👋 Good morning! The AI story this week isn’t about clever chatbots — it’s about scale, infrastructure, and the real-world systems that will either enable or choke the next phase of growth. OpenAI is lobbying Washington to treat AI data centers like semiconductor fabs, arguing that chips mean little without the power, metals, and logistics to keep them running. Investors like Michael Burry are betting that the hype can’t outrun fundamentals forever. And while Google and Baidu race to embed smarter, multimodal systems everywhere, the real question is shifting from what AI can do to what the world needs to support it.
🧑⚖️Infrastructure and Lawsuits at OpenAI: Growth Meets Growing Pains
OpenAI has put forward a detailed pitch to the U.S. government, asking that the tax credit from the Chips Act, specifically the Advanced Manufacturing Investment Credit (AMIC), currently geared toward semiconductor fabrication, be expanded to also cover AI data centers, AI servers and the associated power-grid infrastructure.
In a letter addressed to the White House’s science and technology policy office, OpenAI argues that “broadening coverage of the AMIC will lower the effective cost of capital, de-risk early investment, and unlock private capital to help alleviate bottlenecks and accelerate the AI build in the US.”
They’re also asking for faster permitting and environmental review of the infrastructure, along with a strategic reserve of raw materials like copper, aluminum and rare earths—components essential for AI infrastructure at scale.
Taken together, this makes one thing clear: the next frontier in AI isn’t just smarter models-it’s the hardware, power and logistics that make those models practical to deploy and scale.
At the same time OpenAI faces new scrutiny, seven families have filed lawsuits accusing ChatGPT of contributing to mental health crises, reviving questions about safety, accountability, and how AI tools are used in emotionally sensitive contexts.
📈Trendlines: The Big Short 2.0? Michael Burry’s $1B Move Against AI giants
Michael Burry - the investor behind The Big Short - is once again going against the tide. His fund, Scion Asset Management, has reportedly placed over $1 billion in put options against two of the biggest names in the AI rally: Nvidia and Palantir.
Both companies have seen explosive growth this year, with Nvidia’s market cap touching $5 trillion and Palantir’s stock up more than 170%. Yet, Burry seems unconvinced. His bearish move suggests he believes valuations are detached from fundamentals, a possible sign that we’re entering bubble territory in AI.
He’s not alone in his caution. Bridgewater founder Ray Dalio recently warned that market gains are overly concentrated in a handful of AI-driven giants, calling current conditions “bubble-like.”
Whether Burry’s contrarian play pays off or not, it’s a reminder that even in a tech revolution, hype often runs ahead of reality, and smart money knows when to step back.
🔨AI Tools and updates: Gemini is entering your livingroom and Baidu outperformes GPT-5 and Gemini
Google is threading AI deeper into daily life. Gemini is now built into the Google TV Streamer, turning entertainment devices into conversational, adaptive systems. The company also unveiled Private AI Compute, a privacy-preserving framework that lets devices use the cloud’s power without sharing raw user data. And if you’re on iPhone, Google Photos can now edit your pictures just by describing the change you want (“make the sky bluer,” “remove the crowd”).
Together, these updates paint a clear picture: AI tools are spreading into every layer of digital life, consumer tech, enterprise systems, and national infrastructure. The frontier isn’t just smarter models anymore, it’s smarter deployment, smarter policy, and smarter guardrails.
Meanwhile, Baidu has entered the race with ERNIE-4.5-VL-28B-A3B-Thinking-an open-source multimodal model the company claims outperforms GPT-5 and Google’s Gemini across image, video, and text understanding. Whether that claim holds up remains to be seen, but it reinforces a clear trend: multimodal systems are becoming the new standard for enterprise AI, and open-source challengers are no longer trailing far behind.
💡Quick Hits and numbers
In less than three years 1.2 billion people have used AI tools - This makes the adoption rate greater than the internett and the personal computer.
88 % of employees say they use AI at work (mostly basic tools), yet only 5 % believe they’re maximising its potential for transformation.
23 % of organisations say they are scaling agentic‑AI across business functions, and 39 % say they’ve begun experimenting with it.
🧩Closing thought
AI’s next breakthroughs won’t come from model upgrades alone — they’ll come from who builds, funds, and governs the infrastructure beneath them. Policy, power grids, and investor discipline will shape the next chapter as much as algorithms do. For founders, operators, and investors alike, the edge will belong to those who see beyond the software, to the systems, supply chains, and incentives that make the software possible.