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kingstnap 41 minutes ago [-]
There would need to be another paradigm shift if they wanna keep inflating AI usage.
We went from simple chatbots to thinking models which massively exploded token utilization.
We then went from simple thinking models to tool calls and agents. Agents, and particularly long horizon agents, burn truly insane numbers of tokens blowing thinking models well out of the water.
People are trying to do agentic swarms as the next step but I don't think those make sense as of right now. Particularly they are just too insanely expensive and not that useful.
Plus right now the models just aren't good at it. It's like early agents when they first started making tool calls.
Agents are really quite bad at using subagents. They don't really internalize how to deploy them and they also don't utilize them in the ways that make sense (produce planning documents, have verifiable artifacts, break down tasks in ways that minimize risk, recognize model limitations in instruction following, iterate on results, etc).
layer8 17 minutes ago [-]
So there needs to be a new paradigm shift every few months or so? Because I remember people hailing AI reaching a new level of capability less than half a year ago, and saying it’d still be so much worth it even at ten times the price. And that already has lost momentum? If that’s the case, then AI companies are hugely overvalued. These contrasts are just wild to me.
Your last paragraph is also striking in that it exemplifies how far away from general intelligence they still are.
We went from simple chatbots to thinking models which massively exploded token utilization.
We then went from simple thinking models to tool calls and agents. Agents, and particularly long horizon agents, burn truly insane numbers of tokens blowing thinking models well out of the water.
People are trying to do agentic swarms as the next step but I don't think those make sense as of right now. Particularly they are just too insanely expensive and not that useful.
Plus right now the models just aren't good at it. It's like early agents when they first started making tool calls.
Agents are really quite bad at using subagents. They don't really internalize how to deploy them and they also don't utilize them in the ways that make sense (produce planning documents, have verifiable artifacts, break down tasks in ways that minimize risk, recognize model limitations in instruction following, iterate on results, etc).
Your last paragraph is also striking in that it exemplifies how far away from general intelligence they still are.