Please be specific because outside of anecdotal blog posts by people who don’t know what they’re talking about it’s not true. Look at scaling laws, composite benchmarks from the epoch capability index, nothing at all suggests “model progress is slowing down”
Qwen3.6 9B is as good as GPT-4o and runs on my M2 MacBook Air. Models are getting stronger and less costly at the same time, but these are somewhat separate branches of research. Frontier labs are spending more because they are still getting marginal returns and there is more capacity to spend than there was a year ago.
You are right, I was mistaken about the version. I evaluated it in general chat assistant prompts plucked from my history across a range of topics but did not use it for coding - there was never a time when I thought 4o was “good enough” for agentic coding.
They are intrinsically linked beyond a certain point. If we're making progress but costs are spiraling exponentially then it stands to reason that we will soon reach a point where we can no longer afford the increasing costs and thus progress will slow.
(barring some breakthrough that reduces costs, which of course may happen, but for which recent model improvements are not strong evidence of)
I guess within the domain of AI, a pertinent question would be: "do I want to use anything but the best?" The errors older models give being directly analogous to being stupider in my eyes.
Depends — many tasks in various pipelines have a reasonable Pareto frontier and diminishing returns after a certain level of performance. You may just have a high budget constraint (say like YouTube computing ASR subtitles; they are not going to be using the best ASR models because it’s expensive). If it’s myself, with a coding agent, I’m going to get the best thing I can afford.
If higher bandwidth networking consisted primarily running more and more ethernet lines in parallel, you would most certainly agree that "networking has stagnated".
"Reasoning" and now "Agentic" AI systems are not some fundamental improvement on LLMs, they're just running roughly the same prior-gen LLMS, multiple times.
Hence the conclusion that LLM improvement has slowed down, if not stagnated entirely, and that we should not expect the improvements of switching to these "reasoning" systems to keep happening.
“ChatGPT came up with an idea which is original and clever. It is the sort of idea I would be very proud to come up with after a week or two of pondering, and it took ChatGPT less than an hour to find and prove”
Until you or I can actually use Mythos in Claude without an nda or other strings attached, Mythos is not released and is just an effective marketing tool for Anthropic.
At least to me this is a pretty sour grapes take. There are all kinds of released products that are expensive or need an NDA. You're just too poor to afford it. But make no mistakes there are governments using this in mass and likely against you.
Model progress at spitting out unhallucinated facts is slowing down hard. Model progress at solving hard math challenges/programming tasks doesn't seem to be slowing down that I can tell.