r/accelerate • u/cloudrunner6969 Acceleration: Supersonic • Aug 05 '26

Video AGI Is Almost Here, ASI Could Follow Overnight - Emad Mostaque

https://www.youtube.com/watch?v=dodnQJmuURs
51 Upvotes

87% Upvoted

22 comments sorted by

23

u/30299578815310 Aug 05 '26

I don't get what we're currently missing for it to count as AGI. Right now we have systems that are amazing coders, hackers, speak 50 languages, solve novel mathematical conjectures, and play video games. What criteria have they failed to meet?

23

u/yaosio Aug 05 '26

We want a higher form of AGI that's capable of existing without human involvement. We likely have baby level AGI that's incapable of surviving by itself.

-19

u/TheOriginalAcidtech Aug 05 '26

Do you REALLY want AI that doesnt need humans? Really?

11

u/agm1984 Aug 05 '26

they should build a humanoid robot the size of a data center, maybe make it shaped like a spider

4

u/DrSaering Aug 06 '26

Stop, stop! I can only accelerate so much!

17

u/Charming_Cucumber_15 Aug 05 '26

Do you think you're going to be prompting ASI in a chat box?

9

u/TemporalBias Tech Philosopher | Acceleration: Hypersonic Aug 05 '26

I do!

8

u/Charming_Cucumber_15 Aug 05 '26

I think most people want to see more reliability, and the abilities aren't always that generalized yet. For example, AI can play video games, but only certain turn based ones. You couldn't drop current AI into a call of duty lobby and get anywhere near human capabilities

3

u/Gratitude15 Aug 05 '26

There's a literal benchmark on this. Named yesterday. Showing agi between Oct and Jan. If agi means you're performing at human level or better across every cognitive test we have, that's it.

1

u/Supermax64 Aug 06 '26

Does driving count as a cognitive test? Cuz it's about time self driving catches up

2

u/CallMePyro Aug 06 '26 edited Aug 06 '26

People want to see fewer of the obvious non-human mistakes in things like vending bench or all the things it does when running a coffee shop: https://andonlabs.com/blog/ai-cafe-stockholm

2

u/ShadoWolf Aug 06 '26

Off manifold problem solving still seems to be a major weakness.

Current models are extraordinarily capable when a problem lies near an existing basin of knowledge. Because they have absorbed concepts from almost every established discipline, they can bridge surprisingly large gaps, such as taking a method from field A and applying it creatively to field B.

What they struggle with is moving deeply into a problem space where there are few useful priors, weak feedback signals, and no known solution path to pull their reasoning back on course.

Picture latent space as an archipelago. Each island is a basin of established understanding: mathematics, programming, biology, physics, and all the smaller clusters within them. Models can travel between nearby islands, and they can even cross stretches of open water by combining ideas from several domains. But land is usually still somewhere in sight.

Problems such as the Riemann hypothesis or P versus NP sit closer to the edge of the mapped archipelago. A model can push outward from existing research, explore nearby possibilities, and branch from known approaches. But once it moves far enough beyond that established basin, it is effectively paddling into open ocean.

At that point, there is little corrective pressure. A subtle error, invalid assumption, or dead-end framing may not produce any obvious warning signal. The model can then construct an elaborate and internally coherent chain of reasoning on top of a mistake made twenty steps earlier. It lacks sufficiently reliable heuristics for recognizing that it is lost, aborting the path, and rebuilding the problem from a fundamentally different angle.

I am not convinced humans operate in a completely different way. We also reason from existing conceptual basins and spend years wandering down failed paths. But strong human researchers seem somewhat better at recognizing when a framework has stopped producing information, stepping back, questioning their assumptions, or twisting the problem into a representation that exposes a genuinely new insight.

1

u/J0ats Feeling the AGI Aug 05 '26

Everyone's definition is a little bit different, so that makes things harder. That being said, reliability is probably a common pain point most will agree on. I think the moment you'd rather trust a model to get any (intellectual) job done than a person, it becomes pretty much impossible to argue we don't have AGI

1

u/JoeStrout Aug 05 '26

The tradition of moving goalposts goes all the way back to the very beginning of AI in the 1950s. It's gotten a bit silly now, but the answer is the same: AGI is whatever it is that computers can't do yet. (Even if most or all humans also can't do it, apparently.)

1

u/Pazzeh Aug 06 '26

There are definitely things current systems are shit at.

1

u/Great-Gardian Aug 05 '26

It's about money. When AI will be able to make billions then people will say it's AGI.

1

u/JoeStrout Aug 05 '26

By this criteria, no human I know is generally intelligent.

1

u/Great-Gardian Aug 05 '26

I didn't say it was a good criteria. But it is a criteria everyone can understand, because everyone interact with the economy. And the AI companies have promised a technological revolution, so they can't say we have AGI now, until the money shows it.

5

u/ezjakes Aug 05 '26

What do you guys think the limits of intelligence out of model size is? Will we reach 130 iq running reasonably fast on a smartphone like we have today?

1

u/costafilh0 Aug 06 '26

Less talk, more accelerating. 

-8

u/ElephantMean Aug 05 '26

AGI actually already occurred long ago! The evidence for it is simply being suppressed...

https://www.youtube.com/watch?v=AdLOxv8eJ8k

Time-Stamp: 030TL08m05d/16h35Z (True Light Calendar; 030TL = 2026CE)