How to pronounce “scali” in English

Scaling is about getting better.

scaling back joint military exercises with South Korea. Why? Well, because of what he calls his very good relationship

Scaling it up means bringing many of these tools into the classroom.

scaling issues, et cetera.

Scaling day was something that people wanted to be a part of because they knew it was part of the future.

scaling a business and figuring out how in the world to to do that um every time

scaling outside of Regulation and I think that unfortunately is sort of the mo of a lot of um a lot of startups so

Scaling up is what my life is all about.

Scalia knew nothing of this.

Scalia's joke, nonetheless, seems to put him back on offense.

Scalia seems confused. 'But that's what Article Three already says.' 'Not exactly,' I clarify.

Scalia listens closely as I propose a judging body composed of three people appointed by the President, whose sole responsibility is to determine whether the Justices are passing

Scalia is evidently amused by the idea.

biological scaling relationships? And then the president at the time said, "You know what?

- ... the scaling process, but then there is more rapid scaling and there are slower scaling. So innovation, invention, I think is useful to understand so you

like scaling laws applied to interpretability, or scaling laws applied to post-training, or just seeing how does this thing scale.

And scaling doesn't mean having to scale your organization.

So scaling a business, the hardest thing to do is to keep the ways of working and the values and the principles, keeping them true and alive.

and scaling those through data and automation?

the scaling of these solutions.

So scaling is important.

The scaling up is very seamless.

And scaling by three orders of magnitude to trillions of pixels per frame to capture all of the historical Landsat, it really

So scaling the small naps and walks out to days and weeks, what's recommended?

And scaling the organization's what's really the big initiative right now.

like scaling the IO and running millions of jobs at the same time.

So scaling smartly, very important for small organizations.

So scaling is not arithmetic, you have to really think calculus, if you will.

The scaling of these quantities is determined by the constraints of flows in networks.

You think you're scaling abundance, but we experience it as you scaling scarcity.

These are the scaling exponents WBE theory predicts, including many that are not multiples of a quarter, but all follow from the same theory.

- Some of the scaling laws are easy to explain once you've got the three-quarters law for metabolism.

Swapping in the scaling law Kleiber had found, that gives us M to the minus one quarter, meaning bigger animals should have slower

It's about scaling excellence.

in order to keep scaling?

And so the next scaling law is the agentic scaling law. It's kind of like multiplying AI.

where the traditional scaling laws are talked about for pre-training, which is how big your model is and how big your dataset is, and then scaling reinforcement learning,

in the context of scaling laws?

It's all about scaling inference, scaling post-training, scaling context, continual learning, scaling data, synthetic data?

With inference scaling, you don't spend money during training, you spend money later per query, and then it's also like math. How long is my model gonna be

was during inference scaling to achieve peak performance in certain tasks.

What I think is scaling is something I call the cognitive light cone, and the cognitive light cone is the size of the biggest

- Do you think the scaling laws are holding strong,

So I do think scaling laws are working, but it's tough to get, at any given time, the models we all use the most

- This is a scaling law shirt, by the way.

- And of course the scaling here is bigger networks, bigger data, bigger compute.

But the big scaling law, I guess the underlying Scaling Hypothesis has to do with big networks, big data leads to intelligence.

Unlike with the scaling laws where it feels like there's some, you know, law that's driving these models to perform better, on the inside, the models aren't, you know,

talk about scaling, I I will just say we have a plan. We have what it takes