This grammatical mistake drives me nuts. I notice it is common with ESLs for some reason.
From GPT-4 to AGI: Counting the OOMs
21–30 of 77 posts
Re: From GPT-4 to AGI: Counting the OOMs
#22AGI is not a continuum from LLMs; true intelligence is characterized by comprehension, reasoning, and self-awareness, transcending mere data patterns.
What is an abstract reasoning task that your average 15 year old (who has "general intelligence") can do that you think LLMs can't do?
Re: From GPT-4 to AGI: Counting the OOMs
#23AGI is not a continuum from LLMs; true intelligence is characterized by comprehension, reasoning, and self-awareness, transcending mere data patterns.
What LLMs have done is really redefine my internal definition of "intelligence."
Putting aside the fact I don't believe in free will, I'm no longer sure my own brain is doing anything substantially different to what an LLM does now. Even with tasks like math I wonder if my brain is not really "working out" the solution but merely using probabilities based on every previous math problem I have seen or solved.
Re: From GPT-4 to AGI: Counting the OOMs
#24Earlier quoted context omitted.
Doing any job for more than an hour without completely forgetting it's goals and tasks
How long do you expect LLMs/agents to be unable to do this?
I think LLMs are a dead end on the path to AGI.
Re: From GPT-4 to AGI: Counting the OOMs
#25Earlier quoted context omitted.
What is an abstract reasoning task that your average 15 year old (who has "general intelligence") can do that you think LLMs can't do?
These "it's like a young/stupid person" arguments are wretched. LLMs are interesting but it should be obvious their development is not comparable to the development of human beings.
It's obvious to everyone who isn't willfully blind that LLMs aren't truly intelligent, and all the mental gymnastics that people go through to try to portray LLMs as genuinely intelligent is just so tedious.
Re: From GPT-4 to AGI: Counting the OOMs
#26Also from a month ago: https://news.ycombinator.com/item?id=40584237
In my opinion, this author has drunken the kool-aid and then some. There is simply no evidence that more scaling of LLMs will lead to AGI, and on the contrary there is plenty of evidence that the current "gaps" that LLMs have are innate and unsolvable with just more scaling.
Re: From GPT-4 to AGI: Counting the OOMs
#27> By the end of this, I expect us to get something that looks a lot like a drop-in remote worker. An agent that joins your company, is onboarded like a new human hire, messages you and colleagues on Slack and uses your softwares, makes .. I work at a company with ~50k employees each of whom has different data access rules governed by regulation. So either (a) you train thousands of models which is cost-prohibitive or…
Re: From GPT-4 to AGI: Counting the OOMs
#28> By the end of this, I expect us to get something that looks a lot like a drop-in remote worker. An agent that joins your company, is onboarded like a new human hire, messages you and colleagues on Slack and uses your softwares, makes .. I work at a company with ~50k employees each of whom has different data access rules governed by regulation. So either (a) you train thousands of models which is cost-prohibitive or…
They won't be used in your business and your business will be less efficient until the regulations change or you end up competing with someone who is willing to ignore the regulations. Also, there are lots of countries without as stringent regulations, it’s not about the inefficiencies that are gone that is the problem, is it about the efficiencies that are created that is the problem. This is a country to country is…
And fine grained access control is a foundational data governance issue for every enterprise.
Re: From GPT-4 to AGI: Counting the OOMs
#29Earlier quoted context omitted.
Doing any job for more than an hour without completely forgetting it's goals and tasks
How long do you expect LLMs/agents to be unable to do this?
It's actually not very easy to achieve this. I could give a very long winded answer (don't tempt me) but suffice to say it's a resolution problem.
All AI have a fixed resolution on creation. Long running tasks focus on a very particular narrowing space per step, the resolution required for an infinite task is infinite resolution.
No 9s of error will ever fix this.
Funny enough, small animals do this with ease so I strongly disagree the idea that our AI outcompete even small mammals in every way.
Re: From GPT-4 to AGI: Counting the OOMs
#30Earlier quoted context omitted.
How long do you expect LLMs/agents to be unable to do this?
Personally, I think that phenomenon (along with "hallucinations") is fundamentally baked into LLMs writ large. I think LLMs are a dead end on the path to AGI.
I think hallucinations are a major unsearched gateway to AGI.