#ai-infrastructure

#ai-infrastructure

The Roundhill Generative AI & Technology ETF ( NYSEARCA:CHAT) soared just over 45% in 2025, outpacing the S&P 500's 17% gain and the Nasdaq-100's 21% advance. The fund's 2026 performance trajectory depends on hyperscaler spending on AI infrastructure and the fund's concentrated exposure to companies building that infrastructure. Hyperscaler Capital Spending Is the Engine The biggest macro factor affecting CHAT's performance is capital expenditure by the world's largest cloud providers.

SoftBank said it will acquire digital infrastructure investor DigitalBridge for about $4 billion. The Japanese conglomerate said it is doubling down on building the data centers, connectivity, and power needed to support AI at a global scale. "As AI transforms industries worldwide, we need more compute, connectivity, power, and scalable infrastructure," said Masayoshi Son, chairman and CEO of SoftBank Group. The deal underscores SoftBank's push to control more of the physical infrastructure behind AI as competition for computing resources intensifies.

There are few certainties in life: death, taxes and massively increased workloads on infrastructures through the unstoppable rise of AI. And enterprises and connectivity providers know only too well that AI has fuelled an unprecedented surge in network demand. Keeping pace with the next wave of AI growth will require new long-haul networks to enable the rapid scaling of capacity needs in both existing and emerging enterprise setups - especially within datacentres.

As memory prices continue to rise, it is time engineers reconsidered their applications and toolchains' voracious appetite for memory. Does a simple web page really need megabytes to show a user the modern equivalent of Hello World? Today's Windows Task Manager executable occupies 6 MB of disk space. It demands almost 70 MB before it will show a user just how much of a memory hog Chrome is these days. The original weighs in at 85 KB on disk.

AI represents what Diameter Capital sees as a long-running, disruptive cycle - but buying the most obvious winners isn't the only way to play it, he said on the "Goldman Sachs Exchanges" podcast published on Friday. Diameter Capital, which manages approximately $25 billion in assets, has focused on where AI demand could create less obvious bottlenecks - and where those bottlenecks show up in credit markets.

Magnificent Seven stocks have been some of the most successful growth stocks and make up a large portion of the S&P 500. However, all of those same stocks have valuations above $1 trillion, which makes it harder for those same stocks to double, triple, or 10x from current levels. That's why some investors are seeking smaller growth stocks that are posting impressive revenue growth. These stocks have the potential to outperform the Magnificent Seven stocks

The company will merge with TAE Technologies-a privately held fusion energy firm that's backed by Alphabet, Chevron Technology Ventures, and others-in a deal that's worth more than $6 billion. It's an all-stock deal, which is expected to close sometime next year, and is a huge and eyebrow-raising move for Trump Media, which is best known as the owner of President Trump's social media platform, Truth Social.

It was never clearer that the world you and I grew up in no longer exists than on a hot, arid summer afternoon in Riyadh, Saudi Arabia in May of this year. The oil-rich Saudis, keen to jump into the AI arms race, had invited all the tech and business elites who will decide the future of mankind to an investment forum in the desert.

More recently, Lumen partnered with IBM to unlock scalable AI for businesses, as well as with Google Cloud to provide advanced cloud and network solutions to meet the growing demands of AI workloads. Lumen strengthened its financial position and freed up capital for long-term growth by refinancing its term loans, as well as selling off its fiber-to-the-home business to AT&T. CEO Kate Johnson projected the company's return to growth by 2029.

It's clear that there are a lot of new opportunities to use new AI advances to accelerate our core business that should have strong ROI over the next few years, so I think we should invest more there [...] our AI investments continue to require serious infrastructure, and I expect to continue investing significantly there too.

The Portfolio Role: Broad AI Exposure Without Picking Winners AIQ provides comprehensive AI participation without concentrating capital in a handful of names. The fund combines appreciation from companies building AI infrastructure (semiconductors, cloud computing) with those deploying AI applications (software, automation, consumer tech). No single position exceeds 4.5% of the portfolio. Alphabet ( NASDAQ:GOOGL) leads at 4.44%, followed by Samsung Electronics at 3.92% and Advanced Micro Devices ( NASDAQ:AMD) at 3.63%. Even NVIDIA ( NASDAQ:NVDA) represents just 2.84% of assets.

Starting December 17, the computer maker is set to hike prices across its commercial product lines, according to an internal list of upcoming price changes sent to staff on December 9 and seen by Business Insider. The list outlines price hikes for Dell'scommercial business - meaning its sales to corporate clients rather than individual consumers. The commercial business accounts for about 85% of Dell's annual revenue in the Client Solutions Group (CSG), the division that sells laptops and PCs, according to its latest annual results.

Amid this change, agentic Retrieval-Augmented Generation (RAG) becomes a critical asset. Whereas classic RAG grounded models in trusted data; agentic RAG adds multi-step reasoning, tool use and secure system coordination on top. In short, agentic RAG provides the scaffolding businesses usually can't construct themselves. Especially in the mid-market and for SMBs, obstacles like aging infrastructure, overextended teams and limited resources often stand in the way of custom-built AI.

The feat was achieved by re-architecting key components of Kubernetes' control plane and storage backend, replacing the traditional etcd data store with a custom Spanner-based system that can support massive scale, and optimizing cluster APIs and scheduling logic to reduce load from constant node and pod updates. The engineering team also introduced new tooling for automated, parallelized node pool provisioning and faster resizing, helping overcome typical bottlenecks that would hinder responsiveness at such a scale.

Global IT spending has grown at the fastest rate in nearly 30 years, according to IDC, largely thanks to the boom in AI and cloud services and PC refresh cycles. Figures from IDC's latest show that spending on hardware, software, and IT services is on course to rise by 14%. That's the fastest year of growth since 1996, when the launch of Windows 95, expanding PC usage, and internet adoption were the primary drivers of IT spending. Now it's all about the massive AI infrastructure investment wave driving another 'supercycle' of tech spending, IDC noted, with the figure set to reach $4.25 trillion.

Cofounders Chris Lattner and Tim Davis have spent decades building the software plumbing that sits beneath the modern tech industry. Lattner is famous for creating Apple's Swift programming language. He also built the software underpinning Google's TPU AI chips, with Modular cofounder Tim Davis. They're now aiming that expertise at CUDA itself. The attempt borders on madness, but it's the kind of audacious project that could transform the AI industry.

US tech giant Microsoft announced on Tuesday that it will invest $17.5 billion (15 billion) in India over the next four years as it looks to strengthen the country's cloud and artificial intelligence infrastructure. CEO Satya Nadella shared the news of Microsoft's largest-ever investment in Asia in a post on X after meeting Indian Prime Minister Narendra Modi in New Delhi. Nadella said the multi-billion-dollar commitment is aimed at helping India develop the "infrastructure, skills, and sovereign capabilities" essential for an AI-driven future. Nadella is currently on a three-day visit to India, meeting policymakers and participating in AI-related events in Bengaluru the nation's technology center and Mumbai, its financial capital.

On December 3, The Wall Street Journal reported memory manufacturer Micron would wind down Crucial, its consumer business, to focus on components for the AI industry. The PC I'm writing this article on has an SSD and RAM from Crucial. Overnight, Micron decided to end a business it spent decades building, and from a certain perspective, I guess it makes sense. In recent months, OpenAI has signed more than $1.4 trillion worth of infrastructure deals, creating unprecedented demand for server-grade solid-state storage and RAM.

Datacenter capital expenditure is forecast to grow 17 percent annually through 2030, reaching $1.6 trillion, with supply chain constraints pushing up the price of components. The latest Cloud and Datacenter Market Snapshot [PDF] from analyst Omdia states that investment into AI infrastructure continues apace, despite all the talk of it being a bubble ready to burst. However, adoption of AI remains relatively low, it claims, with many more users and higher usage per user expected.

Even after adjusting for inflation, big tech companies are issuing more bonds than during the late 1990s. And the companies aren't just refinancing existing debt-they're taking on additional debt. "While the increasingly aggressive (and creative) borrowing by AI companies won't be their downfall, if they do fall short of investors' expectations and their stock prices suffer, their debts could quickly become a problem," Zandi wrote.