After its ambitious Feb. 18 landing on Mars, NASA’s Perseverance Mars rover is already getting critical help from the multiple onboard AI systems that are designed to guide its two-year exploratory mission on the red planet.
Perseverance successfully completed its 293-million-mile voyage from Earth to Mars and landed safely on the Martian surface at 3:55 p.m. EST Thursday.
The International Space Station will soon get a delivery of powerful AI, edge and cloud computing tools from HPE and Microsoft Azure to expand technology experiments aimed at preparing NASA for launching future crewed exploratory missions to Mars. The new equipment and software, including HPE’s specialized, second-generation Spaceborne Computer-2 (SBC-2), will mark the first time that broad AI and edge computing capabilities will be available to researchers on the space station, Tom Keane, Microsoft’s vice president of Azure Global, wrote in a Feb. 11 post on the Azure blog.
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Shell, C3.ai, Microsoft and Baker Hughes are collaborating on an Open AI Energy Initiative (OAI) that aims to grow AI use across the energy and process manufacturing industries. The OAI is envisioned by the partners as an open ecosystem of AI technologies that will provide a framework for energy operators, service providers, equipment providers and the software vendors who serve them to create new AI and physics-based models, monitoring, diagnostics and more to help solve critical industry needs, according to the group.
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Upstart AI vendor Run:AI dove into AI by creating Kubernetes-based software to help customers get more production out of their existing AI infrastructure investments. Run:AI’s software is an orchestration and virtualization layer that pools together compute resources so they can be instantly allocated on demand as needed.
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Nvidia today launched a certified systems program in which participating vendors can offer Nvidia-certified servers with up to eight A100 GPUs. Separate support contracts directly from Nvidia for the certified systems are also available. Besides the obvious marketing motives, Nvidia says the pre-tested systems and contract support should boost confidence and ease deployment for those taking the AI plunge. Nvidia-certified systems would be able to run Nvidia’s NGC catalog of AI workflows and tools.
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DeepMind requires deep pockets. Reports surfaced this week that the London-based AI lab acquired in 2014 by Google parent Alphabet for about $600 million lost a staggering $649 million in the last year. The Financial Times and other media outlets also reported Thursday (Dec. 17) that Alphabet (NASDAQ: GOOGL) has written off roughly $1.5 billion in debt associated with loan and interest repayments due from DeepMind.
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Finding ways to bring AI more deeply into the business worlds of fintech, technology and academia is the mission of the new National Council for Artificial Intelligence (NCAI).
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