So are we assuming here that LLMs won’t become more efficient over time? GPT-3 has been a frontier model just a few years ago and it’s performance blew everyone’s mind at that time. I can now run equivalent LLM on my personal computer. Why can’t we expect that after a few years Claude Sonnet level of capability won’t be possible to accomplish locally?
Maybe they meant removed people
Hopium administered
Defenders finally have a chance to win, decisively
I’m curious how it will turn out to be in a long term. Are we going to have safer software? Because not only defenders will have a powerful tool, but attackers too. But at the same time, number of bugs is finite… Can we in theory one day achieve literally zero bugs in codebase?
What’s in this article is true, but to be honest I’ve never seen anyone using lines of code as an optimization metric. Even among the most AI enthusiastic people. I mean: the author of the article seem to be fighting non-existing problem.
Why not? Why Microsoft develops it’s .NET ecosystem? Why Google develops Go/Dart? It costs them lots of money and they give it for free.
The answer is: they don’t earn money on it directly, but these tools are a way to tie programmers to their cloud services. If you use .NET you’ll probably end up on Azure. If Go - probably you’ll use GCP.
So I suspect the same will be with LLMs. At some point they will say: “hey, you can use this LLM however you want, but as you are already using it, then you may want to know our platform is optimized for it”