Lifeboat Foundation

Yuval Noah Harari is one of the world’s most famous public intellectuals, historians and writers. He is probably most famous for his book ‘Sapiens: A Brief History of Humankind’. (Subscribe: https://bit.ly/C4_News_Subscribe)

His most recent book, ‘Sapiens: A Graphic History, Volume 2: The Pillars of Civilization’ has just been published and offers a different way of telling the story of humankind for a younger audience.

Continue reading “Will artificial intelligence create useless class of people? — Yuval Noah Harari” »

On why AI must be able to compose these models dynamically to generate combinatorial representations. Dr. Jonathan Mugan is a principal scientist at DeUmbra and is the author of The Curiosity Cycle.

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MIT researchers developed a technique that reduces the tendency for contrastive learning models to use shortcuts, by forcing the model to focus on features in the data that it hadn’t considered before.

Magnets on the end of a robot arm could help move debris or fix satellites without ever being touched.

Monarch Tractor is leveraging technology more commonly associated with battery-powered Teslas and autonomous Waymo vans for robotic farm tractors.

Meta’s new tactile-sensing skin could allow robots to “feel” in a new way, which will somehow make the metaverse more life-like.

Thanks to this new category of algorithms that has proved its power of mimicking human skills just by learning through examples. Deep learning is a technology representing the next era of machine learning. Algorithms used in machine learning are created by programmers and they hold the responsibility for learning through data. Decisions are made based on such data.

Some of the AI experts say, t here will a shift in AI trends. For instance, the late 1990s and early 2000s saw the rise of machine learning. Neural networks gained its popularity in the early 2010s, and growth in reinforcement came into light recently.

Well, these are just a couple of caveats we’re experienced throughout the past years.

Australian researchers have developed disruptive technology allowing autonomous vehicles to track running pedestrians hidden behind buildings, and cyclists obscured by larger cars, trucks, and buses.

The autonomous vehicle uses game changing technology that allows it to “see” the world around it, including using X-ray style vision that penetrates through to pedestrians in blind spots and to detect cyclists obscured by fast-moving vehicles.

The iMOVE Cooperative Research Centre-funded project collaborating with the University of Sydney’s Australian Centre for Field Robotics and Australian connected vehicle solutions company Cohda Wireless has just released its new findings in a final report following three years of research and development.

The big question that may be on many viewers’ minds is whether the robots are truly navigating the course on their own—making real-time decisions about how high to jump or how far to extend a foot—or if they’re pre-programmed to execute each motion according to a detailed map of the course.

As engineers explain in a second new video and accompanying blog post, it’s a combination of both.

Continue reading “Watch Boston Dynamics’ Atlas Robot Crush a New Parkour Course” »