Shanghai, China – November 18, 2021 – Lattice semiconductor Corporation (NASDAQ: LSCC), a leading provider of low-power programmable devices, today announced its latest roadmap for low-power, AI/ML solutions , these solutions can help network edge applications such as client computing devices extend battery life and bring innovative user experiences. Built with the award-winning collection of Lattice sensAITM solutions and running on Lattice Nexus® FPGAs, they help OEMs develop smart, real-time, low-power, hardware-accelerated AI-enabled devices that are field upgradeable , to support more AI algorithms in the future.
Client computing devices increasingly demand responsive and context-aware user experiences, high-quality video conferencing, and collaborative applications. The Lattice Nexus FPGA and sensAI solutions collection is an ideal platform for developing computer vision and sensor fusion applications that enhance user engagement and collaboration and protect user privacy. For example, the client device can analyze the image data captured by the camera to determine whether people behind you are too close to the user, and can also blur the screen to protect privacy when the user’s attention is shifted elsewhere, or dim the screen to prolong battery life.
“AI applications based on vision, sound and other sensors will revolutionize the client computing experience,” said Matt Dobrodziej, vice president of marketing and business development at Lattice. “Our sensAI supports a variety of network edge AI solutions that empower client devices with contextual awareness. , so they know when, where and how they are being used. Our Nexus FPGAs do this with industry-leading low power consumption.”
AI computing devices developed with sensAI and running on Lattice FPGAs have 28% longer battery life compared to devices that use CPUs to drive AI applications. sensAI also supports in-field software updates to keep AI algorithms evolving, and gives OEMs the flexibility to choose different sensor and SoC technologies to fit their devices.
Lattice is working with leading AI ecosystem partners to develop a roadmap for the development of the Lattice client computing AI experience.
“Our Glance by Mirametrix attention-sensing software captures the user’s face, eye and gaze movements to understand the user’s awareness and attention,” said Stephen Morganstein, vice president of Mirametrix. “This unique technology enables smart devices to provide a more natural and immersive user experiences and device interactions. Lattice’s collection of sensAI solutions and low-power FPGAs can help developers implement novel AI capabilities and improve device battery life.”
The latest version (v4.1) of the sensAI Solutions Collection is now available to support Lattice’s AI-based application roadmap with enhancements and new features including:
Client Computing AI Experience Reference Design
o User detection: Client devices are automatically powered on or off when a user approaches or leaves the device
o Attention Tracking: When the user’s attention is not on the screen, reduce the screen brightness of the device, save battery, and prolong the use time
o Face Framing: Enhances the video experience in video conferencing applications
o Bystander Detection: Detects potential peepers standing behind the device, blurring the screen for data privacy
More application support – The performance and accuracy improvements of sensAI version 4.1 help expand its target applications, including applications such as high-precision object detection and defect detection used in automated industrial systems. This collection of solutions features a new hardware platform, including an onboard image sensor, two I2S microphones, and expansion connectors for adding more sensors, enabling the development of voice and vision-based machine learning applications.
Easy-to-use tools – sensAI has also updated the neural network compiler to support Lattice sensAI Studio, a GUI-based tool with a library of AI models that can be configured and trained for various mainstream application scenarios. sensAI Studio now supports AutoML capabilities to create machine learning modules based on application and dataset goals. Some models based on Mobilenet’s machine learning inference training platform are optimized for the latest Nexus line of products, the Lattice CertusPro™-NX. sensAI is also compatible with other widely used machine learning platforms, including the latest versions of Caffe, Keras, TensorFlow, and TensorFlow Lite.