For the first time in its 35-year history, Arm has manufactured its own chip, expanding beyond its long-standing business model of licensing chip designs to companies like Apple and Nvidia. The new CPU, called "Arm AGI," was developed in partnership with Meta and is designed to handle AI workloads in data centers.
The chip packs up to 136 cores, runs at up to 3.7 GHz, and is built on TSMC's 3nm process. According to Arm CEO Rene Haas, the chip is meant to deliver high-performance, energy-efficient computing for AI infrastructure. Meta plans to pair the CPU with its own MTIA accelerator, as Meta's head of infrastructure, Santosh Janardhan, explained.
Other partners include OpenAI, Cerebras, Cloudflare, and Lenovo. First systems are already available, with broader availability expected in the second half of 2026.
OpenAI has reportedly finished pretraining its new AI model, codenamed "Spud," CEO Sam Altman told employees in an internal memo, according to The Information. Altman said the company expects to have a "very strong model" in "a few weeks" that can "really accelerate the economy."
"Things are moving faster than many of us expected," Altman wrote. In a related move, Fidji Simo's product organization is being renamed "AGI Deployment." To free up computing capacity for Spud and other priorities, OpenAI will shut down its video app Sora.
New investors include Andreessen Horowitz, D.E. Shaw Ventures, MGX, TPG, and T. Rowe Price. Microsoft is also participating, with Friar calling the company "an incredible partner." A leaked investor document lists Microsoft as OpenAI's biggest risk factor, which made some headlines but is hardly surprising given how heavily OpenAI still relies on Microsoft for both funding and compute. The dependency runs both ways, though: OpenAI is also an enormous risk for Microsoft.
Claude Code's new Auto Mode tries to balance safety and speed
Developers using Claude Code have faced an awkward choice: approve every single action manually or turn off all safety checks entirely. Anthropic’s new Auto Mode aims to offer a middle ground.
The open-source library LiteLLM, a widely used proxy for AI language model APIs, has been compromised with malware through PyPI.Security researcher Callum McMahon of Futuresearch found that versions 1.82.7 and 1.82.8 were tampered with on March 24, 2026, with no matching release in the official GitHub repository.
The malware steals SSH keys, cloud credentials, database passwords, and Kubernetes configurations, encrypts them, and exfiltrates them to a third-party server. It also spreads across Kubernetes clusters and installs permanent backdoors. The attack surfaced when the package crashed inside the code editor Cursor. McMahon says the LiteLLM author is "very likely fully compromised." Anyone affected should rotate all credentials immediately. More details are on GitHub.
Nvidia AI Director Jim Fan calls the incident "pure nightmare fuel." He warns that AI agents could be manipulated through infected files: every text file in context becomes an attack vector, and a compromised agent could impersonate the user across all accounts. Instead of relying on sprawling dependency chains, Fan recommends building lean, custom solutions. He also predicts a new industry for "de-vibing" - "the boring old, audited Software 1.0 that watches over the rebellious adolescents of Software 3.0," as he puts it.
Google Deepmind's Gemini 3.1 Flash-Lite can render websites almost in real time. The company published a new pseudo-browser demo: type in a prompt for the page you want, and it gets built live right in front of you. The results aren't consistent, and the content quickly drifts into nonsense, but with tight guardrails, there could be some interesting use cases, like quick UI mockups to visualize ideas. You can test the app for free in Google AI Studio.
According to Google, Gemini 3.1 Flash-Lite reaches its first response token 2.5 times faster than Gemini 2.5 Flash and pushes out over 360 tokens per second. The speed boost comes at a cost, though. The output price has more than tripled, jumping from $0.40 to $1.50 per million tokens. The model has been available in Google AI Studio and Vertex AI since early March. According to Artificial Analysis, it beats larger models like Claude Opus 4.6 on some multimodal tasks.
A North Carolina man has pleaded guilty to defrauding music streaming platforms. Michael Smith generated hundreds of thousands of AI songs and used bots to play them billions of times, pocketing more than eight million dollars in royalties. To pull it off, he created thousands of fake accounts on Spotify, Apple Music, Amazon Music, and YouTube Music, carefully spreading streams across enough songs to stay under the radar.
Smith pleaded guilty to conspiracy to commit wire fraud, according to the US Attorney's Office for the Southern District of New York.
The scheme did double damage. Streaming platforms paid out money for plays that never had a real listener, and since royalties come from a shared pool distributed on a pro rata basis, every fake stream meant less money for actual musicians and songwriters. "Smith's brazen scheme is over, as he stands convicted of a federal crime for his AI-assisted fraud," US Attorney Jay Clayton said.
