As one who clearly see the huge potential of this tech this is an interesting outlook; make sure to make your products resilient to changing vendors and price hikes and it will probably be fine.
Side note: Google seems to be playing the long game..
AI foundries, Nvidia, the hyperscalers, enterprise buyers of AI, consumers, the US, China, the rest of the world, startups, investors, FOSS, students, teachers, coders, lawyers, publishers, artists... each stand to win or lose in profoundly different ways.
Otherwise we all end up talking past each other.
I feel like we've pretty much already hit a fundamental barrier in compute that is unlikely to be overcome in the near future barring a profound, novel algorithmic approach or an entirely novel computing model.
Nothing interesting without some fundamental breakthrough IMO. Model/agent providers add another level of "thinking" that uses 10x the energy for 10% gain on benchmarks.
And if they aren't, then they will be soon enough.
I don’t think over the last 5-8 years there has been a shortage of code-slingers, as evidenced by all the tech layoffs. Using LLMs to generate more code does not equal productivity. There’s that famous story about the -2000 LOC commit, etc.
There should be some amazing new end-user-facing software, or features in existing software, or reduced amounts of bugs in software, any day now...?
datadrivenangel•47m ago
This is the most plausible looking path forward: LLMs + conventional ML + conventional software inverts how our economy operates over the next few decades, but over the next few years a lot of people are going to lose a lot of money when the singularity is actually a sigmoid curve.