{"id":891489,"date":"2026-03-18T10:52:10","date_gmt":"2026-03-18T10:52:10","guid":{"rendered":"https:\/\/www.electronicsweekly.com\/?p=891489"},"modified":"2026-03-19T09:24:38","modified_gmt":"2026-03-19T09:24:38","slug":"embedded-ambient-scientific-integrates-10-ai-cores-in-gpx10-pro","status":"publish","type":"post","link":"https:\/\/www.electronicsweekly.com\/news\/products\/embedded-ambient-scientific-integrates-10-ai-cores-in-gpx10-pro-2026-03\/","title":{"rendered":"Embedded: Ambient Scientific integrates 10 AI cores in GPX10 Pro"},"content":{"rendered":"<p>The GPX10 Pro SoC has 10 programmable AI cores for a custom instruction set and is based on Ambient Scientific&#8217;s proprietarty DigAn architecture and MAC circuit design.<\/p><div class=\"elect-content\" style=\"margin-left: auto; margin-right: auto; text-align: center; \" id=\"elect-1499165061\"><div id=\"x02\">\r\n<script type=\"text\/javascript\"> if ($(window).width() <= 768) { googletag.display('x02'); } <\/script>\r\n<\/div>\r\n<\/div>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-891492\" src=\"https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-300x214.webp\" alt=\"Ambient Scientific GPX10 Pro \" width=\"300\" height=\"214\" srcset=\"https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-300x214.webp 300w, https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-1024x731.webp 1024w, https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-768x549.webp 768w, https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-1536x1097.webp 1536w, https:\/\/static.electronicsweekly.com\/wp-content\/uploads\/2026\/03\/18104846\/Ambient-no-text-2048x1463.webp 2048w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>The chip&#8217;s AI engine supports\u00a0 a variety of neural networking model types, including CNNs, RNNs, LSTMs and GRUs, locally at the edge. According to <a rel=\"image\" href=\"http:\/\/www.ambientscientific.ai\" target=\"_blank\" rel=\"nofollow\">Ambient Scientifi<\/a>c, the SoC offers up to 100x improvements in power, performance and area compared to conventional 32-bit microcontrollers.<\/p><div class=\"elect-test\" style=\"margin-left: auto; margin-right: auto; text-align: center; \" id=\"elect-359881777\"><div id=\"DFP-EW-InRead1\">\r\n<script type=\"text\/javascript\"> if ($(window).width() > 768) { googletag.display('DFP-EW-InRead1'); } <\/script>\r\n<\/div>\r\n<BR>\r\n<\/div>\n<p>It is able to perform edge AI functions faster and at much lower power than today\u2019s MCUs, NPUs or GPUs achieve, said the company. This is achieved by mapping the neural network model\u2019s matrix-multiply operations and activation flows directly to in-memory analogue compute blocks. This eliminates wasted cycles and overhead which can be found in a conventional processor\u2019s general-purpose instruction set, said CEO, GP Singh.<\/p><div class=\"elect-post-content-2\" style=\"margin-left: auto; margin-right: auto; text-align: center; \" id=\"elect-2054371058\"><div id=\"DFP-EW-InRead1-Mobile\">\r\n<script type=\"text\/javascript\"> if ($(window).width() <= 768) { googletag.display('DFP-EW-InRead1-Mobile'); } <\/script>\r\n<\/div>\r\n<\/div>\n<p>AI processing is performed in two sets of five MX8 AI cores in two separate power domains. One set is in an always-on block which supports ultra-lower power sensor interfacing and fusion. The example given is that the SoC consumes less than 100\u00b5W for always-on keyword spotting. The 10 MX8 cores perform up to 2,560 multiply-accumulate (MAC) operations per cycle, for peak AI throughput of 512-GOPs.<\/p>\n<p>The compute function is supported by 2MB of on-chip SRAM. There is an Arm Cortex-M4F CPU core, a low power ADC, enhanced I<sup>2<\/sup>S logic, and interfaces for up to eight simultaneous analogue and 20 digital sensors; e.g., accelerometer or gyroscope.<\/p>\n<p>Ambient Scientific provides the comprehensive Nebula\u2122 AI enablement toolchain to accelerate the training, development and deployment of AI models to the GPX10 and GPX10 Pro. It is compatible with leading model training frameworks including TensorFlow, Keras and ONNX. The chip\u2019s AI cores, which are programmable in the Nebula toolchain, give designers the flexibility to adapt to evolving AI model types and topologies.<\/p>\n<p>Ambient Scientific also provides the SenseMesh\u2122 hardware sensor fusion layer, which enables low-latency sensor fusion by connecting multiple sensors to a core via a tightly-coupled mesh. This produces instant responses to trigger events, and ultra-low Idle mode power, as it offloads sensor polling from the CPU.<\/p>\n<p>The GPX10 Pro can be used for local AI inference in wearable and monitoring edge and endpoint devices, including those powered by a single coin cell battery. Examples include pet collars, livestock monitors, smart rings and smart watches.<\/p>\n<p>Later this year, Ambient Scientific will introduce the GPX64 which will have edge AI capability for use with robotics, drones and ADAS, said Singh. Its precision machine vision will be 10-50x higher resolution than exisiting devices, with around 300 frames per second and up to 520Mpixel performance, said Singh.<\/p>\n<p>Other Embedded World news:<\/p>\n<blockquote class=\"wp-embedded-content\" data-secret=\"l1GbKE6jvu\"><p><a rel=\"image\" href=\"https:\/\/www.electronicsweekly.com\/news\/embedded-world-2026-get-the-full-electronics-weekly-guide-2026-03\/\">Embedded World 2026: Get the full Electronics Weekly Guide<\/a><\/p><\/blockquote>\n<p><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; visibility: hidden;\" title=\"&#8220;Embedded World 2026: Get the full Electronics Weekly Guide&#8221; &#8212; Electronics Weekly\" src=\"https:\/\/www.electronicsweekly.com\/news\/embedded-world-2026-get-the-full-electronics-weekly-guide-2026-03\/embed\/#?secret=d2C98ULUPm#?secret=l1GbKE6jvu\" data-secret=\"l1GbKE6jvu\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The GPX10 Pro SoC has 10 programmable AI cores for a custom instruction set and is based on Ambient Scientific&#8217;s proprietarty DigAn architecture and MAC circuit design. The chip&#8217;s AI &#8230;<\/p>\n","protected":false},"author":7791,"featured_media":891492,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17258,12660,12695,12694,12684,12640,12665],"tags":[16811,17499,14450,14618],"class_list":["post-891489","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-embedded-systems","category-internet-of-things","category-medical-electronics","category-microprocessors","category-news","category-products","tag-ai","tag-ambient-scientific","tag-embedded-world","tag-soc","interest-embedded","interest-iot","interest-medical"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.7 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Embedded: Ambient Scientific integrates 10 AI cores in GPX10 Pro | Electronics Weekly<\/title>\n<meta name=\"description\" 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