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This has quietly been a miracle month in medicine. In the last 5 weeks we’ve got news on: - retatrutide, the triple agonist GLP-1 from Lilly, basically melting fat and body-wide inflammation at record levels - RevMed’s new pancreatic cancer drug showing unprecedented abilities to extend life - small trial of a one-and-done PCSK9 gene editing therapy for slashing LDL cholesterol - Mayo’s AI-assisted radiology showing vastly improved cancer detection - this new therapy for metastatic solid tumors This stuff is at varying levels of evidence. Retatrutide is ~100% on its way, other stuff needs more clinical trial data. But put it together and we’re maybe on the verge of majorly reducing the mortality of heart disease and cancer, the two leading causes of death in America.

A drone flying with no battery tether sounds impossible until you see it. GuRu wirelessly transmitted power through the air to directly run an untethered drone from 30 feet away and has kept one flying for 96 hours straight. Power beaming is moving out of science fiction fast.

Just a reminder: Elon Musk made the starship more pointy because of the movie "The Dictator" 🤣

BREAKTHROUGH: Colossal scientists hatched healthy chicks from artificial eggs. No shells. No hens. Just bioengineered eggs that breathe like the real thing. This could help bring back giant extinct birds like the South Island giant moa, whose eggs were ~80x a chicken’s. (1/10)

Apple accidentally left Claude.md files in today's Apple Support app update (v5.13)

Your brain has a circuit that doesn't know you live in a city. Its only job is to monitor whether birds are still singing. Right now, in this room, it is on. The circuit predates primates. Mammals have been using ambient soundscape continuity as a predator-detection system for roughly 200 million years. Birds stop singing when something larger moves through their territory. For most of mammalian history, a forest full of song meant no large predator was nearby, and the cessation of sound was the warning. Your nervous system never updated this software. The Max Planck Institute tested the inverse in 2022 with 295 participants. Six minutes of birdsong dropped anxiety with a medium effect size. Six minutes of traffic noise raised depression with the same. The effect worked on subjects who lived in dense urban environments and had no regular contact with nature. The brain still ran the check. Birdsong sits in the 1,000 to 8,000 Hz range. Your brainstem reads continuous patterns in that band as a signal that nothing dangerous is currently moving through the environment. EEG data shows birdsong at 45 to 50 decibels boosts alpha wave activity by 14.1% relative to silence. Alpha is the brainwave signature of relaxed alertness. Push the same birdsong above 60 decibels and the response flips. Stress markers rise 29%. The circuit only trusts the signal at the volume of quiet conversation, which is exactly the volume birds sing at from a typical distance. Three things happen simultaneously when the brain registers ambient safety. The amygdala downregulates. The parasympathetic nervous system takes over from the sympathetic. Heart rate variability rises, cortisol drops. The posterior cingulate cortex, which sits at the center of the rumination circuit, quiets down. King's College London tracked this through a smartphone study with over 1,200 participants and found the mood lift lasted hours after the sound stopped. People diagnosed with depression got the same response as healthy controls. Most of what gets labeled mental fatigue is hypervigilance running in the background. Birdsong tells the circuit it can stand down, and the brain reallocates the freed compute everywhere else. A quiet park feels different from a quiet office because the parks have sentinels.

This is AWESOME... Some guy just sequenced his entire DNA genome on his kitchen table 🧬🧪 It tells his cancer risk, drug responses, what his kids will inherit, and which diseases are coming decades before the symptoms. Your genome is a 3.2 billion letter source code that predicts more about your health than any other test in existence. Almost no one has ever read their own. This used to require a hospital, a specialist, and a referral that most doctors won't write. The raw data would sit in a medical record you'd never see. Until now. Here's how he did it: → Rubbed a cheek swab against the inside of his mouth for 60 seconds → Extracted the DNA from his cells using a $150 kit → Prepped the DNA for sequencing with enzymes that attach a motor protein to each strand → Loaded the sample onto a nanopore device the size of a highlighter, plugged into a MacBook The device works by pulling single strands of DNA through holes one atom wide. As each letter passes through, it changes the electrical resistance in a tiny but measurable way. A neural network listens to the signal and reconstructs the sequence. 48 hours later, he had his full genome on his hard drive. The data never touched a server. No spit kit in the mail. No company owning his most sensitive biological information. No risk of the whole thing getting auctioned off in a bankruptcy, which is exactly what happened to 23andMe's 15 million customers earlier this year. AI is unlocking personal health in a way that has been impossible. We're still so early.

Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License.

AI is making CEOs delusional