OpenAI Says “AGI” Is Here — What Does That Actually Mean?

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Ed Elson (1:50)

Welcome to Prof G Markets. I'm Ed Elson. It is September 8th. Let's check in on yesterday's market vitals.

US markets were closed for Labor Day, but stock futures fell as the US and Iran escalated their attacks. Brent crude climbed towards $98 per barrel. Copper hit an all-time high on the prospect that Trump will expand his tariffs on the metal. And finally, the Japanese yen rose to its highest level since February as the dollar fell.

Okay, what else is happening? OpenAI's newest and most powerful model is officially here, GPT-6 Astra. Released on Friday, Astra was trained on more than 100,000 NVIDIA GPUs at the Stargate Data Center in Texas. That makes it the largest training run in OpenAI's history, and it costs two and a half times the cost of OpenAI's previous model.

Astra represents a large advance in capabilities for OpenAI, and across the AI industry, leaders have been celebrating. In response to the model, NVIDIA CEO Jensen Huang said artificial general intelligence, or AGI, has arrived. Meanwhile, OpenAI's president, Greg Brockman, said, welcome to the AGI era, describing Astra as a generational leap. Now, if Astra is indeed AGI, then that would be a very big deal, as many AI researchers have specifically cited AGI as the milestone that might change society forever. Sam Altman, for example, once said that AGI could quote break capitalism. Meanwhile, Stuart Russell, a prominent AI scientist, has said that when we achieve AGI, human wages will quote go to zero. Well, AGI has supposedly arrived, but capitalism and wages remain intact, which would imply one of two things. Either the industry's predictions about AGI were wildly wrong, or this isn't really AGI. Here to give us his view, we are speaking with Gary Marcus, author, scientist, entrepreneur, and emeritus professor of psychology and Neuro Science at NYU. Gary, thank you so much for joining us on the show. I'd like to just start with your reactions to the model itself, Astra. What do you make of it? Can you describe some of its capabilities, and then we will get into whether or not it is artificial general intelligence, AGI?

Gary Marcus (4:18)

In terms of the model itself, it's a bit better than the models before. What we have now is an era where some people call it benchmark maxing or bench maxing, where these systems are often, it would appear, trained on lots of benchmarks. They do really well on the benchmarks, and then they don't typically do as well in the real world. Every time we see the same phenomenon, model comes out, everybody's super excited about it. Then after a few days, people are like, yeah, but I tried it and it doesn't really work on this, it doesn't really work on that, it deleted by files, the code it writes is for shit.

The code it writes is for shit is something I saw about Astra yesterday on Twitter.

Some people will like it, some people won't.

But every model is hyped as if it's this quantum leap forward and it never turns out to be true. Each new model is better than the last one, there's no doubt about that. Astra is better than Fable, its competitor on a bunch of measures. In real world practice, it's better on some and not others based on people's different accounts. It used to be when a new model came out, I would personally test a lot of things about it, but now the scope of what people want to do with them is so vast, no one person can do that. And you sort of have to see what the world's experience with it is. And what the world's experience has been with all prior models is they don't live up to expectations. We've talked about this before. The return on investment isn't there, certainly wages haven't dropped to zero. Instead, we have what I call the Klarna effect, which is Klarna said they were gonna get rid of a bunch of humans, and then they quietly walked that back and started rehiring humans. We've now seen that dozens of times. We may see a version of the Klarna effect with Astra where a bunch of people say we're gonna lay off a bunch of people and then quietly rehire them.