The 10 most important AI stories of June 25, 2026, hand-curated from the day's coverage. Every story links to its primary source.
SpaceX recently completed the largest IPO ever, raising more than $85 billion and debuting at a ~$1.77 trillion valuation. Shares have since pulled back (a common post-IPO pattern, especially in volatile markets), but the raise was enormous. xAI is part of that story because of the earlier integration. FEb 2026, SpaceX acquired xAI and the ... Read more
On Semiconductor said the deal bumps up its total addressable market by $30 billion to $243 billion by 2030.
AI is moving from chat and web search to delegated work.Why it matters: The frontier AI labs have spent years promising that effective AI agents will act as our minions in the workplace and at home, and that might soon be a reality.The big picture: Use of Codex — OpenAI's agentic coding and work platform — is accelerating, according to a new report from OpenAI, Columbia, Duke and the University of Pennsylvania.The researchers separate Codex users into three categories: OpenAI employees, outside organizations and individual users. Then they measured usage of Codex versus ChatGPT, by tokens.99.8% of OpenAI employees' output tokens were produced with Codex, compared with 63% for organizations and 16.5% for individuals. OpenAI's own Codex use is meant to represent how users might turn to agents when cost, access, training and buy-in are mostly removed.Among active users of ChatGPT and Codex at organizations outside OpenAI, just above 0% used Codex in August 2025. That share is now around 17%.Between the lines: The number of individuals using Codex is still small, but those who use it use it a lot, per the report, shared first with Axios.By the numbers: In a sample of individual Codex users, 80.6% made at least one Codex request estimated to represent more than 30 minutes of work by an "experienced human." 70.2% of Codex users made at least one request estimated to save more than an hour of human work.25.6% had delegated work estimated to take more than eight hours for a human to ...
This article is brought to you by Capital One.After five years leading natural language understanding and eventually the entire Alexa AI organization at Amazon, Prem Natarajan made a nontraditional move: He became Chief Scientist at a bank. Not just any bank: Capital One, a financial institution serving over 100 million customers, helping everyday Americans manage their financial lives.For Natarajan, a veteran of DARPA-funded research and academia who had watched machine learning evolve from task-specific applications to foundation models, the logic was clear. Some of the most interesting advances in AI research and deployment were shifting from big tech’s horizontal platforms to industry verticals like finance, where the most complex problems aren’t just building models but making AI work under the constraints of real-world customer problems, contextual business knowledge, continuous learning, with an incredibly high bar for accuracy and privacy.That’s also what made Capital One the right place to do it. For decades, the company has been recognized as one of the most data- and analytics-driven financial institutions in the industry. Its business model from the very beginning was built around using data and technology to personalize financial products for customers. A decade ago, Capital One went all in on the cloud and rebuilt its data ecosystem, creating a unified environment for data, compute, and AI and machine learning experimentation. Today, its modern infrastructure, d...
Qualcomm's data center entry analyzed: how the Modular acquisition, HBC memory architecture, and Arm-based C1000 CPU challenge NVIDIA in AI inference.
GLM-5.2 — the latest Chinese open-source model capturing Silicon Valley's attention — is raising fresh concerns among security researchers that advanced AI hacking capabilities are becoming dramatically cheaper and more accessible.Why it matters: The barrier to entry for malicious hackers eager to automate and personalize their attacks is getting lower and lower. Driving the news: Z.ai's GLM-5.2, which was released last week, has agentic capabilities that rival those of Claude Opus 4.8 and OpenAI's GPT-5.5 while costing roughly half as much to run.Two separate security evaluations from Graphistry and Semgrep found that GLM-5.2 performed on par with leading U.S. models on cybersecurity investigation and vulnerability-discovery benchmarks.Researchers at Graphistry also suggested that GLM-5.2 may be an "illegal distillation of both GPT-5.5 and Opus 4.8" — a claim that, if true, could help explain how Chinese models have been rapidly narrowing the gap with U.S. competitors.Z.ai did not respond to a request for comment.The big picture: Unlike Claude or ChatGPT, open-weight models like GLM-5.2 can be downloaded and modified directly, allowing users to remove safety controls, fine-tune them for specific tasks, and operate them without relying on a commercial provider.Graphistry said GLM-5.2 is the first open-weight model it has tested that it would recommend for a "frontier-like" cybersecurity experience.Threat level: Hackers are already talking in Russian-language forums about how ...
This year, FIFA is providing an AI agent that any team can use. Is it enough to level the playing field or will future winners be determined by which team can afford the best tools?
As UK police embrace the AI revolution, a WIRED investigation reveals the messy inside story of one region’s experiment with predictive analytics.
The Pentagon has quietly revised its doctrine on how the US military picks its targets in battle, opening the way for artificial intelligence to make critical wartime decisions in the future.
General Intuition has raised $320 million to scale AI trained on millions of hours of gameplay, betting action data can help AI develop something closer to human intuition.
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