The pursuit of artificial intelligence (AI) dates back to the great philosophers who believed that they could mechanise the process of thinking. This gave birth to mechanised calculations, which in turn, led to the development of the first computers. The growth of modern AI started in the 50s, spurred by the discovery of neurons in the brain.
In the 1950s, Alan Turing published a landmark paper, wherein he speculated the possibility of a “thinking machine”. With computers becoming more available, scientists realized that machines that could also work with symbols—the essence of thought. The first attempts at AI were focused on reasoning and natural language and solutions based on simplified models of the world. The early successes were a robot that could stack blocks and a machine that could construct simple sentences and do basic planning. However, these early developments were not sustainable because computing power and memory were limited, whereas data processing requirements were immense. Scientists had also underestimated the extent of the challenges.
AI received a shot in the arm in the 1980s with the development of expert systems i.e. programs that solve domain-specific problems. The key here was usefulness as the expert systems addressed real-world problems in specific areas. There was also the realisation that AI could be achieved only by massive amounts of data and computation.
AI’s evolution during the 1990s has been steady, with some innovations bettering humans in areas requiring considerable reasoning, logic and cognitive abilities.
IBM’s Deep Blue beat Garry Kasparov in 1997, the first driverless cars underwent successful runs, and IBM’s Watson defeated Jeopardy champions. In 2016, Google’s AlphaGo defeated a world-class player in Go, a Chinese game considered more difficult to master than chess. The earlier pursuits were largely academic, whereas later the focus shifted to commercial gain.
Widespread applications in various sectors
AI has had ripple effects, mainly on computer science and information analytics. It has applications in areas like data mining, industrial robotics, logistics, speech recognition, banking software, and Google search. Today, AI is present in many interactions that we consider an essential part of our daily lives. It powers Siri, Cortana and Google Now— the key voice-based interaction agents for our smart phones. It is present in the cloud services, healthcare, robotics, and marketing and communication insights. AI-based apps power many of our smartphone apps for document organisation and management, schedule coordination, and natural language processing.
In finance, AI is used for fraud detection, operations optimisation and trading. In healthcare, it is used for image interpretation and medical diagnosis. In the communications industry, it appears as online chatbots and online assistants. In aviation, AI technologies are used to train air traffic controllers (ATC), in speech recognition and in aircraft design. It is employed in optical character recognition, handwriting recognition, speech and face recognition, virtual reality and image processing. It also finds application in fields like automated reasoning, data mining, robotics, hybrid intelligent systems and intelligent agents.
Artificial intelligence in India
Although India is in a position to directly implement AI-based systems that will drive our economy, it has not been adopted on a large scale. The technology can also have a huge impact on traditional sectors such as auto manufacturing, healthcare and banking. Some Indian tech majors have embraced AI, like TCS (Ignio), Infosys (AiKiDo and Mana), and Wipro (Vicarious, an AIbased company in California). However, it is the start-up ecosystem that is taking up AI in a large way.
AI startups in India
There are a few Indian AI start-ups—Niki.ai, Arya. ai, Snapshot and vPhrase—that have been making their mark globally. Niki.ai runs AI-powered chatbots that simplifies the online ordering experience. It is the first AI-powered smart purchasing assistant in the world and has received an investment from Ratan Tata’s fund. On the other hand, Arya.ai has been chosen as one of the 21 companies globally that work on standout innovation. Arya.ai provides AI tools that developers can use to make their own robots. vPhrase analytics helps companies communicate insights from their data in their own personalised way. With the interest in AI only set to increase, India is bound to have more start-ups in the space doing breakthrough work.
Dearth of talent in AI in India
In terms of talent, AI is similar to the semi-conductor industry of the 1950s. A lot of work has been done in universities for many years, even as commercial companies ignored AI. However, with the emergence of faster computing, all-pervasive mobile phones, increasing human-computer interactions and an emphasis on automation, companies are seeking AI expertise from the academia. Indian talent in AI is witnessing a strange scenario: the few people in the sector are experiencing very high demand, almost giving them unicorn status, but supply remains limited. The problem is an inability to find the correct mix of technical skills and cultural fit. Companies are looking to the West to find people who have the requisite expertise. Not surprisingly, it is Google, Microsoft and other Silicon Valley behemoths that are the prime hunting grounds for talent. The brain drain syndrome appears to be happening again, but in reverse.
In a world characterised by automation and insightdriven decisions, artificial intelligence and its offshoots— deep learning and machine learning—are here to stay in a ubiquitous, transparent and seamless manner. With driverless cars and machine bots fulfilling shopping orders becoming more common, we can expect the demand for AI talent to increase.