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viraptortoday at 4:56 AM3 repliesview on HN

> exponential progress

First you need to define what it means. What's the metric? Otherwise it's very much something you can argue about.


Replies

nicboutoday at 2:00 PM

Time spent being human and enjoying life.

I can’t point at many problems it has meaningfully solved for me. I mean real problems , not tasks that I have to do for my employer. It seems like it just made parts of my existence more miserable, poisoned many of the things I love, and generally made the future feel a lot less certain.

scotty79today at 11:16 AM

Define it however you like. There's not a single chart you can draw that even begins to look like a signoid.

noodletheworldtoday at 8:15 AM

> What's the metric?

Language model capability at generating text output.

The model progress this year has been a lot of:

- “We added multimodal”

- “We added a lot of non AI tooling” (ie agents)

- “We put more compute into inference” (ie thinking mode)

So yes, there is still rapid progress, but these ^ make it clear, at least to me, that next gen models are significantly harder to build.

Simultaneously we see a distinct narrowing between players (openai, deepseek, mistral, google, anthropic) in their offerings.

Thats usually a signal that the rate of progress is slowing.

Remind me what was so great about gpt 5? How about gpt4 from from gpt 3?

Do you even remember the releases? Yeah. I dont. I had to look it up.

Just another model with more or less the same capabilities.

“Mixed reception”

That is not what exponential progress looks like, by any measure.

The progress this year has been in the tooling around the models, smaller faster models with similar capabilities. Multimodal add ons that no one asked for, because its easier to add image and audio processing than improve text handling.

That may still be on a path to AGI, but it not an exponential path to it.

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