POLICY

How data centers became a proxy war over AI

Data centers have existed for decades. But in the age of AI, they've recently become political pawns.

The rapid expansion of AI factories across the US has created a new political battleground. Opposition has spanned across the political spectrum, with Democrats like Sen. Bernie Sanders and Rep. Alexandria Ocasio-Cortez and Republicans like Gov. Greg Abbott calling for moratoriums on building new data centers. 

And the reason is clear: public sentiment towards data centers has turned sharply negative, no matter your political affiliation. A Gallup poll published in May found that an average of 7 in 10 Americans oppose data center construction in their area, including 48% who strongly oppose such facilities being built locally.

However, data centers may just be the scapegoat for broader societal anxiety around AI, such as its potential impacts on the economy, jobs, national security and even the way we learn and think, said Jeremy Roberts, senior director of research and content at Info-Tech Research Group, told The Deep View. "AI itself is underwater in polling. It's pretty easy to be against something that is the opposite of a job creator. That's pretty cross-cutting." 

It's why the political rallying cry against them has become a clear avenue for populism, Roberts said. It's a textbook example of a leader claiming to champion the general masses over a corrupt elite group. 

"Data centers are built by the richest people, run by the richest people, and a lot of the marketing around them has basically been that this is going to concentrate wealth further," said Roberts. "It exacerbates a populist gap." 

Politicians protesting data centers are already affecting the buildout of AI infrastructure that tech companies have been pushing. For instance, in July, New York Gov. Kathy Hochul instituted the nation's first statewide moratorium on hyperscale data centers of 50 megawatts or more for a year. Texas followed suit in early August, with Gov. Abbott implementing a moratorium on approving new data centers.

As a result, tech companies may simply have to become more resourceful about the way they build data centers, said Roberts. For instance, rather than building large, hyperscale facilities, they may end up building smaller ones and connecting them with innovative networking technologies. 

Still, the impacts are already being felt at a local level as citizens show up in droves to city council meetings across the country to oppose data centers being built in their neighborhoods. Jason Morris, land use attorney and partner of Withey Morris Baugh in Phoenix, Arizona, told The Deep View that data center cases "have gone from being my easiest cases to being my most difficult."

"There is an amount of hysteria surrounding data centers that I haven't seen associated with any other land use," said Morris. "This has become, for better or for worse, AI's Achilles' heel." 

To counter this, the Trump Administration is moving to limit those voices. The Environmental Protection Agency plans to cut a federal requirement that forces states to solicit public input on air pollution permits for industrial facilities, data centers included. However, with the public already so resistant to AI, cutting off that avenue for input may only worsen the narrative around the tech, Jason Elliott, former senior advisor to Gov. Gavin Newsom and founder of Versus Consulting, told The Deep View.

"If you don't let people have a chance to weigh in, they're going to assume the worst," said Elliott. "It's really beneficial to give constituents an opportunity to express themselves or point out something that local elected officials hadn't thought of."

The reality of the impacts of data centers themselves is much more complex than headlines often make them seem. Yes, these facilities undeniably use power and water, make noise and strain the electrical grid, but so do many other industrial processes and industries, such as chemical manufacturing, coal and primary metals. The outcry against data centers is practically synonymous with the anxiety around AI broadly. The negative sentiment could pose a real threat to the frontier AI labs fueling a utopian vision of societal transformation, a vision that's propping up potential trillion-dollar IPOs for Anthropic and OpenAI. To achieve the kind of transformation these companies are projecting, the public has to get on board. And repairing public perception won't be solved by data center regulation alone. 

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PRODUCTS

How Google is turning books into AI context

Google has introduced Expert Intelligence, which is less flashy than its name suggests but still full of promise.

Gemini Notebook, previously known as NotebookLM, now lets you load ebooks in addition to the resources you could already add, including notes, PDFs, slides, web pages, and more. Once in the notebook, you can interact with it as you normally would, asking questions about it or doing the other things you can do in Gemini Notebook, such as making flashcards, building slide decks and infographics, and creating podcast-like audio overviews of the content. 

At first, when I heard about the feature, I was really excited because it seems extremely valuable for readers. Often, when reading a book, you want to reference a particular part later or learn more about what you're reading. Being able to chat with Gemini Notebook about a book's contents would make either task easier and could even be a useful tool for improving reading comprehension. 

However, there is a major caveat: You can only insert books from the Google Play Store that you have previously purchased.

The Google Play Store limitation restricts how many users can use ebooks to enrich their "notebooks" or information repertoires, since most ebook readers buy their books on platforms like Amazon Kindle. People are already expressing on X their desire for Kindle and Apple Books integrations, or even for academic journals to be referenced, such as MIT Press Open Access.  

Yet that doesn't mean the feature should be discounted, as companies often first integrate features with internal products at launch and then, due to popular demand or after seeing how the trial run went, expand to other sources. Also, to help bridge that gap, Google is buying one book per person in the US while supplies last.

To see if a book you plan to buy is eligible for Expert Intelligence, visit Google Play Books, where a Gemini Notebook badge will be listed when you click the "Tools" badge on a book’s detail page.

In the era of AI slop and user distrust, it is more important than ever for AI companies to make it clear where their sources come from and ease concerns about AI hallucinations and accuracy. For that reason, since NotebookLM first came onto the scene, people have been excited about the tool because it lets users reference only their own sources and notes rather than scraping information from the internet, which can often be inaccurate. The Expert Intelligence feature builds on that by integrating ebooks, though it will need broader reach across more ebook publishers and platforms to be useful. 

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HARDWARE

AMD’s case for a more open AI stack

AI's appetite for compute keeps growing, but so does the pressure to deliver more intelligence per watt and per dollar. Can AMD's first rack-scale AI system open up an ecosystem dominated by Nvidia?

In this episode of The Deep View Conversations, we sit down with Andrew Dieckmann, AMD's general manager of its data center GPU business, to unpack the company's Helios platform and the rapidly changing economics of AI infrastructure.

Dieckmann explains why frontier AI requires more than just GPUs. It demands tightly engineered racks that combine GPUs, CPUs, networking, software, cooling and serviceability. The conversation examines the tension around AI data centers: hyperscalers still cannot get enough compute, while communities worry about power, water and whether the benefits justify the buildout. Andrew argues that responsible deployment and open ecosystems are essential as these systems become intelligence factories.

The conversation then turns to Helios: AMD's performance claims against Nvidia Vera Rubin, pricing and value, the first likely customers, and the Cerebras partnership for high-throughput, low-latency inference. Andrew closes with his advice for leaders navigating AI velocity: reassess priorities more often and use coding agents as force multipliers for scarce engineering talent.

Topics covered:

• Why AMD is moving from chips to full rack-scale systems
• AI demand, data center constraints, and community impact
• Open hardware, open software and customer choice
• How agentic AI changed infrastructure planning
• Helios performance, efficiency, pricing and customers
• AMD Helios versus Nvidia Vera Rubin
• How AMD and Cerebras split inference workloads

This conversation offers a clear look at the technology and economics shaping the infrastructure that will power everyday AI and the breakthroughs to come.

📺 Watch on YouTube

🎧 Listen in your favorite podcast player 

Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm

LINKS

• Rocket Money launches Rowan, a personal finance agent built with Claude

• A16Z raises $1.1 billion Machine Age AI infrastructure fund

• Meta tests ABB robots for data center cable and server tasks

• OpenAI will reportedly eventually build a humanoid robot 

• Anthropic raises standard weekly limits for Claude Code for paid users

• Sony, Warner sue Anthropic for intellectual property theft

• Expert Intelligence: Google launches ability to integrate ebooks in Gemini Notebook

• Hy4 preview: 770B, 49B active, 1M context, open-source model

• ChatGPT: Users can personalize a Temporary chat with existing memories

• GLM-5.3: Z.ai made it open-weight

• Innovaccer: Artificial Intelligence Researcher

• Rillet: Applied AI Engineer

• Socratix AI: Member of Technical Staff, AI Agents

• Promise: Software Engineer - AI

GAMES

POLL RESULTS

Do you think that Nvidia purchasing Hugging Face would be a good decision for the chipmaker?

Yes (54%)
Somewhat (22%)
No (18%)
Other (6%)