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The Coming Age of Machine Intelligence

By Amir Husain, Published: August 18,2016

Marc Andreessen once said that software was eating the world. The point he was trying to make was that software increasingly represents the value in most economic processes. In this sense, where software was previously one small component of a complex process that involved lots of human input and complex non-digital systems, it now represents the bulk of the intelligence and value-add. Think about cars before Tesla. You had carburetors, fuel injection systems, spark plugs, complex mechanical transmission systems, cooling systems, pumps and much more. With an electric car, all this physical complexity is replaced essentially with electric motors driving wheels. Most of the mechanical subsystems are gone. Acceleration, braking, charging, navigation is now all about software. In cars, as with many other high value economic goods and processes, the value has shifted to the digital, leaving the physical behind.

The march of digitization – the ongoing process of software eating the world – will continue unabated. In times to come, software will get smarter and smarter. It’ll make decisions on its own, interpret data and reason through complex processes without requiring human input, and consume more information than any human ever could.

In fact, this is the picture of a very near term future. Today, the amount of data being produced is so vast that we confront interpretive and analytical skills shortages few know about, and even less talk about. Even in an economy like the United States, there is a lack of maintenance skills to oversee the physical infrastructure that powers daily life and commerce in the country. If every US mechanical engineer and maintenance expert who already qualifies for a retirement in the utility industry were to call it quits, we wouldn’t have much of a power infrastructure left. And it’s not just the skills shortage, it’s also the cyber threat we face to this same infrastructure from individuals, terrorist groups and nation states. Simply training more people or taking a conventional approach to tackling this multi-trillion-dollar problem won’t suffice. It would be too late and in the end, too little.

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While automation and digitization yield immense dividends, one of the downsides is that they transform everything around us – generators, power grids, cars, planes and homes – into “computers” that can fall prey to cyber-attacks. In the age of IoT (Internet of Things), security is no longer just about credit card theft and identity compromise. Security now takes on a physical dimension and operators of industrial equipment that are looking to optimize their operations by connecting all their expensive assets need to be protected against these emerging threats. In addition, the amount of sensor data that has to be ingested and understood in order for these problems to be solved is beyond human capabilities.

How does one go about dealing with these challenges? Through the application of Artificially Intelligent smart software that mimics – and goes beyond – many of the reasoning processes employed by human experts. The company I founded in Austin, Texas, SparkCognition, is one of the world’s leading developers of AI systems for the Industrial IoT market.  The business model we created was a highly innovative Artificial Intelligence platform initially targeted to Energy customers that learns from data, automates maintenance & security and augments the diminishing number of human experts. We are now expanding our partner network, growing into new verticals such as Government, and continuing to enhance our core AI capabilities with increasing investments in our Austin based engineering team.

So how are we applying AI to industry? One example is through the pioneering application of predictive, machine learning techniques to security data. For example, algorithms that can provide a forecast for potential attacks based on an analysis of myriad factors, which can include observed patterns, unstructured data analysis and non-local sensors. While machine learning gives an analyst a “leg up” in finding malicious traffic, threat research activities are still required and can be very tedious. The good news is that when ML-based predictive analytics are combined with natural language processing (NLP), a capability SparkCognition uses extensively in its Cognitive Pipelines, the result is an augmentation of the analyst’s ability to distinguish real malicious traffic from anomalous outliers. Instead of the analyst engaging in searches and reading literature manually, algorithms are combing through massive collections of text and making these determinations automatically. This is just one way in which Cognitive Pipelines combine multi-algorithm workflows, leveraging different AI techniques to automate more of a human security expert’s workload.

Applying AI to IoT is the next big expansion for the wider information technology market. Players that have a significant position in the 4-5 billion device laptop, smartphone, and PC market will be confronting a 10-20X market expansion within the next few years. If they cannot maintain relevance to IoT then even if they maintain their current footprint, they will be left with a minuscule share of the newly expanded market. They will become irrelevant. Not unlike Blackberry, once a market-share giant, that ignored the move toward touch-based smartphone technology and was left with minimal market share as the new market expanded and made it irrelevant.

Entrepreneurs looking to move into the IoT space need to keep this overall shift in mind. They have many opportunities to rethink the IT industry and redefine what it’s all about. All the giants currently standing can be disrupted. What does storage look like in the age of IoT? What does networking look like? Compute? Analytics? Algorithms? User Experiences? Everything will be rethought. There is opportunity everywhere.

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We are at the cusp of an exciting time when Internet connected things – big and small – are about to be integrated with autonomous software powered intelligence. This will result in amazing things that will come pretty close to our conception of magic. Self-driving cars are just an early preview. Autonomous passenger drones such as those demonstrated by Chinese company Ehang will be our magic carpets, increasingly automated warehouses and factories run by robots such as those built by Kuka, our Aladin’s lamps, and inexpensive collaborative multi-purpose desktop fabricators like MakerArm, Santa’s elves. All this is coming our way soon. But as the physical and the digital are melding together, cyber threats can and will have real world consequences. Autonomous cars can be hacked, drones can be crashed and robots commandeered. Perhaps the most important element in fulfilling the amazing promise of AI-powered IoT is to have a secure infrastructure that ensures that the benefits in this brave new world outweigh the risks. That is precisely the goal we’ve committed ourselves to.

Amir Husain, recognized as  Austin’s Top Technology Entrepreneur of the Year and Onalytica’s Top 100 global Artificial Intelligence influencers, is an American serial entrepreneur and inventor based in Austin, Texas. He is the Founder & CEO of SparkCognition, Inc. an award-winning Machine Learning/AI driven Cognitive Analytics Company, a Member of the Board of Advisors for IBM Watson, and a Member of the Board of Advisors for The University of Texas at Austin, Dept. of Computer Science. Amir holds over 40 awarded and pending US patents.

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