Last month, Google DeepMind's AlphaGo programme famously defeated professional Go player, Lee Sedol, in what has been described as a breakthrough for artificial intelligence research. Unlike previous gaming computers, such as IBM's chess-playing Deep Blue which defeated Garry Kasparov in 1997 and IBM's Watson which won Jeopardy! in 2011, AlphaGo implements a fundamentally different type of AI search algorithm that leverages neural networks trained with a combination of supervised and reinforcement learning. Previous game-playing computers relied heavily on deterministic search techniques custom built for a narrow problem domain. For example, IBM's Deep Blue, though expert at chess, would have to be entirely reprogrammed to play checkers. The novelty of AlphaGo's search algorithm lies in its use of deep neural networks, a method of programming that does not rely on any specific domain information.

According to Gartner, "Big Data Discovery" is the next big trend in analytics. Each of these areas has seen explosive growth, but there are clear upsides and downsides to each. For example, Data Discovery excels in ease of use, but allows only limited depth of exploration, while Data Science provides powerful analysis but is slow, complex, and difficult to implement. Since the disadvantages of the three technologies map to nicely to the advantages of the others, they are now starting to blend, and Gartner believes Big Data Discovery will be a distinct new market category by 2017. The emerging Big Data Discovery tools will be simpler to use than data science products and accessible to a wider ranger of users, with more powerful manipulation of a wider variety of data sources. According to Gartner Analyst Joao Tapadinhas, these tools will be used by new "Citizen Data Scientists" who marry the skills of traditional business analysts with some of the expertise of expert statisticians.

I'm impressed with Tyler Vigen for his work popularizing Spurious Correlations. He has found an effective way to convey an important message. Namely that correlation does not equal causation. Lots of things are correlated but that doesn't mean that they have anything to do with each other. To create his graphs Vigen indulges in "Data Dredging… a technique used to find something that correlates with one variable by comparing it to hundreds of other variables" (Vigen, 2015, page xii).

Google's work in artificial intelligence is impressive. It includes networks of hardware and software that are very similar to the system of neurons in the human brain. By analyzing huge amounts of data, the neural nets can learn all sorts of tasks, and, in some cases like with AlphaGo, they can learn a task so well that they beat humans. They can also do it better and in a bigger scale. AI seems to be the future of Google Search and of the technology world in general.

Artificial intelligence (AI) is the buzzword in almost all industries. Decision-makers want to make use of massive data they get from various sources. This is where data analytics and artificial intelligence come into play. According to Reportbuyer, the AI market is estimated to grow to 5.05 billion by 2020 at a CAGR of 53.65 per cent from 2015 to 2020. This growth can be attributed to factors such as diversified application areas, improved productivity and increased customer satisfaction. The AI market in APAC is expected to grow at the highest CAGR between 2015 and 2020.

One of our useful feature inside Marketeer is the way of the Machine Learning works helping you to do effective customer engagement. One of this important features is the Lost-User Detection. The list of visitors inside the Conversational Panel, will show you when a visitor is LOST to have effective engagement. Use this tool to convert more at your website! Useful feature to understand is your customer is happy with your service is to know their feedback.

Symantec vice president global portfolio and solutions product management for enterprise security Bhagwat Swaroop (pictured) has been involved in the process of setting a course for the company following the divestiture of Veritas. He told iTWire that Symantec's unified security strategy has four legs: Machine learning is "finding its way into everything we do," he said. Symantec started applying machine learning more than a decade ago, and now has a team of between 30 and 40 people working to apply it to autonomous anomaly detection. Rather than focusing on detecting specific attributes of malware, spam and so on (which the Bad Guys can learn to work around), the idea is to take a more dynamic approach by examining relationships instead. This give "top of the line" detection of new threats, Swaroop said, with the lowest rate of false positives.

Hanson Robotics touted their android, Sophia, at this year's SWXW in Austin, Texas. The android is arguably the most human like robot to date, capable of masking 62 different facial expressions. Fundamentally, Sophia was designed to be "as conscious, creative and capable as any human," according to to CEO of Hanson Robotics, David Hanson. In addition to her various facial expressions, Sophia can recognize people, hold eye contact, carry on intelligent conversations with speech recognition software and is even capable of learning. Sophia is clothed in a patented silicon skin called Frubber, an elastic form of rubber used in robotics.

Microsoft researchers have come up with a novel way of getting computers to tell stories about what's happening in multiple photographs by using artificial intelligence (AI). Today the company is publishing an academic paper (PDF) describing the technology, which could one day power services that are especially useful to the visually impaired. Microsoft is also releasing the photos, captions, and "stories" developed in the research. The new capability is significant because it goes well beyond just identifying objects in images, or even videos, in order to generate captions. "It's still hard to evaluate, but minimally you want to get the most important things in a dimension. With storytelling, a lot more that comes in is about what the background is and what sort of stuff might have been happening around the event," Microsoft researcher Margaret Mitchell told VentureBeat in an interview.

Why, you may ask, is that news? Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov, and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can. Go is played on a far larger board (19 by 19 squares, compared to 8x8 for chess) and has more possible moves than there are atoms in the universe, so raw computing power was unlikely to beat a human with a strong intuitive sense of the best moves.