The evolution of AI — How it broke into the mainstream economy

“A year spent in artificial intelligence is enough to make one believe in God.”

— Alan Perlis, recipient of the first Turing award.

Atheists might not take kindly to this statement, but it does a good job of highlighting AI’s potential to transform our society and enable our progress to the next frontier of human evolution. However, it is imperative to get a deeper understanding of AI’s origin and development, before one can delve deeper into its potential applications.

The story of Artificial Intelligence’s origin

The Oxford dictionary defines it as:

‘The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.’

Even though modern computing systems are performing certain tasks which are beyond human intelligence, it is necessary for us to look at the roots of AI evolution to fully appreciate the progress made so far.

The initial applications of AI emerged in the 1940s and 50s with programs built for breaking codes and playing games such as checkers and chess. After Alan Turing had proposed the famous Turing Test to measure machine intelligence and Isaac Asimov postulated the ‘Three Laws of Robotics’, it was only a matter of time before the field of AI became formalized.

John McCarthy, an American computer scientist at MIT, first coined the term ‘Artificial Intelligence’ in 1956 when he invited a group of researchers to a summer workshop in Dartmouth to discuss what would subsequently become the field of AI. MIT cognitive scientist Marvin Minsky and others who attended the workshop were extremely optimistic about AI’s future and predicted a breakthrough within a generation.

However, they didn’t realize that solving such a momentous problem will not be a simple task, especially after government funding for AI projects dried up in response to various critical media reports. The key challenge was to build hardware with the requisite computing power and create a large enough database with sufficient information about the world.

The rise of the expert systems and the knowledge revolution resulted in a mini-revival of research in the 1980s as funding increased due to the competition between the British and Japanese governments. However, AI recaptured popular imagination in 1997 when IBM’s Deep Blue supercomputer defeated the Russian grandmaster Garry Kasparov in a chess tournament.

While the public marveled at this technological breakthrough, researchers were not surprised by the fact that the Deep Blue’s computer was 10 million times faster than the Ferranti Mark 1 program that Christopher Strachey taught to play chess in 1951. This exponential increase was predicted by Moore’s law, which stated that the speed and memory capacity of computers doubles every two years. Hence, the first obstacle of insufficient computing capability was slowly being overcome.

AI’s march in the 21st century

Surprisingly, throughout the 2000s, researchers and scientists still avoided using AI to describe their work as they feared being labeled ‘wide-eyed dreamers’ after the unrealized promises about the application of AI in the commercial world. But the smartphone decade has completely removed the reservations prevalent in the community.

When IBM’s Watson won in Jeopardy against the reigning human champions in 2011, it was another reminder that AI technology was ready to break into the mainstream economy. The smartphone revolution gave us the ability to access large amounts of data via the internet and process it using faster computers and advanced machine learning techniques (where the computer automatically learns from data). The synergy generated from the simultaneous occurrence of these important breakthroughs has resulted in AI applications which are successfully solving many business problems.

Machine Learning has become so integral in E-Commerce in areas like visual search, product recommendations, and automated tagging, that Amazon stated, “Without ML, Amazon couldn’t grow its business, improve its customer experience and selection, and optimize its logistic speed and quality.”

The financial sector, notorious for its reliance on outdated technology, is also witnessing AI’s penetration into their operations. Goldman Sachs is using the Kensho platform whose ML systems mine through the web and use statistical computing and natural language processing to assess correlations between world events and asset prices.

Healthcare, which is a very challenging sector, is benefitting from AI’s ability to transform existing paradigms in areas like diagnosis and processing data from Electronic Medical Records (EMR). For example, Google’s AI model can already detect diabetic retinopathy with a level of accuracy on par with human retinal specialists.

However, what truly marks the indispensability of AI’s role in human society is the extent of its involvement in our daily lives. We have started relying on intelligent assistants like Apple’s Siri and Google’s Assistant, which use natural language to answer our questions, make recommendations and perform actions. Gmail uses smart compose features to manage our emails, Uber uses AI driven pricing models to help us book cab-rides and Tesla has already introduced self-driving functionality in its electric cars.

Any discussion on AI would be incomplete without a separate mention of Google and how it has reorganized its business strategy by positioning itself as an AI-first company. It has placed AI at the core of the Android OS functionalities with features like Google Lens and its ML toolkit for app developers. More importantly, their Tensorflow framework and the TPU processors are built to deliver AI as a service as they enable engineers to build and train ML models in the cloud and run actions in embedded systems.

Interestingly, some observers point to the following statement to back up their claim that Google has always been an AI company masquerading as a search company -

“Artificial Intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and give you the right thing.”

-Larry Page, Founder, Google

What lies in store for us– an AI managed future?

Although this might seem as monumental progress from an outsider’s perspective, we are only getting started when it comes to realizing the true potential of AI. The first stage of AI has focused on building applications leveraging Artificial Narrow Intelligence (ANI) which is limited to only one functional area, like infants. The second stage, Artificial General Intelligence (AGI), is at an advanced level: it covers fields like reasoning, problem-solving and abstract thinking, which is mostly on par with adults.

We are already seeing clear signs of the onset of AGI as the modern tech giants are devoting significant resources to AI R&D. DeepMind’s Alphazero has already mastered three games Go, Chess and Shogi, with a surprisingly innovative and risky gameplay strategy. Alibaba’s language processing AI has outscored top humans at a Stanford University reading and comprehension test, scoring 82.44 against 82.304 on a set of 100,000 questions.

Influential technology and business figures believe that we are at the cusp of completely transitioning into the second stage of AGI — the beginning of true autonomy as machines and software will start untethering themselves from human supervisors and embark upon their fateful path as sentient beings. Even though such predictions might be viewed with a touch of skepticism, there is no doubt that the market for commercial AI applications will grow rapidly in the next 5 years.

On a final note, it would be prudent to not make any presumptions about the speed of AI development as we are at an inflection point in the history of technological evolution.

“The pace of progress in artificial intelligence (I’m not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast — it is growing at a pace close to exponential.”

-Elon Musk, CEO, SpaceX and Tesla (2014)

In our next blog, we will touch upon the key concepts of AI and Machine Learning which will enable us to develop a better understanding of the AI market and its future applications.