I don’t condone the use of pirated content for training. But anything that was bought is above the board as far as I’m concerned. Can let the lawyers fight out the minutia and inevitable licensing specifics after the fact (book publishers are hawks).

Fun fact, did you know that every library in the world has an independent contract with every major book publisher?

In cases I am familiar with, they added a condition that a physical book can only be lent X times. After that, the library must purchase a new copy (even if the original copy is in pristine condition). Yeah, hawks.

Generally speaking, on AWS you can buy compute, storage, network and other basic 'goods' and just like a supermarket where you can get either flour and eggs, a cake mix or a ready-made cake, AWS is willing to serve it to you in various levels of ready-ness, and you can start at the level you want, and build your own layers on top if you don't like AWS's solutions.

And AWS's solutions are generally built like that as well, there's no magic to Lambda or Fargate or EKS, its just they run the same EC2s, but with some proprietary magic that lifts some complexity from your shoulders, at the cost of generally some markup, and loss of some otherwise desirable features.

But the core thing is that AWS's offerings are generally solid, so as AI evolves and companies become more willing to take on more complexity, they will move to lower level services, but not necessarily out of AWS itself.

A lot of innovation at AWS is invisible on the outside. They pioneered hyperscale datacenters with publicly accessible capacity, software-defined networks, secure VMs, and so on.

> I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.

I worked at AWS before COVID. It was really a varied experience, but it was not _bad_ overall. We prided ourselves on making sure our APIs are solid, stable, and backwards compatible. When we had to make a backwards-incompatible change, we actually contacted every affected customer and ensured that their workflows wouldn't be broken.

> Instead, labor and computing power are being diverted toward a singular “frontier-model effort” led by Pieter Abbeel, director of the Berkeley Robot Learning Lab whose robotics company Covariant was hoovered up by Amazon in 2024. At the time Abbeel joined the tech giant, Covariant’s founders were working on AI models for robots, which lines up pretty well with Amazon’s push to automate everything it possibly can.

Amazon can't hope to compete in the LLM genAI (what is colloquially known as AI anyway) space. That is toast, the race is over for them, too much competition, no way to make money.

But industrial automation? Globally, Amazon employs about 1M people in fulfillment/operations roles, the utter majority of their headcount. If there is one company on this world that has the money and compute capacity to spare for a high performance, real world application of fusion between modern machine learning and robotics, it's Amazon - and to make life easier for Amazon, unlike every other competitor they don't have to pay or partner with another company for real world testing. They can just go and deploy a robot in their warehouse if they want to.

Achieve a breakthrough in a fully automated picker robot, and they can save half a million people on their payroll, if not more, they'd save shrink loss and handling mishaps as well. That is one hell of an opportunity to save money by R&D. And if they patent everything they do, they can lock their competitors out of that technology for a loooong time.

You'd think with all the data collected by these tech companies, they'd understand the common usage scenarios of their products. But instead we have AI Alexa that can't egg timer, or Gemini Assistant that can't navigate or make phone calls.