21–30 of 74 posts
It ought to be clear to a cognitive scientist (which the author is) that we do not know how human thought processes work except at a very course level.
The idea that we have an understanding refined enough to take the next step and "simulate" these processes is just pure crackpot bunk.
“Implementing this in a machine will enable artificial general intelligence” If that’s true why didn’t he just implement it? Why should I take anyone seriously that just talks about code instead of actually coding it? This would be much more compelling if he just showed benchmarks and performance instead of writing up an argument. Furthermore, I don’t believe him.
I looked it up, the author has PhD in Brain and Cognitive Science. Are you aware of the fact that even partially implementing something like this, would require multi-year effort with dozens of engineers at minimum and will cost millions of dollars just for training.
Unfortunately, that means that's also the bar for being able to utter the words "IMPLEMENTING THIS IN A MACHINE WILL ENABLE ARTIFICIAL GENERAL INTELLIGENCE" and being taken seriously. In fact the bar is even higher than that, since merely meeting the criteria you lay out is still no guarantee of success, it is merely an absolute minimum.
The fact that that is a high bar means simply that; it's a high bar. It's not a bar we lower just because it's really hard.
Earlier quoted context omitted.
I looked it up, the author has PhD in Brain and Cognitive Science. Are you aware of the fact that even partially implementing something like this, would require multi-year effort with dozens of engineers at minimum and will cost millions of dollars just for training.
That's a tiny team, a short timescale, and a trivial cost. Seriously, when you're a bit older you'll see more wasted on the most useless ideas.
“Implementing this in a machine will enable artificial general intelligence” If that’s true why didn’t he just implement it? Why should I take anyone seriously that just talks about code instead of actually coding it? This would be much more compelling if he just showed benchmarks and performance instead of writing up an argument. Furthermore, I don’t believe him.
Today, I think active inference and free energy principle (from Friston) are perhaps having a bit more impact (at least showing up in some RL innovations), but are still a long way off from creating something that thinks like we do.
Earlier quoted context omitted.
I looked it up, the author has PhD in Brain and Cognitive Science. Are you aware of the fact that even partially implementing something like this, would require multi-year effort with dozens of engineers at minimum and will cost millions of dollars just for training.
That's a tiny team, a short timescale, and a trivial cost. Seriously, when you're a bit older you'll see more wasted on the most useless ideas.
Earlier quoted context omitted.
I looked it up, the author has PhD in Brain and Cognitive Science. Are you aware of the fact that even partially implementing something like this, would require multi-year effort with dozens of engineers at minimum and will cost millions of dollars just for training.
The perfect way to never have your theories invalidated
But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reasoning and idea exploration.
Where LLMs fail is in lookup, memory, and learning. But we've all seen how easy it is to extend them with RAG architectures.
My personal, non-scientific prediction for the basic modules of AGI are:
- LLMs to do basic reasoning
- a scheduling system that runs planning and execution tasks
- sensory events that can kick off reasoning, but with clever filters and shortcuts
- short term memory to augment and improve reasoning
- tools (calculators etc.) for common tasks
- a flexible and well _designed_ memory system -- much iteration required to get this right, and i don't see a lot of work being done on it, which is interesting
- finally, a truly general intelligence would have the capability to mutate many of the above elements based on learning (LLM weights, scheduling parameters, sensory filters, and memory configurations). But not everything needs to be mutable. many elements of human cognition are probably immutable as well.
“Implementing this in a machine will enable artificial general intelligence” If that’s true why didn’t he just implement it? Why should I take anyone seriously that just talks about code instead of actually coding it? This would be much more compelling if he just showed benchmarks and performance instead of writing up an argument. Furthermore, I don’t believe him.
I looked it up, the author has PhD in Brain and Cognitive Science. Are you aware of the fact that even partially implementing something like this, would require multi-year effort with dozens of engineers at minimum and will cost millions of dollars just for training.
Here's an article I wrote describing the song but without actually writing any of the notes because I can't read or write music either.
But I've listened to a lot of music and my tunes are better than those.
I went to school for music description so I know what I'm talking about.
“Implementing this in a machine will enable artificial general intelligence” If that’s true why didn’t he just implement it? Why should I take anyone seriously that just talks about code instead of actually coding it? This would be much more compelling if he just showed benchmarks and performance instead of writing up an argument. Furthermore, I don’t believe him.
These sentences from section 5.2 convince me that the author is oddly not even interested in building what he's talking about, or making a plan to do so.
- Isn't the point of a markov process that it _is_ stateful, but that _all_ its state is present at in each x_i, such that for later times k > i, x_k never needs to refer to some prior x_j with j - "Here's a list of broad, flexible families of computational processing that can have some concept of a sequence. Your turn, engineers!"