Xnor.ai Unveils First Battery-free, Solar AI Technology, Enabling a New Wave of Edge AI Computing

Xnor pioneers new machine learning and computer architecture approach
to deliver an efficient AI technology that operates independently of the
cloud or a power source – opening new possibilities to scale AI across
industries, societies and to even the most remote geographies


SEATTLE–(BUSINESS WIRE)–lt;a href=”https://twitter.com/hashtag/AI?src=hash” target=”_blank”gt;#AIlt;/agt;–Xnor.ai (Xnor), the company that first proved it was possible to run
state-of-the-art AI on resource constrained compute platforms, today
unveiled its newest innovation – a standalone battery-free,
solar-powered AI technology that will enable AI to run in an always-on
mode on a range of edge devices. Xnor’s solution, deployed on a hardware
device roughly the size of a US quarter is able to intelligently detect
visual objects, including people. This breakthrough machine learning and
computer architecture approach reaches a greater power efficiency so
that even state-of-the-art deep learning models, previously dependent on
powerful GPUs, can be powered by a simple solar cell.

“Power will become the biggest bottleneck to scaling AI” said Ali
Farhadi, Co-founder of Xnor.ai. “What Xnor has proved today is that it
is now possible to run AI inference at such low power that you don’t
even need a battery. This will change not only the way products are
built in the future, but how entire cities and countries deploy AI
solutions at scale.”

With this innovation, AI technologies – embedded into solutions ranging
from consumer wearables to autonomous vehicles – can be scaled faster,
more efficiently, and with far less environmental impact. By
thoughtfully co-designing machine learning algorithms with hardware
architecture, Xnor’s technology is so efficient that if deployed on an
Application Specific Integrated Circuit (ASIC), will run on the order of
Microjoules per inference. Even at these stunningly low power numbers,
state-of-the-art accuracy is preserved.

“With technology this low power, a device running on only a coin cell
battery could be always on, detecting things every second, running for
32 years!” – Saman Naderiparizi – Head of Hardware Engineering, Xnor.ai

Running AI at extremely low power levels sends a strong message that
it’s now possible to build AI solutions without consuming unnecessarily
large amounts of energy that contribute to society’s carbon footprint
and global warming.

According to a study by the Natural
Resources Defense Council
, US data centers that are processing an
ever increasing number of traditional AI algorithms are estimated to
consume nearly 140 billion kilowatt-hours of electricity each year by
2020, which is the equivalent to the output of 50 large coal-fired power
plants. This not only costs American businesses $13 billion annually,
but releases nearly 100 million metric tons of carbon pollution every
year.

To demonstrate the viability of Xnor’s AI technology, embedded within
the current version is a camera capable of capturing and analyzing video
content using state-of-the-art deep learning algorithms. The camera can
identify, classify, and code objects within a frame, and then send
information to the recipient in near real-time using low data rate
wireless communication protocols designed for IoT applications.
Importantly, photo and video data never leaves the device, as only
insights from the analyzed frames are distributed, resulting in
significantly higher security to help guarantee that a user’s privacy is
protected.

The solution is so small and lightweight that it can balance on the tip
of your finger. Products built using this technology will work out of
the box without the need to charge or connect to the Internet, enabling
Xnor to bring advanced AI capabilities to virtually any device,
including in the most remote areas.

For more information on the transformative power of this new technology,
check out our demo video.

Contacts

Sophie Lebrecht
sophie@xnor.ai