Combining Digital Twins with Artificial Intelligence (AI) decision-making technologies can transform agrifood production systems and supply chains – offering possible remedies to the problems of malnutrition, greenhouse gas (GHG) emissions, and food waste, say researchers.
Combining Digital Twins with Artificial Intelligence (AI) decision-making technologies can transform agrifood production systems and supply chains – offering possible remedies to the problems of malnutrition, greenhouse gas (GHG) emissions, and food waste, say researchers.
You've probably heard about the amazing capabilities of some recent AI models, such as GPT, AI21, or BLOOM. Perhaps you use one of these models yourself. Either directly, or through another product like Wordtune, YouWrite, Jasper – or ChatGPT.
It turns out that while these models are trained on language data, they can be used for other applications as well.
In my latest article, you can read more about applications in materials discovery, cybersecurity, and even building management.
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
Explore the rise of intelligent EV hardware and how real-time processing, ML acceleration, and hardware virtualization are enabling safer, smarter, software-defined electric vehicles.
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
Combining Digital Twins with Artificial Intelligence (AI) decision-making technologies can transform agrifood production systems and supply chains – offering possible remedies to the problems of malnutrition, greenhouse gas (GHG) emissions, and food waste, say researchers.
You've probably heard about the amazing capabilities of some recent AI models, such as GPT, AI21, or BLOOM. Perhaps you use one of these models yourself. Either directly, or through another product like Wordtune, YouWrite, Jasper – or ChatGPT.
It turns out that while these models are trained on language data, they can be used for other applications as well.
In my latest article, you can read more about applications in materials discovery, cybersecurity, and even building management.
EPFL researchers have teamed up with Dartfish and the Lausanne Hockey Club to push the boundaries of sports-performance analysis by applying computer vision and machine-learning technology to action on the ice.
The manufacturing industry (largely) welcomed artificial intelligence with open arms. Less of the dull, dirty, and dangerous? Say no more. Planning for mechanical assemblies still requires more than scratching out some sketches, of course — it’s a complex conundrum that means dealing with arbitrary 3D shapes and highly constrained motion required for real-world assemblies.
#10 of our Voice of Innovation fireside chat series: Robotics and AI reporter Rachel Gordon speaks to Daniel Situnayake, a founder, engineer, and teacher, on what it means to run sophisticated machine learning algorithms on small devices at the edge of a network.
Producing chirality, a property found throughout nature, through large-scale self-assembly could lead to applications in sensing, machine perception and more.
Datacation is a startup in a technology area so advanced it can't even be called 'next-generation'. Perhaps 'next next gen' because so far we don't know all the possible business applications of machine learning and AI, nor do we know the limits.
Digital transformation and the Industrial Internet of Things (IIoT) continue to impact industry at all levels. While it's seen its earliest adoption in large-scale manufacturing and transport, it's spreading rapidly into other sectors.
Intelligent Flying Robots is a revolutionary approach to Non-Destructive Testing (NDT) that enables accurate contact-based inspection to fulfill industrial asset inspection standards with many advantages.
Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying.
We all know how AI-based systems can be a real burden to your company’s energy bill and to reaching global climate goals. How about exploring AI’s capabilities to achieve the opposite? By deploying artificial intelligence to reduce your carbon footprint instead of enlarging it