高通CEO Cristiano Amon指出，AI智能体因执行自主任务、调用工具及协调多系统，将消耗远超聊天机器人的模型token。聊天机器人仅消耗语言token，而智能体需为决策、工具调用、结果验证、计划修订等环节花费token。高盛预测，到2030年AI智能体token使用量将增长24倍，乐观情况下月消耗可达120 quadrillion，推理成本则每年下降60%-70%。Uber和微软已开始重新评估昂贵的智能体使用成本。
AI will require “gazillions” of tokens.
- Qualcomm CEO Cristiano Amon:
Agentic AI will consume dramatically more tokens because it performs autonomous tasks, uses multiple systems, and interacts with tools.
A chatbot spends tokens on language; an agent spends tokens on deciding, checking, calling tools, reading outputs, revising plans, and coordinating with other software.
So, AI demand will grow hugely when software starts letting agents act, not just answer.
Today a single human-AI exchange may be large, a reasoning task may be much larger, but we are already entering the agentic era, where an autonomous workflow can become exponentially larger still because the model is no longer producing one response.
It is running a process.
When a SaaS product redesigns itself around human-agent interaction, every task can become a chain of hidden micro-decisions, and each micro-decision consumes context, memory, tool calls, verification, and output tokens.
Another point is people hear “more tokens” and think only of bigger data centers, when the deeper change is economic: software usage may stop being measured mainly by clicks, seats, or sessions.
It will be measured by how much machine reasoning/tokens gets spent on behalf of each user.
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From "Reuters" YouTube channel, (link in comment)
Goldman Sachs: "Token use by AI agents is expected to multiply 24 times by 2030" AI agents are now creating the first serious cost test for the AI boom. As was reported this week, Uber and Microsoft are already rethinking expensive agent usage. A chatbot may answer once, but an agent plans, calls tools, checks results, edits mistakes, and repeats the loop. That loop can make one user request consume 10x, 50x, or even far more tokens than a normal answer. Goldman’s bullish case is that monthly token use could reach 120 quadrillion by 2030, while inference cost per token keeps falling 60%-70% per year. The fight is now between agent productivity and token waste.在 X 查看被引用的帖子
来源：Rohan Paul · x.com