Press release
Ceva Extends its Smart Edge IP Leadership, Adding New TinyML Optimized NPUs for AIoT Devices to Enable Edge AI Everywhere
- Ceva-NeuPro-Nano NPUs deliver optimal balance of ultra-low power and best performance in small area to efficiently execute TinyML workloads in consumer,
About this update from Ceva, Inc.
[{"type":"text","content":"- Ceva-NeuPro-Nano NPUs deliver optimal balance of ultra-low power and best performance in small area to efficiently execute TinyML workloads in consumer, industrial and general-purpose AIoT products\n- Ceva-NeuPro Studio complete AI SDK for the Ceva-NeuPro NPU family supports open AI frameworks including TensorFlow Lite for Microcontrollers and microTVM to simplify the rapid development of TinyML enabled applications \n- Optimized NPUs for embedded devices build on Ceva's market leadership in IoT connectivity and strong expertise in audio and vision sensing to help semiconductor companies and OEMs unlock the potential of edge AI\nROCKVILLE, Md., June 24, 2024 /PRNewswire/ -- Ceva, Inc. (NASDAQ: CEVA), the leading licensor of silicon and software IP that enables Smart Edge devices to connect, sense and infer data more reliably and efficiently, today announced that it has extended its Ceva-NeuPro family of Edge AI NPUs with the introduction of Ceva-NeuPro-Nano NPUs. These highly-efficient, self-sufficient NPUs deliver the power, performance and cost efficiencies needed for semiconductor companies and OEMs to integrate TinyML models into their SoCs for consumer, industrial, and general-purpose AIoT products.\n\nTinyML refers to the deployment of machine learning models on low-power, resource-constrained devices to bring the power of AI to the Internet of Things (IoT). Driven by the increasing demand for efficient and specialized AI solutions in IoT devices, the market for TinyML is growing rapidly. According to research firm ABI Research, by 2030 over 40% of TinyML shipments will be powered by dedicated TinyML hardware rather than all-purpose MCUs. By addressing the specific performance challenges of TinyML, the Ceva-NeuPro-Nano NPUs aim to make AI ubiquitous, economical and practical for a wide range of use cases, spanning voice, vision, predictive maintenance, and health sensing in consumer and industrial IoT applications.\nThe new Ceva-NeuPro-Nano Embedded AI NPU architecture is fully programmable and efficiently executes Neural Networks, feature extraction, control code and DSP code, and supports most advanced machine learning data types and operators including native transformer computation, sparsity acceleration and fast quantization. This optimized, self-sufficient architecture enables Ceva-NeuPro-Nano NPUs to deliver super...