I work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First. ...Full Bio
I work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First.
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Artificial Intelligence Timeline: Infographic
2018 promises to be a good year for Artificial Intelligence
The year 2017 proved to be very vital for the development of artificial intelligence. There was a strong build-up of academic whispers, research breakthroughs and there was public based policy discussion. Suddenly, everyone began to take interest in AI, talk about it and reflect over how it could be used in human society. Artificial intelligence began to get used in all areas ranging from healthcare to art & much more.
Overall, there were three important developments in AI that took place in 2017.
The first, was the development of Google Deep Mind's AlphaGo Zero.
AlphaGo Zero built on the earlier astonishing success of the AlphaGo program, which mastered the game of Go - an East Asian game widely believed to be significantly more complex than chess. AlphaGo was taught how to play the game through a database of hundreds of thousands of videos of humans playing Go. This method of training AlphaGo is generally indicative of the process by which AI has been achieved thus far - extremely data-intensive, and dependent to a great extent on humans "teaching" the program.
AlphaGo Zero, however, attempted to move beyond such data dependence by making the program teach itself how to play the game of Go. There was minimal human support, and in Google's own words, the program "learns to play simply by playing games against itself, starting from completely random play". This is a significant breakthrough for the field of AI for two reasons. First, as pointed out by Demis Hassabis, the chief executive officer of Deep Mind, it means that future developments in the field need no longer be constrained by the limits of human knowledge or the quality of the data available for training. Second, the overreliance on data to fuel AI developments has increasingly concentrated new research in a handful of big tech companies: Google, Apple, Amazon, Baidu and Alibaba. AlphaGo Zero, by making potential advances less dependent on access to data, could make research more dispersed.
Second, 2017 was also the year when countries across the world began putting AI at the heart of their future plans and policy measures. China released a plan to turn itself into an AI superpower by 2030, Russian President Vladimir Putin noted that "whoever becomes the leader in this sphere, will become the ruler of the world", and India set up its own AI Task Force to study the possible effects of AI on a variety of economic and social spheres. Alongside, the military effects of AI were recognized as a question of increasing relevance for the international community. The UN held the first round of formal talks on the question of Lethal Autonomous Weapon Systems - weapons that can theoretically act independent of human control via AI technologies, in November. Further talks on this issue have been scheduled for February and March.
Third, an interesting facet of the conversations surrounding AI in 2017, was the climbdown in the latter half of the year from the earlier exuberance, often misinformed, of the capabilities of AI. An increasing number of AI researchers and developers began pointing out that in spite of the significant technological leaps in the last few years, AI is in fact not as smart as has been widely reported and presumed. AI as it stands right now is "dumber than a five year old, no smarter than a rat". Historically, AI has had numerous boom- and-bust cycles. The current boom cycle started roughly in 2012 with the publication of a set of papers which showed that the then theoretical idea of "deep learning:" was now practical. However, last year an increasing number of academics and researchers began arguing that current AI advancements have in fact plateaued, signalling the possibility of a new bust cycle. If so, a new generation of breakthroughs is necessary to continue powering the AI euphoria.
In 2018, it is necessary to talk about AI within the contours of the reality of the technology and its present capabilities. An honest conversation about the possible benefits and drawbacks of AI cannot be undertaken under a cloud of hype and hyperbole - no "killer robots" and no visions of a robot-ruled future. For this, it is also necessary to move past the idea of AI being a replacement for humans across the board, and begin having a deeper conversation about its effectiveness as a tool in the hands of humans.
Presently much of the discussion about AI has been in the context of Western nations. However, the impact of AI is going to be felt globally. In 2018, it is therefore important for researchers & other academicians to study the impact of AI in other countries like India as well. This has begun in China, where the state now views AI as a technology central the growth & development of the nation. China however wishes to use it to its own advantage. A similar effort needs to be made by India by having an active collaboration between the government, industry, academia & others. They need to figure out how AI will impact the economy, what are the ways in which it could be used & how they can become a part of this revolution.