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Results 321 - 330 of 354 for Model-based design software
  • Article - 13 Nov 2023
    Advanced Navigation is a pioneering Australian company that has been at the forefront of developing AI-driven robotics and navigation solutions for GPS-denied environments across air, land, sea, and...
  • Article - 14 Aug 2023
    As part of an Editorial short series, AZoRobotics takes a look at how the renewable energy sector is harnessing the power of robotic technologies. Here, we take a look at robots in hydropower...
  • Article - 19 Jun 2023
    In this article, we explore how AI is being used to help automate the imaging pipeline.
  • Article - 20 Feb 2023
    The global commercial drone market has seen significant growth in recent years, driven by technological advancements and increased adoption across various industries. Read more about the commercial...
  • Article - 13 Feb 2023
    Agronomy is a branch of agriculture that deals with crop production and soil management. At present, digital technology has enabled the acceleration of agricultural practices, and this approach is...
  • Article - 30 Jan 2023
    Chromatography is an analytical technique used to detect contaminants in food, soil, and water samples. Could AI enhance this technique?
  • Article - 26 Jul 2022
    Introducing robots to industrial processes can create significant advantages for businesses in nearly every sector, and barriers to entry in terms of cost, technical expertise, and long-term servicing...
  • Article - 6 Jul 2022
    Robot interoperability enables synergies between different technologies to materialize over time. In turn, this creates new businesses, business models, and use cases throughout all realms of human...
  • Article - 4 Jul 2022
    AZoRobotics speaks with Alex Zhavoronkov, Ph.D., Founder and CEO of Insilico Medicine, about the company's use of artificial intelligence to identify potential dual-purpose therapeutic targets for...
  • Article - 7 Apr 2022
    Because of the rapid growth of artificial intelligence (AI), a variety of machine learning (ML) approaches may now be applied to elucidate the critical data analysis problem for in situ TEM.

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