Good morning! Modern problems require modern solutions, but let’s face it, old school methods are funnier. With AI turning classrooms into cheat code factories, it was only a matter of time before some professor hauled out typewriters and went to war on cognitive surrender. The prof got fed up with students letting AI and translation tools do the writing for them, so she made the whole class do it the hard way. Suddenly, they had to think for themselves and actually talk to each other again. Can’t imagine how traumatic that must have been.
Word of the day: Cognitive surrender (noun) – The art of outsourcing your brain to AI, then feeling smarter for it.
World models have a memory problem. When a robot opens a cabinet or moves a package in a 3D simulation, the model predicts what happens next, then immediately forgets the room just changed. In a new paper called EgoSim, researchers built a first person world model that updates the scene after each action, so every step starts from the new, updated room. That’s huge because robots can’t learn reliable multi-step behaviors if their simulation keeps losing track of what just happened. Until world models can clearly remember how each move changes their environment, calling it “autonomy” is still just remote control with better branding. [full paper]
Anthropic tells OpenClaw the free lunch is over. Claude subscriptions suddenly stopped covering third-party tools this weekend, forcing users to pay metered usage or bring their own API keys just to keep OpenClaw alive. OpenClaw gained a cult following by turning Claude into a local desktop agent that people relied on to run their businesses. Anthropic isn’t specifically targeting OpenClaw, but its users are definitely making the most noise. Reddit exploded with people sharing hacks, from stripping OpenClaw’s fingerprints from prompts to routing requests through alternate models. OpenClaw proved there’s huge demand for local desktop agents, and Anthropic clearly wants to own the space. [Verge]
Leads have questions before they buy. By the time you follow up, half are gone. Chatbase puts an AI sales agent on to qualify, answer questions, and books meetings – without adding headcount.
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AI’s dirtiest secret just spilled all over the floor. Behind every major AI lab sits a little known company called Mercor that builds the proprietary training data their models run on. Now Mercor has been hit by a breach serious enough for Meta and OpenAI to pause work with it. The breach exposed the hidden supplier layer where labs stash the ingredients they guard most closely. The AI race loves acting like it runs on genius alone. In reality, a huge chunk of it still runs through vendors nobody has heard of until one of them blows up. [Wired]
MIT says Silicon Valley is chasing the wrong AI story. In a new paper, researchers tested 41 AI models on over 11,000 workplace tasks. They asked a simple question: How often can AI produce work good enough for a manager to approve and move on? The answer was about 60% of the time. At this rate, that number could reach 90% by 2029. The researchers concluded the real money isn’t in chasing AGI, but in AI’s ability to produce work that’s simply “good enough” for your boss. Amazing how quickly “acceptable” became a billion dollar strategy. [full paper]
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AI coding is turning developers into productivity addicts. At first vibe coding seemed like a cheat code for endless efficiency. Now devs wonder how much their brains can actually handle. Even Andrej Karpathy admits to slipping into “AI psychosis” during marathon coding sessions. Running multiple AI agents at once demands nonstop attention, forcing devs to shift context at breakneck speed. Researchers call the AI induced burnout “brain fry.” Some devs say agentic coding is like gambling, with each successful prompt providing a quick hit of dopamine that keeps them coming back for more. The future of coding has the same reward loop as a slot machine. [Axios]
fun stats
⌚ $10.1 billion. Current valuation of WHOOP, the Boston based health wearable startup after raising $575 million – nearly 3x its 2021 number. Hold on to your fitness data, is it IPO time?
💼 67,000. Number of software engineering job openings in March 2026, a 3 year high. So much for AI killing coding jobs.
🧹 $100 million. How much robotics firms now spend each year on human data to train AI. Gig workers in Nigeria and India are strapping iPhones to their heads just to teach robots how chores should get done.