Tech Alert: BrainChip Examines New Approach to Optimizing Time-series Data

A new white paper by BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, unveils Temporal Event-based Neural Networks (TENNs) - an innovative way to bring greater accuracy and efficiency to complex models on compact edge devices. TENNs are extremely effective in accelerating 3D and 1D time series applications including video, vision, audio, and vital signs in healthcare to name a few.

The paper, “Temporal Event-based Neural Networks: A new approach to Temporal Processing,” shows how TENNs enable intelligent, energy-efficient edge solutions and details how BrainChip’s 2^nd Generation Akida™ IP platform supports this innovation. TENNs provide radical, innovative ways to reduce complexity, size, and compute requirements, while still delivering the accuracy expected for the desired, intelligent, responsive experience at the edge.

“While CNNs have long been the backbone of image classification in AI and ML, they are not as efficient in handling spatiotemporal data and applications such as video object detection from video streams, and Time series data, thereby limiting its usage in cost-effective, thermally constrained edge devices,” said Anil Mankar, co-founder and CDO at BrainChip. “The TENN is a new approach that exploits the temporal correlations much more efficiently, revolutionizing AI at the edge.”

To learn more about how TENNs supercharge the processing of raw time-continuous streaming data and time series analytics used in forecasting and predictive maintenance, interested parties can download the white paper at https://brainchip.com/wp-content/uploads/2023/06/TENNs_Whitepaper_Final.pdf

About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY)

BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida^TM, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security. Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like Tensorflow/Keras. In enabling effective edge compute to be universally deployable across real world applications such as connected cars, consumer electronics, and industrial IoT, BrainChip is proving that on-chip AI, close to the sensor, is the future, for its customers’ products, as well as the planet. Explore the benefits of Essential AI at www.brainchip.com.

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