Depositphotos enhanced by CogWorld
Introduction
The rise of the silicon brain
that can give rise to thought, emotion and behavior in a machine seems
to be on the way. This is mainly due to rapid advances in software and
hardware that are paving the way for next generation computational
systems with cognitive abilities modeled after the human brain. This
will prove to be a significant evolutionary development and especially
important to enhancing machine intelligence
for the complex problems that need to be solved for the future of
humanity. So, as we envision a rapidly evolving silicon brain taking in
the data from its surroundings in cyberspace, geospace, space (CGS) and
run the data through some known/unknown computing processes and then
tell the computer/machine to act, feel or behave in a certain way seems
to bring humanity a lot more questions than answers. This is mainly
because it is not known how the information on the silicon brain will be
processed, stored or recalled; how the computer commands will emerge
and become effective, and even how the silicon brain will experience the
sensory world around it in CGS, and how it will think, feel or
empathize.
As we evaluate all these emerging questions surrounding the rise of
the silicon brain, there is an intense effort already going on to create
neuromorphic chips that can mimic the human brain. There is also an initiative emerging to create a neuromorphic chip based on an octopus brain.
While the emerging neuromorphic chips are still nowhere near as capable
as a human brain or octopus brain, much is expected to change for
machine intelligence very rapidly in the coming years, as these chips
begin learning to process available sensory data from CGS to evolve
their abilities in real time for the goals defined for them.
Need for Increased Computing Power
As we rapidly move towards neuromorphic computing, it is important to
understand why there is a need to move away from traditional chips and
towards neuromorphic chips. One of the main reasons is we are simply
running out of computing capacity as existing and emerging technologies
are accelerating global computing power
consumption. Now, as technologies like artificial intelligence, machine
learning blockchain and the internet of things begin to require
significant computing power, there is a need to not only process
computation more efficiently, but also evolve both hardware and
software. Neuromorphic computing may solve this ongoing problem of
computing power by doing all the functioning
in the chip rather than sending messages back and forth with the larger
server/cloud and by being event driven and only operating when it needs
to, thereby imitating the brain.
As a result, the rise of neuromorphic chips and computing seems to
bring much-needed energy efficiency for low energy requirements, high
performance speeds, greater resilience, the capability to learn from its
CGS environment, and the much-needed increase in computing power. That brings us to an important question: what will be the impact of the increased computing power on the nation’s economy?
Neuromorphic Computing Chips: Future of Artificial Intelligence and Blockchain
Neuromorphic computing chips may be the future of not only artificial
intelligence but also of blockchain, as they give us an ability to
develop low energy consuming cryptocurrency as well as distributed
systems. In addition, it further allows the integration of individuals
and entities across nations: its government, industries, organizations
and academia (NGIOA) by potentially creating new modes of connectivity,
efficiency, collaboration, learning and problem solving in real time. That
brings us to an important question: how will neuromorphic chips change
the way new ideas, innovations and initiatives are developed across
nations?
As seen over the years, there have been formidable advances in
computing and software. However, the developments have so far only been
dedicated to software and not on hardware. Neuromorphic computing and
chips bring the much-needed evolution in computer hardware, allowing us
to enhance machine intelligence
for the complex problems that need to be solved for the future of
humanity. With the evolving computing power, nations need to
individually and collectively begin to evaluate where to apply the power
of computing chips first. Perhaps it is time to apply the power of
neuromorphic chips and make the national digital infrastructure
resilient to the destructive power of electromagnetic
spectrum/electronic warfare.
Emerging Systems on a Chip
Much like humans, the emerging neuromorphic chips enabling
intelligent machines that will be able to understand and interact with
the human ecosystem in cyberspace, geospace and space (CGS) seems to be a
fundamentally disruptive innovation. We have seen many advances
already, from the emerging SpiNNaker system and many other systems. We
also have many interesting applied research initiatives emerging from
across nations, such as information processing in the human/octopus
silicon brain to green cryptocurrency initiatives and more. Each of
these initiatives is using their own neuromorphic computing architecture
and approach.
It is a known fact that the human brain
is incredibly complex, with a network of 100 billion neurons that
function individually in an environment that is not fully understood by
humans yet. The same can be said for the octopus brain.
To regulate human bodily functions and respond to external stimuli, the human brain neurons
work with electrical and biochemical networks and environments.
Moreover, while what is consciousness is still debated and not agreed
upon and not fully understood yet, it seems the neurons play an
important role in human/machine consciousness. Now, it is believed that much of what the human brain does is built into the wiring, which are the neurons. So, the question is what do we know about what controls the neurons?
While over the years, much about the human brain genome has been
decoded; understanding of the human brain remains complex with many
unknowns. This is especially important from the perspective that nearly
90 percent of the human brain is composed of glial cells,
and not neurons, and the glial cells are just coming to be understood.
So, the question is, are glial cells controlling neurons? If so, how
will we create silicon glial cells that will be perhaps necessary not
only to clean up molecular trash created by neurons, but also to play a
role in learning and memory, to help repair damaged silicon brain areas
and to perhaps control neurons and neural pathways by providing the
necessary biochemical environment. Now it is also believed that glial
cells can communicate with neurons and with each other through what is
commonly known as gap junctions
across large areas of the human brain. How important are gap junctions
and would they play a role in a silicon brain? And, when almost every
disease of the human brain is partly or solely the result of glial malfunction,
should we also not focus on mimicking glial cells replication on
neuromorphic chips to prevent future machine malfunctions? If not, how
are we creating a silicon brain without some sort of silicon glial
cells? What will be the impact if we do and if we don't?
Acknowledging this emerging reality, Risk Group initiated the much-needed discussion on The Future of Systems on a Chip with Prof. Stephen Furber on Risk Roundup.
What's Next
The lines are seemingly blurring between a human/octopus brain and a
silicon brain. So, as we dream and work towards building/creating a
silicon brain that thinks like a human brain or octopus brain, is
intelligent and has the potential to build entire systems on a chip, it
is important to evaluate the promise and perils of our pursuit for
human/octopus like intelligence in computers or machines.
While the silicon brain is aiming to improve intelligent machines to
be able to handle complex systems tasks efficiently, the ultimate goal
is to understand how the physical processes in neuromorphic chips turn
into behaviors and perception of the human world!
About the Author
Jayshree Pandya (née Bhatt), Founder and CEO of Risk Group LLC,
is a scientist, a visionary, an expert in disruptive technologies and a
globally recognized thought leader and influencer. She is actively
engaged in driving the global discussions on existing and emerging
technologies, technology transformation and nation preparedness.
Her work focuses on the impact of existing and emerging technological
innovations on nations, nation preparedness and the survival, security
and sustainability of humanity. Her research in this context evaluates
the evolution of intelligence in all forms, researches strategic
security risks emerging from disruptive innovations, reviews the
diminishing capacities of the risk management infrastructure, points out
the changing role of decision makers, defines dynamic decision-making
approaches with machine intelligence, integrates all components of a
nation: governments, industries, organizations and academia (NGIOA) and
defines strategic security risks so that nations can improve the state
of risk-resilience across cyberspace, geospace and space (CGS). As
nations make a move from centralization towards decentralization, the
re-defining and re-designing of systems at all levels evaluated in Dr.
Pandya’s comprehensive research scholarship includes artificial
intelligence, machine learning, deep learning, internet of things,
blockchain, cryptocurrency, quantum computing, virtual reality,
synthetic biology, big data analytics, drones, nanosatellites,
biotechnology, nanotechnology, gene editing and much more. Her research
is much needed for the survival and security of humanity today and in
the coming tomorrow.
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