Perception and expression of emotion are key factors to the success of dialogue systems or conversational agents. However, this problem has not been studied in large-scale conversation generation so far. In this paper, we propose Emotional Chatting Machine (ECM) that can generate appropriate responses not only in content (relevant and grammatical) but also in emotion (emotionally consistent). To the best of our knowledge, this is the first work that addresses the emotion factor in large-scale conversation generation. ECM addresses the factor using three new mechanisms that respectively (1) models the high-level abstraction of emotion expressions by embedding emotion categories, (2) captures the change of implicit internal emotion states, and (3) uses explicit emotion expressions with an external emotion vocabulary. Experiments show that the proposed model can generate responses appropriate not only in content but also in emotion.

Since the introduction of 3-D Secure in 2007, adoption rates have been slow, and have varied between countries. Concerns about lower conversions and rising customer friction are preventing higher penetration rates, but new fraud prevention software solutions offer ways to balance customer satisfaction and security requirements. Roger Lester, Payments Expert at Featurespace, explores how advanced machine learning and adaptive behavioral analytics technology help balance 3-D Secure checks against futureproofing an organization's fraud defenses. Why has adoption of 3-D Secure been mixed? Designed to be an additional layer of security for online payments, the 3-D ("3 Domain") Secure protocol has been adopted by all major card networks--more familiar to many of us under commercial names, such as "Verified by Visa" and "MasterCard SecureCode."

We just announced the raising of $5.3 million in funding to further our drive to bring automation to the back-office finance operations of small and mid-sized enterprises. The funding puts YayPay at a major inflection point in which we can accelerate our momentum by recruiting more great talent, roll out a full suite of intelligent order-to-cash automation software, and increase sales activities. You can read the press release here. Eugene Vyborov and I co-founded YayPay with a vision to help finance teams perform their most valuable work, and we're doing exactly that. We released our first software module in January, have collected over $100 million in receivables, and processed more than 150,000 invoices.

You've probably heard by now that machine learning algorithms can use big data to predict whether a donor will give to a charity, whether an infant in a NICU will develop sepsis, whether a customer will respond to an ad, and on and on. Machine learning can even drive cars and predict elections. I believe it can, but these recent high-profile hiccups should leave everyone who works with data (big or not) and machine learning algorithms asking themselves some very hard questions: do I understand my data? Do I understand the model and answers my machine learning algorithm is giving me? And do I trust these answers? Unfortunately, the complexity that bestows the extraordinary predictive abilities on machine learning algorithms also makes the answers the algorithms produce hard to understand, and maybe even hard to trust. Although it is possible to enforce monotonicity constraints (a relationship that only changes in one direction) between independent variables and a machine-learned ...

Frost & Sullivan's research, Disruption in Global Financial Services, 2017--Machine Learning is Imperative, provides an overview of ML market dynamics, including technology trends, drivers, and challenges for adoption. Case studies and profiles of some of the key players in the report cover Google, IBM, Orange, Swisscom, Onfido, Darktrace, Klarna, Infosys, SAP, and Rasa.ai. To access more information on this analysis, please visit: https://goo.gl/4CtAwr "The biggest advantage of ML solutions is their ability to learn from every transaction and instance. Today, companies and consumers are more comfortable with hybrid services. However, the fact that machines are evolving at a rapid pace, learning continuously and using this knowledge to improve customer satisfaction and experience is the biggest differentiator," stated Digital Transformation Senior Industry Analyst Deepali Sathe.

Audi laid out its plans for autonomous vehicles and how it intends to use AI to us back in July, and now the automaker is ready to show off what it's been working on. At this year's IAA auto show in Frankfurt, Audi debuted the AIcon and ElAIne (above and below), a pair of cars capable of Level 4 autonomy (conditional, but fully automated driving) that it claims are empathetic to their drivers' needs. "They will be able to continually interact with their surroundings and passengers, and thus adapt themselves in a better way than ever before to the requirements of those on board," Audi wrote in a lengthy press release. The idea is that, through machine learning, the platform will be able to anticipate what you want before you ask. The example Audi gives is one of its cars suggesting a service (think: Indian take-out or maybe a spa day) and booking it for the driver like a personal assistant might.

In treating brain cancer, time is of the essence. A new study, in which IBM Watson took just 10 minutes to analyze a brain-cancer patient's genome and suggest a treatment plan, demonstrates the potential of artificially intelligent medicine to improve patient care. But although human experts took 160 hours to make a comparable plan, the study's results weren't a total victory of machine over humans. The patient in question was a 76-year-old man who went to his doctor complaining of a headache and difficulty walking. A brain scan revealed a nasty glioblastoma tumor, which surgeons quickly operated on; the man then got three weeks of radiation therapy and started on a long course of chemotherapy.

A novel imaging approach using artificial intelligence was associated with improved detection of parameters associated with melanoma, according to results presented at the International Conference on Image Analysis and Recognition. The researchers suggested that a number of quantitative imaging approaches to dealing with melanoma have focused largely on skin lesions using "hand crafted imaging features." The current study employed "machine-learning" software, which records abstract quantitative features on images and can model physiological traits of the patients, according to study background. The two features of melanoma that were assessed in the analysis were eumelanin and hemoglobin concentrations observed on dermal imaging. The researchers created a non-linear random forest regression model culled from the images.

In 2014 the world came into contact with Artificial Intelligence (AI) for the home with the release of Amazon Echo. This type of personal AI had been introduced previously in the mega-hit movie "Iron Man' with the AI system called "Jarvis." The main character Tony Stark uses Jarvis for anything he needs executed: lighting, television, phone calls, dinner orders, simple chores and computer data analysis. Up to a few years ago, people thought this was only possible in movies and fiction. One start-up company in New Jersey attempted to reinterpret and repurpose existing leisure drones with an added benefit of AI.

Rolls Royce has revealed its plans for making autonomous naval vessels which will be capable of surveilling the waters for 100 days at a go with a range of 3,500 miles at maximum speeds of more than 25 knots. "Rolls-Royce is seeing interest from major navies in autonomous, rather than remote controlled, ships. Such ships offer a way to deliver increased operational capability, reduce the risk to crew and cut both operating and build costs…Over the next 10 years or so, Rolls-Royce expects to see the introduction of medium sized unmanned platforms, particularly in leading navies, as the concept of mixed manned and unmanned fleets develops. With our experience and capabilities we expect to lead the field," Benjamin Thorp, Rolls-Royce, General Manager Naval Electrics, Automation and Control, stated in the press release. The self-navigating ship will be capable of navigating entirely without a human crew and will not be affected by human issues such as tedium.