Gerd LeonhardHOST
Finally, after 80 years, we're going to take our course, Build or Surrender.
Gerd LeonhardHOST
Arthur Mensch, the CEO of Mistral, a French AI company, one of the few AI companies made in Europe, he wrote a piece called Build or Surrender.
Gerd LeonhardHOST
We have to build our own stuff.
Gerd LeonhardHOST
I know that's a tall mission.
Cecilia RikapGUEST
And I remember replying, you know why you're so divided? Because some of you are just thinking of AI as the models, whereas others are thinking about the whole ecosystem and whether the same companies that today control the ecosystem will continue controlling it.
Cecilia RikapGUEST
So if we just think about AI as the models, what we actually see is that companies like OpenAI and Anthropic are rivaling with Coir, Mistral, which are Canadian and a French company, with other startups from the US, with the Chinese startups, with the Gemini and Lama and so on.
Cecilia RikapGUEST
So the models that are directly developed by the big tech.
Cecilia RikapGUEST
So they are really in a very competitive market, trying to always present themselves as the ones that bring success.
Nici SweaneyGUEST
We use all of the data around how people are interacting with them to help train the next model.
Nici SweaneyGUEST
Open source models like Gemma, Fi, Mistral, Kimike, these are large language models and generative IAM models that you can download and host on your own laptop or even on your smartphone.
Nici SweaneyGUEST
As long as your laptop's kind of less than five years old, you should be totally fine to do this.
Nici SweaneyGUEST
And what it means is that you actually... own that generative AI model.
Cliff HarveyHOST
Even if it's as simple as asking again, double check this or taking it to a different model.
Cliff HarveyHOST
You know, when we're doing some online infrastructure stuff, remember how I got some coding instructions from Gemini and then inputted them into Mistral and it's like classic AI mistake.
Cliff HarveyHOST
Yeah.
Cliff HarveyHOST
here's what you should actually do and then you feed it into maybe chat gpt and it's like well that's pretty good but it's actually not correct here's what you should actually do so yeah it's it's pretty interesting
![[YOU] on AI · Weekly](https://particle.news/cdn-cgi/image/format=auto,width=128/https://cdn.particle.pro/url/media/e7d9e99f-8092-5c80-a84b-b213f56c926a/ec44c458d8498e9f1ca7bfc72cec56a9e73e442d62cb75555a77db842e14aa8d)
Daniel ReyesCORRESPONDENT
That is a significant capability at fully open weights.
Daniel ReyesCORRESPONDENT
And earlier in the week, Mistral's new flagship model, which has approximately 1 trillion parameters but only 52 billion active at any moment, became the talk of the benchmarking community.
Daniel ReyesCORRESPONDENT
It supports more than 160 languages and multimodal input.
Daniel ReyesCORRESPONDENT
VentureBeat had reported open waits were due on October 27th, which would be just two days from now.
Monica PaoliniGUEST
over how they're used, over what they do, and the question becomes a little bit more subtle.
Monica PaoliniGUEST
So for instance, companies like Mistral in France, they're taking an interesting approach, I think, in terms of not replicating everything, but to take it in a way that we can actually use tools that are developed somewhere else, but we retain control and we know what's going on and we know how to control things.
Monica PaoliniGUEST
But then there is a question of sovereignty, which is also to do with policy, control and security.
Monica PaoliniGUEST
And that is independent from what you use and where it's developed.
12 MINS LATER
Monica PaoliniGUEST
So you might have some open source component and then some proprietary stuff on top because open source on its own doesn't typically, it doesn't take you to a full product.
Monica PaoliniGUEST
A full product would always have a combination of the two.
Monica PaoliniGUEST
But if you look at companies like Mistral, they're basically using a combination of the two, trying to understand what's best.
Monica PaoliniGUEST
And I think that, so the open source is specific to software, but I think that, and I'm a big proponent of openness, where you have open interfaces.
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