Azeem Azhar

time compression.

And LLM has, as a result, I think of ChatGPT, that famous paper that now feels so outdated, the stochastic parrot paper, have become that byword for AI.

They've encapsulated the general transformer architecture that underpins large language models, but other things like diffusion models and state space models.

The AI index tracks a bunch of notable AI models.

I'm not quite sure what makes a model notable or not, but it tracks about 61 of them at the end of 2024.

Only 40% were true LLMs.

Others used different architectures.

which are needed across domains like time series, electrical systems, proteins, multiomics, and other medical applications.

So the point is there are more exponentials in this AI wave that are doing their thing than just chat GPT and the large language model.

These new technologies really make

new things possible we start to do things that we didn't do before maybe because they weren't possible or just because they were too expensive because what a general purpose technology does has to do is it has to in some way reduce the cost of something we're doing in the market in the economy

And an exponential general purpose technology will reduce that cost even more.

So think about how you might be using this today.

You might get a contract for something that you're signing up to.

And if it's got any degree of materiality, you'll probably get it read by Claude or chat GPT.

Well, we wouldn't go to a lawyer for a contract like that five years ago or two years ago.

But now these are new behaviors that we will generally take.

Well, what does this mean?

Is this a reasonable non-disclosure agreement to sign, something I have to do many, many times a week, and they're not all reasonable.

So there's this new behavior that has emerged, that's been enabled as a consequence of this exponential technology.