Azeem Azhar

They are working while we are sleeping.

They are the robots in the dark factory, the other software robots in the data center continuing to work for us.

And this shift towards agentic workflows, which is taking time, but it's getting more and more mature,

indicates an increase in the amount of compute that enterprises will want to use.

So it's also important to understand that compute is about computation, that is systematically processing information according to some kind of algorithm or set of steps.

It's not just about large language models.

Large language models are the propeller engine of 1930s and 1940s aviation.

And like propeller engines on planes, it's quite possible they will be replaced by something even snazzier.

So let's tackle this idea of infinite demand.

What do I mean by infinite demand?

I don't mean that every atom in the universe will be enlisted for computing, but I'm sure a science fiction writer out there has got a story

on just that subject.

What I mean is practically unlimited, that at each turn of the screw,

Better chips, more sensors, more data, improved algorithms.

We find new things that we want to compute in business, in science, in research, in entertainment.

Better materials, better routings, more efficient stock portfolios.

And of course, that unending array of consumer uses.

We might think that optimizations...

think about DeepSeq will help.

The optimizations like DeepSeq, which reduce the amount of computing you need to get the output that you want, would actually be a break on the amount of compute that is demanded in the global economy.