I’m not sure that self-updating weights is really analogous to “continuous learning” as humans do it. A memory data structure that the model can search efficiently might be a lot closer.

Self-updating weights could be more like epigenetics.

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Jensson 3 days ago | parent | next [-]

Human neurons are self updating though, we aren't running on our genes each cell is using our genes to determine how to connect to other cells and then the cell learns how to process some information there based on what it hears from its connected cells.

So, genes would be a meta model that then updates weights in the real model so it can learn how to process new kinds of things, and for stuff like facts you can use an external memory just like humans does.

Without updating the weights in the model you will never be able to learn to process new things like a new kind of math etc, since you learn that not by memorizing facts but by making new models for it.

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HarHarVeryFunny 2 days ago | parent | prev | next [-]

There's a difference between memory and learning.

Would you rather your illness was diagnosed by a doctor or by a plumber with access to a stack of medical books ?

Learning is about assimilating lots of different sources of information, reconciling the differences, trying things out for yourself, learning from your mistakes, being curious about your knowledge gaps and contradictions, and ultimately learning to correctly predict outcomes/actions based on everything you have learnt.

You will soon see the difference in action as Anthropic apparently agree with you that memory can replace learning, and are going to be relying on LLMs with longer compressed context (i.e. memory) in place of ability to learn. I guess this'll be Anthropic's promised 2027 "drop-in replacement remote worker" - not an actual plumber unfortunately (no AGI), but an LLM with a stack of your company's onboarding material. It'll have perfect (well, "compressed") recall of everything you've tried to teach it, or complained about, but will have learnt nothing from that.

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danenania 2 days ago | parent [-]

I think my point is that when the doctor diagnoses you, she often doesn’t do so immediately. She is spending time thinking it through, and as part of that process is retrieving various pieces of relevant information from her memory (both long term and short term).

I think this may be closer to an agentic, iterative search (ala claude code) than direct inference using continuously updated weights. If it was the latter, there would be no process of thinking it through or trying to recall relevant details, past cases, papers she read years ago, and so on; the diagnosis would just pop out instantaneously.

	▲	HarHarVeryFunny 2 days ago \| parent [-]
		Yes, but I think a key part of learning is experimentation and the feedback loop of being wrong. An agent, or doctor, may be reasoning over the problem they are presented with, combining past learning with additional sources of memorized or problem-specific data, but in that moment it's their personal expertise/learning that will determine how successful they are with this reasoning process and ability to apply the reference material to the matter at hand (cf the plumber, who with all the time in the world just doesn't have the learning to make good use of the reference books). I think there is also a subtle problem, not often discussed, that to act successfully, the underlying learning in choosing how to act has to have come from personal experience. It's basically the difference between being book smart and having personal experience, but in the case of an LLM also applies to experience-based reasoning it may have been trained on. The problem is that when the LLM acts, what is in it's head (context/weights) isn't the same as what was in the head of the expert whose reasoning it may be trying to apply, so it may be trying to apply reasoning outside of the context that made it valid. How you go from being book smart, and having heard other people's advice and reasoning, to being an expert yourself is by personal practice and learning - learning how to act based on what is in your own head.

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imtringued 2 days ago | parent | prev [-]

In spiking neural networks, the model weights are equivalent to dendrites/synapses, which can form anew and decay during your lifetime.