InformationWeek.com: News, analysis and research for business technology professionals, plus peer-to-peer knowledge sharing. Engage with our community. Facebook is using our data to build the 'world's best' Artificial Intelligence lab. · Elon Musk: Artificial Intelligence Poses 'Existential Risk' Elon Musk, the billionaire scientist behind Tesla Motors and SpaceX, made a dire warning over.

AI leap in India. The rise of a technology has Bill Gates issuing warnings of an apocalypse. Elon Musk, too. Even Stephen Hawking. What’s worrying these technologists? It’s Artificial Intelligence or AI, an idea whose time has come—it is incubating in science labs and being deployed by start- ups and industrial units alike. Why are Gates and Co.

Specifically, it’s over machine learning, an early form of AI that has in recent years become mainstream, causing both delight and nervousness among AI experts and technology companies. AI involves building computers capable of taking smart decisions by themselves, the way humans do. Machine learning and various other sub- fields such as deep learning are the means to achieve AI. Google announced this week that it is rethinking all its products to base them on AI; it has created a new unit called Google. The revival of interest in machine learning has been driven by a confluence of factors, such as the massive increase in computing power, emergence of neural networks (connected transistors that replicate the structure of neurons in the human brain) and the easy availability of vast amounts of data, thanks to the Internet.

Compared to AI leaders in the Silicon Valley and China, India is a laggard but even here, nearly 3. AI, according to Tracxn, a start- up tracker. Among dedicated AI- only Indian start- ups, 2. Kalaari Capital, a venture capital firm.

Life 3.0: Being Human in the Age of Artificial Intelligence [Max Tegmark] on Amazon.com. *FREE* shipping on qualifying offers. New York Times Best Seller How. Artificial intelligence (AI): The ability of a computer to perform tasks commonly associated with intelligent beings.

Internet companies tap machine learning techniques for a range of uses—to recommend products for you, for instance, or to predict where cabs should be placed so that when you open your cab- hailing app, there’s one a couple of minutes’ drive away. Healthcare start- ups use AI to help hospitals make speedy and accurate blood reports and medical diagnoses, saving lives. Others get fashion brands and retailers to buy the right quantities of stock. Suddenly, AI is everywhere.

Lounge looks at 1. AI and machine learning techniques to transform healthcare, education, auto and retail. Their success is far from assured. They struggle to find quality talent; they face stiff competition from other AI start- ups; their solutions haven’t yet stood the test of time (most are less than five years old); and they are vulnerable to a variety of other factors that typically bring down start- ups, AI or not. Given the number of AI start- ups, the list is far from comprehensive. Yet the work that these 1.

How does this work? Traditional code writing entailed programming computers, essentially telling computers what to do. With machine learning, computers are taught to do things themselves.

Pedro Domingos, a professor in computer science and engineering at the University of Washington, puts it fittingly in his book, The Master Algorithm: How The Quest For The Ultimate Learning Machine Will Remake Our World: “The Industrial Revolution automated manual work and the Information Revolution did the same for mental work, but machine learning automates automation itself.”This is what has people worried—and thrilled. The likes of Gates and Musk fear that machines that learn to think for themselves may become smarter than humans and start taking control of things—the stuff of science fiction. But others such as Domingos believe it will lead to a near- utopian state where people, freed of chores and menial work (now automated), will pursue things that truly excite them. No matter which side of the fence you are on, there’s little doubt that AI represents potentially the most disruptive leap in technology in decades. Apart from disrupting incumbents across businesses, AI may worsen a major socio- economic headache for India: employment. The threat from automation to engineering jobs in Indian IT companies is well documented. But IT is by no means the only business where jobs are at risk.

Automation may be a threat to 6. India, according to an October 2.

World Bank report. Watch Pretty Cool Too Putlocker. Even Domingos, who expresses a never- failing belief in the potential of AI to do good for humankind, acknowledges that the technology is likely to make many jobs redundant. Case in point: One of the 1.

That represents only a mild threat from AI, especially in a country that is already failing to meet the growing demand for jobs. Investors and experts in AI privately worry about this threat—but they aren’t worried enough yet to look for solutions.

That must say something about where their priorities lie—and about the disruption that Artificial Intelligence will cause.—By Mihir Dalal***Netradyne, Bengaluru and San Diego, USInvestment: Raised $1. Rs. 10. 2. 8 crore) from Reliance Industries Ltd in June 2.

The team: Founded by Avneesh Agrawal, a former Qualcomm Inc. India and South Asia, and David Julian, a former principal engineer at the US- based chip- maker. Intelligence factor: Netradyne’s Driveri, a powerful camera that analyses driving patterns and can help determine the cause of an accident.

The soap- bar- sized device is attached to a vehicle’s rear- view mirror and rests on the inside of the windscreen, pointing towards the road. In July 2. 01. 5, Agrawal, along with his long- time friend and colleague Julian, set up Netradyne, wanting to tackle that intractable problem of the modern world—road accidents. Netradyne’s main product is Driveri, which packs in four high- definition cameras generating 3.

LTE network), has a global positioning system, gyroscope sensors and accelerometer, and a Nvidia processor, the same one that is used in the i. Phone 5. The unit captures visuals of the car’s surroundings, analyses driving patterns and stores the data on a cloud platform. It uses machine learning and deep- learning systems to analyse the entire scene in front of the car: traffic lights, stop signs, objects in its course, distance to every other vehicle, relative speeds and direction. The data generated enables the platform to determine whether the driver is overspeeding or driving rashly, adhering to traffic rules, is potentially drowsy or drunk, or taking multiple halts along the route. In the event of an accident, it also sends real- time alerts to the fleet operator. According to Agrawal, similar technology is used to power autonomous car projects across the world, such as those being developed by Google (Alphabet Inc.), Uber Inc., Robert Bosch Gmb. H and large car- makers like Toyota, Volkswagen Group and Daimler AG. Doc Martin Season 2 Episode 6 on this page.

After testing the product for over 7. Netradyne launched Driveri in the US market in March and plans to launch it in India by June- July.

It recently signed its first US client, Load One, a mid- sized cargo company that operates a fleet of 3. The solution is also useful for retail customers like parents of first- time teenage drivers. Agrawal says Netradyne’s main focus currently is to ensure driver safety. The product is being marketed to commercial fleet operators to enable them to monitor drivers and enhance the safety of cargo.“Using the solution, fleet managers can train drivers on safe driving practices, besides maintaining a close check on valuable cargo.. Watch Switch Putlocker. They can also create a scorecard for drivers and incentivize them on safe driving,” says Agrawal. Agrawal, whose company employs around 6.

Driveri customers to see a significant reduction in the number of traffic violations and accidents; in turn, safer driving would result in greater fuel efficiency and lower maintenance costs. The other big market is insurance.“What we are essentially doing is quantifying risk,” Agrawal says.