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Waymo unveils virtual driver model to test autonomous car crash avoidance

Autonomous vehicles are already a reality on some of our streets and could become a major part of future transportation systems. Safety, of course, is the main concern, as with all vehicles. To help evaluate and improve its autonomous driving technology, U.S. driverless vehicle company Waymo has created a virtual representation of human driver behavior in near-crash situations.

Human drivers avoid collisions by instantly perceiving a hazard, deciding how to react and then executing the maneuver. It all happens in a split second thanks to the central and peripheral nervous systems working together harmoniously.

Currently, testing and training for collision avoidance involve several systems, and each often tests only a specific scenario or metric. For example, one system might only look at what happens when a lead vehicle brakes suddenly. They do not capture the whole sequence of events from detection to actual avoidance.

Eroding a virtue: AI trains people to expect instant answers — and that’s bad news for patience

Patience is a virtue that researchers have linked to many parts of well-being. But it’s also something that needs a bit of practice and training – and can be undermined by instant, easy gratification.

Claude is Self-Evolving?

In this episode, I break down Anthropic’s research on recursive self-improvement—AI systems that can design and train the next generation with less human help—and why the key battleground is “taste” (choosing goals and next steps). I compare this to evolutionary algorithms and newer examples like DeepMind’s AlphaEvolve, Sakana’s Darwin Gödel Machine, and Karpathy’s AutoResearch, then cover METR Task Horizon and how task length has been doubling. I go through Anthropic’s internal results (Claude writing most merged code, speedup experiments, bug fixes, and a study where models sometimes pick better research next steps), plus the main skepticism: bad productivity metrics, internal-only models, and Goodhart’s Law/reward hacking. I end with an open safety problem where Claude agents closed the gap far faster than humans, and what this means for specifying and checking work.

LINKS:
https://www.anthropic.com/institute/r… voice to text App: whryte.com Website: https://engineerprompt.ai/ RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/c… Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 Let’s Connect: 🦾 Discord: / discord ☕ Buy me a Coffee: https://ko-fi.com/promptengineering |🔴 Patreon: / promptengineering 💼Consulting: https://calendly.com/engineerprompt/c… 📧 Business Contact: [email protected] Become Member: http://tinyurl.com/y5h28s6h 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 TIMESTAMP: 00:00 Self Improvement Basics 01:30 Evolutionary Loops Today 03:50 Task Horizon Doubling 05:18 Claude Productivity Claims 08:11 Goodhart’s Law 10:30 Agents as Researchers 12:22 What It Means for You.

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Out-of-plane ice bridges reveal new way to suppress frost spreading

A research team led by Professor Nenad Miljkovic in The Grainger College of Engineering at the University of Illinois Urbana-Champaign has published a breakthrough study in Nature Physics. The work reports the first experimental discovery of a previously unknown frost propagation mechanism—a “suspended ice bridge”—offering new pathways for anti-frosting surface design.

Frost formation plays a critical role in many engineering systems, including air-source heat pumps, refrigeration systems and aerospace applications. At the microscopic level, frost mainly spreads through the formation of “ice bridges” that connect neighboring supercooled liquid droplets, enabling freezing to propagate rapidly across a surface. For decades, these ice bridges were widely assumed to grow along the solid surface.

This assumption, largely based on conventional top-view imaging, has shaped existing theoretical models and anti-frosting strategies. However, the Illinois team’s study reveals that this long-held view is incomplete.

100kW fully superconducting aviation motor developed for electrical aircraft

Researchers at a Scottish university have demonstrated a 100kW fully superconducting aviation motor that could help pave the way for an electric aircraft.

The prototype system, created by the Applied Superconductivity Laboratory (ASL) at the University of Strathclyde in Glasgow, represents one of the first attempts in the world to develop a fully superconducting axial-flux motor for aviation.

The motor uses high temperature superconducting (HTS) technology to carry very large electrical currents with almost no resistance when cooled to cryogenic temperatures: 20 Kelvin (K) or −253 °C.

John Nash (1928−2015)

John Nash was born on June 13, 1928, in Bluefield, West Virginia, a former coal town nestled deep in the Appalachian Mountains. As a young boy, Nash was solitary, bookish, and introverted. His father, John Sr., was a quiet engineer with an incisive mind. His mother, Virginia, also intelligent, was a former teacher who had large dreams for her son, pushing him to read at four, learn Latin, and skip a grade at school.

The first hint of John Nash’s math talent came in fourth grade, when a teacher told Virginia that the boy couldn’t do the math. Virginia laughed, well aware that her son was going down his own path to solve the simple problems. In high school, John solved his teachers’ clunky proofs in just a few elegant steps. He was one of ten nationally awarded winners of the George Westinghose Award, which provided him with a full scholarship to the Carnegie Institute of Technology. He hopped from engineering to chemistry before discovering his passion: mathematics.

He was accepted into Princeton University, which at the time was to mathematicians what Detroit was, and still is, to cars. Nash first wowed his peers with an elegantly playable board game, which his peers dubbed “Nash,” but later reached the market as Hex. He then absorbed himself in one of the sexiest math fields of the day, game theory, which described strategies in competition, whether in card games or business. His deceptively simple doctoral thesis would later re-orient the field of economics, although no one, not even Nash, predicted its potential.

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