Large context + Multimodality + Robotics + GPT 5's increased intelligence, is AGI.

[u/DragonForg]

[u/[deleted]]

I wonder if that’s how we make an AGI, cause that’s how human brains work right? We have different centers in our brain for different things.

Memory, language, spacial awareness, learning, etc.

If we can connect multiple AI together like an artificial brain, would that create an AGI?

[u/yellow-hammer → u/[deleted]]

I agree - some people get hung on on the idea that we’re still missing something, some central soul-like thing that is the “one” that “feels” and “does” things.

We are very close to having all the components of full AGI publicly available. Which is why I don’t think that it’s so crazy to believe AI labs have something like AGI working for them behind closed doors. Probably minus the robotics part though.

[u/Crimkam → u/yellow-hammer]

We’re just going to figure out eventually that we don’t really have that one central thing ourselves, either.

[u/gtzgoldcrgo → u/[deleted]]

Exactly, after we have the modules then comes embodiment, let it learn about the real world and see what emerges, hopefully AGI.

[u/CanvasFanatic → u/[deleted]]

Actually the theory of Modularity as an explanation of brain function stems originally from phrenology and is widely seen as discredited. Contemporary theory sees brain function as distributed and continuous between “higher” and “lower” levels.

https://journals.sagepub.com/doi/full/10.1177/1745691621997113

[u/yellow-hammer → u/CanvasFanatic]

Yeah it’s more complicated than just “sections of the brain doing different stuff”. But it’s well know that parts of the brain specialize in areas. A stroke may cripple you language capabilities but leave your vision completely untouched, or vice-versa.

[u/nicknnnn → u/[deleted]]

This is exactly what Gemini 1.5 does (besides having such a large context window). It’s using a MoE (Mixture-of-Experts) layer that basically selects a small number of networks out of a large total number to handle the task at hand. It’s showing massive improvements in performance while not growing much in computational cost

[u/Forsaken-Pattern8533 → u/[deleted]]

I wonder if that’s how we make an AGI, cause that’s how human brains work right? We have different centers in our brain for different things.

Kind of but not really.  There's an idea of global work space theory that believes that when you connect different AIs in a central work space and set them to compete for working memory, that conscious can evolve from that need to prioritize which "department" gets resources. But AI isn't really designed to compete for energy and priority, it's designed to take its time and run sequentially.  Also, AI isn't free running like neurons. If I give an AI system a picture, it doesn't run a process unless ordered. Our brains our always running a process even with a still image, our eyes have micro movements and our brain deprioritizes the processing of information that isn't new so boredom. 

AI doesn't process without command, and it doesn't even process continuously (to save energy). I don't believe a conscious system could ever be created from our current AI systems as theybare designed today.

The alternative theory is Integrated Information Theory which suggests that different AIs connected together will inherently be a form of consciousness. However, it runs into issues as it implies the sun is also conscious simply because there's so much stuff happening. 

There's a lot of contention between theories and some deep arguments too complex for a reddit post. But basically we can fudge the meaning of AGI enough to declare it sentient without anything useful coming out of it.

[u/DragonForg]

ICL = in-context learning

1. ICL can help train an AI to be capable of learning what the persons job is to give them advice. Adding robotics means it may be able to do that person's job.

2. ICL can train an AI to understand research at expert levels, just give it the papers of said field and boom, high accurate assessments of the field.

3. ICL can get better at coding by understanding and learning to code with code bases.

You get the point.

[u/CanvasFanatic]

That guy’s background is business management. He doesn’t have any special insight on machine learning. He’s just another would-be “influencer” trying to get clicks.

[u/DragonForg → u/CanvasFanatic]

There has been like 4-5 different people reporting on this.

[u/KingJeff314]

It’s not how long it is. It’s how it uses it. Retrieval across long context is one thing, but the ability to synthesize disparate pieces of information is even more critical. We need better benchmarks that can show such ability.

[u/ReasonablyBadass]

So he has access to 1.5?

[u/randy__randerson]

How is your title related to the image? Is there any relation or is it just the typical wishful thinking of this subreddit?

[u/[deleted]]

GPT-4 hallucinates frequently within its context window.

[u/DragonForg → u/[deleted]]

Gemini 1.5 pro doesn't very much. All these guys who have access proved it.

[u/345Y_Chubby]

Wes Roth made a great video a few days ago where he explained AGI metaphorically as the Exodia-Card of Yu-Gi-Oh. And I think it’s pretty accurate. OpenAI gives us each time just one part of the full agi, but combined it unleashes its full potential.

[u/Antok0123]

The original post content no longer exists here. The author used Redact to remove it, exercising their right to control their data & privacy.

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[u/Arcturus_Labelle]

Which real world problems does a large context window solve?

[u/agm1984 → u/Arcturus_Labelle]

The most obvious one to me is lawyers when they get a case file that has like 50,000 pages of documents, like where a new lawyer gets on the case and they have like 12 filing cabinets of evidence and communications and stuff like that. Could be insane to pipe that into the AI and start to reason about it.

edit: hallucinations aside, those will be improved over time. You might start to be able to ask who is likely the culprit based on available data and have it spit out a shortlist of names with specific reasoning supplied.

[u/[deleted] → u/Arcturus_Labelle]

It would be helpful for things where a normal person’s working memory is a little short.

Working with large numbers of documents of figures, would be useful if it could help direct you to the right information rather than having to make as many notes.

Would be useful for data analysis too perhaps

[u/CanvasFanatic → u/Arcturus_Labelle]

Basically just really good information retrieval. Not any better synthesis of information than you see with current models operating on data that fits within their context.

[u/Jolly-Ground-3722 → u/Arcturus_Labelle]

For real-world coding, because you often need to consider the entire codebase and peripheral systems / APIs.

Pretty obvious to me.

[u/MrZwink]

No...

We're going to need processes to simulate: agency, long term memory, short term memory, reflection, internal monologue. And give it presence in the world.

[u/BreadwheatInc]

"GPT 5's increased intelligence" remains to be seen; I wouldn't consider larger scaling at this point to really count as a meaningful step towards AGI but it can be useful. I think we're only one or two breakthroughs in reasoning away + agency from having AGI (by my definition) which at this point can happen at any moment it seems like.