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.
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.
As the backbone of artificial intelligence (AI), machine learning, cloud computing and the internet of things (IoT), datacentres are at the centre of modern business infrastructure, but as businesses become more dispersed, the infrastructure surrounding datacentres has become more critical and complex, with network outages no longer isolated events and their cost to businesses never higher, a study from Opengear has found.
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.
Mako, a startup co-founded by Cornell Tech assistant professor Mohamed Abdelfattah, has raised $8.5 million in seed funding to tackle one of artificial intelligence's most pressing infrastructure challenges: optimizing the computing efficiency of graphics processing units, or GPUs. The $8.5 million round was led by M13, with participation from Neo, Flybridge, and others. The company plans to use the funding to grow its engineering team and accelerate product development.
Join Coursedog's Platform team to architect and deliver the AI infrastructure powering Intelligent Academic Operations. You'll design orchestration pipelines and AI integration frameworks.
LM Caches play a critical role in improving the efficiency and scalability of deploying large language models by caching and reusing previously computed results.
Accessing critical AI infrastructure is hindered by fundamental problems: crushing costs, extreme concentration, and insufficient capacity. A company seeking large-scale compute must often sign long-term contracts with hyperscalers, far beyond the budgetary reach of most academics and startups.
Microsoft recently signed a deal with Vaulted Deep to bury over 4.9 million metric tonnes of organic waste in an effort to offset its carbon emissions.
