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Happy Thursday! There’s an old joke on Wall Street: if Warren Buffett buys something, thousands of investors spend the next week trying to figure out what he knows that they don’t. That’s exactly the reaction to his reported $10 billion bet on Google’s AI expansion.

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Warren Buffett doesn't do big tech, except when he does. Berkshire Hathaway is anchoring Alphabet's record $80 billion equity raise with a $10 billion stock purchase, a rare departure for the Oracle of Omaha. Alphabet says demand for its AI solutions is literally exceeding available supply, forcing even a $400 billion revenue company to tap markets for more capital. The raise pressures Microsoft, Amazon, and Meta to match this spending intensity or risk falling behind in the infrastructure arms race (read more).

Dell, Nokia, Lenovo, and Intel have added roughly $1.7 trillion in market value by pivoting to AI infrastructure, proving that installed base and manufacturing scale matter more than narrative freshness when capital expenditure cycles accelerate. Oracle provides the template: mocked for cloud irrelevance for years, it transformed into an AI heavyweight by owning the database layer where enterprise workloads live. The investment logic is brutal and simple, AI infrastructure spending is projected to exceed $500 billion annually by 2027, and legacy vendors already own the factories, supply chains, and customer contracts that AI-native companies must build from scratch (read more).

Anthropic shipped Claude Opus 4.8 just 41 days after its predecessor, a compressed timeline that signals pressure to keep pace with OpenAI and Google. The model emphasizes "honesty," flagging uncertainties rather than manufacturing confident-sounding wrong answers, a response to a March leak revealing 29% false claim rates in early internal builds. The same day, Anthropic closed $65 billion at a $965 billion valuation, eclipsing OpenAI's reported worth and suggesting a pre-IPO positioning. Whether "transparency marketing" matches verifiable performance is now the billion-dollar question for a company valued near $1 trillion on trust alone (see the announcement).

🛠️ THIS WEEK’S AI COMBO: 1 PROMPT + 1 TOOL

⚡️ MIND SPARK

🫧 "Don't Sell Yet” says Ray Dalio: The Bridgewater founder says the AI bubble is 80% formed, but exiting now means missing the final lucrative ascent. He pegs the actual pop to Federal Reserve tightening, not mere overvaluation, meaning monetary policy matters more than any technology metric (read more).

🚀 SpaceX's $1.75 Trillion IPO Breaks Wall Street's Calculator: SpaceX filed for the largest IPO in history, and the financial infrastructure literally couldn't handle it. Index providers are scrambling to reorganize systems designed for smaller debuts. Elon Musk would become the world's first trillionaire at the targeted valuation (read more).

🦾 NVIDIA Expands Its Robotics Push: NVIDIA released new open-source AI models and tools for robotics, with more than 30 partners, including Boston Dynamics, ABB, and FANUC. NVIDIA’s strategy remains clear: build the software ecosystem, then benefit as demand for its hardware grows, putting more pressure on rivals like Intel and AMD (see press release).

🏛️ Trump Scales Back AI Rules: After industry opposition and internal debate, President Donald Trump signed a narrower AI executive order focused on voluntary federal reviews of the most advanced AI models. The order limits state-level AI regulation but includes no formal enforcement, instead relying on incentives such as government contract preferences.

💥 Blue Origin’s New Glenn Explodes During Test: Jeff Bezos’ Blue Origin lost a New Glenn rocket during a pre-launch static fire test, marking another setback after recent technical problems. The failure increases scrutiny of the company’s launch program and highlights the lead held by SpaceX in the commercial space race.

🤖 Gemini Spark Shows AI’s Social Blind Spot: Google’s new Gemini Spark assistant can manage tasks across email, calendars, and documents, but an early test revealed how AI can miss important personal context despite having access to relevant information. The episode highlights the limits of today’s AI agents as they take on more real-world responsibilities.

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