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.

With improvements in facial-recognition technology and the increasing popularity of smartphones, the threat to one's privacy unexpectedly posed by Internet photos posted by strangers is growing day by day. To protect against unwanted scrutiny, trading company Nissey Corp., based in Sabae, Fukui Prefecture, has developed special glasses that thwart electronic facial recognition. The Privacy Visor is a set of white titanium goggles with lenses that have a mesh-like surface providing many tiny spaces to see through. "Since the view might not be clear, driving or riding on bicycles must be avoided," a Nissey spokesman warned. The glasses were jointly developed with the National Institute of Informatics, a research institute dedicated to information technology.

I still ponder on this question "Under current US laws, can I possibly win a suit against a law firm for poor representation because they used AI on my case and I lost my case that ended up causing me to lose millions and impacted my reputation? And, could this firm lose their license through the state board resulting from my claim & suit as well as others who claimed poor representation due to AI used on their case?" I believe they can under current laws. Last week, BigLaw firm BakerHostetler announced that it was partnering with ROSS Intelligence to bring artificial intelligence to its Bankruptcy, Restructuring, and Creditor Rights practice. ROSS will be used to help BakerHostetler's non-robot lawyers research more quickly and intelligently.

Google is offering Parsey McParseface and SyntaxNet to interested developers that want to integrate artificial intelligence to their application and system projects without having to build their own platform from scratch. SyntaxNet will be an open-sourced neural network framework that can be used by developers to create software that could have the capabilities to understand how the human language works. Google is also rolling out Parsey McParseface as a parser for the English language. AI is a highly-complicated subject but there is no doubt that the advancements in technology has improved the platform. Digital assistants such as Siri, Alexa and Cortana are products of good AI technology.

A TensorFlow implementation of the models described in Andor et al. (2016). At Google, we spend a lot of time thinking about how computer systems can read and understand human language in order to process it in intelligent ways. We are excited to share the fruits of our research with the broader community by releasing SyntaxNet, an open-source neural network framework for TensorFlow that provides a foundation for Natural Language Understanding (NLU) systems. Our release includes all the code needed to train new SyntaxNet models on your own data, as well as Parsey McParseface, an English parser that we have trained for you, and that you can use to analyze English text. So, how accurate is Parsey McParseface?

Continuing the topic started last week, this week I would like to show you how these little lightweight programs called chatbots are taking their own place within organizations, doing no less than increasing employees productivity and streamlining business processes. Currently, chatbots are very popular in the consumer space. From the business perspective, eCommerce, delivery and transportation businesses boost their business opportunities by letting their end customers order services and goods even more conveniently. But if you look very closely, you will see that bots are slowly taking over the enterprise space as well, and I'm not talking about company employees using third-party bots via enterprise messaging apps like Slack. I'm talking about enterprise companies building their own corporate chatbot to add value to their product, create a better interaction experience for their B2B customers and improve own business processes.

Today, Google introduces Parsey McParseface -- a free new tool, born from Google's research division to help computers better parse and understand English sentences. "We were having trouble thinking of a good name, and then someone said, 'We could just call it Parsey McParseface!' So… yup," says a Google spokesperson. Parsey McParseface is a piece of a larger framework called SyntaxNet, itself a big part of Google's popular home-built TensorFlow software for building artificial intelligence, as explained in a blog entry. With this release, any developer anywhere can download, use, and even start to improve Google's tools in their own software. One of the biggest problems in artificial intelligence, today, is that speech recognition by computers may be better than ever, but they still have trouble understanding exactly what we mean. After all, language is complicated: Consider that "Buffalo buffalo Buffalo buffalo buffalo buffalo" is a 100% gramatically correct sentence in American English.

Most people don't realize this yet, but artificial intelligence is about to be integrated into everything. The technology, although decades old, has recently become advanced enough that a skilled programmer, even one that's not an artificial intelligence expert, can start integrating it into their consumer-facing products that you touch and feel everyday. It means we're not only going to start talking to the computer instead of pushing buttons, but the computer is going to start talking back! So, out of all the things we can tell our computer, why would we tell it our most intimate thoughts and our deepest secrets? The robot doesn't care if you are inexperienced, unhealthy, or financially illiterate.