TL;DR

Nvidia slams U.S. China chip curbs; $2T US-Gulf AI deals; xAI, OpenAI launch massive GPU projects.

Highlights

• Nvidia CEO Jensen Huang calls U.S. AI chip export controls to China a "failure," citing $15B in lost revenue and a drop in China market share from 95% to 50%; local competitors Huawei and DeepSeek gain ground Nvidia Corp 1.
• Trump administration secures $2T in US-Gulf AI deals, including export of 500,000 Nvidia chips to UAE and 18,000 to Saudi Humain; Gulf states pledge reciprocal investment in U.S. AI infrastructure 2.
• Elon Musk’s xAI to deploy 1 million Nvidia Blackwell GPUs in a $30–$40B supercomputer project; Tesla will continue sourcing Nvidia and AMD chips 3.
• Tesla to launch driverless robotaxi service in Austin by end of June, targeting 1,000 vehicles within months; regulatory scrutiny intensifies 4.
• Google announces AI Mode for Search, Gemini 2.5 upgrades, Gemini Diffusion (5x faster text generation), and 3D Beam calls at I/O 2025; Gemini API now serves 400M+ users monthly 57.
• Apple to open AI models to developers at WWDC 2025, focusing on on-device integration for iOS 19, iPadOS 19, and macOS 16 6.
• Google introduces open-source Gemma 3n (multimodal, local-device AI) and MedGemma (multimodal medical AI) at I/O 2025 8.
• Google and partners (Samsung , Xreal, Warby Parker ) to launch Android XR smart glasses with Gemini AI by early 2026; $150M committed to Warby Parker for AI eyewear 9.
• AMD launches 96-core Threadripper 9000 CPUs and Radeon AI PRO R9700 GPU, claiming up to 4x AI throughput over prior gen; July availability 10.
• FDA to deploy AI-assisted review agency-wide by June 30, appointing a Chief AI Officer; aims to accelerate regulatory review and harmonize AI standards 11.
• Super Micro to expand U.S. server production in Texas and Mississippi; Quanta reports triple-digit AI server growth, with new GB200/GB300 shipments ramping up 12.
• OpenAI, SoftBank, and Oracle launch $500B Stargate AI data center in Texas; Sam Altman highlights progress toward humanoid robots 15.
• Google releases SynthID watermark detector for AI-generated content and Lyria 2 music AI model via API, competing with Suno 13.
• Mistral AI releases Devstral, a 24B-parameter open-source coding model, topping SWE-Bench with a 46.8 score 14.

Commentary

Export controls on AI chips are reshaping global supply chains and competitive dynamics. Nvidia ’s sharp criticism of U.S. restrictions underscores their limited effectiveness: while intended to slow China’s AI progress, they have instead spurred local innovation and cost U.S. firms billions in lost sales 1. The Trump administration’s pivot to country-specific AI export agreements—evidenced by major deals with Gulf states—marks a shift toward managed technology diffusion, with reciprocal investment and security protocols to address concerns about diversion to China 2.

AI infrastructure investment is intensifying. Projects like xAI’s planned 1 million-GPU supercomputer and the $500B OpenAI/SoftBank/Oracle Stargate data center in Texas highlight the scale of demand for compute 315. Server manufacturers such as Super Micro and Quanta are expanding U.S. production to meet this need, while AMD ’s latest Threadripper CPUs and AI GPUs offer new options for enterprise and hyperscale buyers, increasing competition with Nvidia 1012.

On the product front, Google and Apple are accelerating AI integration across consumer and enterprise platforms. Google ’s I/O 2025 announcements—AI-powered Search, Gemini 2.5, Gemini Diffusion, and open-source models—demonstrate a push for both broad adoption and developer engagement 578. Apple ’s move to open its AI models to third-party developers at WWDC signals a focus on on-device intelligence and ecosystem expansion 6. Google ’s partnerships for Android XR smart glasses and new watermarking tools (SynthID) reflect ongoing investment in both hardware and AI transparency 913.

Regulation is also advancing, with the FDA’s agency-wide deployment of AI-assisted review and appointment of a Chief AI Officer 11. This move could streamline regulatory processes and set a precedent for AI adoption in government, but also raises questions around privacy, transparency, and standards harmonization. Industry groups are calling for updated guidance as AI proliferates in sensitive sectors like healthcare.

For AI professionals, key areas to monitor include evolving export policies, hyperscale data center buildouts, hardware supply chain shifts, and regulatory developments—especially as AI adoption accelerates in both consumer and enterprise markets.