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Back to This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick, with Ethan Mollick.

Why Are AI Token Prices Falling?

Ethan Mollick says AI token prices face real downward pressure because a huge move for token efficiency is underway and costs will decrease even as more compute comes online. Lower cost means AI does more stuff for less money in a very short period of time, so long-term token costs do not worry him.

A chart from Andreessen Horowitz compares the price of compute with the price of tokens. Compute has stayed steady and risen a little, while the price of tokens is falling dramatically. Alex Kantrowitz calls the drop the most deflationary technology he can remember in the price paid for the technology. Use is still rising because agent-style work requires more tokens, and a Fable class model can call a Haiku class model to do work and organize work for lower costs. The token-cost concern will go the way of vibe coding and RAG.

Grokipedia·Ethan Mollick·Andreessen Horowitz

Transcript

This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·

Big Technology Podcast

More from this episode

  1. Why Don't Companies See AI Productivity Gains Yet?Ethan Mollick says you do not get organizational productivity gains instantly from individual ones.
  2. Are Large Companies Seeing a Return From AI?Ethan Mollick says surveys show 85 percent of companies had positive ROI from AI as of last year.
  3. How Did a $200 Million Data Migration Drop to $20 Million?Ethan Mollick says no single move unlocks the full potential of AI inside a company. The work is structural change, and for many organizations it takes years.
  4. How Much of America's 20th-century Edge Came From Management?Ethan Mollick says 40 percent of the advantage of American companies in the 20th century came from better management, according to a paper by Raffaella Sadun…
  5. What Is the AI Capability Overhang?Ethan Mollick calls the overhang a huge gap between current AI capabilities and future capabilities.
  6. When Did Practical AI Agents Become Possible?Ethan Mollick says practical agents were not possible until models reached Opus 4.6 level or 4.5 level around November and December of last year.
  7. Why Do Superforecasters Keep Getting AI Wrong?Ethan Mollick says superforecasters keep getting AI wrong because an exponential is hard to predict. The labs have been right.
  8. Do AI Tutors Actually Help Students Learn?Ethan Mollick says a universal tutor of high quality now exists in AI, and when the tool is set up as a tutor the evidence seems to show positive effects in a…
  9. Will AI Replace All Human Labor by 2035?Ethan Mollick says nobody really knows what happens to jobs.
  10. Will Personal AI Agents Flood Customer Service?Ethan Mollick says a perfectly legal distributed denial of service on customer service departments is coming, authorized by millions of consumers, once it is…

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