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Category: robotics/AI – Page 1353

Kinova, a Canadian company that specializes in robotic arms, is launching Link 6, a new generation industrial robot designed for all businesses looking to benefit from automation.

The Link 6 collaborative robot features automation solutions that enable greater daily efficiency while improving the quality and consistency of production results. Kinova’s newest robot helps you start producing faster thanks to a rich interface on its wrist, feed-through of power and data, optional Gigabit Ethernet adapter, and optional wrist vision module.

The company says its Link 6 controller provides the highest processing power and memory capacity on the market, making it ready to use with the AI solutions of the future while keeping the size of the controller compact. Link 6 robotic arm is developed and designed with any user in mind: an experienced industrial integrator and an operator with no particular robotic skills.

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Translator, a Microsoft Azure Cognitive Service, is adopting Z-code Mixture of Experts models, a breakthrough AI technology that significantly improves the quality of production translation models. As a component of Microsoft’s larger XYZ-code initiative to combine AI models for text, vision, audio, and language, Z-code supports the creation of AI systems that can speak, see, hear, and understand. This effort is a part of Azure AI and Project Turing, focusing on building multilingual, large-scale language models that support various production teams. Translator is using NVIDIA GPUs and Triton Inference Server to deploy and scale these models efficiently for high-performance inference. Translator is the first machine translation provider to introduce this technology live for customers.

Z-code MoE boosts efficiency and quality

Z-code models utilize a new architecture called Mixture of Experts (MoE), where different parts of the models can learn different tasks. The models learn to translate between multiple languages at the same time. The Z-code MoE model utilizes more parameters while dynamically selecting which parameters to use for a given input. This enables the model to specialize a subset of the parameters (experts) during training. At runtime, the model uses the relevant experts for the task, which is more computationally efficient than utilizing all model’s parameters.

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Black holes with masses equivalent to millions of suns do put a brake on the birth of new stars, say astronomers. Using machine learning and three state-of-the-art simulations to back up results from a large sky survey, researchers from the University of Cambridge have resolved a 20-year long debate on the formation of stars.

Star formation in galaxies has long been a focal point of astronomy research. Decades of successful observations and theoretical modeling resulted in our good understanding of how gas collapses to form new stars both in and beyond our own Milky Way. However, thanks to all-sky observing programs like the Sloan Digital Sky Survey (SDSS), astronomers realized that not all galaxies in the local Universe are actively star-forming—there exists an abundant population of “quiescent” objects which form stars at significantly lower rates.

The question of what stops star formation in galaxies remains the biggest unknown in our understanding of galaxy evolution, debated over the past 20 years. Joanna Piotrowska and her team at the Kavli Institute for Cosmology set up an experiment to find out what might be responsible.

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The six-foot drone is made by by ZALA Aero, a subsidiary of famed Russian arms manufacturer Kalashnikov. After being fired from a portable launcher the KUB-BLA can loiter over a target area for up to half an hour, flying at speeds of around 80mph.

Once it has recognised a suitable target it deliberately crashes into it, detonating its seven-pound high explosive payload.

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There are about 6,500–7,000 languages currently spoken in the world. But that’s less than a quarter of all the languages people spoke over the course of human history. That total number is around 31,000 languages, according to some linguistic estimates. Every time a language is lost, so goes that way of thinking, of relating to the world. The relationships, the poetry of life uniquely described through that language are lost too. But what if you could figure out how to read the dead languages? Researchers from MIT and Google Brain created an AI-based system that can accomplish just that.

While languages change, many of the symbols and how the words and characters are distributed stay relatively constant over time. Because of that, you could attempt to decode a long-lost language if you understood its relationship to a known progenitor language. This insight is what allowed the team which included Jiaming Luo and Regina Barzilay from MIT and Yuan Cao from Google’s AI lab to use machine learning to decipher the early Greek language Linear B (from 1,400 BC) and a cuneiform Ugaritic (early Hebrew) language that’s also over 3,000 years old.

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Mikhail Kokorich is the founder of Destinus. This serial entrepreneur has been dubbed Russia’s Elon Musk by his public relations team. The Russian businessman says his business, Destinus, is developing a hydrogen-powered, zero-emissions transcontinental delivery drone that can travel at speeds up to Mach 15.

Destinus plans to combine the technological advancements from a spaceplane with the ordinary and straightforward physics from a glider to create a hyperplane that will meet the many demands of a hyper-connected world.

This hyperplane will use clean hydrogen fuel to transport cargo between Europe and Australia in mere hours. The hyperplane will be fully autonomous; it will take off from ordinary runways, traveling leisurely to the coast before accelerating to supersonic speeds.

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Elon Musk signaled plans to scale Tesla to the “extreme” while teasing the release of Tesla’s “Master Plan Part 3” on Twitter one day before opening the automaker’s first European factory.

On Monday, Musk revealed on Twitter the themes that will dominate the next installment in Tesla’s long-term playbook: artificial intelligence and scaling the automaker’s operations.

“Main Tesla subjects will be scaling to extreme size, which is needed to shift humanity away from fossil fuels, and AI,” Musk tweeted. “But I will also include sections about SpaceX, Tesla and The Boring Company.”

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