Media Alert: BrainChip Highlights Akida 2.0 Innovations at tinyML Asia Technical Forum in Korea
26 Octobre 2023 - 3:15PM
Business Wire
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, will highlight innovative
features of the Akida™ 2.0 architecture platform to attendees of
the tinyML Asia Technical Forum November 16th in Seoul, Korea.
Machine learning (ML) is at the forefront of providing
artificial intelligence to all aspects of computing. It is the
technology powering many of today’s advanced applications from
image recognition to voice interfaces to self-driving vehicles and
beyond. Many of these initial ML applications require significant
computational resources, most often found in cloud-scale data
centers. To enable industry usage and adoption, it is, therefore,
necessary to significantly reduce the power consumed to bring
applications to end devices at the cloud edge (smartphones,
wearables, vehicles, IoT devices, etc.) and to reduce the load on
required data center resources.
At the forum, Sean Hehir, BrainChip CEO, will showcase new Akida
features, including Temporal Event-based Neural Networks (TENNs),
Visual Transformers and on-device learning.
“tinyML Asia is the ideal event to meet developers and providers
of ML that are pushing boundaries on intelligent services at the
Edge for portable applications,” said Hehir. “We look forward to
sharing the latest benefits of neuromorphic processing from Akida’s
2nd generation that unlock complex multi-dimensional streaming
applications on devices with limited memory, battery, and compute
resources, untethered from the cloud.”
The Akida neural processor is designed to provide a complete
ultra-low power Edge AI network processor for vision, audio, smart
transducers, vital signs and, more broadly, any sensor application.
BrainChip’s scalable solutions, which can be used standalone or
integrated into systems on chip to execute today’s models and
future networks directly in hardware, empowers the market to create
much more intelligent, cost-effective devices and services that can
be universally deployed across real-world applications in connected
cars, healthcare, consumer electronics, industrial IoT,
smart-agriculture and more, including use in a space mission and in
the most stringent conditions.
Those interested in a private meeting with BrainChip can contact
sales@brainchip.com to schedule an appointment.
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™, 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.
Follow BrainChip on Twitter:
https://www.twitter.com/BrainChip_inc Follow BrainChip on LinkedIn:
https://www.linkedin.com/company/7792006
View source
version on businesswire.com: https://www.businesswire.com/news/home/20231026639840/en/
Media: Mark Smith JPR Communications 818-398-1424
Investors: Tony Dawe Director, Global Investor Relations
BrainChip tdawe@brainchip.com
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