The Rise Of The Silicon Brain

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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.

Disclosure: Risk Group LLC is my company. 

 

Risk Group discusses the Potential of SpiNNaker for the Future of Systems on a Chip with Prof. Stephen Furber, ICL Professor of Computer Engineering, School of Computer Science at The University of Manchester based, in the UK.

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! 

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Jayshree Pandya, Ph.D., contributor, is Founder of Risk Group & Host of Risk Roundup. 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 strategic security 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 very survival, security and sustainability of humanity.