#ai-infrastructure

#ai-infrastructure

Nava - $30M Series C Employee Benefits Nava, a tech-enabled employee benefits brokerage platform, has raised $30M in Series C funding led by Thrive Capital. Founded by Brandon Weber, Donald DeSantis, Kareem Zaki, and Lincoln Reis in 2019, Nava has now raised a total of $90M in reported equity funding. Crosby - $20M Series A Technology Crosby has raised $20M in Series A funding led by Bain Capital Ventures, Index Ventures, and Elad Gil. Crosby was founded by Ryan Daniels and John Sarihan.

Regardless of this year's stock market volatility, the explosive demand for semiconductors and microchips that has grabbed news headlines and led the market higher over the past few years remains. As the drive toward integrating artificial intelligence (AI) into our everyday lives progresses, a handful of mega-cap companies are capable of meeting that demand. While Nvidia Corp. ( NASDAQ: NVDA) may get the lion's share of attention, companies like Broadcom Inc. ( NASDAQ: AVGO) will also be playing a central role in supply.

24/7 Wall St. hosts Doug McIntyre and Lee Jackson analyze a major move by BlackRock to acquire the utility company AES, describing it as the beginning of a larger wave of consolidation across the utility and banking sectors. It could signal how companies like BlackRock might be positioning themselves to control the energy sources needed to power data centers and AI infrastructure.

He reportedly wants 250 gigawatts of new electricity-equal to about half of Europe's all-time peak load-to run gigantic new data centers in the U.S. and elsewhere worldwide by 2033. Building or expanding power plants to generate that much electricity on Altman's timetable indeed seems almost inconceivable. "What OpenAI is trying to do is absolutely historic," says Virun Sivaram, Senior Fellow for Energy and Climate at the Council on Foreign Relations.

It takes a lot of computing power to run an AI product - and as the tech industry races to tap the power of AI models, there's a parallel race underway to build the infrastructure that will power them. On a recent earnings call, Nvidia CEO Jensen Huang estimated that between $3 trillion and $4 trillion will be spent on AI infrastructure by the end of the decade - with much of that money coming from AI companies.

Europe is awarding €70 million to a consortium of Dutch organizations to build an AI factory in Groningen. The total investment of €200 million is intended to make the Netherlands more technologically independent from American and Chinese platforms, while giving startups and SMEs access to enormous computing power. The project will be rolled out in phases. The expertise center will start in 2026, followed by the fully operational supercomputer in 2027. The AI factory combines three functions: an expertise center, a data facility, and an AI supercomputer.

If you've never heard of Nebius Group ( NASDAQ:NBIS) until recently, you're definitely not alone. Shares of the up-and-coming AI infrastructure cloud play have gained a shocking 335% year to date and more than 560% in the past full year. Undoubtedly, the parabolic rise of Nebius has made the relatively unknown AI play a fairly sizable $33 billion company, making it large enough to get noticed, but still small enough to be capable of further upside as the AI revolution continues

While some analysts and tech leaders have claimed the AI industry is in a bubble, Dell said the boom is still going strong because of AI companies' insatiable appetite for computing power. If customers were buying without a real need, Dell would be worried, but "we don't see that at all," he told . "In fact, we see kind of the opposite."

Micron Technology ( ) has emerged as a key player in the artificial intelligence (AI) ecosystem through its high-bandwidth memory (HBM) chips, which provide the high-speed data processing essential for training large language models and running inference tasks. These chips enable AI accelerators from companies like Nvidia ( NASDAQ:NVDA ) to handle massive datasets efficiently, positioning MU as a vital supplier amid surging demand from data centers.

( Advanced Micro DevicesNASDAQ:AMD) shocked investors yesterday with a landmark multi-year agreement to supply OpenAI with 6 gigawatts of its Instinct graphics processing units (GPUs), starting with 1 gigawatt in the second half of 2026. The deal, which could generate tens of billions in annual revenue for AMD, includes a warrant allowing OpenAI to acquire up to 160 million shares - roughly 10% of the company - for a nominal fee, tied to deployment milestones and stock price targets up to $600 per share.

unveiled extra £1bn funding to accelerate the UK towards its goal of scaling its compute capacity by twenty-fold by 2030. Starmer was joined on stage by chief Jensen Huang, who hailed the UK's AI sector, but warned that the country lacked a critical component: "If you're in the world of AI, you do machine learning. You can't do machine learning without a machine."

Billions of dollars are flowing into artificial intelligence companies such as OpenAI and Anthropic, yet investors in software firms that should also be well-positioned to benefit from the AI boom have largely been left on the sidelines. Cloud-based company Salesforce is down 28% year to date, closing at $240.36. Adobe is down 21% ending at $346.74. And a Morgan Stanley basket of SaaS stocks, a group of software-as-a-service companies the bank tracks to gauge sector performance, fell more than 6% this year.

Much of this edge stems from seasonal factors, including the Christmas holiday shopping surge that boosts retail and consumer sectors from November through December. Strong earnings reports in Q4 also often fuel optimism, as companies close out the year with solid results. The quarter also aligns with the close of the old investing adage to "sell in May and go away," where investors who sidelined themselves during the slower summer months return to the markets adding capital, driving demand.

U.S. technology company Nvidia and Fujitsu, a Japanese telecommunications and computer maker, agreed Friday to work together on artificial intelligence to deliver smart robots and a variety of other innovations using Nvidia's computer chips. "The AI industrial revolution has already begun. Building the infrastructure to power it is essential in Japan and around the world," Nvidia Chief Executive Jensen Huang said, hugging his Fujitsu counterpart Takahito Tokita on stage. "Japan can lead the world in AI and robotics," Huang told reporters at a Tokyo hotel.

This page will be updated throughout the day to reflect any new fundings. AI INFRASTRUCTURE Modal Labs, a serverless platform for AI, data, and ML teams, has raised $87M in Series B funding led by Lux Capital. Founded by Akshat Bubna and Erik Bernhardsson in 2021, Modal Labs has now raised a total of $110M in reported equity funding. REACH NYC TECH LEADERS AlleyWatch is NYC's leading source of tech and startup news, reaching the city's most active founders, investors, and tech leaders.

If Fundstrat's Tom Lee isn't consistently Wall Street's biggest bull, he's certainly one of the most vocal. Either way, the man's track record has been nothing short of respectable. And while time will tell if he's right to stay bullish on the broad stock (and especially the small caps), I do think that he's a market strategist who's worth listening to closely whenever he has another call to make.

Google has helped strike another deal with a Bitcoin miner. On Thursday, Cipher Mining announced that it was leasing a data warehouse it owns in Colorado City, Texas, to an AI computing startup. The Bitcoin miner projects the contract to net the company $3 billion over its initial 10-year term and $7 billion if two five-year extensions are exercised. Cipher Mining struck the deal with Fluidstack, an AI computing startup based in the U.K.

On Thursday, the AI platform Clarifai announced a new reasoning engine that it claims will make running AI models twice as fast and 40% less expensive. Designed to be adaptable to a variety of models and cloud hosts, the system employs a range of optimizations to get more inference power out of the same hardware. "It's a variety of different types of optimizations, all the way down to CUDA kernels to advanced speculative decoding techniques," said CEO Matthew Zeiler. "You can get more out of the same cards, basically." The results were verified by a string of benchmark tests by the third-party firm Artificial Analysis, which recorded industry-best records for both throughput and latency.

I'll go on record as to say I'm the best thing that's ever happened to him,