Mark Zuckerberg
speaker
5,804 appearances
83 recordings
47 series
first heard Jun 2023
last heard 31 Aug
Mark Zuckerberg’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 31 in all, peaking in Jan 2026 with 6.
Appearances
And we launched America's Workforce Academy to provide free training and guaranteed jobs at our infrastructure sites.
Today, we're starting a new Future Is for Everyone fund to invest in the community's teachers, first responders, energy and water infrastructure, and more ways to support those communities directly.
We're also working to make sure that everyone has a personal superintelligence agent that works 24-7 on your behalf to improve your health, your relationships, your career, your finances, and more.
You can use our latest models in the meta AI app, and I'm looking forward to sharing more soon.
It's contact, a huge tackle.
It's
is the ability to distill models. You know, most people, the primary value isn't just like taking a model off the shelf and saying like, okay, like Meta built this version of Llama, I'm going to take it and I'm going to run it exactly in my application. It's like, no, well, your application isn't doing anything different if you're just running our thing, you're at least going to fine tune it or try to steal it into a different model. And when we get to stuff like the Behemoth model,
like the whole value in that is being able to basically take this very high amount of intelligence and distill it down into a smaller model that you're actually going to run. But this is like the beauty of distillation. And it's like one of the things that I think has really emerged as a very powerful technique in the last year since the last time we sat down is you can basically take a model that is much bigger and
take probably like 90 or 95% of its intelligence and run it in something that's 10% the size. Now, do you get 100% of the intelligence? No, but like 95% of the intelligence at 10% of the cost is like pretty good for a lot of things. The other thing that's interesting is now with this like more varied open source community where it's not just Lama, you have other models, you have the ability to distill from multiple sources.
So now you can basically say, okay, Lama's really good at this. Like maybe the architecture is really good because it's fundamentally multimodal and fundamentally more inference friendly and more efficient. But like, let's say this other model is better at coding. Okay, well just, you can distill from both of them and then build something that's better than either of them for your own use case. So Alex, you've been talking about distillation and the compression of intelligence for a while. Yes. What do you make of Zuck's comments?
Future for everyone is to make sure that everyone has access to personal superintelligence.
See?
So today I am proud to share that we are open sourcing a new class of on-device models that we are calling Muse Glimmer.
Okay.
It's a thirty billion parameter dense model that runs on your laptop, and it's the highest performing model of its size.
In the coming weeks, we are also going to open the weights for Muse Spark 1.2, our latest foundation model.
And one of the leading models in the world.
Is it?
Is it?
And we've got even bigger models that are coming soon too.
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