[brokencode]

They are using the current models to help develop even smarter models. Each generation of model can help even more for the next generation.

I don’t think it’s hyperbolic to say that we may be only a single digit number of years away from the singularity.

[lm28469]

I must be holding these things wrong because I'm not seeing any of these God like superpowers everyone seem to enjoy.

[brokencode]

Who said they’re godlike today?

And yes, you are probably using them wrong if you don’t find them useful or don’t see the rapid improvement.

[mrandish]

> using the current models to help develop even smarter models.

That statement is plausible. However, extrapolating that to assert all the very different things which must be true to enable any form of 'singularity' would be a profound category error. There are many ways in which your first two sentences can be entirely true, while your third sentence requires a bunch of fundamental and extraordinary things to be true for which there is currently zero evidence.

Things like LLMs improving themselves in meaningful and novel ways and then iterating that self-improvement over multiple unattended generations in exponential runaway positive feedback loops resulting in tangible, real-world utility. All the impressive and rapid achievements in LLMs to date can still be true while major elements required for Foom-ish exponential take-off are still missing.

[sekai]

> I don’t think it’s hyperbolic to say that we may be only a single digit number of years away from the singularity.

We're back to singularity hype, but let's be real: benchmark gains are meaningless in the real world when the primary focus has shifted to gaming the metrics

[brokencode]

Ok, here I am living in the real world finding these models have advanced incredibly over the past year for coding.

Benchmaxxing exists, but that’s not the only data point. It’s pretty clear that models are improving quickly in many domains in real world usage.