this post was submitted on 19 Mar 2025
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[–] Not_mikey@lemmy.dbzer0.com 75 points 1 week ago (11 children)

The actual survey result:

Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed. 

So they're not saying the entire industry is a dead end, or even that the newest phase is. They're just saying they don't think this current technology will make AGI when scaled. I think most people agree, including the investors pouring billions into this. They arent betting this will turn to agi, they're betting that they have some application for the current ai. Are some of those applications dead ends, most definitely, are some of them revolutionary, maybe

Thus would be like asking a researcher in the 90s that if they scaled up the bandwidth and computing power of the average internet user would we see a vastly connected media sharing network, they'd probably say no. It took more than a decade of software, cultural and societal development to discover the applications for the internet.

[–] pennomi@lemmy.world 4 points 1 week ago (1 children)

Right, simply scaling won’t lead to AGI, there will need to be some algorithmic changes. But nobody in the world knows what those are yet. Is it a simple framework on top of LLMs like the “atom of thought” paper? Or are transformers themselves a dead end? Or is multimodality the secret to AGI? I don’t think anyone really knows.

[–] relic_@lemm.ee 5 points 1 week ago

No there's some ideas out there. Concepts like heirarchical reinforcement learning are more likely to lead to AGI with creation of foundational policies, problem is as it stands, it's a really difficult technique to use so it isn't used often. And LLMs have sucked all the research dollars out of any other ideas.

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