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The generative adversarial relationship between generators and discriminators makes it possible for the AI to combine the CT and MRI images quickly and accurately, removing artefacts while retaining as much visual information as possible.
5G, which uses mm-waves, has beam-based cell coverage, while 4G has a sector-based range. A machine-learned algorithm can help the 5G cell site figure out a list of possible beams from either the serving cell site or the cell site next to it.
Machine learning could be a useful tool for making food safer. New research from UC Davis shows that a method that uses AI and optical imaging can quickly and accurately find bacteria in food. It could be a good way to stop outbreaks and illnesses spread through food.
Several key components must be considered when adding AI to a drone. To begin with, a powerful onboard computer is needed to process the massive amount of data collected by the drone's sensors. This computer should have enough computational power to run AI algorithms efficiently.
AI technologies can balance the needs of charging electric vehicles with the capabilities of the grid, keeping them from being overloaded during peak times. Vehicle-to-grid (V2G) technology, made possible by AI, lets EVs send extra energy back into the grid. It helps keep the grid stable and gives EV owners ways to make money.
Hackers are using AI to strengthen malware and attacks to circumvent cybersecurity advances. For example, thieves use AI to hide harmful code in apps that are supposed to be safe.
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