I'm somewhat hesitant to write this post because I worry its central claim will be misconstrued, but I think it's important to say now, so I'm writing it anyway.
Claude Opus 4.6 was released on February 5th. GPT-5.3 came out the same day. We've had a little over two weeks to use these models, and in the past day or so, I and others have started to realize, AGI is here.
Now, I don't want to overstate what I mean by this, so let me be clear on the criteria I'm using. If I were sitting back in 2018, before the release of GPT-2, and you asked me what AGI would be capable of, I'd probably have said something like this:
able to think (and engage in novel reasoning)
able to plan (and create plans for actions never before envisioned)
able to achieve goals (including instrumental goals set by itself)
flexible enough to meaningfully attempt most tasks a human can
It's hard to deny that Opus 4.6 and GPT-5.3 are able to do 1-3. The only one up for real debate is 4, because there are things that I can do, like make a peanut butter sandwich, that Claude and ChatGPT cannot. But given the capabilities these models are demonstrating, this feels more like a limitation of their harnesses than the models themselves. Given a few weeks and some advances in robotics, I'm confident the current models could be used to make sandwiches, though perhaps at the cost of millions of tokens.
To be clear, these models aren't AGI the way we expected it. When people talk about AGI, they often use the word to mean the whole thing, with continuous and transfer learning completely solved, full-spectrum multimodal perception, and embodiment in the form of robot interfaces. Instead, what we have is more like minimum viable AGI, meaning it's an AI just general enough that we should meaningfully begin applying the AGI label.
It's possible that, in retrospect, we should have made this declaration earlier. Maybe it should have come when Opus 4 or GPT-5 were released, or maybe when Claude Code came out. But those models were worse on all four of my criteria in ways that made it harder to say they were across the AGI threshold, and those who did say it were easier to dismiss.
Now it's harder to deny the claims. I work with these models every day to write code, and the amount of work I can delegate to them is incredible, surpassing what I would expect of a junior engineer. They're even capable enough to build a just-barely-functioning paperclip maximizer, which is a terrifying sentence to write. In the coming weeks and months, these models are only going to get more powerful, and as they do, things are going to get weirder.
You may think I'm early in making a declaration of AGI, and perhaps I am. But I hope you can agree that, if it's not there yet, AGI is coming soon, and I fear that we are nowhere near ready for it.
I'm somewhat hesitant to write this post because I worry its central claim will be misconstrued, but I think it's important to say now, so I'm writing it anyway.
Claude Opus 4.6 was released on February 5th. GPT-5.3 came out the same day. We've had a little over two weeks to use these models, and in the past day or so, I and others have started to realize, AGI is here.
Now, I don't want to overstate what I mean by this, so let me be clear on the criteria I'm using. If I were sitting back in 2018, before the release of GPT-2, and you asked me what AGI would be capable of, I'd probably have said something like this:
It's hard to deny that Opus 4.6 and GPT-5.3 are able to do 1-3. The only one up for real debate is 4, because there are things that I can do, like make a peanut butter sandwich, that Claude and ChatGPT cannot. But given the capabilities these models are demonstrating, this feels more like a limitation of their harnesses than the models themselves. Given a few weeks and some advances in robotics, I'm confident the current models could be used to make sandwiches, though perhaps at the cost of millions of tokens.
To be clear, these models aren't AGI the way we expected it. When people talk about AGI, they often use the word to mean the whole thing, with continuous and transfer learning completely solved, full-spectrum multimodal perception, and embodiment in the form of robot interfaces. Instead, what we have is more like minimum viable AGI, meaning it's an AI just general enough that we should meaningfully begin applying the AGI label.
It's possible that, in retrospect, we should have made this declaration earlier. Maybe it should have come when Opus 4 or GPT-5 were released, or maybe when Claude Code came out. But those models were worse on all four of my criteria in ways that made it harder to say they were across the AGI threshold, and those who did say it were easier to dismiss.
Now it's harder to deny the claims. I work with these models every day to write code, and the amount of work I can delegate to them is incredible, surpassing what I would expect of a junior engineer. They're even capable enough to build a just-barely-functioning paperclip maximizer, which is a terrifying sentence to write. In the coming weeks and months, these models are only going to get more powerful, and as they do, things are going to get weirder.
You may think I'm early in making a declaration of AGI, and perhaps I am. But I hope you can agree that, if it's not there yet, AGI is coming soon, and I fear that we are nowhere near ready for it.
Follow up post: What to Do About AGI