Artificial intelligence sounds mysterious to many people, but it has been a part of our life, an expert said at the Third World Internet Conference in Wuzhen, East China's Zhejiang province, on Wednesday. The voice recognition function for mobile internet search used by Baidu, for instance, is an application of artificial intelligence, said Sun Ninghui, director of the Institute of Computing Technology, Chinese Academy of Sciences. The tech company's "Baidu Doctor", which can simulate dialogues between a patient and a doctor, and read large amount of literature and the patient' records, is another example of how artificial intelligence is applied, he added. Besides, artificial intelligence is also used in image recognition and teaching, according to Sun. More applications such as autonomous vehicles would soon enter our life, Sun said, referring to Baidu's driverless vehicle which recently underwent road tests.

Bad hair days may soon be prevented by just looking at your smart phone. Parham Aarabi and Wenzhi Guo, researchers at the University of Toronto Faculty of Applied Science & Engineering, have developed a machine learning algorithm that learns directly from human instructions rather than an existing set of examples. The algorithm outperformed conventional methods of training neural networks by 160 percent and outperformed its own training by 9 percent. The algorithm is seen as a significant leap forward for artificial intelligence as it learned to recognize hair in pictures with greater reliability than that enabled by the training. The two researchers were able to train the algorithm to identify people's hair in photographs--a much more difficult task for computers than it is for humans.

The year 1995 was heralded as the beginning of the "New Economy." Digital communication was set to upend markets and change everything. It wasn't that we didn't recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the "New Economy" could be described at a high level: Digital technology would cause a reduction in the cost of search and communication.

Infosys has made an investment of R14.5 crore in a Denmark-based artificial intelligence start-up, Unsilo. Founded in 2012, this Danish company is focused on solutions in the area of advanced text analysis. Infosys has earmarked $500 million for its innovation fund which invests in start-ups across the globe. Of this, $250 million has been set aside for start-ups in India. "We will partner with Unsilo to bring their artificial intelligence and machine learning technology to our global clients. They join and expanding portfolio of innovative young companies from around the world that Infosys works with to help enterprises drive their digital transformation," said Ritika Suri, executive vice president & global head of corporate development & ventures at Infosys.

Want to play around with Google's AI projects? Well, now you can thanks to a website which makes the company's tinkering with artificial intelligence available for the public to sample. If you head over to the AI Experiments web page, you'll find eight different experiments on offer, designed to illustrate what machine learning can do and appeal to a wider audience (with the option to submit your own work, to boot, if you've concocted anything along these lines yourself). The web-based apps include one which is an experiment in seeing whether a neural network can recognise a sketch. With Quick Draw, you simply doodle something on your touchscreen and the AI gives its best guess as to what that object is.

Once upon a time, Artificial Intelligence (AI) was the future. But today, human wants to see even beyond this future. This article try to explain how everyone is thinking about the future of AI in next five years, based on today's emerging trends and developments in IoT, robotics, nanotech and machine learning. We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments.

Google Photos enhancements provide more incentive to keep memories hosted by Google. The premise of Google Photos is simple enough: one place for all your photos, resulting in a simple way to punch them up or share them. The service's unlimited -- albeit reduced quality -- storage has been a game changer for preserving memories. But Google started hinting at Photos' promise when it introduced tools to simply (or automatically) weave photos into sets of expression, such as collages, movies, or montages that string together photos and clips of video to music. It's similar to what was possible for years with Apple's Instant iMovie feature -- except nobody had time to create that.

The same algorithms that personalize movie recommendations and extract topics from oceans of text could bring doctors closer to diagnosing, treating and preventing disease on the basis of an individual's unique genetic profile. In a study to be published Monday, Nov. 7 in Nature Genetics, researchers at Columbia and Princeton universities describe a new machine-learning algorithm for scanning massive genetic data sets to infer an individual's ancestral makeup, which is key to identifying disease-carrying genetic mutations. On simulated data sets of 10,000 individuals, TeraStructure could estimate population structure more accurately and twice as fast as current state-of-the art algorithms, the study said. TeraStructure alone was capable of analyzing 1 million individuals, orders of magnitude beyond modern software capabilities, researchers said. The algorithm could potentially characterize the structure of world-scale human populations.

We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments. The following proposed list does not want to be either exhaustive or truth-in-stone, but it comes from a series of personal considerations that might be useful when thinking about the impact of AI on our world. Companies like Vicarious or Geometric Intelligence are working toward reducing the data burden needed to train neural networks.

If you're still getting your arms around deep learning, start with the very basics. This video series by Deep Learning TV provides an introduction that assumes no knowledge of math, programming, or statistics. The series starts with neural networks and deep learning concepts and later gets into techniques such as convolutional nets, restricted Boltzmann machines, deep belief nets, recurrent nets, autoencoders, and recursive neural tensor nets.