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Notes -
Did they? Did it?
There was a big flurry of development 3 - 4 years ago enabled by Nvidia's (then new) multimodal framework and novel tokenization methods, but my impression is that those early breakthroughs have since given way to increasingly high compute times for increasingly marginal gains.
As for the path forward, while llms and other generative models have thier uses, i find it unlikely that they represent a viable path towards "True AGI" as despite the claims of grifters and hype-men like Altman, they remain non-agentic nor are they "reasoning" or "inferring" in the sense that most people use that word. The reason of an LLM is more like the verbal/intellectual equivalent of a space filling curve. The more itterations of Hilbert you run the more of the square you color-in but you're still constraining yourself to points on a line (or tokens in the training data). Once you understand this, the apperant stupidity of LLMs becomes both less remarkable and far more predictable.
If we do see "True AGI" in the next 5-10 years I predict that it will come out of what will seem to a lot users here like left feild. But leave the algorithm engineers all nodding to each other. EG a breakthrough in digital signal processing leads to self-driving cars picking thier route for the scenery.
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