Synaptics is collaborating with Google on Edge AI for the IoT to define optimal implementation of multimodal processing for context-aware computing.
This collaboration will see Google’s MLIR-compliant ML core integrated on the Synaptics Astra hardware with open-source software and tools. In doing so, it will accelerate the development of AI devices for the IoT that support the processing of vision, image, voice, sound, and other modalities that provide context for interactivity in applications including wearables, appliances, entertainment, embedded hubs, monitoring, and control across consumer, automotive, enterprise and industrial systems.
The Synaptics Astra AI-Native compute platform for the IoT combines scalable, low-power compute silicon for the device Edge with open-source, easy-to-use software and tools, a strong partner ecosystem, and wireless connectivity. The platform builds upon Synaptics’ expertise in neural networks, field-hardened AI hardware and compiler design expertise for the IoT, and refined, in-house support of a broad base of modalities. Google’s ML core, meanwhile, is a highly efficient open-source machine learning (ML) core that is compliant with the multi-level intermediate representation (MLIR) compiler.
“We are on the brink of a transformative era in Edge AI devices, where innovation in hardware and software is unlocking context-aware computing experiences that redefine user engagement,” commented Vikram Gupta, Senior Vice President and General Manager of IoT Processors, Chief Product Officer at Synaptics. “Our partnership with Google reflects a shared vision to leverage open frameworks as a catalyst for disruption in the Edge IoT space. This collaboration underscores our commitment to delivering exceptional experiences while validating Synaptics’ silicon strategy and roadmap for next-generation device deployment.”
“Synaptics’ embrace of open software and tools and proven AI hardware makes the Astra portfolio a natural fit for our ML core as we ramp to meet the uniquely challenging power, performance, cost, and space requirements of Edge AI devices,” added Billy Rutledge, Director of Systems Research in Google Research. “We look forward to working together to bring our capabilities to the broad market.”
There’s plenty of other editorial on our sister site, Electronic Specifier! Or you can always join in the conversation by commenting below or visiting our LinkedIn page.
