Targeting embedded sensors in wearables/smart home as well as in the industrial and automotive sectors, Innatera’s Pulsar neuromorphic processor is now commercially available, bringing brain-like intelligence to next-generation devices.
Pulsar delivers up to 100 times lower latency and 500 times lower energy consumption than conventional AI processors.
Innatera said that the need for real-time, secure and energy efficient data processing is in high demand with sensors being embedded into a range of applications. Pulsar processes data locally at the sensor level. This eliminates the need for power-hungry edge processors or data centers to make sense of sensor data, the company said.
“As demand for real-time, power-efficient intelligence in edge devices continues to grow, Pulsar delivers the capabilities that traditional AI hardware simply can’t – ultra-low latency, minimal power draw, and on-device decision-making,” said Sumeet Kumar, co-founder and CEO of Innatera. “More importantly, it lays the foundation for a new class of intelligent systems that are adaptive, autonomous, and scalable. Pulsar is our first major step toward making that future a reality.”
How it would be used
Neuromorphic processors can be used for a range of applications. Innatera is focused on applications involving a range of sensors like:
- Radar
- Microphones
- Inertial measurement units
- Infrared sensors
- Any use case where sensing is carried out continuously
Generally, applications using these types of chips involve finding spatial and temporal patterns in the data stream, but other kinds of processing are also possible.
“Innatera’s Pulsar chip has the potential to redefine what’s possible at the edge,” said David Harold, senior analyst at Jon Peddie Research. “By using brain-inspired Spiking Neural Networks, it brings real-time processing to ultra-low-power devices without leaning on the cloud. That means sensors that can think for themselves — faster responses, lower energy use, and smarter performance across everything from wearables to industrial systems.”
