191–200 of 394 posts
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People over-estimate the short term and under-estimate the long term.
Compound growth starting from 0 is... always 0. Current LLMs have 0 general reasoning ability We haven't even taken the first step towards AGI
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Why does AGI necessitate having feelings or consciousness, or the ability to suffer? It seems a bit far to be giving future ultra-advanced calculators legal personhood?
The general part of general intelligence. If they don’t think in those terms there’s an inherent limitation. Now, something that’s arbitrarily close to AGI but doesn’t care about endlessly working on drudgery etc seems possible, but also a more difficult problem you’d need to be able to build AGI to create.
If we go by this definition then there's no caring, or a noticing of drudgery? It's simply defined by its ability to generalize solving problems across domains. The narrow AI that we currently have certainly doesn't care about anything. It does what its programmed to do
So one day we figure out how to generalize the problem solving, and enable it to work on a million times harder things.. and suddenly there is sentience and suffering? I don't see it. It's still just a calculator
1- https://cloud.google.com/discover/what-is-artificial-general...
My pet peeve: talking about AGI without defining it. There’s no consistent, universally accepted definition. Without that, the discussion may be intellectually entertaining—but ultimately moot. And we run into the motte-and-bailey fallacy: at one moment, AGI refers to something known to be mathematically impossible (e.g., due to the No Free Lunch theorem); the next, it’s something we already have with GPT-4 (which, w…
That's because of the I part. An actual complete description accepted by different practices in the scientific community.
"Concepts of "intelligence" are attempts to clarify and organize this complex set of phenomena. Although considerable clarity has been achieved in some areas, no such conceptualization has yet answered all the important questions, and none commands universal assent. Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen, somewhat different, definitions"
Might as well be 10 - 1000 years. Reality is no one knows how long it'll take to get to AGI, because: 1) No one knows what exactly makes humans "intelligent" and therefore 2) No one knows what it would take to achieve AGI Go back through history and AI / AGI has been a couple of decades away for several decades now.
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Compound growth starting from 0 is... always 0. Current LLMs have 0 general reasoning ability We haven't even taken the first step towards AGI
0 and 0.0001 may be difficult to distinguish.
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0 and 0.0001 may be difficult to distinguish.
You need to show evidence of that 0.0001 first otherwise you're going off blind faith
LLMs may well reach a closed endpoint without getting to AGI - this is my personal current belief - but people are certainly motivated to work on AGI
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Something new != truly novel. ChatGPT creates something new every time I ask it a question.
adjective: novel definition: new or unusual in an interesting way. ChatGPT can create new things, sure, but it does so at your directive . It doesn't do that because it wants to which gets back to the other part of my answer. When an LLM can create something without human prompting or directive, then we can call that intelligence.
I was a little bored of the novel I have been reading so I sat down with Gemini and we collaboratively wrote a terrible novel together.
At the start I was promoting it a lot about the characters and the plot, but eventually it starting writing longer and longer chapters by itself. Characters were being killed off left right and center.
It was hilariously bad, but it was creative and it was fun.
LLMs are basically a library that can talk. That’s not artificial intelligence.
There’s increasing evidence that LLMs are more than that. Especially work by Anthropic has been showing how to trace the internal logic of an LLM as it answers a question. They can in fact reason over facts contained in the model, not just repeat already seen information. A simple example is how LLMs do math. They are not calculators and have not memorized every sum in existence. Instead they deploy a whole set of me…
If you ask the LLM to explain how it got the answer the response it gives you won't necessarily be the steps it used to figure out the answer.
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I would be thrilled with AI assistive technologies, so long as they improve my capabilities and I can trust that they deliver the right answers. I don't want to second-guess every time I make a query. At minimum, it should tell me how confident it feels in the answer it provides.
> At minimum, it should tell me how confident it feels in the answer it provides. How’s that work out for Dave Bowman? ;-)
He just had to fall back upon his human wit in that specific instance, and everything worked out in the end.
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You need to show evidence of that 0.0001 first otherwise you're going off blind faith
I didn't make a claim either way. LLMs may well reach a closed endpoint without getting to AGI - this is my personal current belief - but people are certainly motivated to work on AGI