alt Hacker NewsIMHO there is a point where incremental model quality will hit diminishing returns.
It is like comparing an 8K display to a 16K display because at normal viewing distance, the difference is imperceptible, but 16K comes at significant premium.
The same applies to intelligence. Sure, some users might register a meaningful bump, but if 99% can't tell the difference in their day-to-day work, does it matter?
A 20-30% cost increase needs to deliver a proportional leap in perceivable value.
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Depends a lot on the task demands. "Got 95% of the way to designing a successful drug" and "Got 100% of the way" is a huge difference in terms of value, and that small bump in intelligence would justify a few orders of magnitude more in cost.
It probably depends what you're using the models for. If you use them for web search, summarizing web pages, I can imagine there's a plateau and we're probably already hitting it.
For coding though, there is kind of no limit to the complexity of software. The more invariants and potential interactions the model can be aware of, the better presumably. It can handle larger codebases. Probably past the point where humans could work on said codebases unassisted (which brings other potential problems).
I'm seeing a lot of sentiment, and agree with a lot of it, that opus 4.6 un-nerfed is there already and for many if not most software use cases there's more value to be had in tooling, speed, and cost than raw model intelligence.
I agree, but also the model intelligence is quite spikey. There are areas of intelligence that I don't care at all about, except as proxies for general improvement (this includes knowledge based benchmarks like Humanity's Last Exam, as well as proving math theorems etc). There are other areas of intelligence where I would gladly pay more, even 10X more, if it meant meaningful improvements: tool use, instruction following, judgement/"common sense", learning from experience, taste, etc. Some of these are seeing some progress, others seem inherent to the current LLM+chain of thought reasoning paradigm.
yeah thats is my biggest issue - im okay with paying 20-30% more but what is the ROI? i dont see an equivalent improvement in performance. Anthropic hasnt published any data around what these improvements are - just some vague “better instruction following"
Longer version of the comment https://www.linkedin.com/pulse/imperceptible-upgrade-petko-d...
> IMHO there is a point where incremental model quality will hit diminishing returns.
You mean a couple of years ago?
>IMHO there is a point where incremental model quality will hit diminishing returns.
It's not necessary a single discrete point I think. In my experience, it's tied to the quality/power of your harness and tooling. More powerful tooling has made revealed differences between models that were previously not easy to notice. This matches your display analogy, because I'm essentially saying that the point at which display resolution improvements are imperceptible matters on how far you sit.
Whenever we get the locally runnable 4k models things are going to get really awkward for the big 3 labs. Well at least Google will still have their ad revenue I guess.