Tech
Google justifies its massive AI spending with a booming cloud business
Alphabet investors have very publicly worried that the company’s massive AI spending isn’t worth the money. With the company’s latest earnings report, those investors should be able to relax a little.
The takeaway: Google’s cloud business — driven largely by enterprise AI adoption — is booming. The search giant saw Google Cloud revenue spike 82% from where it was this time last year, climbing to $24.8 billion. That’s well above last quarter’s generous year-over-year growth, which showed a revenue jump of 63% to $20 billion — and it also handily beats what Wall Street analysts expected for this quarter’s growth (the expectation was $22.46 billion).
Those cloud gains were driven largely by enterprise AI solutions and enterprise AI infrastructure adoption, the company said, while also noting that its backlog of cloud contracting work — that is work that it hasn’t yet converted into revenue — had climbed to $514 billion.
The company’s profit hit $112.1 billion, which is a massive jump from this time last year, when the company reported $28.1 billion in profit, the company’s earnings report shows. Meanwhile, Alphabet’s overall revenue grew 24% year-over-year during the past quarter to $119.8 billion. The company also saw Google Services revenue jump 15% to $94.5 billion.
“Our AI investments are redefining what’s possible across every part of our business,” said Google CEO Sundar Pichai during Wednesday’s earnings call. “We have exciting momentum across the board.”
More people are also adopting Gemini, Google’s AI chatbot, as the app currently enjoys 950 million monthly active users, the company said. In Q4 of 2025, Google reported that the app had 750 million users.
It’s worth noting that spiking revenue isn’t unusual for Google. This marks the company’s 12th consecutive quarter of double-digit revenue growth. But even by that standard, this quarter represents a particularly bountiful period for the tech giant.
Alphabet’s spending is still hefty, with its capital expenditures — the money it spends building data centers, buying chips, and expanding infrastructure — estimated to be between $180 billion and $190 billion for the year — a fact not lost on analysts during Wednesday’s earnings call. Several pressed Pichai on when, and how much, those investments will pay off.
“I think our compute capacity investments in ’27,” he said. “We are seeing strong demand indicators, including long-term deals,” he continued. “I think, if anything, the dynamics look healthier than where we were about a year ago, so that’s what gives us the confidence to undertake those investments,” he said.
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Tech
After shocking quarter, IBM insists that AI isn’t killing the mainframe
On Wednesday, IBM officially reported earnings and the news was as bad as everyone knew it would be.
While the 115-year-old company still generates boatloads of cash — $17.2 billion in revenue, $9.9 billion in gross profit, nearly 58% margins, and $2.2 billion in net earnings for the quarter — its results fell well short of Wall Street’s expectations.
It was such a bad miss that IBM CEO Arvind Krishna and the board took an unprecedented step of warning investors ahead of time that the earnings was “was worse than our expectations,” offering everyone a sneak peek.
He published a “letter to investors,” last week sharing preliminary results. It warned of abysmal revenue in the company’s all-important “infrastructure” category and said that profit margins were also going to take a hit. The company’s stock instantly tanked 25%, it’s biggest single-day decline ever. Until then, the stock had performed well under Krishna’s six years of leadership, buoyed by the AI data center boom that had been lifting all boats.
On Wednesday, IBM also lowered its full-year growth forecasts, meaning this horrible quarter would impact the rest of the year. The culprit? IBM’s cash-cow mainframe business was down 42%.
That’s a cascading problem, because as CFO Jim Kavanaugh explained on the quarterly call with investors, IBM earns $3 in software revenue for every $1 of mainframe hardware it sells.
However, the CEO and CFO spent the call insisting that this was a temporary blip and all would be well soon.
What happened, they said, was that “tens” of customers that were due to buy a new mainframe during the quarter, opted not to do so. That may not sound like a lot of customers, but mainframes are systems that cost hundreds of thousands to millions of dollars, and with maintenance contracts and software, generate many millions more.
The same AI boom that lifted IBM’s boat, also sank it.
Instead of buying a new mainframe, these clients bought other hardware, Krishna explained. They were faced with astronomically high cost increases of 15% to 30% for data center gear and PCs.
“When they were faced with that issue, then they decided to move budget to those areas where they were having that extreme price,” Krishna said.
Enterprise hardware makers like Dell and HP have warned that rising costs on components like memory, caused by the AI build-out boom, have forced them to raise prices. Apple has said the same.
But Krishna promised that those customers will still buy their new mainframes eventually — along with their new software contracts. In fact, he said some of them have already done so this quarter. “We see no evidence of clients moving off the mainframe,” he said.
We’ll have to wait and see. But the tech industry has predicted the death of the mainframe for many decades now. Maybe even AI won’t kill it.
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Tech
Samsung Unveils Galaxy Z Fold8 Ultra and Fold8 at Unpacked 2026
Samsung’s Galaxy Z Fold8 Ultra and Fold8 debut at Unpacked 2026 with new cameras, AI tools, prices, and clear trade-offs for buyers choosing a foldable.
The post Samsung Unveils Galaxy Z Fold8 Ultra and Fold8 at Unpacked 2026 appeared first on TechRepublic.
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Tech
China Considers Export Controls on AI Models, Training Data and Chip Technology
China is considering tighter controls on AI models, training data, and chip designs, potentially limiting how Chinese technology reaches global users.
The post China Considers Export Controls on AI Models, Training Data and Chip Technology appeared first on TechRepublic.
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