Special Edition of The #AIEye: How #AI is shaping the future – Interviews
with GBT Technologies Inc. (OTCPINK: $GTCH) and BrainChip Holdings Limited (ASX:BRN)
Point Roberts WA, Vancouver BC – September
26, 2019 – Investorideas.com (www.investorideas.com), a global investor news source
covering Artificial Intelligence (AI)
brings you today’s special edition of The AI Eye- watching stock
news, deal tracker and advancements in artificial intelligence.
Today’s edition features recent interviews
with two experts in C Level management positions discussing recent developments
within their companies and the overall sector: Dr. Danny Rittman, CTO of GBT
Technologies Inc. (OTC PINK:GTCH),
and Mr. Louis DiNardo, President and CEO of BrainChip Holdings Limited (ASX:BRN).
Read
this in full at https://www.investorideas.com/news/2019/artificial-intelligence/09261AIEye-Interview-GTCH.asp
Listen
to the podcast interview with Dr. Danny Rittman, CTO of GBT Technologies Inc. (OTC
PINK:GTCH) discussing how the company leverages AI in the IoT space and
recent develops with analog computing
GBT Technologies’ employment of
internet-of-things (IoT) technology predates the development of the company’s
AI core, according to CTO Danny Rittman. In fact, it was the company’s
development of IoT technologies that led to a growing need to create an
artificial intelligence core.
“We went further into the data science …
[and] figured out that we needed to be more on the secure side, we need to
handle vast amounts of data, especially as we went into autonomous machines
domain etc…” he said. “So, we realized
we would need a mechanism that involved AI. For the past year and-a-half, GBT
developed a core AI that is based on machine learning.”
“IoT will become more and more permanent in
our daily domain, and of course GBT is progressing forward with this trend
because our technology is natively IoT,” he said. “It started as a radio
technology, and since IoT is basically radio-activated … we were naturally
embedded in this domain a few years ago.”
A report from Zion Market Research
echoes GBT’s leveraging of AI in IoT in its finding that globally, the AI in
IoT market is projected to grow to $19.9 billion USD by 2025. This represents a
compound annual growth rate (CAGR) of 25.89 percent from 2018-2025.
Recently, the company has announced R&D
in analog computing, which Rittman points out will complement and enhance GBT’s
tech.
“Analog computing for artificial
intelligence, and for machine learning, will enable much further capabilities
for the IoT domain,” he said.
In a recent press release,
Rittman expanded on the role of analog computing with regard to replicating
human intelligence:
"With
this new research activity we are laying the foundation of a true human-like
learning system. Analog computing for machine learning enables robots to
interact with humans, not only based on visual cues, but also according to tone
of speech and body language. Our AI technology plans to incorporate both high
and low-level computing, which we believe is a more accurate model of human
intelligence.”
Listen
to the podcast interview with Mr. Louis DiNardo, President and CEO of BrainChip
Holdings Limited (ASX:BRN) discussing the company’s Akida neural
processing core (NPC) and the Edge AI market
BrainChip Holdings Limited, a neuromorphic
computing firm, combines neural science with digital technology to produce its
Akida neuromorphic system-on-a-chip for edge application. The company’s
President and CEO, Mr. Louis DiNardo, explained how the technology takes cues
from the human brain:
“We’ve developed, and began to market, what
we call an event-based neural network processor,” he said. “The technology is
inspired by the spiking nature of the human brain. Whenever you, I or anyone
sees, hears, thinks or touches anything, our nervous system generates small
bioelectrical spikes that create memory. By mimicking brain processing,
BrainChip has pioneered a hardware-spiking neural network called Akida.”
DiNardo explained the application of the
BrainChip’s technology on edge computing.
“Akida is exceptionally well-suited to
applications at the Edge, where sensor inputs are analyzed at the point of
acquisition, rather than transmissions to the cloud or a data centre,” he said.
“The device is designed to provide a complete, ultra low-power AI edge network
for vision, audio and other smart transducer applications. This creates a
reduction in system latency, when the time it takes to get from a sample to a
decision. Reducing system latency provides a faster response, it’s a more
power-efficient system, and it can reduce the carbon footprint of data
centres.”
Expanding on the idea of carbon footprint
reduction, DiNardo highlights the advantages of edge computing over
alternatives such as the cloud.
“Data centres are basically power hogs,” he
said. “They suck up a lot of power, and when you can do analysis at the edge
and only go back to the central processing unit, the data centre or the cloud
to make decisions on metadata, you can reduce the overall carbon footprint of
the data centre.”
“Our belief is that smart vision systems,
including consumer, industrial, [and] the internet-of-things present a
target-rich environment. Acoustic analysis and smart sensors in a wide array of
end use-cases, including very good opportunities in the automotive industry and
cybersecurity also offer great promise.”
For
a list of artificial intelligence stocks on Investorideas.com visit here or become an Investor Ideas member
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