7 ms·

That is a good area to explore. Their map of the past is fixed. They are frozen at some point in their psychological time. What has stopped working? Their hippo

That is a good area to explore. Their map of the past is fixed. They are frozen at some point in their psychological time. What has stopped working? Their hippocampus and medial temporal lobe. These are like the write-head that move data from the hippocampus to the neo cortex. Their "I" can no longer update itself. Their DMN is frozen in time. So if intelligence is purely the "I" telling a continuous coherent story about itself. The difference is that although they are fixed in time which is a characteristic shared by a specific LLM model. They can still completely activate their task positive network for problem solving and if their previous information stored is adequate to solve the problem they can. You could argue that is pretty similar to an LLM and what it does. So it is certainly a signifiant component of intelligence. There is also the nature of the human brain, it is not just those systems of memory encoding, storage, and use of that in narratives. People with this type of amnesia still can learn physical skills and that happens in a totally different area of the brain with no need for the hippocampus->neocortex consolidation loop. So, the intelligence is significantly diminished, but not entirely. Other parts of the brain are still able to update themselves in ways an LLM currently cannot. The human with amnesia also has a complex biological sensory input mapping that is still active and integrating and restructuring the brain. So, I think when you get into the nuances of the human in this state vs. an LLM we can still say the human crosses some threshold for intelligence where the LLM does not in this framework. So, they have an "intelligence", localized to the present in terms of their TPN and memory formation. LLMs have this kind of "intelligence". But the human still has the capacity to rewire at least some of their brain in real time even with amnesia.

supern0va 7mo ago
>But the human still has the capacity to rewire at least some of their brain in real time even with amnesia. Sure, but just because LLMs don't have what we'd describe as human intelligence, doesn't mean they don't have intelligence. I think we're witnessing the creation and growth a weird new type of intelligence right now.
- bitexploder 7mo ago
  Anyone who dismisses your assertion is not very curious. What I am more interested in is what are its limits and can it perform novel reasoning. It probably needs efficient enough novel reasoning to update itself with new information to become a general reasoning intelligence capable of solving unknown problems. Right now they operate purely in the domain of words. They solve problems with words. They don’t seem to have very complex semantic maps. They approximate semantic maps with statistical brute force by generating words. They have a model of the past to generate the words. When something matches the word map is easy. When something is not reducible or did not have a good word match the only thing it can do is experimentally generate words until it seems to match the problem. But it is brute force. It is good they can solve known problems that fit known problem shapes. But their language dependency makes this very fragile. Without semantic meaning it has no way to evaluate if it is hallucinating easiy.

supern0va 7mo ago

>But the human still has the capacity to rewire at least some of their brain in real time even with amnesia. Sure, but just because LLMs don't have what we'd describe as human intelligence, doesn't mean they don't have intelligence. I think we're witnessing the creation and growth a weird new type of intelligence right now.

bitexploder 7mo ago
Anyone who dismisses your assertion is not very curious. What I am more interested in is what are its limits and can it perform novel reasoning. It probably needs efficient enough novel reasoning to update itself with new information to become a general reasoning intelligence capable of solving unknown problems. Right now they operate purely in the domain of words. They solve problems with words. They don’t seem to have very complex semantic maps. They approximate semantic maps with statistical brute force by generating words. They have a model of the past to generate the words. When something matches the word map is easy. When something is not reducible or did not have a good word match the only thing it can do is experimentally generate words until it seems to match the problem. But it is brute force. It is good they can solve known problems that fit known problem shapes. But their language dependency makes this very fragile. Without semantic meaning it has no way to evaluate if it is hallucinating easiy.