As you may be aware, we recently boosted our Text Analysis API offering with a cool new feature, Aspect-Based Sentiment Analysis. The whole idea behind Aspect-Based Sentiment Analysis (ABSA) is to provide a way for our users to extract specific aspects from a piece of text and determine the sentiment towards each aspect individually. We've built models for 4 different domains (industries). You can see the domains and the domain specific aspects listed in the image below. We explain it quickly and simply here to help get you up to speed.

Viv is a new digital AI assistance created by makers of Siri. Since co-founder of the artificial intelligent software Dag Kittlaus announced the news, a lot of people are asking what Viv can do and how is it better than Siri. During a conference at TechCrunch, Kittlaus showed the basic voice commands that drive Viv. However, the digital assistance software is currently in development and does not have the voice capability. Viv responded to some complex questions that demonstrated by Kittlause and it is, in fact, better than Siri at understanding difficult sentence structures.

Human language is still one of the most difficult tasks for computers to understand, one that tech giants from Google Inc. to Microsoft Corp. and many startups and researchers are struggling to solve. Today, Google is introducing one more tool in a growing arsenal of artificial intelligence tools intended to unlock the secrets of natural language understanding. The search company is releasing SyntaxNet, an artificial neural network system for NLU systems, into open source. It will be part of Google's TensorFlow open-source library of software code, which allows developers and researchers to create their machine learning models so they can create their own services. SyntaxNet has the code needed to train new language models on a company's or researcher's own data.

Ever find yourself in an endless game of being put on hold and pushing numbers to try to reach a certain department on a customer service call? Ever find yourself throwing your hands up in frustration and shouting, "WHY CAN'T I JUST TALK TO A REAL PERSON?!" This sentiment is coloring the way we use the internet. As messaging apps make their way onto more mobile devices and brands follow marketing trends with their own tools like Facebook Messenger for Business, searching for terms and clicking through multiple menus to find what we're looking for feels increasingly passé every day. It's hard to know which came first--advanced chatbot technology or the mounting use of chat-based apps--but it's clear that we're at an inflection point. What role will chatbots have in serving consumers, and how does their adoption affect brands' current methods of reaching people?

Nvidia's (NVDA) AI technology with Facebook (FB), Alphabet (GOOGL) and Microsoft (MSFT) is powering "superhuman" levels of inference, or artificial intelligence, Nvidia CEO Jen-Hsun Huang said Thursday, after the Tesla Motors (TSLA) partner blasted Q1 views on record deep-learning sales. "The truth is that nobody really knows how big this deep-learning market is going to be," Huang said on the company's earnings conference call. He referred specifically to gains that customer Microsoft was making with AI and deep learning. "The work that recently was done at Microsoft Research, they've achieved superhuman levels of inferencing … of image recognition and voice recognition that's really kind of hard to imagine," he said, "and these networks are now huge." On the stock market today, Nvidia stock rocketed 15% and hit an all-time high of 41.

It's probably not likely, but if you need to stop by a physical bank branch, you might encounter a new kind of teller: the virtual one. Bank of America has implemented ATMs with a new technology called Teller Assist in which customers interact with a live person, but over video chat. Before this full-on technology revolution there are innovations slowly bridging the gap. This seems to be the step between in-person tellers and the advanced future technology of machine intelligence. As machine learning evolves and gets better at understanding human speech patterns, the machine-to-person engagement will probably become the standard of many daily interactions.

An unclassified 2016 Department of Defense (DoD) document, the Human Systems Roadmap Review, reveals that the US military plans to create artificially intelligent (AI) autonomous weapon systems, which will use predictive social media analytics to make decisions on lethal force with minimal human involvement. Despite official insistence that humans will retain a "meaningful" degree of control over autonomous weapon systems, this and other Pentagon documents dated from 2015 to 2016 confirm that US military planners are already developing technologies designed to enable swarms of "self-aware" interconnected robots to design and execute kill operations against robot-selected targets. More alarmingly, the documents show that the DoD believes that within just fifteen years, it will be feasible for mission planning, target selection and the deployment of lethal force to be delegated entirely to autonomous weapon systems in air, land and sea. The Pentagon expects AI threat assessments for these autonomous operations to be derived from massive data sets including blogs, websites, and multimedia posts on social media platforms like Twitter, Facebook and Instagram. The raft of Pentagon documentation flatly contradicts Deputy Defense Secretary Robert Work's denial that the DoD is planning to develop killer robots.

Messaging is the new battleground among powerful tech companies. Facebook, Snapchat and Microsoft are racing to build ever more powerful chat apps, based on artificial intelligence, virtual assistants and bots. Some industry insiders predict that messaging will become the next big computing platform, providing a new way for consumers to do everything from shop online to reading the news. As Google kicks off its annual developer conference near San Francisco next week, a growing number of users, software developers and analysts think Google needs to get on the ball and make some messaging-based announcements. The company's Hangouts chat app was an early success when it was introduced years ago, but appears to have languished recently. Here's why Google can't afford to ignore the messaging threat: Everyone's talking about how chat is the next big thing.

They met for the first time in a hotel bar at Lake Tahoe in 1998, one evening after a technology conference. Bill Joy was an eminent computer-systems designer, chief scientist for Sun Microsystems. Ray Kurzweil was an award-winning inventor and technologist, whose many creations included a reading machine for the blind and an advanced music synthesizer. Their conversation focused on the future relationship between humans and machines. What they saw that evening, as they gazed together into the coming decades, was something that has come to be called the Singularity.

What do machines dream of? New images released by Google give us one potential answer: hypnotic landscapes of buildings, fountains and bridges merging into one. The pictures, which veer from beautiful to terrifying, were created by the company's image recognition neural network, which has been "taught" to identify features such as buildings, animals and objects in photographs. They were created by feeding a picture into the network, asking it to recognise a feature of it, and modify the picture to emphasise the feature it recognises. That modified picture is then fed back into the network, which is again tasked to recognise features and emphasise them, and so on.