Nathaniel (NLW) Whittemore

The biggest hurdles generally are the imagination for what's now possible, the sheer speed at which the tech is changing, and the change management to make it happen.

So while on the one hand, Karpathy is arguing that today's agents aren't good enough, broadly speaking, or at least that they have a ton of work to go, you've got Aaron Levy, who's got to be in one of the best positions in the world to understand where enterprise leaders actually are, pointing out that there's a capability overhang where we haven't even close to adopted the capability set that we currently have.

I tweeted yesterday, hard to get real worked up over AGI timelines when less than 5% of work that could be improved by today's AI actually is.

That less than 5%, by the way, is just my estimate.

But I think it's extremely clear that we are at the very, very early innings of integrating this technology into the real world.

And the reason that I think the AGI timeline's lengthening doesn't mean that we're in a bubble is that I believe that we're going to see massive demand uptick just based on the AI that we have.

As the AI investor put it, my take is that the AGI timeline argument and therefore the bubble claim is nonsense.

This was unexpectedly intensified by Andre's recent podcast.

AI doesn't need AGI to be transformative.

Today's LLM models and infrastructure like NVIDIA's Blackwell are already capable of disrupting trillions of dollars worth of knowledge work.

Maybe even more crisply, I saw this post from Jacqueline Rice Nelson, the CEO of Tribe, who hosted a private dinner last week with OpenAI, where the main takeaway from all of the leaders from major financial institutions that participated was this.

Even if there is a bubble, there's no way I'm stopping using ChatGBT.

Anyways, if nothing else, it was a very interesting weekend.

Lots of good food for thought, and I'm sure lots of developments to come this week.

For now, that's going to do it for today's AI Daily Brief.

Until next time, peace.