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ETH Zurich’s advanced ANYmal robot can operate with a 198 lbs payload

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.

Meet Barry, a dynamically balancing quadruped robot optimized for high payload capabilities and efficiency, which promises to help humans tackle challenging manual work scenarios. The quadruple’s new leg design ensures that it can “handle unmodeled payloads up to 198 pounds (90 kilograms) while operating at high efficiency,” according to a study by the team.

The rise of AI fake news is creating a ‘misinformation superspreader’

AI is making it easy for anyone to create propaganda outlets, producing content that can be hard to differentiate from real news.


Artificial intelligence is automating the creation of fake news, spurring an explosion of web content mimicking factual articles that instead disseminate false information about elections, wars and natural disasters.

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World’s first human brain-scale neuromorphic supercomputer is coming

ICYMI: DeepSouth uses a #neuromorphiccomputing system which mimics biological processes, using hardware to efficiently emulate large networks of spiking #neurons at 228 trillion #Synaptic operations per second — rivalling the estimated rate of operations in the human brain.


Australian researchers are putting together a supercomputer designed to emulate the world’s most efficient learning machine – a neuromorphic monster capable of the same estimated 228 trillion synaptic operations per second that human brains handle.

As the age of AI dawns upon us, it’s clear that this wild technological leap is one of the most significant in the planet’s history, and will very soon be deeply embedded in every part of our lives. But it all relies on absolutely gargantuan amounts of computing power. Indeed, on current trends, the AI servers NVIDIA sells alone will likely be consuming more energy annually than many small countries. In a world desperately trying to decarbonize, that kind of energy load is a massive drag.

But as often happens, nature has already solved this problem. Our own necktop computers are still the state of the art, capable of learning super quickly from small amounts of messy, noisy data, or processing the equivalent of a billion billion mathematical operations every second – while consuming a paltry 20 watts of energy.

Tesla’s Trillion Dollar Opportunity: AI Robotics and Autonomy

Follow me on X — https://twitter.com/TeslaBoomerMama Thank you so much for watching this video, I do hope you found it enjoyable. If you would like to follow me or my other content on other platforms, you can find me here: X — https://twitter.com/TeslaBoomerMama SubStack — https://alexandramerz.substack.com LinkedIn — https://www.linkedin.com/in/merzalexandra/ Words that make this video searchable: Tesla, Tesla stock, TSLA, Elon Musk, Electric cars, Self-driving cars, Renewable energy, Innovation, Technology, Investing, Finance, Business, Market analysis, Stock market, Stock trading, Price prediction, Analyst recommendations, Short-term outlook, Long-term outlook, Risks, Opportunities, News, Events, Research, Charts, Data, ESG, Alexandra Merz, Tesla Boomer, Tesla Boomer Mama.

Tesla’s Optimus: $30 Trillion Market Potential

Tesla’s potential market size for its humanoid robot, Optimus, presents a massive opportunity worth trillions of dollars, far surpassing the impact of their electric vehicles.

Questions to inspire discussion.

What is the potential market size for Tesla’s humanoid robot, Optimus?
—The potential market size for Optimus presents a massive opportunity worth trillions of dollars, far surpassing the impact of Tesla’s electric vehicles.

A digital twin system that could enhance collaborative human-robot product assembly

The digital twin system created by Zhang, Ji, and their colleagues creates a virtual replica of a scene in which a human and robot agent are collaborating.


Robotics systems have already been introduced in numerous real-world settings, including some industrial and manufacturing facilities. In these facilities, robots can assist human assembly line and warehouse workers, assembling some parts of products with high precision and then handing them to human agents tasked with performing additional actions.

In recent years, roboticists and computer scientists have been trying to develop increasingly advanced systems that could enhance these interactions between robots and humans in industrial settings. Some proposed solutions rely on so-called ‘digital twin’ systems, designed to accurately reproduce a , such as specific products or components that are being manufactured.

Researchers at Nanjing University of Aeronautics and Astronautics in China recently introduced a new digital twin system that could improve the collaboration between human and robotic agents in manufacturing settings. This system, introduced in a paper published in Robotics and Computer-Integrated Manufacturing, can create a virtual map of real-world environments to plan and execute suitable behaviors as they cooperate with humans on a given task.

Google researchers make AI tech solve math puzzles “beyond human knowledge”

Artificial intelligence researchers claim to have made the world’s first genuine scientific discovery using a large language model (LLM), which is behind ChatGPT and similar programs. This signals a major breakthrough.

The discovery was made by Google DeepMind, an AI research laboratory where scientists are investigating whether LLMs can do more than just repackage information learned in training and actually generate new insights.

It turns out that they can, and the implications are potentially huge. DeepMind said in a blog post that its FunSearch, a method to search for new solutions in mathematics and computer science, made “the first discoveries in open problems in mathematical sciences using LLMs.”

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