Fintech startup YayPay has raised $5.3 million in funding led by QED Investors along with co-investors Birchmere and Fifth Third Capital, the direct equity investment subsidiary of Fifth Third Bancorp, with support from 500 Fintech Fund, Aspect Ventures, Gaingels, Techstars, and Zelkova. The funding will aid YayPay's drive to bring automation to the back-office finance operations of mid-sized enterprises. YayPay will use the funding to grow headcount, pursue product development, and increase sales activities. "With modern software powered by machine learning, we aim to turn finance teams into revenue heroes by giving them workflow tools that finally match in robustness those used by their sales and marketing departments. The funding puts YayPay at a major inflection point in which we can now recruit more great talent, roll out a full suite of intelligent order-to-cash automation software, and accelerate sales activities," said Anthony Venus, co-founder and CEO of YayPay.

Banking providers must raise service levels, profitability and competitiveness by efficiently and effectively fusing digital technologies with personalized human interactions. Retail banks and credit unions are plagued by inconsistent online- and offline capabilities, and generic customer propositions. To overcome these fundamental issues, Boston Consulting Group (BCG) says financial institutions must embrace a "bionic" a strategy. According to BCG, a bionic transformation essentially consists of three interrelated elements. First is the blending of digital and personal interactions to create a more responsive and cost-effective distribution model.

If you sell your expertise for a living, you will discover significant benefits in transferring your knowledge to the world of Artificial Intelligence (AI). It is now possible to create an online chatbot with near human characteristics to deliver your intellectual property to the world. From your website your clients will be able to interact with the AI system to receive a personalised experience of the way you deliver your specialist skills. The Chatbot will be able to track the client's progress and adapt the learning experience to suit their individual mood, personality and abilities. Your unique talents will be instantly made available to a global audience 24 / 7. Up until August 2016 the software to build a chatbot has been in prototype with major corporations but now it's going mainstream.

There have been numerous questions surrounding the iPhone X's Face ID, especially after the demo blip during the keynote. To address concerns, Apple software engineering chief Craig Federighi has been making media rounds about the facial recognition feature. Federighi went on John Gruber's "Talk Show" and assured users' concerns about the Face ID will "melt away" when they start using the 10th-anniversary device. "You don't even think about it, it just works" he said. He also said concerns about the Face ID are similar to when Apple revealed the Touch ID, which launched on the iPhone 5s.

Early diagnosis can help patients make lifestyle changes which may help slow the progression of Alzheimer's. A devastating chronic neurodegenerative disease, Alzheimer's disease (AD) currently affects around 5.5 million people in the United States alone. Causing progressive mental deterioration, it ultimately advances to impact basic bodily functions such as walking and swallowing. Looking for a way to help, researchers at the University of Bari and Istituto Nazionale di Fisica Nucleare in Italy have developed new machine learning AI technology that may help identify Alzheimer's a decade before doctors usually can, by way of non-invasive MRI brain scans. An early diagnosis -- before any of the symptoms a doctor might recognize become apparent -- could give patients a chance to make changes to their lifestyle which may slow Alzheimer's progression.

If you are practitioner interested in deep learning for NLP, you may have different goals and requirements from the material. For example, you may want to focus on the methods and applications rather than the foundational theory. The course is comprised of 13 lectures, although the first and second lectures are both split into two parts. The complete lecture breakdown is provided below. The GitHub repository for the course provides links to slides, flash videos and reading for each lecture. I would recommend watching the videos via this unofficial YouTube playlist. Below is a course overview slide taken from the first lecture.

Every face does not tell a story; it tells thousands of them. Over evolutionary time, the human brain has become an exceptional reader of the human face--computerlike, we like to think. A viewer instinctively knows the difference between a real smile and a fake one. In July, a Canadian study reported that college students can reliably tell if people are richer or poorer than average simply by looking at their expressionless faces. Scotland Yard employs a team of "super-recognizers" who can, from a pixelated photo, identify a suspect they may have seen briefly years earlier or come across in a mug shot.

Inc. (NASDAQ:AMZN) has become one of the leaders in the emerging field of artificial intelligence (AI). Many of the ways the company uses the technology go on behind the scenes for things such as improving search results, better product recommendations, and enhanced forecasting and inventory management. The more public face of Amazon's AI ambitions can be found in its Echo family of smart speakers powered by Alexa, its voice-activated digital assistant, which has become the leader in the burgeoning smart-speaker market. With that much riding on AI, it should come as no surprise that Amazon has announced plans to expand its AI research by building a new R&D center in Barcelona, Spain. Amazon is setting up AI labs around the globe in search of AI talent.

Robotic exoskeletons could help people with cerebral palsy maintain the ability to walk -- and offer a replacement for costly and invasive orthopedic procedures. Cerebral palsy is the leading cause of childhood disability in the United States, affecting about 3.3 children per 1,000 births. The neurological disorder is a lifelong affliction that can have a devastating impact on an individual's mobility, even when managed well with current physical and occupational therapies. But a new robotic design could significantly improve mobility outcomes. A recent study in the journal Science Translational Medicine found that wearing a robotic exoskeleton – a leg brace powered by small motors – helped children achieve significant mobility improvement.

When we build these models, we always use a set of historical data to help our machine learning algorithms learn what is the relationship between a set of input features to a predicted output. We'll show how you can evaluate these issues by assessing metrics of bias vs. variance and precision vs. recall, and present some solutions that can help when you encounter such scenarios. If we were to train a machine learning model and it learned to always predict an email as not spam (negative class), then it would be accurate 99% of the time despite never catching the positive class. Similarly, increasing the number of training examples can help in cases of high variance, helping the machine learning algorithm build a more generalizable model.