Microsoft unveiled two chips at its Ignite conference in Seattle on Wednesday.
The first, its Maia 100 artificial intelligence chip, could compete with Nvidia’s highly sought-after AI graphics processing units. The second, a Cobalt 100 Arm chip, is aimed at general computing tasks and could compete with Intel processors.
Cash-rich technology companies have begun giving their clients more options for cloud infrastructure they can use to run applications. Alibaba, Amazon and Google have done this for years. Microsoft, with about $144 billion in cash at the end of October, had 21.5% cloud market share in 2022, behind only Amazon, according to one estimate.
Virtual-machine instances running on the Cobalt chips will become commercially available through Microsoft’s Azure cloud in 2024, Rani Borkar, a corporate vice president, told CNBC in an interview. She did not provide a timeline for releasing the Maia 100.
Google announced its original tensor processing unit for AI in 2016. Amazon Web Services revealed its Graviton Arm-based chip and Inferentia AI processor in 2018, and it announced Trainium, for training models, in 2020.
Special AI chips from cloud providers might be able to help meet demand when there’s a GPU shortage. But Microsoft and its peers in cloud computing aren’t planning to let companies buy servers containing their chips, unlike Nvidia or AMD.
The company built its chip for AI computing based on customer feedback, Borkar explained.
Microsoft is testing how Maia 100 stands up to the needs of its Bing search engine’s AI chatbot (now called Copilot instead of Bing Chat), the GitHub Copilot coding assistant and GPT-3.5-Turbo, a large language model from Microsoft-backed OpenAI, Borkar said. OpenAI has fed its language models with large quantities of information from the internet, and they can generate email messages, summarize documents and answer questions with a few words of human instruction.
The GPT-3.5-Turbo model works in OpenAI’s ChatGPT assistant, which became popular soon after becoming available last year. Then companies moved quickly to add similar chat capabilities to their software, increasing demand for GPUs.
“We’ve been working across the board and [with] all of our different suppliers to help improve our supply position and support many of our customers and the demand that they’ve put in front of us,” Colette Kress, Nvidia’s finance chief, said at an Evercore conference in New York in September.
OpenAI has previously trained models on Nvidia GPUs in Azure.
In addition to designing the Maia chip, Microsoft has devised custom liquid-cooled hardware called Sidekicks that fit in racks right next to racks containing Maia servers. The company can install the server racks and the Sidekick racks without the need for retrofitting, a spokesperson said.
With GPUs, making the most of limited data center space can pose challenges. Companies sometimes put a few servers containing GPUs at the bottom of a rack like “orphans” to prevent overheating, rather than filling up the rack from top to bottom, said Steve Tuck, co-founder and CEO of server startup Oxide Computer. Companies sometimes add cooling systems to reduce temperatures, Tuck said.
Microsoft might see faster adoption of Cobalt processors than the Maia AI chips if Amazon’s experience is a guide. Microsoft is testing its Teams app and Azure SQL Database service on Cobalt. So far, they’ve performed 40% better than on Azure’s existing Arm-based chips, which come from startup Ampere, Microsoft said.
In the past year and a half, as prices and interest rates have moved higher, many companies have sought out methods of making their cloud spending more efficient, and for AWS customers, Graviton has been one of them. All of AWS’ top 100 customers are now using the Arm-based chips, which can yield a 40% price-performance improvement, Vice President Dave Brown said.
Moving from GPUs to AWS Trainium AI chips can be more complicated than migrating from Intel Xeons to Gravitons, though. Each AI model has its own quirks. Many people have worked to make a variety of tools work on Arm because of their prevalence in mobile devices, and that’s less true in silicon for AI, Brown said. But over time, he said, he would expect organizations to see similar price-performance gains with Trainium in comparison with GPUs.
“We have shared these specs with the ecosystem and with a lot of our partners in the ecosystem, which benefits all of our Azure customers,” she said.
Borkar said she didn’t have details on Maia’s performance compared with alternatives such as Nvidia’s H100. On Monday, Nvidia said its H200 will start shipping in the second quarter of 2024.
TikTok’s grip on the short-form video market is tightening, and the world’s biggest tech platforms are racing to catch up.
Since launching globally in 2016, ByteDance-owned TikTok has amassed over 1.12 billion monthly active users worldwide, according to Backlinko. American users spend an average of 108 minutes per day on the app, according to Apptoptia.
TikTok’s success has reshaped the social media landscape, forcing competitors like Meta and Google to pivot their strategies around short-form video. But so far, experts say that none have matched TikTok’s algorithmic precision.
“It is the center of the internet for young people,” said Jasmine Enberg, vice president and principal analyst at Emarketer. “It’s where they go for entertainment, news, trends, even shopping. TikTok sets the tone for everyone else.”
Platforms like Meta‘s Instagram Reels and Google’s YouTube Shorts have expanded aggressively, launching new features, creator tools and even considering separate apps just to compete. Microsoft-owned LinkedIn, traditionally a professional networking site, is the latest to experiment with TikTok-style feeds. But with TikTok continuing to evolve, adding features like e-commerce integrations and longer videos, the question remains whether rivals can keep up.
“I’m scrolling every single day. I doom scroll all the time,” said TikTok content creator Alyssa McKay.
But there may a dark side to this growth.
As short-form content consumption soars, experts warn about shrinking attention spans and rising mental-health concerns, particularly among younger users. Researchers like Dr. Yann Poncin, associate professor at the Child Study Center at Yale University, point to disrupted sleep patterns and increased anxiety levels tied to endless scrolling habits.
“Infinite scrolling and short-form video are designed to capture your attention in short bursts,” Dr. Poncin said. “In the past, entertainment was about taking you on a journey through a show or story. Now, it’s about locking you in for just a few seconds, just enough to feed you the next thing the algorithm knows you’ll like.”
Despite sky-high engagement, monetizing short videos remains an uphill battle. Unlike long-form YouTube content, where ads can be inserted throughout, short clips offer limited space for advertisers. Creators, too, are feeling the squeeze.
“It’s never been easier to go viral,” said Enberg. “But it’s never been harder to turn that virality into a sustainable business.”
Last year, TikTok generated an estimated $23.6 billion in ad revenues, according to Oberlo, but even with this growth, many creators still make just a few dollars per million views. YouTube Shorts pays roughly four cents per 1,000 views, which is less than its long-form counterpart. Meanwhile, Instagram has leaned into brand partnerships and emerging tools like “Trial Reels,” which allow creators to experiment with content by initially sharing videos only with non-followers, giving them a low-risk way to test new formats or ideas before deciding whether to share with their full audience. But Meta told CNBC that monetizing Reels remains a work in progress.
While lawmakers scrutinize TikTok’s Chinese ownership and explore potential bans, competitors see a window of opportunity. Meta and YouTube are poised to capture up to 50% of reallocated ad dollars if TikTok faces restrictions in the U.S., according to eMarketer.
Watch the video to understand how TikTok’s rise sparked a short form video race.
The X logo appears on a phone, and the xAI logo is displayed on a laptop in Krakow, Poland, on April 1, 2025. (Photo by Klaudia Radecka/NurPhoto via Getty Images)
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Elon Musk‘s xAI Holdings is in discussions with investors to raise about $20 billion, Bloomberg News reported Friday, citing people familiar with the matter.
The funding would value the company at over $120 billion, according to the report.
Musk was looking to assign “proper value” to xAI, sources told CNBC’s David Faber earlier this month. The remarks were made during a call with xAI investors, sources familiar with the matter told Faber. The Tesla CEO at that time didn’t explicitly mention any upcoming funding round, but the sources suggested xAI was preparing for a substantial capital raise in the near future.
The funding amount could be more than $20 billion as the exact figure had not been decided, the Bloomberg report added.
Artificial intelligence startup xAI didn’t immediately respond to a CNBC request for comment outside of U.S. business hours.
The AI firm last month acquired X in an all-stock deal that valued xAI at $80 billion and the social media platform at $33 billion.
“xAI and X’s futures are intertwined. Today, we officially take the step to combine the data, models, compute, distribution and talent,” Musk said on X, announcing the deal. “This combination will unlock immense potential by blending xAI’s advanced AI capability and expertise with X’s massive reach.”
Alphabet CEO Sundar Pichai during the Google I/O developers conference in Mountain View, California, on May 10, 2023.
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Alphabet‘s stock gained 3% Friday after signaling strong growth in its search and advertising businesses amid a competitive artificial intelligence environment and uncertain macro backdrop.
“GOOGL‘s pace of GenAI product roll-out is accelerating with multiple encouraging signals,” wrote Morgan Stanley‘s Brian Nowak. “Macro uncertainty still exists but we remain [overweight] given GOOGL’s still strong relative position and improving pace of GenAI enabled product roll-out.”
The search giant posted earnings of $2.81 per share on $90.23 billion in revenues. That topped the $89.12 billion in sales and $2.01 in EPS expected by LSEG analysts. Revenues grew 12% year-over-year and ahead of the 10% anticipated by Wall Street.
Net income rose 46% to $34.54 billion, or $2.81 per share. That’s up from $23.66 billion, or $1.89 per share, in the year-ago period. Alphabet said the figure included $8 billion in unrealized gains on its nonmarketable equity securities connected to its investment in a private company.
Adjusted earnings, excluding that gain, were $2.27 per share, according to LSEG, and topped analyst expectations.
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Alphabet shares have pulled back about 16% this year as it battles volatility spurred by mounting trade war fears and worries that President Donald Trump‘s tariffs could crush the global economy. That would make it more difficult for Alphabet to potentially acquire infrastructure for data centers powering AI models as it faces off against competitors such as OpenAI and Anthropic to develop largely language models.
During Thursday’s call with investors, Alphabet suggested that it’s too soon to tally the total impact of tariffs. However, Google’s business chief Philipp Schindler said that ending the de minimis trade exemption in May, which created a loophole benefitting many Chinese e-commerce retailers, could create a “slight headwind” for the company’s ads business, specifically in the Asia-Pacific region. The loophole allows shipments under $800 to come into the U.S. duty-free.
Despite this backdrop, Alphabet showed steady growth in its advertising and search business, reporting $66.89 billion in revenues for its advertising unit. That reflected 8.5% growth from the year-ago period. The company reported $8.93 billion in advertising revenue for its YouTube business, shy of an $8.97 billion estimate from StreetAccount.
Alphabet’s “Search and other” unit rose 9.8% to $50.7 billion, up from $46.16 billion last year. The company said that its AI Overviews tool used in its Google search results page has accumulated 1.5 billion monthly users from a billion in October.
Bank of America analyst Justin Post said that Wall Street is underestimating the upside potential and “monetization ramp” from this tool and cloud demand fueled by AI.
“The strong 1Q search performance, along with constructive comments on Gemini [large language model] performance and [AI Overviews] adoption could help alleviate some investor concerns on AI competition,” Post wrote in a note.