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Original article published at The Market Mogul May 8, 2018.

“Artificial Intelligence (AI) is the solution. What is the problem?” This conversation is representative of the pervasiveness of AI. Unnoticed, an AI revolution is upon us. Something has changed in last half decade to make this happen.

Student Becomes Master

Cat, the lion’s mentor in Indian folklore, had hardly finished teaching her student how to hunt when the lion pounced on her. She escaped by climbing a nearby tree, a trick she had not taught the lion. Like the popularity of this creation-creator story, events of AI matching or exceeding human performance are making big news. Last year AI beat top humans in poker, a strategic thinking game, where both the cards and bluffing matter. A similar feat was achieved in 2016 when a computer dethroned Lee Sedol, the world champion of go, a complex Chinese board game. Besides these shocking successes over humans in strategy and board games, there has been a significant improvement in the technical performance metrics of the machines. This is leading to breakthroughs in autonomous vehicles, visual recognition, natural language processing, lip reading, and many other fields, signalling the development of algorithms with skills superior to humans.

In the annual ImageNet Large Scale Visual Recognition Challenge (ILSVRC), machines showcased dramatic progress, improving from an image recognition error rate of 28% in 2010 to less than 3% in 2016. The best human performance is about 5%. Deploying a new computational technique (Deep Convolutional Neural Net) in 2012 brought this marked improvement in image processing and set off an industry-wide boom. Similarly, both Microsoft and IBM increased the accuracy of ‘Speech Recognition on Switchboard’ from 85% in 2011 to 95% in 2017, equalling human performance. Advances in machine learning, pattern recognition, and a host of other technologies will enable autonomous cars without human drivers to drive on roads this year. Alphabet’s Waymo leads the pack of several self-driving car makers in the race.

Classical Versus Deep Learning AIs

The biological brain consists of two different but complementary cognitive systems, the rational (model based, programmed) and the intuitive (model-free, learning through experience). The understanding of how the mind selects between these modes and the interface between intuition and rational thought is beyond the current technology. In the classical approach, AI, and its subsets Machine Learning and Neural Networks, followed the rule-based (if-then) systems imitating the decision-making process of experts ignoring the intuitive part. For complex problems, it was difficult to encode rules and make available the requisite knowledge base. For almost sixty years classical AI had been languishing as human cognition is not based only on logic.

A new approach, based on continuous mathematics, was developed. In deep learning, the new name given to artificial neural networks, the classical logic-based method has been passed over in favour of experimental computation using continuous mathematics. This change has been possible due to the growing infrastructure of ubiquitous connectivity, exponentially increasing computing power, powerful algorithms, and big data sets.

Artificial neural networks, which mimic the biological brain, are used for mathematical modelling. The human brain is imitated using electronically simulated interconnected neurons stacked on the top of each other in layers. The hidden layers perform mathematical computations on inputs. Iterating through the data sets, the output gets generated via ‘back propagation’, using a technique called ‘gradient descent’, which changes the parameters to improve the model. Maybe stumbling on nature’s design, the process works very well perhaps because of imitating intuition as in the human brain.

Astonishing Results and Possible Futures

The results are so astounding that these cannot be explained even by creators of AI programmes. AI systems are like black boxes taking in questions on one side (“Should this autonomous vehicle accelerate or apply breaks on this yellow light? “What is the next move in this board or strategy game? “What are the objects in this image”) and giving out answers on the other side. It will be difficult to explain how the black box works, but it does work. In some situations, it will be difficult to use such an unpredictable, inscrutable, and unexplainable system. This method, using neural networks inspired by the human brain, requires tons of quality data to be useful compared to the very little data needed by humans. Another flaw in deep learning is its inflexibility in using experience learned in one case to help solve another. Humans can learn abstract concepts and apply them in different applications.

The algorithmic, or specialised, intelligence, known as narrow artificial intelligence (NAI), has existed for years and has now got some teeth. It is benefiting humankind in many ways but is also capable of causing large-scale damage to an increasingly digital and interconnected infrastructure. General artificial intelligence (GAI) is a general purpose human-level intelligence and is perhaps a decade away. While GAI can meet challenges such as climate change, disease, and other problems which humans are not able to solve, it will cause economic and cultural upheaval. GAI, undergoing recursive self-improvement, will give rise to a superintelligence, the third flavour of AI. Superintelligent AIs will radically outperform humans in every field and may pose an existential threat to humans. They could appear in the next few decades, or not at all.

Human intelligence is to be understood first before it can be created. With 20,000 AI research papers being published annually, enrolment in AI programmes and investment metrics rising northwards, humanity may be close to accidentally creating a general artificial intelligence.

Here at Komaya, we love keeping abreast of emerging technology and ways that it might help enhance the web presence of our client’s brands.

Thomas CasselberryWhere do you see opportunities for innovation within the web space?

There are far too many areas within web development in need of innovation today. However, as I see it the biggest areas for innovation in this space are:

Big Data – Everyone is talking about big data and how important and impactful it is on business today. However, I’m not reading much about it when it comes to the web. Let’s face it, businesses who are worth their salt have information and some form of branding and/or marketing on the web. That’s a pretty simplistic achievement by today’s standards. The next big leap for business is to move their practices, information access, and even their management to the web. That will mean the need for broader, device independent access, support for heterogeneous data sources both big and small, embracing the mobile user base regardless of deployment preference: on-premise or cloud, and a lot more use of machine learning and predictive analytics geared toward real-time decision making. All of this encompasses our use of what’s called Big Data today. However, the innovations surrounding the use of it today are small and will pale in comparison to what the future holds.

Web Intelligence – As our knowledge of design and user experience expands, we begin to expand our belief system; re-examining what is and isn’t possible in the world wide web. We already employ intelligent algorithms used for machine learning and predictive analytics.

However, I envision a world where those same algorithms, spread across thousands of source systems, will join into a global intelligence network providing behavior pattern recognition, experience insights, and even pattern-based categorization.

Yes, the web is about to become a whole lot more intelligent and Komaya will be right there helping to shape it, mold it, and to help our clients benefit greatly from it.

Performance – I believe that over the next 3-5 years we will see vast improvements over the current forms of image and video compression of today. Development tools will be smarter and automatically analyze images to find the sweet spot, such that the quality is high enough and the file size is as small as possible. More than that though, web servers of the future will work harder and smarter and will have built-in features that make experience and performance decisions on-the-fly. Those server-side algorithms will process each element of a page transmission and evaluate things like:

  • What is the client type?
  • What is the overall page size being requested?
  • Do images need existing transparency?
  • Do images need their animated elements?
  • Do images contain non-visible data?

and will be able to act accordingly to ensure the down-stream clients, regardless of type get the best possible speed and visual experience. Rest assured that every innovation we see between now and even 5 years from now will itself lead to even more opportunities. It’s an exciting time to be in the web space.

How will sites of the future effect revenue?

The short answer is they already do in some very big ways. As new web standards emerge, we see a continual need from our clients to include more and more visual elements. These changes are exciting and new and draw more and more traffic to their sites, which is good! More traffic can equate to more revenue. However, more imagery equates to bigger page sizes which can become big performance problems very quickly. Page performance effects revenue, plain and simple. Small sites, like AutoAnything, cut their load time in half, and saw revenue grow by 13 percent. Large sites, like Amazon have shown that for every 100 milliseconds of performance slowdown, they experience a 1 percent drop in revenue. This is especially true for mobile users. Large pages mean long load times and poor perceived performance. While that does mean big money for the mobile carriers who are all too eager to cash in on the data plans, it also means a lot of frustration for downstream mobile users which equates to less money for those sites as traffic is driven away by poor performance. Sites of the future will have all of the essential elements in-check, striking a good balance between stellar visual experience and high performance.

How will Komaya’s products and solutions be different five years from today?

Current trends are pointing toward a world in which the web plays larger, more relevant and even strategic roles in everyday business. It’s no secret that web implementations are as varied as the sands in the Sahara. Today’s businesses are already seeing the need to expand their web presence to include social, marketing, and other such information. It’s not a big stretch to say that super visual, interactive, and data oriented sites will emerge as the new normal in the next couple of years. Those exciting new sites will have elements that mix state-of-the-art visualization with data that spans a variety of source systems, and languages, each tailored to the user’s expectations and experience. Yes, it’s apparent that the need for smarter, real-time, on-the-fly operations, data presentations, and visualizations becomes the new norm, even for smaller businesses in which staying alive and continuing to be competitive becomes paramount.
Komaya is gearing up to meet these challenges head-on. In fact over the next three to five years we’ll have sites that employ a wide variety of visualization and data technologies with incredible performance! We’ve got algorithms that interpret or infer what a users’ needs are and make requests to cache necessary data preemptively. I think that’s enough of a peak behind the curtain for now though.

What is the most exciting part of your job?

There are many exciting elements in what I consider my job. Not the least of which are the many opportunities I have to interact with our prospects and clients. I really do enjoy helping them realize their dreams and see their successes! A close second is the opportunity to interact and rub shoulders with some of the smartest developers in the world. There are so many opportunities in front of us. From technologies to explore and employ, to stale areas of web design ripe for innovation, there are far too many variables for things not to be constantly exciting and new around here. Our very existence depends on our ability to make our clients’ visions a reality. That means that things that seem impossible today, are the very things we’re toying with. The goal for all of us at Komaya is to make today’s impossibilities tomorrow’s possibilities and even realities. I believe that we will be a key player in revolutionizing the way we think about web solutions, their varied implementations, and much more. You see, it doesn’t really matter what’s impossible today. To quote Lewis Carroll’s Through the Looking Glass: “Why, sometimes I’ve believed as many as six impossible things before breakfast.”