Alphabet Plans Massive Capex Hike, Reports Cloud Revenue Growth Slowed

Letters spell the word "Alphabet" as they are seen on a computer screen with a Google search page in this photo illustration taken in Paris, France, August 11, 2015. REUTERS/Pascal Rossignol/File Photo
Letters spell the word "Alphabet" as they are seen on a computer screen with a Google search page in this photo illustration taken in Paris, France, August 11, 2015. REUTERS/Pascal Rossignol/File Photo
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Alphabet Plans Massive Capex Hike, Reports Cloud Revenue Growth Slowed

Letters spell the word "Alphabet" as they are seen on a computer screen with a Google search page in this photo illustration taken in Paris, France, August 11, 2015. REUTERS/Pascal Rossignol/File Photo
Letters spell the word "Alphabet" as they are seen on a computer screen with a Google search page in this photo illustration taken in Paris, France, August 11, 2015. REUTERS/Pascal Rossignol/File Photo

Alphabet said on Tuesday it will spend $75 billion on its AI buildout this year, 29% more than Wall Street expected, and investors signaled disappointment at a missed cloud revenue target and began showing impatience over profitability.

Shares of the Google parent fell 9% in extended trading. Alphabet has gained about 9% so far this year.

Wall Street had been expecting 2025 capital expenditures of about $58 billion, according to LSEG data. That would have marked a modest increase over the $52.5 billion spending in 2024. CEO Sundar Pichai defended the dramatic increase on a conference call with analysts, who are raising new questions about capital spending by Google and US rivals following the emergence of China's DeepSeek, which offers cut-rate AI. He said Google's Gemini family of AI models is comparable in efficiency to DeepSeek.

"The cost of actually using (AI) is going to keep coming down, which will make more use cases feasible," Pichai said. "The opportunity space is as big as it comes, and that's why you're seeing us invest to meet that moment." Still, the company posted a deceleration in cloud revenue growth. Alphabet has been spending heavily on an infrastructure development to support AI research and integration into products such as search and cloud services. The majority of capex for 2025 would go into building servers and data centers, Chief Financial Officer Anat Ashkenazi said on the call. She attributed the fourth-quarter results in part to capacity constraints on cloud AI offerings.

Alphabet plans to spend $16 billion to $18 billion in the first quarter, a far bigger number than the roughly $6 million DeepSeek said it spent on the final training run to develop its AI model. To be sure, developers at leading US AI firms said the total training cost was likely magnitudes larger. But revelations around DeepSeek's training cost in January shocked tech stocks, contributing to Nvidia's record one-day drop of $593 billion in market value.

"It's very hard to defend Google after the earnings report," said Dave Wagner, portfolio manager at Aptus Capital Advisors, which holds Alphabet stock. He pointed to the cloud revenue miss and Google's poor track record on utilizing cash for profitability.

"DeepSeek has started to teach the market that maybe some things can be done a little bit more efficiently," he said. "Maybe we're starting to see the market dislike the continued increase in capex."

LEVELING OFF Google Cloud had previously grown fast enough to offset concerns around increased spending, said Brian Mulberry, client portfolio manager at Zacks Investment Management, which holds Alphabet shares.

"When you start to see that revenue level off or at least the growth start to top off a little bit, how you're going to finance the future growth of the company becomes an issue," he said.

Google's cloud business posted a 30% rise in revenue to $11.96 billion in the fourth quarter, slowing down from the 35% increase in the September quarter. Analysts were expecting a rise of 32.3% to $12.16 billion, according to data compiled by LSEG.

The soft cloud numbers come even as Google has built out AI features within its cloud computing platform. Pichai said on the conference call that developer usage on Gemini had doubled in six months to 4.4 million users. Larger cloud rival Microsoft also reported weaker-than-expected growth in its Azure cloud platform last week. Shares of Amazon, the largest cloud provider, which will publish quarterly results on Thursday, were down 1.8% in after-hours trade.

Alphabet's mainstay ad business, which represents about three-quarters of its overall revenue, has been facing rising competition as more advertisers eye social media platforms such as Meta's Facebook and Instagram or ByteDance's TikTok.

Advertising revenue rose 10.6% to $72.46 billion in the fourth quarter. That beat the third quarter's 10.4% growth and topped analysts' estimates of $71.84 billion, according to LSEG.

Ad revenue from YouTube grew 13.8% to $10.47 billion in the fourth quarter, compared with the 12.2% growth in the third quarter. Chief business officer Philipp Schindler said the growth was helped by US election advertising, with combined spending by Democrats and Republicans nearly doubling compared with the 2020 election. The ad tech products and ad-driven search business are both facing scrutiny from US regulators seeking to break up the company, though policy may change under the Trump administration.

Overall, Google's revenue rose 12% to $96.47 billion in the fourth quarter, compared with the average analyst estimate of $96.56 billion, according to data compiled by LSEG.

The company reported a profit of $2.15 per share, beating estimates of $2.13 per share.

Search revenue rose 12.5% to $54.03 billion. Pichai said that AI Overviews, the AI-generated summaries for search queries displayed above Google's traditional links to the Web, had increased search usage.

The monetization rate on ads for AI Overviews, introduced last October, was approximately the same compared to traditional search ads, chief business officer Philipp Schindler said.

Self-driving car unit Waymo will debut internationally in Tokyo in the coming weeks, Pichai said.



Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
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Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson

Shares in Meta skyrocketed by 10 percent at opening on Wall Street on Thursday, a day after the social media giant posted better than expected earnings as the company invests heavily in artificial intelligence.

Microsoft, whose earnings disappointed analysts, saw its share price tumble by 10 percent, with investors showing concern for the return on investment for the software giant's spending on AI.


Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
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Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File

South Korean tech giant Samsung Electronics posted record quarterly profits Thursday, riding massive market demand for the memory chips that power artificial intelligence.

A global frenzy to build AI data centers and develop the fast-evolving technology has sent orders for advanced high bandwidth memory microchips soaring.

That is also pushing up prices for less flashy chips used in consumer electronics -- threatening higher prices for phones, laptops and other devices worldwide.

In the quarter to December 2025, Samsung said it saw "its highest-ever quarterly consolidated revenue at KRW 93.8 trillion (US$65.5 billion)", a quarter-on-quarter increase of nine percent.

"Operating profit was also an all-time high, at KRW 20.1 trillion," the company said.

The dazzling earnings came a day after a key competitor, South Korean chip giant SK hynix, said operating profit had doubled last year to a record high, also buoyed by the AI boom.

The South Korean government has pledged to become one of the top three AI powers, behind the United States and China, with Samsung and SK hynix among the leading producers of high-performance memory.

Samsung said Thursday it expects "AI and server demand to continue increasing, leading to more opportunities for structural growth".

Annual revenue stood at 333.6 trillion won, while operating profit came in at 43.6 trillion won. Sales for the division that oversees its semiconductor business rose 33 percent quarter-on-quarter.

The company pointed to a $33.2 billion investment in chip production facilities -- pledging to continue spending in "transitioning to advanced manufacturing processes and upgrading existing production lines to meet rising demand".

- 'Clearly back' -

Major electronics manufacturers and industry analysts have warned that chipmakers focusing on AI sales will cause higher retail prices for consumer products across the board.

This week US chip firm Micron said it was building a $24 billion plant in Singapore in response to AI-driven demand that has caused a global shortage of memory components.

SK hynix announced Wednesday that its operating profit had doubled last year to a record 47.2 trillion won.

The company's shares have surged some 220 percent over the past six months, while Samsung Electronics has risen about 130 percent, part of a huge global tech rally fueled by optimism over AI.

Both companies are on the cusp of producing next-generation high-bandwidth "HBM4" chips for AI data centers, with Samsung reportedly due to start making them in February.

American chip giant Nvidia -- now the world's most valuable company -- is expected to be one of Samsung's customers for HBM4 chips.

But Nvidia has reportedly allocated around 70 percent of its HBM4 demand to SK hynix for 2026, up from the market's previous estimate of 50 percent.

"Samsung is clearly back and we are expecting them to show a significant turnaround with HBM4 for Nvidia's new products -- helping them move past last year's quality issues," Hwang Min-seong, research director at market analysis firm Counterpoint, told AFP.

But SK still "maintains a market lead in both quality and supply" of a number of key components, including Dynamic Random Access Memory chips used in AI servers, he said.

SK also this week said it will set up an "AI solutions firm" in the United States, committing $10 billion and weighing investments in US companies.


Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
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Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)

Google unveiled an artificial intelligence tool Wednesday that its scientists said would help unravel the mysteries of the human genome -- and could one day lead to new treatments for diseases.

The deep learning model AlphaGenome was hailed by outside researchers as a "breakthrough" that would let scientists study and even simulate the roots of difficult-to-treat genetic diseases.

While the first complete map of the human genome in 2003 "gave us the book of life, reading it remained a challenge", Pushmeet Kohli, vice president of research at Google DeepMind, told journalists.

"We have the text," he said, which is a sequence of three billion nucleotide pairs represented by the letters A, T, C and G that make up DNA.

However, "understanding the grammar of this genome -- what is encoded in our DNA and how it governs life -- is the next critical frontier for research," said Kohli, co-author of a new study in the journal Nature.

Only around two percent of our DNA contains instructions for making proteins, which are the molecules that build and run the body.

The other 98 percent was long dismissed as "junk DNA" as scientists struggled to understand what it was for.

However, this "non-coding DNA" is now believed to act like a conductor, directing how genetic information works in each of our cells.

These sequences also contain many variants that have been associated with diseases. It is these sequences that AlphaGenome is aiming to understand.

- A million letters -

The project is just one part of Google's AI-powered scientific work, which also includes AlphaFold, the winner of 2024's chemistry Nobel.

AlphaGenome's model was trained on data from public projects that measured non-coding DNA across hundreds of different cell and tissue types in humans and mice.

The tool is able to analyze long DNA sequences then predict how each nucleotide pair will influence different biological processes within the cell.

This includes whether genes start and stop and how much RNA -- molecules which transmit genetic instructions inside cells -- is produced.

Other models already exist that have a similar aim. However, they have to compromise, either by analyzing far shorter DNA sequences or decreasing how detailed their predictions are, known as resolution.

DeepMind scientist and lead study author Ziga Avsec said that long sequences -- up to a million DNA letters long -- were "required to understand the full regulatory environment of a single gene".

And the high resolution of the model allows scientists to study the impact of genetic variants by comparing the differences between mutated and non-mutated sequences.

"AlphaGenome can accelerate our understanding of the genome by helping to map where the functional elements are and what their roles are on a molecular level," study co-author Natasha Latysheva said.

The model has already been tested by 3,000 scientists across 160 countries and is open for anyone to use for non-commercial reasons, Google said.

"We hope researchers will extend it with more data," Kohli added.

- 'Breakthrough' -

Ben Lehner, a researcher at Cambridge University who was not involved in developing AlphaGenome but did test it, said the model "does indeed perform very well".

"Identifying the precise differences in our genomes that make us more or less likely to develop thousands of diseases is a key step towards developing better therapeutics," he explained.

However, AlphaGenome "is far from perfect and there is still a lot of work to do", he added.

"AI models are only as good as the data used to train them" and the existing data is not very suitable, he said.

Robert Goldstone, head of genomics at the UK's Francis Crick Institute, cautioned that AlphaGenome was "not a magic bullet for all biological questions".

This was partly because "gene expression is influenced by complex environmental factors that the model cannot see", he said.

However, the tool still represented a "breakthrough" that would allow scientists to "study and simulate the genetic roots of complex disease", Goldstone added.