Good morning. Well, yesterday was crazy. After several consecutive days of deep market losses, President Trump said that his reciprocal tariffs are officially on hold, and the market spiked like a kid being double-jumped on a trampoline.

The S&P posted its biggest gain since 2008.

But they haven’t gone away; the tariffs are just on pause for a few months. And Trump at the same time amped up his trade war with China, boosting that tariff rate to 125%.

In other news, another petition has been filed urging California to look into OpenAI’s conversion plans.

Never a dull day.

— Ian Krietzberg, Editor-in-Chief, The Deep View

In today’s newsletter:

• 🚅 AI for Good: Bullet train tracks

• 🌎 Here’s how Europe plans to become a global AI leader

• ⚡️ Report: How AI will shape the future of energy

AI for Good: Bullet train tracks

The JR Kyushu railway company operates close to 1,500 miles of railroad tracks across Japan, tracks that carry bullet trains that can reach speeds of 160 miles per hour. 

What happened: Last year, the company said it was working with AMD to apply AI methods to automate its track inspection processes. 

• The approach is relatively simplistic in nature: you have a high-speed camera mounted to a rail cart that houses a vision computing box, complete with AI-based image analysis. 

• The on-prem computing device skates along the tracks at 12 miles per hour, significantly improving the efficiency of Kyushu’s track inspections. 

The company previously carried out track inspections on foot. 

Why it matters: Driven by global environmental initiatives, the high-speed rail market is expected to grow significantly from $110.5 billion in 2024 to $165.3 billion by 2031. As more tracks get laid down, and more trains roll into production, these kinds of operational efficiencies could act as a significant enabler to the continued growth of a more sustainable way to travel. 

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Here’s how Europe plans to become a global AI leader

Several weeks ago, European Union President Ursula von der Leyen announced $200 billion worth of investments in AI infrastructure, an investment that came with an affirmation that the AI race isn’t over, and that people shouldn’t count the EU out as a contender. 

That push to gain global leadership in AI remains at the center of the continent-wide AI action plan the EU rolled out Wednesday. 

The details: A focus of this plan involves “regulatory simplification,” a notable step given that the EU’s AI Act — one of the world’s first comprehensive pieces of AI-related legislation — just recently began entering into force. The Act has been roundly criticized for being either excessive or contradictory, something that could act as a challenge to Europe’s newfound goal of technological dominance. 

• The details around this “simplification” aren’t really clear, but the EU said in a statement that it plans to launch an AI Act service desk, to aid corporations in their efforts to comply with the legislation. 

• The plan additionally aims to foster AI skills and talent, develop algorithms, push adoption and build out tons of infrastructure featuring a network of AI factories and AI gigafactories, the latter of which will house a minimum of 100,000 GPUs each. 

Only 13.5% of European companies have adopted the tech thus far, and the EU wants that number to be far higher, the motivation behind its “Apply AI Strategy.” 

The details around these action plans have entered a period of public consultation that will run through June. 

The goal is “a future where tech innovation drives industry and public services forward, bringing concrete benefits to our citizens and businesses through trustworthy AI,” according to Henna Virkkunen, the Union’s executive vice president for tech sovereignty, security and democracy. 

This despite persistent risks around reliability, trust, privacy, security and bias, alongside the costs, not just in dollars, but in the infrastructure, energy and carbon emissions required to build toward this vision. 

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• Up, down, up, down: Stocks posted their biggest single-day rally in years on Wednesday, following Trump’s affirmation that he will pause reciprical tariffs for 90 days. Tesla and Nvidia each surged around 20%; Apple surged 15%.

• Anthropic’s chasing OpenAI: Anthropic unveiled its “max” plan on Wednesday, a plan featuring expanded usage that will cost … you guessed it, $200 per month. OpenAI did that one first. The startup also unveiled a max-ish plan (“expanded usage,” technically) that costs just $100 per month. So, one of my predictions is certainly bearing fruit; that these companies will stop subsidizing the use of their models.

• Trump administration backs off Nvidia's 'H20' chip crackdown after Mar-a-Lago dinner (NPR).

• YouTube is supporting the ‘No Fakes Act’ targeting unauthorized AI replicas (The Verge).

• Musk’s DOGE reportedly deploys AI to monitor federal workers for anti-Trump sentiment (Fortune).

• Google unveils Ironwood, its most powerful AI processor yet (Ars Technica).

• DOGE is getting audited (Wired).

Report: How AI will shape the future of energy

The International Energy Agency (IEA) today published an extensive (300-page!) report on the complex relationship between artificial intelligence and energy. 

The work aims to inject data-based projections into a landscape that has been papered for years, now, in reports concerning the rapid electricity demand incited by the rise of artificial intelligence, and the subsequent surge in carbon emissions, water consumption and grid unreliability — against a backdrop of energy desperation — it is causing. 

The major findings: The focal point of the report revolves around the IEA’s “base case” for AI advancement and AI adoption; this base case holds that the global electricity demand of data centers is set to more than double by 2030 to 925 terawatt-hours (TWh), a number that is slightly more than the entire electricity consumption of Japan today. 

In 2024, data centers consumed 415 TWh, equating to roughly 1.5% of the world’s electricity consumption. 

• AI, according to the report, “will be the most significant driver of this increase” — electricity demand from data centers specifically optimized for AI is projected to “more than quadruple” by the end of the decade. 

• And in the U.S., the power consumption of data centers is set to make up nearly half of the country’s growth in electricity demand between now and 2030. 

The electricity demand associated with data centers began surging in 2017, a spike that was driven by a number of non-AI (depending on how you define it) factors, including the growth of the cloud, the expansion of social media and streaming and the rise, of course, of both traditional and modern forms of AI. 

Still, the relationship between energy and AI is complicated; there is a clear cost, in both dollars and emissions, of rising AI demand, according to the IEA, but there remain significant uncertainties regarding how capable the technology will become, how quickly it will advance and how quickly it will get adopted on a mass scale.

Keeping these differing scenarios in mind, the range of the IEA’s headwinds to tailwinds cases see data center electricity demand somewhere between 700 and 1,700 TWh by 2035. 

AI and emissions: While the report found that data centers are “among the largest sources of growth in emissions,” the peak and decline of those emissions after 2030 will remain at around 1% of the total emissions coming from the energy sector. 

Global carbon emissions from fuel combustion are expected to reach 35 billion tons in 2024, according to the report; in 2024, data centers accounted for around 180 million tons of carbon emissions. 

• Then, there are the “rebound effects” associated with the proliferation of AI. For instance, “cheaper oil and gas could directly induce greater demand and, therefore, higher emissions.”

• Likewise, a surge in autonomous vehicles could drive people away from public transport, increasing vehicular emissions; more efficient generative AI models could “lead to significantly higher use in daily life”; and an expansion in robotics could, likewise, boost energy demand. 

In many ways, the IEA said, AI and automation might be able to help; instantaneous statistical analysis and insights could help energy companies waste less, while aiding grid operators in the challenging task of grid balancing. The technology could also drive innovation in materials generation — as we’ve discussed — which could lead to breakthroughs in battery technology and renewable energy technology, reducing AI’s net emissions. 

These efficiencies could power emission reductions that are larger than the initial emissions themselves. However, the report added that there is “currently no existing momentum of Al adoption that would unlock these emissions reductions to this degree.”

“AI is a tool, potentially an incredibly powerful one, but it is up to us — our societies, governments and companies — how we use it,” IEA Executive Director Fatih Birol said in a statement. 

The landscape: The report shortly follows new executive orders from President Donald Trump designed to boost the coal industry in order to meet mounting AI energy demands. This push comes as the cost of coal remains far higher than renewables and natural gas. 

And on the individual company scale, the electricity demand, water consumption and carbon emissions associated with driving AI have been on a constant increase among the hyperscalers, an increase that has pushed these companies into the arms of nuclear energy.

The poin that I feel often gets missed here is that, as much as it is a good thing for renewables to power AI data centers, their allocation to this additional strain on our planet and our energy grids means that renewables are not being applied — at least, as much as they could be — to reduce our base energy demand, and our base carbon emissions. 

As a share of the whole, AI emissions and demand might not be enormous, but what it is doing is leading to increases in demand that we don’t have enough green capacity to respond to, at a time when we really need clean energy to be the bulk of what we deal with. 

Unfortunately, governments are incentivizing companies to do this quickly.

Not cleanly.

🤔 Your thought process:

Selected Image 2 (Left):

• “The equipment and position of the person in image 2 matches actual glass working.”

Selected Image 1 (Right):

• “I thought the blast furnace in Image 2 looked too much like a gateway to hell; shows what I know about smithing.”

💭 A poll before you go

Thanks for reading today’s edition of The Deep View!

We’ll see you in the next one.

P.S. Enjoyed reading? Put in your earbuds — we’ve got exclusive, in-depth interviews for you on The Deep View: Conversations podcast every Tuesday morning.

Here’s your view on whether AI will have a positive impact on the US:

A third say it will, and a third say it will be equal parts good and bad.

20% say it will, but only if regulators get it together.

And 10% think it won’t.

Equal parts:

• “AI is no different than anything else humans have come up with. But there will be some who use AI as a tool to improve lives, and others will use it to seek their own gains to the detriment of everyone else.”

Yes:

• “Every technology eventually has a more positive than negative outcome because people in general are overwhelmingly good, with positive intentions. There are always a few exceptions, but the good always wins out over the long haul.”

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