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I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
They likely entered the same compute constraint scenario as Anthropic. IE. They had 100 compute units. Demand is 200 units. They have to do a combination of buying more compute, increasing price, lowering limits, etc.
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
They likely entered the same compute constraint scenario as Anthropic. IE. They had 100 compute units. Demand is 200 units. They have to do a combination of buying more compute, increasing price, lowering limits, etc.
If that is true then they should all invest resources into projects that will yield efficient use of the compute. The most efficient producer then gains a huge cost advantage AND capacity to serve more… so yeah.. that logic doesn’t hold.
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
I would say models entered a bottleneck a long time ago. My personal opinion is now they are overfitting newer models on coding and "agentic" capabilities at great expense of general abilities in other domains.
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
For what is worth I find GPT 5.5 qualitatively different than 5.4 and 5.3 If I had to collapse the nature of the difference in one sentence it'd be that the 5.5 does more what I'm asking it to do versus doing a small aspect of what I'm asking then stopping. 5.4 required a lot of "continue" encouragement. 5.5 just "gets it" a bit more What is boils down to for me is that even though it's more expensive I would much ra…
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
They likely entered the same compute constraint scenario as Anthropic. IE. They had 100 compute units. Demand is 200 units. They have to do a combination of buying more compute, increasing price, lowering limits, etc.
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
We'll probably see another stair step change followed by another plateauing curve of incremental improvements when that happens.
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
For what is worth I find GPT 5.5 qualitatively different than 5.4 and 5.3 If I had to collapse the nature of the difference in one sentence it'd be that the 5.5 does more what I'm asking it to do versus doing a small aspect of what I'm asking then stopping. 5.4 required a lot of "continue" encouragement. 5.5 just "gets it" a bit more What is boils down to for me is that even though it's more expensive I would much ra…
Earlier quoted context omitted.
For what is worth I find GPT 5.5 qualitatively different than 5.4 and 5.3 If I had to collapse the nature of the difference in one sentence it'd be that the 5.5 does more what I'm asking it to do versus doing a small aspect of what I'm asking then stopping. 5.4 required a lot of "continue" encouragement. 5.5 just "gets it" a bit more What is boils down to for me is that even though it's more expensive I would much ra…
They must have changed something recently as when 5.5 first dropped I was unable to make it do anything. It would say it will implement, but would never actually do it, no matter how many times I tried to tell it what it needs to do. It would acknowledge what needs to be done, even create step by step plan and then ask if it should do it. I would confirm and then it will just go around reiterating the plan and that t…
I feel that the recent iterations of LLM haven't provided an intuitive qualitative leap. Have they entered a bottleneck period so quickly?
Some releases are just "meh", but I wouldn't rule out exciting new stuff for 2026 just because Opus 4.7 sucked.