Yes, to get you to pay attention to what would otherwise be a fairly dense and nerdy thing, Google is using an homage to Boaty McBoatface for one of the software tools it's releasing today. But don't just laugh (or groan) at the name, what Google is giving developers and researchers access to is a big deal. Today, it's open-sourcing something it calls SyntaxNet and a component for it, Mr. McParseface. These are some of the tools that Google uses to understand natural language when you type it into a box or speak to Google Now. SyntaxNet is the overall framework for parsing sentences, called a "syntactic parser."

A product team at Google is working on a hardware device that would integrate Google's search and voice assistant technology, akin to the Amazon Echo, Recode has learned. Google's device will resemble its OnHub wireless router, according to several sources. We don't know if it has a name yet, but internally the project goes by "Chirp." The Information previously reported that Google was plotting a competing version of Echo, a portable speaker with voice assistant tech. Sources said the device is unlikely to launch next week at Google's I/O developer conference, but plans are for it to land at some point this year.

As a leading technologist, Abinash has a vision that Indians can build great product companies provided the government and telecom operators figure out a way to offer free internet for students. AT: It pains me that we have technology focused on selling retail products to consumers. That said, India has the engineering skills to build technologies like machine learning and artificial intelligence. If the product is driven at large corporate then the founder must have great marketing skills.

It is not often that you meet someone who looks at technology as a tool to make an impact on customers and in turn bring returns to business decisions. It is unfortunate that most of the business world puts customers second, but spend enormous amounts of money in acquiring them. The world of IT is not about information capture, it is about the "machine" learning continuously to understand the queries of clients or consumers – of the enterprise – when a transaction is made on the smart phone. Co-founder of Helpshift Abinash Tripathy is a technology proponent and believes that it can improve lives. But, he is vociferously against technology that focuses on trading – like ecommerce businesses that sell on discounts to capture consumer eye-balls.

When you get right down to it, developing vaccines is about data and luck. Scientists start with a set of variables--what drugs a virus responds to, how effectively, and for whom--and then it's a whole lot of trial and error until they stumble upon a cure. One of the most exciting possibilities in medical research right now is how technology like machine learning could help researchers rapidly process those enormous sets of data, more quickly leading to cures. This is already starting to happen: In a study published Wednesday in the journal Macromolecules, researchers from IBM and Singapore's Institute of Bioengineering and Nanotechnology reveal a breakthrough that could help prevent deadly virus infections. With the help of IBM super computer Watson, they hope their finding will soon make its way into vaccines.

The decision tree in the figure is just one of many decision tree structures you could create to solve the marketing problem. The task of finding the optimal decision tree is an intractable problem. For those of you who have taken an analysis of algorithms course, you no doubt recognize this term. For those of you who haven't had this pleasure (he says, gritting his teeth), essentially what this means is that as the amount of test data used to train the decision tree grows, the amount of time it takes to do so grows as well--exponentially. While it may be nearly impossible to find the smallest (or more fittingly, the shallowest) decision tree in a respectable amount of time, it is possible to find a decision tree that is "small enough" using special heuristics.

Chances are, you're already hip-deep in machine-learning applications. It's how Google Photo organizes those Read more

MasterCard Inc. says new machine-learning technology has helped it quickly control three separate cyberattacks that targeted automated bank tellers, limiting the damage to about 100,000 each. The transaction-monitoring system, which also employs data visualization tools, caught the three attacks during the first two months of 2016, according to MasterCard. The company declined to identify the banks. The Safety Net system, rolled out globally late last year, analyzes more than 1.3 billion transactions per day involving MasterCard debit and credit accounts at banks, merchants and ATMs, using algorithms that assess customer behavior in real-time. In the three attacks this year, directed against two U.S. banks and one bank in South America, Safety Net identified anomalies such as large cash withdrawals or transactions outside the usual geographic area for a given account.

Artificial intelligence (AI) is an emotionally loaded term that strikes fascination into some and fear into others. But if we strip it of fantasy and ignore cyborgs and apocalypse, there is a near-term, practical side of AI that is already unfolding. Most humans can recognise a chair because they have learnt what a chair is – they can identify thousands of examples of chairs even if they have never seen that chair before. Instead of memorising every image of what a chair could be, humans learn what a chair is and then apply that to new images and examples of chairs. But how does a computer learn what a chair is?

As much as we love to fawn over artificial intelligence (AI), it's still not great at recognizing and parsing natural language. That's why Google is open sourcing its new language parsing model for English, which it calls'Parsey McParseface.' Before you even ask, the name has no meaning. When Google was trying to figure out what to call its language parsing technology, someone suggested Parsey McParseface; it's a bit like Apple's Liam, which has no clever backstory either. The overall AI model model is called SyntaxNet (please make your SkyNet jokes now); 'ol Parsey is just for English. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May.