A forthcoming image-focused AI chip from Kneron looks to enable a host of improvements around edge compute, security and automotive applications. Credit: Pixabay Kneron has rolled out a new type of neural processing unit, the KL730, which integrates image signal processing and high energy efficiency for use in edge, security and automotive applications. The San Diego-based chip designer, in an announcement Tuesday, said that the KL730 is powered by a quad-core ARM Cortex A55 CPU, along with its own-brand, fourth- generation neural processing unit, as well as a host of connectivity options, including SD, USB 2 and 3, and Ethernet. Its image processing technology also packs in the ability to read high-definition inputs at up to 8MP at 90 frames per second, hardware dewarping for full panoramic views, and several other image signal processing features. Neural processing units are designed to perform math that is common in neural networks, used in tasks including image recognition. According to Kneron, the KL730 will be capable of up to four effective tera-operations per second, in order to best support lightweight large language models for use in embedded applications. The idea is to provide AI capabilities to a wide range of distributed, imaging-focused applications without the need for a network connection to a dedicated AI core running remotely — in essence, providing “on-device” AI hardware for everything from cars to medical devices to conference rooms. “Running AI requires AI-dedicated chips with an architecture that is completely different from anything we’ve seen before,” said Kneron founder and CEO Albert Liu, in the company’s news release. “A simple re-appropriation of adjacent technologies, such as graphics-dedicated GPU chips, simply isn’t going to do the job.” Systems leveraging the KL730 would use a smaller AI model, like nanoGPT or miniGPT, to provide an “embedded AI” presence in numerous potential use cases, according to a slide deck Kneron provided with the release. The use of the system in conjunction with the sensors increasingly common on modern cars could provide for improved safety and help conquer what have been major stumbling blocks for the industry like pedestrian recognition. It could be used to provide enhanced image processing for surveillance cameras and teleconferencing, identifying license plates and faces automatically. Finally, the deck noted that small robotics technologies could gain improved speech recognition and intent comprehension. The KL730 will be available for sampling in the first quarter of next year, according to Kneron, but the company declined to provide a general ability date. Pricing information was also not disclosed. Related content news Nvidia to power India’s AI factories with tens of thousands of AI chips India’s cloud providers and server manufacturers plan to boost Nvidia GPU deployment nearly tenfold by the year’s end compared to 18 months ago. By Prasanth Aby Thomas Oct 24, 2024 5 mins GPUs Artificial Intelligence Data Center news New middleware doubles GPU computational efficiency for AI workloads in trials, says Fujitsu The company says the computing broker is aimed at solving the GPU shortage for compute-intensive workloads by improving resource allocation and memory management across AI platforms and applications. By Elizabeth Montalbano Oct 22, 2024 4 mins GPUs Artificial Intelligence news analysis Nvidia: Latest news and insights Here’s what you need to know about the AI and processor giant’s latest product and company news. By Dan Muse Oct 15, 2024 6 mins Artificial Intelligence news US targets advanced AI and cloud firms with new reporting proposal This, along with other AI regulations, sparks worries for enterprises about escalating compliance costs and curbing innovation. By Prasanth Aby Thomas Sep 10, 2024 1 min Regulation Artificial Intelligence Cloud Computing PODCASTS VIDEOS RESOURCES EVENTS NEWSLETTERS Newsletter Promo Module Test Description for newsletter promo module. Please enter a valid email address Subscribe