Energy vs Climate X Climate Books Reviews

This week we're sharing an episode from Ed's other podcast, Climate Book Reviews, co-hosted with Dr. Roger Thompson of Arizona State University.

Their guest is John Vaillant, author of Fire Weather: The Making of a Beast. (US and International - Fire Weather: A True Story from a Hotter World)

Many listeners will know Vaillant from his earlier books The Golden Spruce and The Tiger, both gripping works of narrative nonfiction. In Fire Weather, he turns his attention to the massive 2016 Fort McMurray wildfire and what it tells us about the new era of extreme fire.

In this episode:

• How the Fort McMurray fire burned for a week straight — and why traditional firefighting was useless
• The concept of "fire weather" and why wildfires are now generating their own atmospheric systems
• The oil industry's early awareness of climate change and the shift to deliberate misinformation
• Attribution science: can we prove a specific wildfire was caused by climate change?
• What hope looks like in the face of an altered climate

Chapters:
00:00 Cold Open: When Firestorms Become Unstoppable
01:00 Welcome & Introducing John Vaillant
03:00 The Fort McMurray Fire: Inside the Inferno
09:00 Writing Fire — Craft, Research & the Book's Structure
17:00 Community Heroes & Local Response
20:00 We've Altered the Climate: A Shift in Consciousness
23:00 Fire Tornadoes & Australia's Black Summer
28:00 Attribution Science: Proving Climate Change Caused This
33:00 Fire Weather: The New Physics of Wildfire
35:00 The Oil Industry Knew: The Greatest Betrayal
40:00 The Rising Wave of Wildfire Literature
42:00 Finding Hope in the Age of Fire

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The Iran war and the near-closure of the Strait of Hormuz have triggered a major shock to global oil and LNG markets.

Roughly 20 million barrels of oil per day normally move through Hormuz. The IEA says nearly all of that has been disrupted.

Oil and gas prices have surged sharply; and the disruption extends well beyond oil as Qatari LNG exports have been largely severed. Asia is especially exposed, since most Gulf energy exports flow there.

This isn’t just an oil story. It’s a “can people cook dinner” story, a reminder that geopolitics gets real once it enters the kitchen.

In this episode, David, Sara, and Ed unpack what this shock means for global energy markets, the climate, and the pace of the energy transition.

⏱️ TIMESTAMPS
00:17 — Welcome & episode overview
01:54 — How the Iran War is disrupting oil & gas markets
07:28 — 30x induction stove sales in India & accelerating tech adoption
09:38 — AI forecasts say EV sales are rising because of the war?
13:00 — The coming LNG whipsaw: glut or shortage?
16:21 — How much wilder could this get? Escalation risks
17:07 — Global recession risk from tariffs + oil shocks
17:30 — Has the Iran War accelerated peak global emissions?
19:36 — Data centers, energy demand & geopolitics in the kitchen
26:54 — What the war means for Canadian oil, gas & LNG exports
29:49 — Federal-Alberta MOU & pipeline politics
30:52 — The war's legacy: will it help or hurt the energy transition?

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Vijay Gadepally joins Ed and Sara to break down the real energy footprint of AI—and why most people (and companies) are getting it wrong.

They discuss:

• How "agentic" AI systems use an order of magnitude more energy than ChatGPT.
• Whether efficiency gains can keep pace with exploding usage (spoiler: not yet).
• The one simple change that could cut AI energy use by 80%.

Vijay is Senior Scientist at the MIT Lincoln Laboratory Supercomputing Center and Co-Founder of Bay Compute and Radium Cloud. He studies what's actually happening under the hood of AI systems—and has the data to back it up. If you've been wondering whether AI is derailing the clean energy transition, or whether smarter software design could keep energy use in check, this is the conversation you need to hear.

🎙️ TIMESTAMPS
00:00:00 - Introduction & Cold Open
00:01:17 - Welcome & Guest Introduction
00:02:59 - Agentic AI: The New Energy Problem
00:04:10 - A Brief History of AI: From Expert Systems to LLMs
00:08:43 - Agentic AI vs. LLMs vs. Reasoning Models Explained
00:10:00 - The Energy Reality: One AI Node = 10-15 Homes
00:14:13 - Why Energy Consumption is Unpredictable
00:16:02 - The Big Flip: Training vs. Inference Energy Use
00:26:22 - What Does "Efficient AI" Actually Mean?
00:29:37 - Are Tech Companies Optimizing for Energy or Market Share?
00:36:20 - The Low-Hanging Fruit: Cutting AI Energy Use by 80%

Full notes & references

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