21–30 of 394 posts
LLMs are so incredibly useful and powerful but they will NEVER be AGI. I actually wonder if the success of (and subsequent obsession with) LLMs is putting true AGI further out of reach. All that these AI companies see are the $$$. When the biggest "AI Research Labs" like OpenAI shifted to product-izing their LLM offerings I think the writing was on the wall that they don't actually care about finding AGI.
Earlier quoted context omitted.
I feel like it's already been pretty well digested and excreted for the most part, now we're into the re-ingestion phase until the bubble bursts.
maybe silicon valley and the world move at basically different rates idk AI is just a speck outside of the HN and SV info-bubbles still early to mass adoption like the smartphone or the internet, mostly nerds playing w it
> still early to mass adoption like the smartphone or the internet, mostly nerds playing w it
Rather: outside of the HN and SV bubbles, the A"I"s and the fact how one can fall for this kind of hype and dupery is commonly ridiculed.
The most intriguing part is if Humanoid factory worker programming will be made 1000 to 10,000x more cost effective with LLM. Effectively ending all human production. I know this is a sensitive topic but I dont think we are far off. And I often wonder if this is what the current administration has in sight. ( Likely Not )
Earlier quoted context omitted.
We sort of are able to recognize Nobel-worthy breakthroughs One of the many definitions I have for AGI is being able to create the proofs for the 2030, 2050, 2100, etc Nobel Prizes, today A sillier one I like is that AGI would output a correct proof that P ≠ NP on day 1
Isn't AGI just "general" intelligence as in -like a regular human- turing test kinda deal? aren't you thinking about ASI/ Superintelligence way capable of outdoing humans?
Would we even recognise it if it arrived? We'd recognise human level intelligence, probably, but that's specialised. What would general intelligence even look like.
you'd be able to give them a novel problem and have them generalize from known concepts to solve it. here's an example: 1 write a specification for a language in natural language 2 write an example program can you feed 1 into a model and have it produce a compiler for 2 that works as reliably as a classically built one? I think that's a low bar that hasn't been approached yet. until then I don't see evidence of langu…
LLMs are basically a library that can talk. That’s not artificial intelligence.
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 mental math techniques that were discovered at training time. For example, Claude uses a special trick for adding 2 digit numbers ending in 6 and 9.
Many more examples in this recent reach report, including evidence of future planning while writing rhyming poetry.
https://www.anthropic.com/research/tracing-thoughts-language...
LLMs are basically a library that can talk. That’s not artificial intelligence.
Grammar engines. Or value matrix engines. Everytime I try to work with them I lose more time than I gain. Net loss every time. Immensely frustrating. If i focus it on a small subtask I can gain some time (rough draft of a test). Anything more advanced and its a monumental waste of time. They are not even good librarians. They fail miserably at cross referencing and contextualizing without constant leading.
LLMs are unbelievably useful for me - never have I had a tool more powerful to assist my brain work. I useLLMs for work and play constantly every day.
It pretends to sound like a person and can mimic speech and write and is all around perhaps the greatest wonder created by humanity.
It’s still not artificial intelligence though, it’s a talking library.
And in 30 years it will be another 30 years away. LLMs are so incredibly useful and powerful but they will NEVER be AGI. I actually wonder if the success of (and subsequent obsession with) LLMs is putting true AGI further out of reach. All that these AI companies see are the $$$. When the biggest "AI Research Labs" like OpenAI shifted to product-izing their LLM offerings I think the writing was on the wall that they…
Earlier quoted context omitted.
I feel like it's already been pretty well digested and excreted for the most part, now we're into the re-ingestion phase until the bubble bursts.
I am tech founder, who spends most of my day in my own startup deploying LLM-based tools into my own operations, and I'm maybe 1% of the way through the roadmap I'd like to build with what exists and is possible to do today.