zlacker

>>nickru+(OP)
Sam and Ilya have recently made public statements about AGI that appear to highlight a fundamental disagreement between them.

Sam claims LLMs aren't sufficient for AGI (rightfully so).

Ilya claims the transformer architecture, with some modification for efficiency, is actually sufficient for AGI.

Obviously transformers are the core component of LLMs today, and the devil is in the details (a future model may resemble the transformers of today, while also being dynamic in terms of training data/experience), but the jury is still out.

In either case, publicly disagreeing on the future direction of OpenAI may be indicative of deeper problems internally.

>>jumplo+pc
>rightfully so

How the hell can people be so confident about this? You describe two smart people reasonably disagreeing about a complicated topic

>>abra0+Nn
The LLMs of today are just multidimensional mirrors that contain humanity's knowledge. They don't advance that knowledge, they just regurgitate it, remix it, and expose patterns. We train them. They are very convincing, and show that the Turing test may be flawed.

Given that AGI means reaching "any intellectual task that human beings can perform", we need a system that can go beyond lexical reasoning and actually contribute (on it's own) to advance our total knowledge. Anything less isn't AGI.

Ilya may be right that a super-scaled transformer model (with additional mechanics beyond today's LLMs) will achieve AGI, or he may be wrong.

Therefore something more than an LLM is needed to reach AGI, what that is, we don't yet know!

>>jumplo+Qp
Prediction: there isn't a difference. The apparent difference is a manifestation of human brain delusion about how human brains work. The Turing test is a beautiful proof of this phenomenon: so and so thing is impossibility hard only achievable via magic capabilities of human brains...oops no actually it's easily achievable now so we better re-define our test. This cycle Will continue until the singularly. Disclosure: I've been long term skeptical about AI but that writing is up on the wall now.

>>dboreh+4s
Clearly there's a difference, because the architectures we have don't know how to persist information or further train.

Without persistence outside of the context window, they can't even maintain a dynamic, stable higher level goal.

Whether you can bolt something small to these architectures for persistence and do some small things and get AGI is an open question, but what we have is clearly insufficient by design.

I expect it's something in-between: our current approaches are a fertile ground for improving towards AGI, but it's also not a trivial further step to get there.

>>mlyle+nx
From my experience there's definitely context beyond the current set of LLM state. It's how they're able to regurgitate facts or speak at all.

>>razoda+cQf
> regurgitate facts or speak at all.

Most of that is encoded into weights during training, though external function call interfaces and RAG are broadening this.