For those who happen to have a subscription to The Economist, there is a very interesting Money Talks podcast where they interview Anthropic's boss Dario Amodei[1].
There were two interesting takeaways about AGI:
1. Dario makes the remark that the term AGI/ASI is very misleading and dangerous. These terms are ill defined and it's more useful to understand that the capabilities are simply growing exponentially at the moment. If you extrapolate that, he thinks it may just "eat the majority of the economy". I don't know if this is self-serving hype, and it's not clear where we will end up with all this, but it will be disruptive, no matter what.
2. The Economist moderators however note towards the end that this industry may well tend toward commoditization. At the moment these companies produce models that people want but others can't make. But as the chip making starts to hits its limits and the information space becomes completely harvested, capability-growth might taper off, and others will catch up. The quasi-monopoly profit potentials melting away.
Putting that together, I think that although the cognitive capabilities will most likely continue to accelerate, albeit not necessarily along the lines of AGI, the economics of all this will probably not lead to a winner takes all.
There's already so many comparable models, and even local models are starting to approach the performance of the bigger server models.
I also feel like, it's stopped being exponential already. I mean last few releases we've only seen marginal improvements. Even this release feels marginal, I'd say it feels more like a linear improvement.
That said, we could see a winner take all due to the high cost of copying. I do think we're already approaching something where it's mostly price and who released their models last. But the cost to train is huge, and at some point it won't make sense and maybe we'll be left with 2 big players.
1. FWIW, I watched clips from several of Dario’s interviews. His expressions and body language convey sincere concerns.
2. Commoditization can be averted with access to proprietary data. This is why all of ChatGPT, Claude, and Gemini push for agents and permissions to access your private data sources now. They will not need to train on your data directly. Just adapting the models to work better with real-world, proprietary data will yield a powerful advantage over time.
Also, the current training paradigm utilizes RL much more extensively than in previous years and can help models to specialize in chosen domains.
About 1: Indeed. The moderator remarked at the end that once the interview was over, Dario's expression sort of sagged and it felt like you could see the weight on his shoulders. But you never know if that's part of the act.
About 2: Ah, yes. So if one vendor gains sufficient momentum, their advantage may accelerate, which will be very hard to catch up with.
There were two interesting takeaways about AGI:
1. Dario makes the remark that the term AGI/ASI is very misleading and dangerous. These terms are ill defined and it's more useful to understand that the capabilities are simply growing exponentially at the moment. If you extrapolate that, he thinks it may just "eat the majority of the economy". I don't know if this is self-serving hype, and it's not clear where we will end up with all this, but it will be disruptive, no matter what.
2. The Economist moderators however note towards the end that this industry may well tend toward commoditization. At the moment these companies produce models that people want but others can't make. But as the chip making starts to hits its limits and the information space becomes completely harvested, capability-growth might taper off, and others will catch up. The quasi-monopoly profit potentials melting away.
Putting that together, I think that although the cognitive capabilities will most likely continue to accelerate, albeit not necessarily along the lines of AGI, the economics of all this will probably not lead to a winner takes all.
[1] https://www.economist.com/podcasts/2025/07/31/artificial-int...