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Category: robotics/AI – Page 65

NVIDIA CEO Jensen Huang | Rebuilding Industrial Power: AI Factories & the Return of US Manufacturing

NVIDIA CEO Jensen Huang discusses the concept of AI factories—systems that transform electricity into computational intelligence—and explains how AI represents an industrial revolution that will transform every industry, create new jobs in tech and trades, and enable advanced manufacturing through digital twins and physical AI.

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@jacobhelberg (Jacob Helberg)

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Timestamps:
(0:00) Introduction and Jensen’s opening statement on AI’s impact on jobs.
(0:38) Welcome and initial question about AI factories.
(3:17) Discussion of AI as a paradigm shift in modern computing.
(4:51) Explanation of physical AI and its evolution from perception to reasoning.
(9:46) Analysis of what the US needs to do to win the global AI race.
(13:04) Impact of AI on the workforce and job market.
(17:55) How AI enables reshoring and manufacturing through digital twins.
(22:19) Timeline predictions for AI-enabled robots becoming ubiquitous.
(23:52) Closing

Hyundai bets $21B on Atlas humanoid robots for US car assembly

Hyundai Motor Group is taking a bold step into the future of factory automation with plans to deploy Atlas humanoid robots at its Metaplant America facility in Georgia.

These advanced bipedal robots, developed by Boston Dynamics are designed to perform tasks traditionally carried out by humans.

As per a report on Nikkei Asia, Atlas will automate up to 40 percent of vehicle assembly work at the facility by the end of this year.

Autonomous tractor navigates olive groves with optimized steering modes

A team from the University of Córdoba is developing an autonomous tractor with three different steering modes, allowing it to drive in straight lines, make turns efficiently, and shift modes in response to its trajectories.

One of the possible meanings of the name Sergius is “one who serves,” hence the name of the robotic tractor that can autonomously perform agricultural tasks in fields of woody crops. This one-of-a-kind vehicle, designed by the University of Córdoba, is part of an Agriculture 4.0 context in which agricultural tasks are being automated.

The researchers, with the Rural Mechanization and Technology Group at the University of Córdoba, Sergio Bayano and Rubén Sola, designed the vehicle from the ground up, in collaboration with two companies charged with its mechanical manufacturing and programming. The paper is published in the journal Computers and Electronics in Agriculture.

Near Space Labs nabs $20M to take its high-res imaging Swift robots into the stratosphere

When it comes to creating images of the earth from above, satellites, drones, planes and spacecraft are what tend to come to mind. But a startup called Near Space Labs is taking a very different approach to taking high-resolution photos from up high.

Near Space Labs is building aircraft that are raised by helium balloons and then rely on air currents to stay up, move around to take pictures from the stratosphere, and eventually glide back down to earth. On the back of significant traction with customers using its images, the startup has now raised $20 million to expand its business.

Bold Capital Partners (a VC firm founded by Peter Diamandis of XPRIZE and Singularity University fame), is leading the Series B round. Strategic backer USAA (the U.S. Automobile Association) is also investing alongside Climate Capital, Gaingels, River Park Ventures, and previous backers Crosslink Capital, Third Sphere, Draper Associates, and others that are not being named. Near Space Labs has now raised over $40 million, including a $13 million Series A in 2021.

AI-powered advances unlock copper-zeolite catalysts for combating nitrogen oxide emissions

Increasingly stricter regulations on emissions from lean-burn engines, such as the Euro 7 standard, are approaching. This requires the development of catalytic materials that can reduce the toxic nitrogen oxides efficiently at low temperatures. Researchers at the Department of Physics at Chalmers University of Technology, together with industrial partner Umicore, now present a study showing how machine learning could help engines run cleaner.

Catalytic converters reduce the amount of toxic pollutants emitted into the air from a vehicle’s exhaust system. Stricter regulations on emissions standards within the coming years, such as the European Union’s proposed Euro 7, aim at further reducing air pollution from vehicles. Therefore, improved catalysts are needed to limit the emissions of harmful pollutants.

The main technology of selective catalytic reduction of uses ammonia as a reducing agent. Thus, the catalytic material should promote the formation of a nitrogen–nitrogen bond between nitrogen oxides and ammonia in an oxygen-rich environment and prevent unwanted reactions, which include the oxidation of ammonia to even more nitrogen oxides or nitrous oxide.

How can we optimize solid-state batteries? Try asking AI

Scientists are racing against time to try and create revolutionary, sustainable energy sources (such as solid-state batteries) to combat climate change. However, this race is more like a marathon, as conventional approaches are trial-and-error in nature, typically focusing on testing individual materials and set pathways one by one.

To get us to the finish line faster, researchers at Tohoku University developed a data-driven AI framework that points out potential solid-state electrolyte (SSE) candidates that could be “the one” to create the ideal sustainable energy solution.

This model does not only select optimal candidates, but can also predict how the reaction will occur and why this candidate is a good choice—providing interesting insights into potential mechanisms and giving researchers a huge head start without even stepping foot into the lab.

Researchers use laser-induced graphene to develop next-gen AI-powered electronic nose

Researchers at Korea’s Daegu Gyeongbuk Institute of Science and Technology (DGIST) have developed a porous laser-induced graphene (LIG) sensor array that functions as a “next-generation AI electronic nose” capable of distinguishing scents like the human olfactory system does and analyzing them using artificial intelligence.

This technology converts scent molecules into electrical signals and trains AI models on their unique patterns. It holds great promise for applications in personalized health care, the cosmetics industry, and environmental monitoring.

While conventional electronic noses (e-noses) have already been developed and used in areas such as food safety and gas detection in industrial settings, they struggle to distinguish subtle differences between similar smells or analyze complex scent compositions. For instance, distinguishing among floral perfumes with similar notes or detecting the faint odor of fruit approaching spoilage remains challenging for current systems. This gap has driven demand for next-generation e-nose technologies with greater precision, sensitivity, and adaptability.