Lifeboat Foundation

Does the advent of machine learning mean the classic methodology of hypothesise, predict and test has had its day?

Suspended beneath a thick canopy of trees, the sloth inches along with slow strides. Painfully slow. Intentionally slow. Crawling high up among the branches, traipsing along a 100-foot steel cable, the little creature is like a lethargic acrobat. But its goal is not to delight or to put on a show; in fact, just the opposite. This sloth is all about stealth, observation, and collecting as much sunlight as possible.

After all, this is a solar-powered robot.

Parkour is not for the weak-hearted. Luckily, the two latest freerunning champs don’t have a heart at all because, you know, they’re robots.

In a YouTube video released Tuesday, Boston Dynamics—the Waltham, Massachusetts-based robotics company known for its viral clips of machines performing surprisingly human activities—shows off two humanoid robots (both named Atlas) performing the leaps, bounds, and backflips required to complete a parkour course.

Continue reading “These Boston Dynamics Robots Perform Parkour Maneuvers to Push Their Limits” »

At CES 2022, Hyundai reveals its vision for the future, which merges the metaverse with physical robotics.

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Japanese are increasingly turning to “social robots”, John Deere’s latest self-driving tractor will enable autonomous farming, a new South Australian craft beer has been designed entirely by AI.

Adding to its space program’s growing list of achievements.

China’s space program (CNSA) is the first to detect water signals directly from the Moon’s surface thanks to its Chang’e-5 lunar probe, a report from CGTN reveals.

The new breakthrough provides yet another important milestone for the CNSA, which is ambitiously closing the gap between itself and the world’s two historic space superpowers, the U.S. and Russia.

Continue reading “China Detected Water From the Moon’s Surface for the First Time” »

We are currently witnessing an explosion of network traffic. Numerous emerging services and applications, such as cloud services, video streaming platforms and the Internet of Things (IOT), are further increasing the demand for high-capacity communications. Optical communication systems, technologies that transfer information optically using fibers, are the backbone of today’s communication networks of fixed-line, wireless infrastructure and data centers.

Over the past decade, the growth of the internet was enabled by a technique known as digital signal processing (DSP), which can help to reduce transmission distortions. However, DSP is currently implemented using CMOS integrated circuits (ICs), thus it relies heavily on Moore’s Law, which has approached its limits in terms of power dissipation, density and feasible engineering solutions.

As a result, distortions caused by a phenomenon known as fiber nonlinearity cannot be compensated by DSP, as this would require too much computation power and resources. Fiber nonlinearities remain the major limiting effect on long-distance transmission systems.

Areas like deep learning and large language models are set to be high on the AI research agenda this year.

This article was contributed by Valerias Bangert, strategy and innovation consultant, founder of three media outlets, and published author.

AI job automation: The debate

The debate around whether AI will automate jobs away is heating up. AI critics claim that these statistical models lack the creativity and intuition of human workers and that they are thus doomed to specific, repetitive tasks. However, this pessimism fundamentally underestimates the power of AI. While AI job automation has already replaced around 400,000 factory jobs in the U.S. from 1990 to 2007, with another 2 million on the way, AI today is automating the economy in a much more subtle way.