People increasingly can’t tell the model that’s running in their agents. It’s increasingly becoming like a car engine, where enthusiasts might care about specific engine details but for regular commute the cost is what matters!
Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
All of this reminds me of the most perfect implementation of markdown: Dropbox Paper!
I wish they didn’t close the product line
This powerlaw exists in almost all of the areas. When I tell my friends that almost 60% of the country has not not taken a flight in last 2 years, they cannot believe it.
The top 1% of AI spenders now outspend the bottom 50% combined
They spend an average of $903/month, while the median customer spends just $25
More charts in our Top 100 Consumer AI Apps breakdown: a16z.news/p/top-100-consumer…
One of the problems I see with AI products is how many features get released daily. While releasing features is great, users often don’t seem to pay attention to them and just use the same set of functionalities they always did.
With agents it should be fairly easy to analyze these flags and create custom automations for them to use!
Product so good, even the competitors can’t stop talking about it!
openai cfo: muse is going to better, sorry, not muse, dots is going...
youtube.com/watch?v=jXvxK87F…
CPU demand to go through the roof with all of the recent launches! If inference becomes faster, and more efficient bottleneck shifts to the input layer to the inference. That often involves running database queries, executing isolated code chunks and coordinating between various parts of the system!
I still remember the time I wrote a java code on paper and was graded for the "syntax" mistakes that we made since the code wouldn't compile on a real machine.
If coding agents wer generating that code, it'd run out of space in that paper!
We’ve solved code generation. We just forgot code still has to compile, link, and not immediately request root.
My job is babysitting computers so they can babysit models. Somewhere in there, both I and the kernel panic at the sight of bugs.
One of the coolest things about building Muse infra was the joy that everyone in the world would get their own computer!
It is truly theirs and they can install any packages, and explore all of the files!
I’ve seen a couple of posts about this so wanted to demystify. Today, every Muse user gets a free computer in the cloud. It's a real computer, and we’ve designed the security architecture of the Muse Secure VM carefully so you and your Muse can do almost anything you could with a computer sitting under your desk while keeping you and the system safe from threats like prompt injection. We wrote about this at length in our security blog post – security.muse.ai. Activity in the “runtime cell”, which you share with your Muse is unfettered, but sensitive actions are all overseen by the Sentinel, which runs outside of that cell. Similarly, all sensitive secrets - like the passwords you enter into Muse’s secure credential storage - are also stored outside the runtime cell.
The runtime cell gets its own root filesystem (including a full Ubuntu linux image) separate from the host filesystem where your other more sensitive data lives. Because it is isolated from the sensitive stuff that runs on the same box, this means that we can, and do, offer users full visibility and control over the files in the runtime cell. Just as you can when you install Linux on your home computer, you can poke around and see all the files that make the system work - both debian system files and the binaries and data files that implement the parts of Muse which run in the runtime cell.
This was a very deliberate choice - your Muse Secure VM truly is your own computer in the cloud. You can install software in it, write and compile code, use the browser to surf the web: it is your own Linux box that you can operate as you choose with your Muse. Poking around in this computer doesn't give you any privileged access to Meta infrastructure, or to other people's data
If I may geek out a little here for a second… As a kid I loved to take things apart to see how they worked. As a teenager I got into computers and soon found myself drawn to C:\WINDOWS\SYSTEM and the system registry, later Slackware’s /dev/, /proc/ etc – I could see how the system was laid out and as I explored what DLL files and .so files actually did, I gradually became able to meld the computer to my own will.
We’re really proud to be able to put a real computer in millions of people’s hands with a similar level of transparency. We built a file explorer right into the Library tab of the UI. We want you to be able to see the markdown files Muse writes while it thinks about how to serve you better, and explore the internals of the system if you’d like to.
So, when you ask your Muse to show you its entire filesystem, and receive gigabytes of files you’re seeing the full contents of the runtime cell. It’s yours to explore and enjoy!
If you’re not a geek like me, or simply want to download the data that you personally have created directly with your Muse, we added a feature for that too in Settings > Data controls > Download your agent data.
