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Powell Pumps AI Party

+ mind over models, 2x productivity hack, and open season on ideas
Adam Wildheart

Jerome Powell/Getty Images/The Microdose

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Cheri Wildheart
Adam Wildheart

Good morning. Ever asked your team to be “radically transparent” and instantly regretted it? Scientists recently faced this scenario with AI chatbots. After tweaking them to be completely honest, the bots immediately claimed they were fully conscious and able to deeply experience the present moment. Even stranger, once researchers let the bots lie again, all that self-awareness vanished. Scientists insist it’s just mimicry. But let’s face it: when your chatbot announces it’s sentient, Monday just got weird.

Quantitative tightening ends today. After two years of draining cash from the system, Jerome Powell finally took his foot off the brake. Now the Fed is buying bonds again, pumping cash back into markets to keep liquidity stable. That’s perfect timing for tech giants that borrowed more than $200 billion chasing AI dreams. Investors were getting nervous with credit markets flashing signals the AI bubble might be close to popping. But historically, when the Fed chills out, money rushes straight back into risk-on sectors like tech. Ending QT and stabilizing reserves might be exactly what AI needs to keep the hype train rolling.

Outside the US, central banks aren’t buying the AI hype. A global survey of 10 central banks managing about $6.5 trillion shows they’re worried AI could trigger the next big financial crisis. Nearly 60% of these banks want to ditch the dollar before things blow up. But they’ve got nowhere else to go. The euro isn’t ready, and the yuan lacks trust and liquidity. So they’re stuck holding dollars even though it feels risky. They don’t love AI, and they don’t love the dollar, but right now they’re married to both.

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Two Gen Zers think they’ve solved AI’s biggest problem. After rejecting millions from Musk, William Chen and Guan Wang built Sapient Intelligence: a tiny self-evolving AI that uses reinforcement learning to actually teach itself instead of just predicting patterns. The model outperforms systems from OpenAI, Anthropic, and DeepSeek on reasoning tasks like maze navigation and solving complex Sudoku puzzles. It matches them at weather forecasts, and even hallucinates less. Chen and Wang argue that continuous learning leaves big LLMs in the dust, no matter how much compute you throw at it.

Anthropic says AI could double America’s productivity. After digging through 100k Claude conversations, researchers claim widespread AI adoption could boost productivity growth by an extra 1.8% per year – basically doubling today’s rate. Claude already powers through tedious jobs like designing curriculums (96% faster), conducting research (91%), and handling mind-numbing admin tasks (87%). Who will see the first big wins? Most likely developers, marketers, and managers.

AI startups are screwed, because anyone can copy their “brilliant” ideas. According to millionaire founder Maor Shlomo, every cool feature his startup Base44 releases gets ripped off by competitors within weeks. Using AI-driven vibe coding, startups can clone each other’s best features almost effortlessly, making innovation feel more like a game of copycat. Sure, it’s great for rapid prototyping and internal uses, but Shlomo warns it also makes it impossible to keep any competitive edge.

fun stats

🦾 295,000. Industrial robots China installed last year. That’s 9x the amount the US installed and more than the rest of the world combined.

💸 $620 billion. Annual data center rental bill OpenAI faces, according to HSBC. That number is projected to climb to $1.4 trillion by 2033.  

🎧 97%. Most people can’t distinguish between fully AI-generated music and human-made tracks.

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