This is how Google and Meta made money even before the AI era. With AI the new thing is that users can feed more human context and deeper nuance for getting the answers or fulfill the tasks.
I’m skeptical on the net effect of post AI world on systems at large.
We see that Jobs are reorganizing with Human + AI.
But what’s the long term impact of AI on society ?
Will purpose be the new token succeeding Skills and knowledge ?
so far at least, i'm pretty sure AI has been net job-creating.
this was not what i expected--although i was much less pessimistic than others, i thought by this level of capability we'd have seen some impact.
it is possible this direction keeps going!
Healthcare AI is entering a new phase.
Phase 1: Administrative AI (scribes, coding, inbox)
Phase 2: Clinical AI (AI integrated into care delivery)
UpDoc’s FDA-cleared SaMD is one of the strongest signals yet that the industry is crossing that boundary.
We have spent years optimizing AI for compute.
Maybe that’s the wrong objective.
The metric I think will be more valuable is
Intelligence Density ,
how much useful intelligence an AI system delivers per unit of resource.
Per watt.
Per dollar.
Per millisecond.
Per liter of water.
The next frontier may not be bigger models.
It may be maximizing intelligence per unit of resource.
@JeffDean@ylecun Thanks for sharing these, Jeff. One insight that stood out was the importance of measuring environmental impact across the entire serving stack, not just the model. Do you see the industry converging on standardized environmental metrics like we have for latency and throughput?
We talk about optimizing AI for latency, throughput and cost.
it’s time to add a fourth metric:
🌍 Environmental efficiency.
Curious how researchers like @ylecun, @JeffDean and others think about making energy and water first-class AI metrics.
Recent research from researchers at Google argues that AI systems should be evaluated not only on performance but also on energy, carbon, and water consumption across the serving stack.
The future of AI won’t be won by whoever builds the biggest model.
It may be won by whoever delivers the same intelligence using 10x fewer resources.
Efficiency is becoming the new frontier.
Google’s latest sustainability reporting highlights that AI growth is increasing electricity use, water consumption, and emissions even as datacenters become more efficient , illustrating that efficiency gains and overall demand can both rise at the same time.
Microsoft now publicly reports both Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) for its datacenters, showing that water efficiency is becoming an engineering metric rather than just a sustainability report.