Karen Hao

Transportation can literally refer to everything from a bicycle to a rocket.

And we have nuanced conversations about transportation where we always say we need to transition our transportation towards more efficient,

We need to transition towards, you know, public transport, electric vehicles.

And we don't ever say everyone should get a rocket to do every – to serve all of their transportation needs, right?

Like, we're in Austin.

If you used a rocket to fly from Dallas to Austin, like, that would just make not –

No sense.

It's just a disproportionate use of resources to get the benefit of getting from point A to point B. This is how we should think about AI.

So all of the models that we've been talking about, I like to think of them as the rockets of AI.

They use an extraordinary amount of resources and they provide benefit, some dramatic benefit to some people.

But they're also exacting an extraordinary cost on a large swath of people because of the costs of developing this technology.

why don't we build more bicycles of AI?

This is things like DeepMind's AlphaFold, which is a system that predicts how proteins will fold based on amino acid sequences.

It's really important for accelerating drug discovery, for...

Understanding Human Disease, and it won the Nobel Prize in Chemistry in 2024.

And the reason why it's a bicycle of AI is because you're using small curated data sets.

You just have data that has amino acid sequences and protein folding.

So that means you need significantly less computational resources to develop the system, which means significantly less energy, which means less emissions, so on and so forth.

And you're providing enormous benefit to people.

If the horse truly had left the stables, they wouldn't have to train on anything anymore.