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Category: robotics/AI

Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers work more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute.

Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.

The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.

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A team of engineers at the University of California San Diego have built a squid robot that can propel itself through the water untethered, just like the real thing.

“Essentially, we recreated all the key features that squids use for high-speed swimming,” Michael T. Tolley, co-author of the paper published in the journal Bioinspiration and Biomimetics last month.

“This is the first untethered robot that can generate jet pulses for rapid locomotion like the squid and can achieve these jet pulses by changing its body shape, which improves swimming efficiency,” he added.

It moves by sucking in and expelling water behind it — just like the real thing.

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The world’s sea floor is littered with an estimated 14 million tonnes of microplastics, broken down from the masses of rubbish entering the oceans every year, according to Australia’s national science agency.

The quantity of the tiny pollutants was 25 times greater than previous localised studies had shown, the agency said, calling it the first global estimate of sea-floor microplastics.

Researchers at the agency, known as CSIRO, used a robotic submarine to collect samples from sites up to 3,000 metres (9,850 feet) deep, off the South Australian coast.

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From predicting viral load to identifying antiviral drugs, discover some of the AI projects working to fight COVID-19.

What can AI do in the race to contain COVID-19 and potential future pandemics? Discover how machine learning is powering collective pandemic intelligence.

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At 870 degrees Fahrenheit and 90 times Earth’s atmospheric pressure, we’re going to need something a little more robust than your Macbook to run future rovers.

Humanity has sent four rovers to Mars, and worldwide there are four more missions in the works to continue populating the red planet with robotic explorers. Why haven’t we sent a rover to Venus, our other next door planetary neighbor? Because the caustic surface of Venus will incinerate electronics with its 872º F temperatures and seize mechanical components with its immense atmospheric pressures. At 90 times the surface pressure of Earth, the surface of Venus is the equivalent of being almost 3,000 feet underwater.

The Great Galactic Ghoul might devour half the spacecraft we send to Mars, but Venus torched any ghouls living there long ago.

Fortunately, NASA recently took a big step toward achieving the dream of a Venusian rover. As reported by Ars Technica, researchers at the NASA Glenn Research Center built a computer chip that survived Venus-like conditions for an impressive 521 hours, almost 22 days. Even then, the experiment had to end not because the chip was breaking down, but because the Glenn Extreme Environments Rig (GEER) —the chamber that maintains simulated Venus temperatures and pressures—needed to be shut down after running for over three weeks straight.

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Terms such as ‘Artificial Intelligence’ or ‘Neurotechnology’ were new some time not so long ago. We can’t evolve faster than our language does. We think in concepts and evolution itself is a linguistic, code-theoretic process. Do yourself a humongous favor, look over these 33 transhumanist neologisms. Here’s a fairly comprehensive glossary of thirty three newly-introduced concepts and terms from The Syntellect Hypothesis: Five Paradigms of the Mind’s Evolution by Russian-Amer… See More.

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The U.S. #military, like many others around the world, is investing significant time and resources into expanding its electronic #warfare capabilities across the board, for offensive and defensive purposes, in the air, at sea, on land, and even in space. Now, advances in #machinelearning and #artificialintelligence mean that electronic warfare systems, no matter what their specific function, may all benefit from a new underlying concept known as advanced “Cognitive Electronic Warfare,” or #Cognitive EW. The main goal is to be able to increasingly automate and otherwise speed up critical processes, from analyzing electronic intelligence to developing new electronic warfare measures and countermeasures, potentially in real-time and across large swathes of networked platforms.

The holy grail of this concept is electronic warfare systems that can spot new or otherwise unexpected threats and immediately begin adapting to them.

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