Robotic actuators have always forced a choice. You can have strength or sensitivity, power or mobility, but not both in one component. That’s why humanoids still rely on heavy motors, gearboxes, and external sensors stitched together to fake what a single muscle does naturally. Two new papers just hit, and together they look like the closest thing yet to an actual muscle analog for robots. The first, published in PNAS, introduces HARP, a Helical Anisotropically Reinforced Polymer actuator. It solves the mechanics side. Contraction ratios up to 75%, power density of 1.93 kW/kg, 29% energy efficiency. What makes it different is that the design is decoupled, meaning the same framework can be tuned for low-pressure actuation, abrasion resistance, or low hysteresis depending on what you need. That’s a versatile platform, not a one-off. ...

Mira Murati’s Thinking Machines Lab has been quiet since launch, and this is their first real public release. They call it interaction models, and the idea is to design the model around how humans actually collaborate rather than around how long an agent can run alone. Audio, video, text all flowing continuously instead of turn-by-turn. 200ms time-aligned micro-turns, concurrent input and output, a separate background reasoning model for the heavier thinking. ...

Uber’s CTO let something slip at StrictlyVC last week. The plan is to outfit millions of human drivers’ cars with sensors and turn them into a global, always-on data collection grid for autonomous vehicle (AV) companies. They already have partnerships with 25 AV players and call the resulting library an AV cloud, a labelled sensor dataset for training AV models. The framing was generous: “Our goal is not to make money out of this data. We want to democratise it.” Right. Because if there’s one company famous for unprofitable acts of generosity, it’s Uber. ...

Anthropic just announced a new enterprise services company, backed by Blackstone, Hellman & Friedman, Goldman Sachs, and a long list of other private equity heavyweights including General Atlantic, Leonard Green, Apollo, GIC, and Sequoia. The company will staff Applied AI engineers from Anthropic and target mid-sized manufacturers, community banks, and regional health systems. The pitch is simple: small teams working hands-on with customers to find high-impact use cases and ship Claude-powered solutions into existing workflows. ...

Tiago has a great write-up of a Linux kernel exploit, CVE-2026-31431, that I think is one of the most beautiful pieces of security work I’ve read in a long time. It’s a 732-byte Python script that gives an unprivileged local user root access on basically every Linux distribution shipped since 2017. What makes it special isn’t the size, it’s how it works. There’s no buffer overflow, no use-after-free, no memory corruption tricks. The bug is a logic flaw in the kernel’s AF_ALG crypto socket code. The reason this is so elegant is that all the standard kernel defences just don’t apply. Most of them are designed to stop memory corruption attacks. This isn’t one. It’s the kernel doing exactly what it was told to do, with side effects nobody noticed for almost a decade. ...

Amazon just agreed to acquire Globalstar for $11.57 billion. On the surface this is about Project Kuiper, now rebranded Amazon Leo, getting a boost against Starlink. Two dozen extra satellites, an established ground network, direct-to-device tech for future iPhones. But the real prize is something less obvious. Days after the deal was announced, the FCC rejected requests from SpaceX, AST SpaceMobile, Kepler, and Sateliot to access the Big LEO MSS band. The ruling was blunt: spectrum sharing in these bands is impractical. Globalstar and Iridium’s exclusive rights stand. That timing is everything. Amazon now owns one of two companies on Earth with the right to transmit on these specific orbital frequencies, and the regulator just made it clear nobody else is getting in. ...

Mayo Clinic just published a validation study on a model called REDMOD, the Radiomics-based Early Detection Model, that spots pancreatic cancer on routine abdominal CT scans up to three years before clinical diagnosis. On the validation set, the AI caught 73% of cancer cases. Specialist radiologists looking at the same scans caught 39%. The median lead time was about 16 months, with some catches happening 475 days before symptoms. ...

A new bipartisan bill, the American Security Robotics Act, wants to block US government purchases of Chinese ground robots. Humanoids, robot dogs, crawlers. The same tech-sovereignty playbook that already hit drones, semiconductors and security cameras is now being pointed at robotics. Ground robots are already deployed across factories, warehouses and public infrastructure, so this would touch a lot of real systems. I’m honestly neutral on the policy itself. There’s a reasonable national security argument, and there’s an equally reasonable concern that this just slows US adoption while China keeps shipping. What I find more interesting is the supply chain reality underneath it. American robot makers would love to lose Chinese competitors at their market level. But a lot of them still rely on Chinese-made parts to build the robots they ship today. ...

Tesla just tripled its annual capital expenditure to $25 billion in 2026, up from $8.5 billion last year. The money is going into AI infrastructure, chip design, semiconductor research, battery technology, and Optimus robot production. The Fremont factory, which used to make Model S and Model X, is being converted to manufacture Optimus at scale. A dedicated Optimus plant is also being built near Austin. To put the number in context, Musk noted Amazon is spending $200 billion in capex this year and Google $175 billion. The scale gap is real, but the direction is the same. ...

I came across this infographic and spent more time than I expected just reading through it. It’s a good snapshot of how much the anatomy of a server rack has shifted in the last few years. A rack used to be mostly about compute and storage. CPUs on top, drives somewhere in the middle, some networking at the top, and air blowing through the whole thing. The job of the infrastructure was to stay out of the way of the workload. Now the workload is the infrastructure. GPUs are the centre of gravity, and everything else, power distribution, cooling, interconnects, cable management, is designed around keeping them fed and cold enough to run flat out. ...