Rajendra

I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...

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I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing

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Is Artificial Intelligence Over-Hyped In 2017?

By Rajendra |Email | Sep 28, 2017 | 17784 Views

Whether or not artificial intelligence (AI) is overhyped depends upon which community you are talking about.

If you are talking about the academic research community, its not over-hyped. There have been major breakthroughs in AI over the past couple of years, and the celebration is certainly justified.


In my own area of object recognition, we went from 35% accuracy (mean average precision on Pascal VOC) to above 65% in just 3-4 years. Previously, we were advancing by 1-2% per year, despite object recognition being the hottest area of computer vision with the largest fraction of papers appearing in top conferences every year. Deep learning also made major breakthroughs in reinforcement learning, which is what yielded successes in general Atari game playing, and beat world grand master in Go decades ahead of expectations! It has finally enabled speech recognition to achieve useable levels of accuracy.

On the other hand, if you are talking about commercial ventures, then yes. It is over-hyped. Far too many VCs and big company VPs, are funneling money into tech projects that have just been rebranded with the AI tag. This is not any different from the electronics and the web bubbles of a couple decades ago. Having a string of if-then-elseifs in your code doesn't make it AI.

I have talked to otherwise technically knowledgeable VP-level people at big companies, who after listening to Yann LeCun's talks presume that atleast supervised learning is completely solved. Well, if supervised learning is solved, and we have tons of money, we can just throw money to get tremendous amounts of data labeled and solve any problem, right? Wrong! When Yann LeCun says a problem is solved, he is largely speaking a researcher's mind. If you get 80% object recognition accuracy on roads, you have not solved the autonomous vehicles problem!

Just listen to the advertisements of a computing giant of former years hyping up their database search program, and you will realize how the general public and industry execs are being fooled! In summary, if you don't know exactly how you will make money from a technology and you keep hearing about that technology all the time, you are likely in a bubble!

Source: Forbes