#ai-infrastructure

#ai-infrastructure

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 and $4 trillion will be spent on AI infrastructure by the end of the decade - with much of that money coming from AI companies themselves.

Altogether, Lumen said construction was underway coast-to-coast, and that it has delivered "significant" progress in its mission to build the backbone for the artificial intelligence (AI) economy. It added that it was moving forward with a multibillion-dollar build, with plans to add 34 million intercity fibre miles by the end of 2028, as part of the 47 million intercity fibre mile target.

Moody's said late last week that the OpenAI "contract size is staggering - highlighting the tremendous potential for Oracle's AI Infrastructure. However, the related risks of the build are significant." It pointed to the significant "counterparty risk" in Oracle's projected growth - the possibility that another party fails to meet its obligations. "Counterparty risk is always a key consideration in any type of project financing, particularly where there is a high reliance on revenue from a single counterparty," Moody's analysts wrote on Wednesday.

The OpenAI CEO said in a post on X on Monday that the company is launching "new compute-intensive offerings" over the next few weeks. Altman said because of the costs involved, some features will initially be limited to Pro subscribers, while certain new products will have extra fees. Altman framed the push as an experiment in stretching AI infrastructure to its limits: "We also want to learn what's possible when we throw a lot of compute, at today's model costs, at interesting new ideas," he wrote.

In his conference keynote, Groundbreaking SuperPoD Interconnect: Leading a new paradigm for AI infrastructure, Eric Xu, the deputy chairman of the board and rotating chairman of the IT and networking giant, stressed that Huawei's goal was to sustainably meet long-term computing demand by building SuperPoDs - defined as a single logical machine, made up of multiple physical machines that can learn, think and reason as one - and SuperClusters, with the semiconductor manufacturing process nodes that he said were "practically" available to the Chinese mainland.

When Oracle launched its cloud service, Oracle Cloud Infrastructure (OCI), in 2016, very few in the tech industry believed the company could become a serious player in the public cloud market. Established giants like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud had not only dominated the market for years but also had set a high bar for innovation, scale, and performance that seemed insurmountable to newcomers.

Top tech names were on the guest list for the banquet thrown for President Trump during his second state visit to the UK on Wednesday. The banquet seating chart included NVIDIA CEO Jensen Huang; Apple CEO Tim Cook; venture capitalist and White House AI and crypto czar David Sacks; Alphabet and Google president Ruth Porat; Microsoft CEO Satya Nadella; Salesforce CEO Marc Benioff; and OpenAI's Sam Altman, according to the New York Times.

With today's announcement, Google is deepening our roots in the UK and helping support Great Britain's potential with AI to add £400 billion to the economy by 2030 while also enhancing critical social services. Google's investment in technical infrastructure, expanded energy capacity, and job-ready AI skills will help ensure everyone in Broxbourne and across the whole of the UK stays at the cutting-edge of global tech opportunities.

Shares are jumping 5% in morning trading today, approaching $120 per share, fueled by blockbuster news of a $6.3 billion deal with Nvidia ( NASDAQ:NVDA ). The agreement, signed under their existing master services pact, commits the chip giant to snapping up any unsold cloud capacity from CoreWeave through April 2032. This backstop ensures steady revenue amid soaring AI demand, highlighting CoreWeave's pivotal role in powering next-gen computing.

Concerns about the prospects for Lumen Technologies Inc. ( NYSE: LUMN) have lingered. However, recent quarterly results suggested a positive shift in its financial health due to a focus on strengthening its balance sheet and improving liquidity by reducing debt. The global telecommunications company has also focused on improving customer satisfaction. However, it still faces challenges with declining revenue and with free cash flow.

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.

[A]s we introduce all photonics networks and this end to end connectivity, extend it into the data center, we're reducing the latency such that it starts to feel much more like it's just another server and another rack in the same data center. We're literally approaching the speed of light in terms of how we transmit signals from end to end and the latency in, say, thousand of kilometers is still measured in a small number of milliseconds

AI workloads are already expensive due to the high cost of renting GPUs and the associated energy consumption. Memory bandwidth issues make things worse. When memory lags, workloads take longer to process. Longer runtimes result in higher costs, as cloud services charge based on hourly usage. Essentially, memory inefficiencies increase the time to compute, turning what should be cutting-edge performance into a financial headache.

The private fund landscape is entering a new phase of sophistication. As the market matures, the focus is shifting towards the forward-looking evolution of how capital is raised. This new era prioritizes long-term value, where success in 2025 and beyond will be defined by superior strategy, clear specialization, and disciplined execution. Markets could see a flight to quality, as discerning investors consolidate relationships with established managers who possess clear, defensible strategies.

During a Goldman Sachs technology conference in San Francisco, he said that the company has approximately $106 billion in contracts outstanding. According to him, more than half of that can be converted into revenue in the next two years. In the second quarter of 2025, parent company Alphabet reported $13.6 billion in revenue for Google Cloud, an increase of 32 percent over the previous year.

Nebius Group said on Monday it will provide Microsoft with GPU infrastructure capacity, in a deal worth $17.4 billion, over a five-year term, sending its shares soaring over 47% after the bell. The deal underscores the surging demand for high-performance AI computers, as companies invest heavily to bolster their AI infrastructure. Microsoft may also acquire additional services capacity under the deal, bringing the total contract value to about $19.4 billion.

The Weekly Notable Startup Funding Report takes us on a trip across various ecosystems in the US, highlighting some of the notable funding activity in the various markets that we track. The notable startup funding rounds for the week ending 9/5/25 featuring funding details for Lead, Lendistry, and Baseten, and seventeen other deals representing $14.4B (not a typo) in new funding that you need to know about.

Funded entirely by private investment and backed by the government of Gibraltar, the Pelagos Data Centres Project represents a transformative step for the territory's digital and economic landscape. It will also make an important contribution to meeting Europe's demand for datacentre capacity, positioning Gibraltar as a significant new node in Europe's digital infrastructure that can serve the broader needs of the UK and continental Europe.

We've spent several years now obsessing over models and assistants, but here's a new interesting truth: the next competitive edge in AI won't be another benchmark, but electrons. And not just any electrons, but cheap ones. As the " AI wars" heat up, the winners won't simply be those with the best UX or the most compute. They'll be the firms that can secure abundant low-cost power at scale, hour after hour, year after year.

Nvidia (NASDAQ: NVDA) has firmly established itself as the leading player in artificial intelligence (AI) infrastructure, as it accounts for nearly 92% of the data center GPU market. That dominance has been the foundation of its robust financial performances of recent years. In its fiscal 2026 second quarter (which ended July 27), Nvidia reported revenues of $46.7 billion, up 56% year over year and exceeding guidance, while its GAAP ( generally accepted accounting principles) gross margin was 72.4%.

Mortgage rate squeeze: AI investments are diverting capital from the housing market, contributing to the housing affordability crisis and impacting home sales. Utilities impact: The AI industry's high energy demands are driving utilities to expand capacity, with projects like nuclear reactors aiming to meet data center needs, potentially benefiting consumers with stable pricing. Water consumption: AI data centers are significant water consumers, leading to shortages and increased utility bills for residents, exacerbating housing market pressures.

Dell Technologies reported record revenue of $29.8 billion in the second quarter of fiscal 2026, up 19 percent from a year earlier. Earnings per share rose 38 percent to $1.70, while adjusted earnings were $2.32. Revenue from servers and networks grew 69 percent to $12.9 billion, driven by strong demand for AI systems. COO Jeff Clarke said Dell shipped more AI solutions in the first half of the year than it did in all of 2025

"It's not just computing capacity that contributes to the cost of AI: IT needs to reexamine existing storage operations too, Kimball said. "I would take a long look at my storage infrastructure and how to better optimize on and off prem. The infrastructure populating most enterprise datacenters is out of date and underutilized. Moving to servers that have the latest, densely populated CPUs is a first start," he said.