Good morning 👋 Ever dive straight into a new project without reading the instructions only to resurface days later, questioning your life choices? According to a study in Computers in Human Behavior, AI might give you that same false confidence. It’s called the Dunning-Kruger effect: a cognitive bias where the least skilled people vastly overestimate their abilities, while experts underestimate theirs. When you outsource your thinking to AI, it’s even easier to believe you’re a genius.
🎁 Amazon’s AI shopping assistant will generate an extra $10 billion in sales this year. CEO Andy Jassy says 250 million shoppers already rely on its chatbot Rufus to find products faster, and the numbers back him up. Customers using Rufus are 60% more likely to buy something. Amazon didn’t just build a smarter chatbot. It built an AI-powered money machine designed to keep shoppers away from competitors like Google and ChatGPT. If you’re still calling AI a bubble, Amazon’s got $10 billion reasons why you’re wrong.
🔮 Investors are betting $1B on a radical, unproven AI idea. A new startup called Humans& thinks the real money is in building AI that doesn’t replace humans. Instead of automating jobs away, they want to train AI models to understand and collaborate with us. This concept might’ve stayed just a sci-fi dream, but it’s backed by heavy hitters like ex-xAI researcher Eric Zelikman, Googler Georges Harik, and researchers from Meta, Anthropic, OpenAI and DeepMind. Only one small hitch: their new approach needs way more compute than today’s AI. Even in the frothy AI funding scene, some investors think this billion-dollar idea is too wild to work.
📊 Big Tech is hiding billions in AI debt off its balance sheets. Meta just locked in $60 billion to build AI data centers, and half of that won’t show up in their official financials. xAI pulled a similar move, raising $20B to load up on Nvidia chips without taking debt directly. These tech giants are leaning on special purpose vehicles (SPVs), complicated structures infamous for their role in past financial meltdowns. Wall Street expects nearly $800B more of these hidden deals in the next three years. But surely Musk and Zuck are way smarter than Enron’s accountants, right?
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🚚 A new highway in France charges EVs while they drive. Built near Paris, it wirelessly charges electric vehicles in motion with up to 300 kW of power, roughly 2x the amount heavy trucks need to go the distance. This means smaller batteries and less downtime, making eclectic freight transport a practical reality. France wants over 5k miles of electrified roads by 2035, turning its highways into giant power grids and completely reshaping fleet economics. Meanwhile, the US is still burning fossils to keep data centers running.
🗑️ “Disposable apps” are becoming a real thing. Vibe coding is getting so good that now anyone can spin up simple dashboards from CSV files or create custom apps on the fly. They don’t have to scale, just be good enough in the short term. Whether this single-use software approach is genius or garbage depends entirely on your data and security needs. Perfect for a weekend hackathon, maybe less so for your Series A pitch deck.
🔌 Microsoft is sitting on a mountain of AI chips it can’t even plug in. CEO Satya Nadella says their data centers don’t have enough electricity to power the GPUs they’ve purchased. OpenAI piled on, urging the US to add 100 GW of new electricity generation each year just to stay competitive. Wishful thinking only goes so far. Last year alone, China built over 8x more capacity than the US, stacking solar, hydro, and nuclear. America’s only real shot at hitting 100 GW/year may be dusting off those subsidies for solar and wind.
fun stats
of the entire S&P 500 index is made up of big tech’s Magnificent 7 stocks: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla 📈 Last week they reported soaring profits – and growing debt as they continue to pour billions into AI investments.
[WSJ]