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Jigar Shah Profile picture
@JigarShahDC
May 17 • 6 tweets • 2 min read • Read on X
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America cannot lead the AI race without building the power and computing infrastructure AI requires. On that I agree completely. But the piece gets the diagnosis wrong — and a wrong diagnosis produces the wrong cure. 🧵
The Gallup poll it cites shows a majority of Americans oppose data centers near their home, including 63% of Republicans. The real enemies of AI are electric utilities that use data centers to jack up rates and GW+ developers that fail to engage communities.
The electricity price comparison also misses the structural problem. Investor owned utilities don’t make money when you use what we have already paid for more efficiently. They only make money when they invest new money even if they don’t need to.
Give communities a good deal. Reduce their bills with great demand flexibility through batteries in homes. Demand response payments. Lower bills because of the data center.

utilitydive.com/news/governors…
Fix the interconnection queue. Accelerate transformer manufacturing. Deploy demand flexibility. Give communities a stake. That builds the coalition America needs to win the AI race. Get utilities to stop exclusively focusing on shareholders and get them to care about customers.
Deploy Action did a poll and found that 86% of voters want utilities to prove grid efficiency before building new infrastructure. 80% support demand response competing with utilities. 11% view their regulators favorably.

Voters already know the answer. The grid is not full. The tariff structure is.

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More from @JigarShahDC

Jigar Shah Profile picture
May 18
76 countries are now in “emergency measures” for the oil crisis, up from 55 just six weeks ago. That’s not a statistic. That’s the fastest spreading energy emergency in history. And the number is still climbing. 🧵
What does “emergency measures” actually mean? It’s a huge range. Lithuania is cutting train fares. Australia made public transport free. Myanmar and South Korea are telling people they can only drive on certain days. That’s the mild end.
The middle: Philippines declared a full state of national emergency. Indonesia, Japan, South Korea and India are spending billions on fuel subsidies which should be spent on solar instead. Bangladesh asked businesses to turn off unnecessary lights. Pakistan is rationing fuel.
Read 5 tweets
Jigar Shah Profile picture
May 18
Bain & Standard Chartered’s 2026 SE Asia Green Economy Report: data centres, EVs & green industrial parks will drive 100+ TWh of new power demand in 3-4 years, requiring $200B+ in investment. $540B in announced green spending is on a credible path to deployment. 🧵
@JavierBlas on Odd Lots today: everyone expected oil at $200+ with 60+ days of Hormuz closed. We’re not there because bypass pipelines, SPR drawdowns, and inventory burns have cushioned the shock. But the biggest surprise? ~5% demand destruction that nobody saw coming.
@JavierBlas Where did that 5% oil demand destruction come from? Not just EVs — it’s price-driven behavioural change, Asia absorbing the sharpest hit, and crucially: countries with existing clean energy infrastructure simply felt less pain. The energy transition was quietly doing work.
Read 5 tweets
Jigar Shah Profile picture
May 11
.@EpochAIResearch has quietly assembled the most rigorous data set on AI infrastructure in existence. Here's what it tells us about how much compute we need by 2030, how many giant campuses are actually required, and where the real distributed inference opportunity lies. 🧵
The baseline: AI compute stock is growing at 3.4× per year, doubling every 7 months. Training compute for frontier models grows at 5× per year. US AI data center capacity will exceed 50 GW by 2030 — approaching 5% of total US generation capacity.
This is not scary for the grid.
But not all of that 50 GW needs to be concentrated. Final frontier training runs — the kind that require extreme GPU synchrony — represent only ~10% of total R&D compute spend. The other 90% is experiments, fine-tuning, inference, and synthetic data. Distributable.
epoch.ai/gradient-updat…
Read 12 tweets
Jigar Shah Profile picture
May 10
Everyone's asking: what actually powers AI data centers?

The answer is more complicated — and more interesting — than "natural gas vs renewables."

A 🧵 on what's really happening, and where it's going.
Start with the obvious: data centers need firm power, not really 24/7 as they run at 50% capcity factors.
Solar/Wind are fuel, batteries are really providing the capacity.

So the assumption is gas & nuclear carry the load.

Big Tech energy portfolios tell a more nuanced story.
Amazon & Microsoft: 40+ GW wind/solar each
Google & Meta: ~15 GW wind/solar each
All four signed nuclear deals as well
The nuclear numbers are smaller
In short they are sticking to their commitments to clean energy and buying NG units for "capacity" for speed to power.
Read 13 tweets
Jigar Shah Profile picture
May 9
I hear this framing all of the time and it is disappointing to hear it from @OurWorldInData.

Basically says that we use alot of land to grow biofuels. Put solar panels on that same land and you could power every car and truck on Earth.

It just doesn't work that way. 🧵
i get that Biofuel crops currently occupy ~32 million hectares globally. That generates about 1,400 TWh/yr of fuel energy.

Solar panels on the same land? ~32,000 TWh/yr.

But this is productive land and most landowners want to grow things. Most of the land is not near a substation.
Plants convert <1% of sunlight into biomass. Then you lose more turning that biomass into liquid fuel.

Solar panels convert 20% of sunlight into electricity.

Add in EV efficiency (no combustion waste, regenerative braking) and a solar EV travels 70× as far per hectare as a biofuel car.
Read 7 tweets
Jigar Shah Profile picture
May 8
PJM just cried "Uncle". They admit that capacity prices are up 1,000%+ in two auctions and that money goes to existing generators, doesn't send a signal to build new on 3 year contracts.

The prescription is pretty bold.

They aren't doing a market patch, this is a rethink 🧵
Grid 1.0 was built on one assumption: demand is passive. Show up whenever. Take whatever you need. The grid serves you.

That worked for factories and homes. It doesn't work when a hyperscaler drops 500 MW peak on a node.
PJM opens the door to changing their "must serve" requirements. They will figure out how reliable they can be and make only those promises. States can figure out what they want to do to fill in the gaps. That returns $16B to the states to implement that solution.
Read 6 tweets

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