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The Download: AI agents hype, and Google’s electricity plans

by Theinsightpost
July 3, 2025
in Tech
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The Download: AI agents hype, and Google’s electricity plans

—Yoav Shoham is a professor emeritus at Stanford University and cofounder of AI21 Labs.

At Google’s I/O 2025 event in May, the company showed off a digital assistant that didn’t just answer questions; it helped work on a bicycle repair by finding a matching user manual, locating a YouTube tutorial, and even calling a local store to ask about a part, all with minimal human nudging. Such capabilities could soon extend far outside the Google ecosystem.

The vision is exciting: Intelligent software agents that act like digital coworkers, booking your flights, rescheduling meetings, filing expenses, and talking to each other behind the scenes to get things done.

But if we’re not careful, we’re going to derail the whole idea before it has a chance to deliver real benefits. As with many tech trends, there’s a risk of hype racing ahead of reality. And when expectations get out of hand, a backlash isn’t far behind. Read the full story.

Google’s electricity demand is skyrocketing

We got two big pieces of energy news from Google this week. The company announced that it’s signed an agreement to purchase electricity from a fusion company’s forthcoming first power plant. Google also released its latest environmental report, which shows that its energy use from data centers has doubled since 2020.

Taken together, these two bits of news offer a fascinating look at just how desperately big tech companies are hunting for clean electricity to power their data centers as energy demand and emissions balloon in the age of AI. Of course, we don’t know exactly how much of this pollution is attributable to AI because Google doesn’t break that out. (Also a problem!) So, what’s next and what does this all mean?

—Casey Crownhart

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

+ To read more about whether nuclear energy is really a viable way to power the AI boom, check out Casey’s recent article, which is part of Power Hungry: AI and our energy future—our new series shining a light on the energy demands and carbon costs of the artificial intelligence revolution. You can take a look at the rest of the package here.

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      Clear examples do more than decorate an explanation: they show how an idea behaves under recognizable conditions. In education and software documentation alike, strong illustrations begin with a defined goal, then reveal the steps, assumptions, and result without unnecessary detail. A practical test example should state the input, expected output, and boundary condition, because these elements show whether a rule works beyond the simplest case. Including a contrasting case also helps readers distinguish a valid application from a tempting but incorrect one, while concise notes explain why the outcomes differ. When examples are updated with current data and checked against the underlying rule, they remain useful across classrooms, product guides, and professional training.