I think Yann Lecun was right about LLMs (but perhaps only by accident)

Satya Nadella on AGI:

> Before I get to what Microsoft's revenue will look like, there's only one governor in all of this. This is where we get a little bit ahead of ourselves with all this AGI hype. Remember the developed world, which is what? 2% growth and if you adjust for inflation it’s zero?

> So in 2025, as we sit here, I'm not an economist, at least I look at it and say we have a real growth challenge. So, the first thing that we all have to do is, when we say this is like the Industrial Revolution, let's have that Industrial Revolution type of growth.

> That means to me, 10%, 7%, developed world, inflation-adjusted, growing at 5%. That's the real marker. It can't just be supply-side.

> In fact that’s the thing, a lot of people are writing about it, and I'm glad they are, which is the big winners here are not going to be tech companies. The winners are going to be the broader industry that uses this commodity that, by the way, is abundant. Suddenly productivity goes up and the economy is growing at a faster rate. When that happens, we'll be fine as an industry.

> But that's to me the moment... us self-claiming some AGI milestone, that's just nonsensical benchmark hacking to me. The real benchmark is: the world growing at 10%.

https://www.dwarkeshpatel.com/p/satya-nadella

We've been having really good models for a couple of years now... What else is needed for that 10% growth? Agents? New apps? Time? Deployment in enterprise and the broader economy?

I work in the latter (I'm the CTO of a small business), and here's how our deployment story is going right now:

- At user level: Some employees use it very often for producing research and reports. I use it like mad for anything and everything from technical research, solution design, to coding.

- At systems level: We have some promising near-term use cases in tasks that could otherwise be done through more traditional text AI techniques (NLU and NLP), involving primarily transcription, extraction and synthesis.

- Longer term stuff may include text-to-SQL to "democratize" analytics, semantic search, research agents, coding agents (as a business that doesn't yet have the resources to hire FTE programmers, I would kill for this). Tech feels very green on all these fronts.

The present and neart-term stuff is fantastic in its own right - the company is definitely more productive, and I can see us reaping compound benefits in years to come - but somehow it still feels like a far cry from the type of changes that would cause 10% growth in the entire economy, for sustained periods of time...

Obviously this is a narrow and anecdotal view, but every time I ask what earth-shattering stuff others are doing, I get pretty lukewarm responses, and everything in the news and my research points in the same direction.

I'd love to hear your takes on how the tech could bring about a new Industrial Revolution.

The thesis is simple: these programs are smart now, but unreliable when executing complex, multi-step tasks. If that improves (whether because the models get so smart that they never make a mistake in the first place, or because they get good enough at checking their work and correcting it), we can give them control over a computer and run them in a loop in order to function as drop-in remote workers.

The economic growth would then come from every business having access to a limitless supply of tireless, cheap, highly intelligent knowledge workers