Deploying adaptive AI in distributed water plants - Barbara Accoina adds another $30M for embedded edge ML, appoints new board member

Categories Edge Computing News  |  Funding  |  People adds another $30M for embedded edge ML, appoints new board member

Embedded machine learning solutions provider announced it has raised an additional $30 million to enhance its machine learning-focused chip platform that is being aimed for use in edge AI deployments such as drones, robotics, and surveillance systems The financing round was led by Fidelity Management and Research Company with participation from all the existing investors to bring the total money raised to $150 million. Lip-Bu Tan, a chip industry leader, joined investors in the round and joined the company’s board of directors.

Lip-Bu Tan was previously CEO of Cadence Design Systems, a provider of systems design software. Lip-Bu Tan is currently a founder and chairman of Walden International, a venture capital firm, and a founding managing partner of Celesta Capital and Walden Catalyst Ventures. He also serves as an executive chairman and member of Cadence’s board of directors. The tech leader is currently serving on the boards of Schneider Electric SE and SoftBank Group.

“It is an honor to welcome Lip-Bu Tan as the newest member of’s board of directors,” said Moshe Gavrielov,’s chairman of the board. “His history of investing in and creating deep tech brands that span semiconductors, alternative energy and digital media is unmatched. Lip-Bu has a proven track record of helping companies reach their full potential and I am confident he will elevate as we work to drive industry leadership and market success.” is one of several edge AI chip companies to have received funding this year as investors eye a significant market opportunity. According to a report published by Deloitte, the edge AI chip market is forecasted to grow at a 20% CAGR and exceed sales of 1.5 billion processors by 2024.’s MLSoC platform offers a software-centric approach that the company says provides “push-button” performance for embedded machine learning deployment and scaling on the edge network. With the growing market for computer vision applications,’s MLSoC platform allows the developer to run any computer vision model, framework, sensor and resolution on the chip. According to the benchmark provided by, the machine learning SoC platform performs 10x better per watt than the alternative.’s MLSoC platform supports a wide range of frameworks such as TensorFlow, PyTorch, ONNX, and MXNet for high performance, low power, and secure ML inference. The platform provides up to 50 TOPS for neural network computation with “best-in-class” deep neural network inference efficiency for 500 FPS/W ResNet-50 v1, batch size 1.  The MLSoC hardware is manufactured using 16nm process technology with image pre and post-processing integrated with a dedicated machine learning accelerator and application processor.

“Machine learning has had a profound impact on the cloud and mobile markets over the past decade and the next battleground is the multi-trillion-dollar embedded edge market. has created a software-centric, purpose-built MLSoC platform that exclusively targets this large market opportunity,” said Lip-Bu Tan. “’s unique architecture, market understanding and world-class team have put them in a leadership position. I’m excited to join them as an investor and a board member and I look forward to partnering with to drive success.”

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