Company’s ground-breaking AI technology for extreme edge computing is driving solutions that make life safer, healthier, comfortable, and more convenient without sacrificing privacy and security.
WESTLAKE VILLAGE, Calif., October 8, 2019 – Eta Compute Inc., a company dedicated to delivering machine learning to mobile and edge devices using its revolutionary new platform, announced it will have a major presence at the industry’s most prestigious events this fall.
“Our growing presence at these important industry events is a testament to the impact Eta Compute’s AI solutions are having on extreme edge computing,” said Eta Compute’s CEO Ted Tewksbury. “Our products are becoming increasingly recognized as technologies that will have a tremendous impact on our lives and our future.”
Eta Compute will be exhibiting at Arm TechCon in San Jose on October 9 and 10 in Booth #645 and demonstrating AI applications optimized for edge computing applications. Eta Compute will demonstrate the following use cases operating under 1 milliamp (mA) on its ECM3531:
- End to end low-power object classification, using a camera sensor and transmitting result to a cell phone over BLE
- Sensor fusion and activity recognition consuming 300uA with data from motion sensors
- Always on keyword spotting and 10-word voice commands with MEMS microphones
- Energy harvesting environmental sensor demo using Sub GHz wireless RF to transmit low rate sensor data to the wireless cloud
- Solar-powered BLE beacon working in low-lumen indoor light conditions.
Linley Fall Processor Conference 2019
Semir Haddad, Senior Director, Product Marketing at Eta Compute will present “Practical Machine Learning at the Extreme Edge” during Session 6: AI for IoT Devices on October 23. Machine learning has the potential to revolutionize the capability of the billions of devices at the extreme edge that perform most of the sensing and actuation in our daily life. These devices operate on microcontrollers with severe power constraints, limited performance, and no or very simple operating systems. This presentation will discuss the power-performance tradeoff and software requirements needed to bring machine learning to the extreme edge and how the Tensai SoC addresses these challenges. In addition, the company will have a table top demonstration and a Hosted Speaker Table.
Hari Shankar, Eta Compute Engineering Fellow, will present “Tensai: Flexible and Programmable Architecture to Meet the Evolving Needs of Intelligent Low Power Edge Devices” on October 22, 2019. SENS|MACH is an industry-university workshop on sensors and machine learning, which is focusing on Tiny Machine Learning in 2019.
Semir Haddad, Senior Director, Product Marketing at Eta Compute will present “Vision At The Extreme Edge: Making Sensors See” on November 21 at 11:45 a.m. Machine vision is often associated with applications like security cameras and industrial automation that are not power-constrained. This presentation will show how the combination of low-resolution image sensors with ultra-low-power neural sensor processors like Eta Compute’s Tensai can enable the deployment of vision at the extreme edge.
To schedule a media briefing with Eta Compute during one of these events, email firstname.lastname@example.org.
For more information visit EtaCompute.com or contact the company via email at email@example.com.
About Eta Compute
Eta Compute was founded in 2015 with the vision that the proliferation of intelligent devices at the network edge will make daily life safer, healthier, comfortable and more convenient without sacrificing privacy and security. The company’s DIAL™ technology is the world’s lowest power embedded computing platform and is a natural architecture to support event driven neuromorphic learning and machine intelligence for portable devices. In 2018, the company received the Design Innovation Of The Year and Best Use Of Advanced Technologies awards at ARM TechCon.
Corridor Communications, Inc., Bonnie Quintanilla, 818.681.5777 / firstname.lastname@example.org or Phyllis Grabot, 805.341.7269 / email@example.com