Google has taken a major step toward the future of clean energy by partnering with Commonwealth Fusion Systems (CFS), an MIT spin-out working to build one of the world’s first commercial fusion reactors. This Google fusion deal marks a pivotal moment for the tech giant as it looks to secure reliable, carbon-free power for its growing AI operations.

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Inside Google’s historic fusion power deal

Google will purchase 200 megawatts (MW) of electricity from CFS’s planned ARC fusion power plant in Chesterfield County, Virginia. This amount of power could support roughly 150,000 to 200,000 homes. More likely, it will help run Google’s expanding network of AI data centers. The actual usage will depend on how Google allocates the electricity.

This is Google’s first energy deal involving fusion technology. It is also the largest fusion power purchase agreement signed so far. The ARC plant is projected to begin operations in the early 2030s, though fusion projects often face delays. While the electricity does not yet exist, the deal highlights growing demand for long-term, clean energy solutions.

Steam rises from cooling towers at a nuclear facility. (Kurt “CyberGuy” Knutsson)

How nuclear fusion works and why it matters for clean energy

Fusion is the same process that powers the sun. Instead of splitting atoms like traditional nuclear power, fusion forces hydrogen atoms to fuse together at extremely high temperatures. This reaction releases enormous amounts of energy. It does not produce greenhouse gases or long-lived radioactive waste.

Scientists have worked on fusion for decades, but no one has produced fusion power at commercial scale yet. CFS aims to change that with its SPARC demonstration reactor, now under construction in Massachusetts. The larger ARC plant is planned to deliver commercial fusion energy.

Hands framing the sun during a bright orange sunset. (Kurt “CyberGuy” Knutsson)

Google invests in fusion to meet rising AI energy demands

Google’s energy needs are growing quickly as it scales up artificial intelligence models and data infrastructure. Since 2010, the company has invested in renewable sources like wind, solar, and geothermal. However, these sources are not always available when needed.

Fusion could solve this problem by providing round-the-clock clean energy. By signing this agreement, Google is securing future power and helping to speed up fusion technology development. The company has also expanded its investment in CFS to support the ARC project.

Kurt’s key takeaways

Google’s new partnership with CFS is the largest fusion energy deal ever signed. The company will purchase 200 MW of clean power from a future reactor in Virginia. The ARC plant is expected to come online in the early 2030s. Google is the first major company to sign on as a customer for commercial fusion energy. Unlike traditional nuclear power, fusion produces no carbon emissions and no long-lived radioactive waste. It also offers consistent, 24/7 electricity. As Google’s AI systems drive up energy demand, this deal shows how tech companies are looking beyond wind and solar for scalable, future-proof solutions. If CFS delivers, fusion could finally move from science experiment to real-world power source.

Do you think fusion energy will power the future of AI? Let us know by writing us at Cyberguy.com/Contact.

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What began as a darling of the gaming community is now the power plant of the AI revolution. In a milestone that sets it at the epicenter of the artificial intelligence revolution, Nvidia has become the first public company to achieve a $4 trillion market capitalization. The shareholders are quite hooked, the competitors are definitely spooked, while the rest are just wondering how this chipmaker ended up as the star of the whole digital economy. U.S chipmaker Nvidia reached the milestone on Wednesday after its shares rose 2.5% in early trading, hitting an intraday record high that shocked Wall Street and the international technology community.

The Revamped Chipmaker

Nvidia’s climb has been nothing less than remarkable. It has risen about 20% this year alone due to its pivotal role in fueling AI infrastructure. Its graphics processing units (GPUs), which used to be cherished solely by PC game enthusiasts, are now the main technology. It is powering AI model training and cloud services consumed by tech giants such as Microsoft, Amazon, and Google.

The firm’s growth path can be dated back to May 2023, when it initially reached the $1 trillion level. A year later, it has more than multiplied that figure, this is something that no other company has managed to achieve so quickly. With $44.1 billion in quarterly revenue through April, up 69% year over year, Nvidia’s numbers don’t lag behind its valuation.

Nvidia’s Role in the AI Boom

At the core of Nvidia’s superiority is its evident position as the underlying provider of AI infrastructure. Wedbush Securities analyst Dan Ives said,

“There is one company in the world that is the foundation for the AI Revolution and that is Nvidia”.

The recent release of the Blackwell Ultra chip, which is optimized to run complex reasoning and next-generation AI workloads, shows how Nvidia continues to redefine computing.

Worldwide investment in AI infrastructure will exceed $200 billion by 2028, and Nvidia is well-positioned to gain. Its chips are no longer merely tools, they are transforming into the gold standard for constructing and growing AI models.

Running Ahead of Apple and Microsoft

While Apple and Microsoft have long fought for the crown as the world’s most valuable corporation, Nvidia has surged past them both. Apple, which came into 2024 with almost $3.9 trillion, has weakened in recent months due to economic uncertainty and policy headwinds. Microsoft, with a market value around $3.77 trillion, temporarily caught up with Nvidia but lagged behind as the chip maker’s stock surged. This isn’t symbolic victory alone, rather it indicates a change in market leadership. Semiconductors and AI infrastructure are taking over from consumer electronics and software as the market’s leading growth driver.

Challenges Persist

Nvidia’s rise has not been smooth. This year, China’s DeepSeek shook things up with its low-priced AI model, raising the possibility of less costly, more efficient versions that would cut into Nvidia’s pricey hardware. In combination with U.S restrictions on AI chip exports to China, which cost Nvidia an estimated $2.5 billion in lost revenue, the company’s stock declined by as much as 37% from January to April. Nvidia recovered firmly, up 74% since early April, which is a reflection of investor confidence in its vision and long-term technological superiority. With Huang leading, Nvidia is moving into autonomous robots, cars, and high-end industrial AI models, indicating that the company’s horizon looks way beyond chips and servers.

$6 Trillion Projection

Analysts think that Nvidia’s ride is just getting started. In a recent report, Loop Capital estimated the company might hit a $6 trillion market capitalization by 2028, based on its near-monopoly position in AI-vital technologies. Loop Capital’s analysts Ananda Baruah and Alek Valero wrote,

“While it may seem fantastic that (Nvidia) fundamentals can continue to amplify from current levels, we remind folks that (Nvidia) remains essentially a monopoly for critical tech in the AI sector”.

Significant Moment for the Modern AI Era

Nvidia’s $4 trillion achievement is not just a marketplace milestone, it’s a paradigm shift in what tech leadership looks like today. As Apple awed us with gadgets and Microsoft constructed empires in the realm of enterprise software, Nvidia went on and constructed the digital foundation of the future world. Its graphics processors, which were long stereotyped as existing only in gaming machines, now drive everything from ChatGPT to autonomous cars. However, its real brilliance is its strategic placement. It does not compete with Google, Amazon, or Microsoft, rather it empowers them.

This positions Nvidia as the backbone and less of a brand that is competing to dominate. There are risks, from escalating competition to geopolitical volatility, but with a constant rate of innovation, Nvidia isn’t only leading the AI revolution, it’s creating it.

Dive Brief:

• With proper guidelines and accountability frameworks, artificial intelligence tools can enhance the project-based learning experience for both educators and students, said Jessica Garner, senior director of innovative learning at International Society for Technology in Education.
• “Technology should not be this isolated thing that happens outside of curriculum, instruction and teaching and learning and all of those different pieces,” said Garner, who has experience training educators on the intersection of technology and curriculum. 
• Garner emphasized that when leading AI training specifically, it’s important to focus on how to use the technology to improve the learning experience for students.

Dive Insight:

Project-based learning involves students spending an extended period working on a project that addresses a real-world problem or answers a complex question. This approach has been shown to enhance student engagement and improve student outcomes.

When incorporating AI in the classroom, Garner suggests that students should learn to utilize AI as a tool that enhances their learning rather than having it do the work for them. She said that project-based learning instruction particularly lends itself to work alongside AI for several reasons.

For one, since project-based learning already connects class material to real-world problems, Garner said, students are more likely to discern whether their use of AI will enhance or hinder their learning. 

“If students see value in the assignment, they want to do what’s more helpful to their learning,” Garner said. 

Project-based learning instruction can be intimidating for educators who may not know where to start. AI, Garner said, can serve as a thought partner in this scenario. When educators input the type of lesson they are trying to create — along with the goals and standards the lesson must meet — the AI tool can generate project assignments and activities for each stage of the project, she said.

For students, Garner said, AI can also serve as a way to receive feedback, and depending on the problem or project, AI can potentially help draft part of it. 

Garner explained that students can input their ideas and any challenges they’re facing and receive some initial guidance before meeting with their teacher. She added that AI can also help coach students on delivering presentations by having them record themselves and ask AI for feedback on what they could have done better.

“When I think about the role of the teacher in the classroom, there’s one teacher and, a lot of times, 30 kids. And even if they’re working in groups, you still have six different groups to try to get to in the classroom,” Garner said. “So if you can use AI as the first level of feedback, students can refine and hone in a little bit on what they’re trying to do, so when the teacher gets to each group, they can provide really targeted, specific feedback.”

However, Garner also cautioned educators to be mindful and to always question and verify the sources the AI tool uses to find information. She said it’s important to make sure that these activities are truly aligned with school and district standards and pedagogical themes. 

Similarly, she suggests that schools and districts ensure they have their own acceptable use guidelines for AI. Garner said that in a lot of cases, they don’t necessarily need a brand new policy, but they do need to look at their existing policies to make sure that whatever tools their teachers want to use are covered, as well.  

ISTE also provides hands-on AI project resources for different grade levels on its website.