Lifeboat Foundation

On this episode, learn about digital addiction, and the symptoms of technology addiction with our guest Anna Lembke is a psychiatrist currently working as the Chief of Addiction Medicine at Stanford’s Dual Diagnosis clinic. She was recently interviewed for the Social Dilemma, the amazing Netflix documentary exploring the dangers of social media. On this episode, we really dive deep into the heart of digital addiction—the symptoms of technology addiction, how it starts, how it controls our behavior, and how to escape its magnetic pull. But more specifically, we explore the role of social media and smartphones, and how these tools are hijacking our evolutionary drive for novelty, pleasure, exploration, and connection with other human beings.

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Software developed by Brown researchers can translate expressive and complex plain-worded instructions into behaviors a robot can carry out, all without needing thousands of hours of training data.

When we look out at the Universe, even with Hubble, we’re only seeing the closest, biggest, brightest galaxies. Here’s where the rest are.

The hidden pattern by Ben Goertzel.

Shared with Dropbox.

Dr Gabrielle Lyon is a functional medicine physician and Founder of the Institute of Muscle-Centric Medicine. Most health advice focuses on shedding excess weight. But what if your longevity, healthspan, resilience and quality of life was more determined by gaining muscle than losing fat? This isn’t a bodybuilder’s coping strategy, it’s new science backed by mountains of data. Expect to learn why the quality of your life is a direct correlation to your muscle health, whether it’s more dangerous to be over-fat or under-muscled, whether exercise is more important than nutrition, Gabrielle’s favourite hacks for getting more protein in every day, whether protein timing matters, if it’s possible to achieve this with a plant-based diet and much more…

A team of computer scientists at Google’s DeepMind project in the U.K., working with a colleague from the University of Wisconsin-Madison and another from Université de Lyon, has developed a computer program that combines a pretrained large language model (LLM) with an automated “evaluator” to produce solutions to problems in the form of computer code.

In their paper published in the journal Nature, the group describes their ideas, how they were implemented and the types of output produced by the new system.

Researchers throughout the scientific community have taken note of the things people are doing with LLMs, such as ChatGPT, and it has occurred to many of them that LLMs might be used to help speed up the process of scientific discovery. But they have also noted that for that to happen, a method is required to prevent confabulations, answers that seem reasonable but are wrong—they need output that is verifiable. To address this problem, the team working in the U.K. used what they call an automated evaluator to assess the answers given by an LLM.

RNA polymerase

The key lies in mimicking nature’s machinery. The researchers identified RNA polymerase, a key enzyme that converts DNA into RNA, which is then used to make proteins. They designed two artificial nucleotides that flawlessly mimic the geometry of natural nucleotides. RNA polymerase readily accepted these novel additions when tested, seamlessly incorporating them into transcription.

Barry’s prowess is evident in tests, boasting a maximum payload-to-weight ratio of 2 on flat terrain.

Aiming to solve the challenge of legged robots still being “weak, slow, inefficient, or fragile to take over tasks that involve heavy payloads,” a team of researchers from the Robotic Systems Lab at ETH Zurich has developed a promising proposition.

Continue reading “ETH Zurich’s advanced ANYmal robot can operate with a 198 lbs payload” »