One Tech (Dallas, TX) has ported its edge AI unsupervised training technology to microcontrollers to boost analysis in the Internet of Things. MicroAI Atom is designed to be embedded on microcontroller units (MCUs) and can now train and run AI models directly at the endpoint. This enables silicon manufacturers, original equipment manufacturers (OEMs), smart device manufacturers and smart device owners to reduce the costs of bringing intelligence to the edge and endpoint by at least 80 percent. Enabling unsupervised training on a microcontroller at the nertwork edge allows functions such as predictive maintenance that were previously only available on microprocessors. This differs from the AI accelerators on microcontrollers that run an inference engine that has already been trained. "This is a groundbreaking phase for the industry.

Handing off product packaging to an automated system is a relief, but returning from a meeting to find a treadmill on the fritz and product sitting still -- all while customers call in, clamoring for their shipments -- is not. That's the kind of problem with which businesses are wrestling as they find ways to pass off their repetitive tasks or "chores" to machines, allowing the humans to focus instead on the more nuanced responsibilities. When implementing time-saving machines, what's a business to do to ensure equipment failure doesn't turn automation into only frustration? Intelligence of Things Tracker charts the latest news on how companies are increasingly turning to IoT to predict when and how their equipment is going to break -- and to let them swoop in to the rescue before that expensive oil drill or package sorting machine stutters to a halt, snarling operations and revenue in the blink of an eye. From smart homes and smart cars to intelligent industrial machines that can have their ailments remotely diagnosed, IoT is a rapidly growing field.