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With the advent of AI, however, the cloud division has become a rising star at Google. Annual revenue in the division was $26.3 billion in 2022, and soared 64% to $43.2 billion last year.

What is Wiz?

Wiz, a five-year-old startup founded by four longtime friends who met in the Israeli army when they were still teenagers, is on track for an estimated $1 billion in revenue this year. After getting its start in Israel in 2020, Wiz now oversees an operation that makes security tools protecting the information stored in data centers from its current headquarters in New York.

“Wiz and Google Cloud are both fuelled by the belief that cloud security needs to be easier, more accessible, more intelligent, and democratized, so more organizations can adopt and use cloud and AI securely,” Wiz CEO Assaf Rappaport wrote in a blog post.

Google’s plans for Wiz

In a Tuesday conference call, Google CEO Sundar Pichai predicted Cloud division’s addition of Wiz will result in even better security at a lower cost than can be provided now. That prediction may have been aimed as much at regulators likely to scrutinize how the deal will affect competition and pricing, as much as at prospective customers.

Google had been courting Wiz for some time before finally settling on a price that’s much richer than a reported $23 billion bid that was rejected last July. At that time, Wiz signalled it would instead pivot back to a previously-planned initial public offering. But recent volatility in the stock market has chilled the IPO market, and now Rappaport said Wiz expects to “innovate even faster” by becoming a part of Google.

What do analysts think of the acquisition?

Wedbush analysts called Google’s move to buy Wiz “a shot across the bow” at other tech giants, particularly Microsoft and Amazon, who have already made big bets on cyber security as the fight to dominate cloud computing intensifies. Google had fallen behind its competition in the cloud space, Wedbush said, but the acquisition of Wiz could alter the parameters.

The bid Tuesday easily eclipses the current largest acquisition in Google’s 26-year history—a $12.5 billion takeover of Motorola Mobility in 2012 that didn’t pay off the way that the Mountain View, California, company had hoped. The $32 billion purchase of Wiz would also go down as the biggest-ever cybersecurity acquisition and rank among the 20 most expensive takeovers of a software company in history, according to Mergermarket, a financial intelligence service.

How did investors react?

As often happens with high-priced acquisitions, investors reacted coolly to Tuesday’s news. Alphabet’s shares declined 2% to close at $160.67. Some of GoogleÆs other acquisitions have turned into gold mines, most notably its $1.76 billion purchase of online video pioneer YouTube in 2006 and its $3.1 billion takeover of advertising technology platform DoubleClick in 2008. A $5.4 billion purchase of another security firm, Mandiant, in 2022 also helped fuel the recent growth of Google’s Cloud division, which posted an operating profit of $6.1 billion last year.

Google’s DoubleClick deal is now part of an antitrust case filed by the U.S. Justice Department targeting Google’s technology for distributing ads across the internet. A ruling in that case, involving allegations that Google illegally abused its power to manipulate digital ad prices, is expected this year.
Regulators in the U.S. and abroad are targeting Google on other fronts, too.

Last year, a federal judge in another case brought by the Justice Department last year concluded Google had turned its ubiquitous search engine into an illegal monopoly. The penalization phase of that trial begins next month.

The Justice Department is seeking a rebuke that would include a requirement for Google to sell its Chrome web browser and would ban the company from making agreements with Apple and other companies to make its search engine the default tool for finding online information on the iPhone and other devices.

What’s next for the Google-Wiz deal?

The Wiz deal will also get a close look from antitrust regulators. While many expect the Trump administration to welcome more dealmaking than occurred during the previous years, it has also expressed leeriness about Big Tech getting any bigger. Andrew Ferguson, the Trump administration’s Federal Trade Commission Chairman, has been particularly outspoken about his resolve to keep Big Tech on a short leash.
The deal raises antitrust concerns due to the potential impact on standalone cyber security vendors, as well as potential disruption for bigger rivals.

Still, Wedbush’s analysts note the industry is “ripe for consolidation”—which could pose “massive growth opportunities on the horizon heading into this AI Revolution.”
Antitrust worries were also believed among the reasons Wiz called off sales talks with Google last year while President Joe Biden’s administration was seeking to block a variety of tech deals.

Agreeing to a sale now indicates both Google and Wiz are more confident the deal will gain U.S. approval under the Trump administration, Mergermarket analysts Kevin Ketcham and Kevin McCaffrey wrote in a Tuesday note.

“The two sides likely wouldn’t have struck the deal if they didn’t at least see a potential path to closing,” Ketcham and McCaffrey wrote.

But the business watchdog group Demand Progress Education Fund urged the Trump administration to block Google’s takeover attempt. “It’s time to show the public whether they have the guts to step in and stop a big fish from being gobbled up by one of the biggest fishes in the pond,” said Emily Peterson-Cassin, the group’s director of corporate power.

If they get the regulatory greenlight and meet several conditions spelled out in their agreement, Google and Wiz expect the deal to close in 2026.

The companies they will provide Canadian businesses and researchers with the supercomputers and software they need to train and run AI programs while keeping their data within the country’s borders. 

Vancouver-based Telus aims to deploy Nvidia’s latest-generation AI semiconductors at its data centre in Rimouski, Que., by this summer, with plans to expand at its Kamloops, B.C., facility once the initial capacity is exhausted. 

The data centre will receive 500 graphic processing units to begin with, but Telus chief information officer Hesham Fahmy said that could over several years scale up to tens of thousands, depending on demand. “We want it to be really, really big,” he said in an interview from San Jose, Calif., following a keynote speech from Nvidia CEO Jensen Huang at that company’s annual flagship GTC AI conference. He said he would love it if Telus was the catalyst that brought almost all of Canada’s AI computing within its borders, even if the company itself doesn’t capture all of that business. 

“We really think that AI is going to get infused in every aspect of business” Fahmy said. “Every knowledge worker is going have some sort of AI assistance, we believe, in the near future.”

The Vancouver-based firm says it will be the first North American service provider to become an official Nvidia cloud partner, gaining access to the U.S. tech giant’s research and development, engineering talent and other resources. 

What kind of energy will the new factory use?

AI data centres tend to be voracious energy users, raising environmental concerns. The Rimouski site is to be powered 99% by renewable energy sourced from Hydro-Quebec. It will use natural cooling, which Telus says cuts water use by more than three quarters compared to traditional data centres. 

Telus says the Quebec facility, 250 kilometres from a major urban centre, is highly secure and a good option for customers seeking a core or disaster recovery site. 

Nvidia, based in Santa Clara, Calif., has a stock market value of almost US$3 trillion and is second only to Apple on the S&P 500 index. 

“Sovereign AI infrastructure is critical for every nation to advance their society and economy, while preserving their own data, enabling them to drive a local intelligence revolution with global technology advancements,” Ronnie Vasishta, senior vice-president of telecom at Nvidia, said in a news release. 

At GTC 2025—dubbed the “Super Bowl of AI”—Nvidia CEO Huang focused his keynote on the company’s advancements in AI and his predictions for how the industry will move over the next few years. He said he expects Nvidia’s data centre infrastructure revenue to hit US$1 trillion by 2028.

At GTC 2025—dubbed the “Super Bowl of AI”—Huang focused his keynote on the company’s advancements in AI and his predictions for how the industry will move over the next few years. Demand for GPUs from the top four cloud service providers is surging, he said, adding that he expects Nvidia’s data center infrastructure revenue to hit $1 trillion by 2028.

Huang’s highly anticipated announcement revealed more details around Nvidia’s next-generation graphics architectures: Blackwell Ultra and Vera Rubin—named for the famous astronomer. Blackwell Ultra is slated for the second half of 2025, while its successor, the Rubin AI chip, is expected to launch in late 2026. Rubin Ultra will take the stage in 2027.

The future of AI

In a talk that lasted at over two hours, Huang outlined the “extraordinary progress” that AI has made. In 10 years, he said, AI graduated from perception and “computer vision” to generative AI, and now to agentic AI—or AI that has the ability to reason. “AI understands the context, understands what we’re asking. Understands the meaning of our request,” he said. “It now generates answers. Fundamentally changed how computing is done.”

The next wave of AI, he said, is already happening: robotics.

Robotics fueled by so-called “physical AI” can understand concepts like friction and inertia, cause and effect, and object permanence, he said. “Each one of these phases, each one of these waves, opens up new market opportunities for all of us,” Huang said.

The key to that physical AI, and many of Huang’s other announcements, was the concept of using synthetic data generation—AI or computer-created data—for model training. AI needs digital experiences to learn from, he said, and it learns at speeds that make using humans in the training loops obsolete.

“There’s only so much data and so much human demonstration we can perform,” he said. “This is the big breakthrough in the last couple of years: reinforcement learning.”
Nvidia’s tech, he said, can help with that type of learning for AI as it attacks or tries to engage in solving a problem, step by step.

To that end, Huang announced Isaac GR00T N1, an open-source foundation model designed to assist in developing humanoid robots. Isaac GR00T N1 would be paired with an updated Cosmos AI model to help develop simulated training data for robots.

The cost of training AI

Benjamin Lee, a professor of electrical and systems engineering at the University of Pennsylvania, said that the challenge in training robotics lies in data collection because training in the real world is time-consuming and expensive.
A simulated environment has long been a standard for reinforcement learning, Lee said, so researchers can test the effectiveness of their models.

“I think it’s really exciting. Providing a platform, and an open-source one, will allow more people to learn on reinforcement learning,” Lee said. “More researchers could start playing with this synthetic data—not just big players in the industry but also academic researchers.”

Huang introduced the Cosmos series of AI models, which can generate cost-efficient photo-realistic video that can then be used to train robots and other automated services, at CES earlier this year.

The open-source model, which works with the Nvidia’s Omniverse—a physics simulation tool—to create more realistic video, promises to be much cheaper than traditional forms of gathering training, such as having cars record road experiences or having people teach robots repetitive tasks.

AI in use

U.S. car maker General Motors plans to integrate Nvidia technology in its new fleet of self-driving cars, Huang said. The two two companies will work together to build custom AI systems using both Omniverse and Cosmos to train AI manufacturing models.

The Nvidia head also unveiled the company’s Halos system, an AI solution built around automotive—especially autonomous driving—safety.

“We’re the first company in the world, I believe, to have every line of code safety assessed,” Huang said. At the end of his talk, Huang an open-source physics engine for robotics simulation called Newton, which is being developed with Google DeepMind and Disney Research.

A small, boxy robot named Blue joined him on stage, popping up from a hatch in the floor. It beeped at Huang and followed his commands, standing beside him as he wrapped up his thoughts.

“The age of generalist robotics is here,” Huang said.