natural language

Deep Learning Chatbots: Everything You Need to Know


When you're creating a chatbot, your goal should be to make one that it requires minimal or no human interference. This can be achieved by two methods. With the first method, the customer service team receives suggestions from AI to improve customer service methods. The second method involves a deep learning chatbot, which handles all of the conversations itself and removes the need for a customer service team. Such is the power of chatbots that the number of chatbots on Facebook Messenger increased from 100K to 300K within just 1 year.

Chatbots Opportunities For Insurance: Is It Ready? Insurance Market


We can describe a chatbot as a computer program that conducts a conversation in natural language via auditory or textual methods, understands the intent of the user, and sends a response based on the business rules and data of the organization. Another way to describe chatbot programming is the concept of "micro-engagement," or technology designed to communicate with customers and prospects at various intervals and via multiple channels in order to drive business interactions. Whatever the digital classification, it's important for boards of directors and C-level executives within the insurance industry to understand that chatbots are an increasingly effective way to improve business processes -- but are not a panacea. Roughly 65% of customer interaction can now be automated, and in order to maximize their effectiveness, chatbots must be wed to a comprehensive communications process that also includes humans (who can step in at the appropriate time). Being able to extract information from an insurance claim is a fairly complex task that demands a human component.

Language, trees, and geometry in neural networks


Left image in each pair, a traditional parse tree view, but the vertical length of each branch represents embedding distance. Right images: PCA projection of context embeddings, where color shows deviation from expected distance.

Promising Directions of Using NLP for Post Traumatic Stress Disorder Assessment


This article is part 1 of a series sharing the initial results and directions of Omdena's AI challenge on PTSD treatment with 34 engineers and enthusiasts collaborating. Millions of people suffer from PTSD around the world due to various kinds of traumatic events. Professional help is difficult to find when needed in particular areas, which makes it sometimes impossible for the patient to overcome the trauma they live in. This is why Christoph von Toggenburg reached out to Omdena for leverage AI and community collaboration. Before we dive in deeper let's first understand what PTSD is and how professional psychiatrists treat it.

The Bank of the Future Will Have Data Vaults and Money Vaults


The financial services industry has seen a great deal of disruption from digital-based alternatives. Many of these challengers use advanced technology and expanded data sets to offer apps that provide financial solutions at a lower cost, with less friction and greater personalization than traditional bank or credit union offerings. Toronto-based startup Flybits believes that the best way to compete in the future is not just by developing innovative products and services, but by becoming the repository of choice for data in addition to money. "I definitely see that banks are in a perfect position, if they innovate right, to be the perfect data vaults for the future – managing the privacy and also the data of their customers," says Hossein Rahnama, CEO and Co-Founder of Flybits, in an exclusive interview for Banking Transformed, a new podcast from Jim Marous and The Financial Brand. "Using AI and machine learning, there is the potential to build a'data marketplace' for banks, fintechs and other data providers to partner and build more services together."

To Power A.I., Start-Up Creates a Giant Computer Chip


Some experts believe these chips will play a key role in the race to create artificial intelligence, potentially shifting the balance of power among tech companies and even nations. They could feed the creation of commercial products and government technologies, including surveillance systems and autonomous weapons. Google has already built such a chip and uses it in a wide range of A.I. projects, including the Google Assistant, which recognizes voice commands on Android phones, and Google Translate, which translates one language into another. "There is monstrous growth in this field," said Cerebras's chief executive and founder, Andrew Feldman, a chip industry veteran who previously sold a company to the chip giant AMD. New A.I. systems rely on neural networks.

Artificial Intelligence Beyond The Buzzword From Two Fintech CEOs


AI seems to be well on its way to becoming the most overused buzzword of the tech industry, but don't be put off by the hype. Some fintech companies in Asia are actually making use of natural language processing or machine learning for detecting fraud and making investment decisions. I recently interviewed two CEOs--Simon Loong from the Hong Kong unicorn WeLab and Jianyu Tu from MioTech--to better understand some of the recent developments in AI in Asia's fintech industry. Philippe Branche: First, could you describe your company in a few words? Simon Loong: WeLab is a fintech company providing seamless digital financial services.

Knowledge-Powered Deep Learning for Word Embedding - Semantic Scholar


The basis of applying deep learning to solve natural language processing tasks is to obtain high-quality distributed representations of words, i.e., word embeddings, from large amounts of text data. However, text itself usually contains incomplete and ambiguous information, which makes necessity to leverage extra knowledge to understand it.

Text Mining in Python: Steps and Examples


In today's world, according to the industry estimates only 20 percent of the data in the structured format is being generated as we speak as we tweet as we send messages on What's App, email, Facebook, Instagram or any text messages. And, the majority of this data exists in the textual form which is highly unstructured format, in order to produce meaningful insights from the text data then we need to access a method called Text Analysis. Text Mining is the process of deriving meaningful information from natural language text. Natural Language Processing(NLP) is a part of computer science and artificial intelligence which deals with human languages. In other words, NLP is a component of text mining that performs a special kind of linguistic analysis that essentially helps a machine "read" text.

Microsoft harvests unintentional audio in program that listens to Xbox users via Cortana and Kinect

Daily Mail - Science & tech

Microsoft's listening program continues to grow in scope after a new report reveals that contractors harvested unintentional audio from Xbox users through Cortana and the Kinect. Motherboard reports that Xbox users were recorded by Microsoft as part of a program to analyze users' voice-commands for accuracy and that those recordings were assessed by human contractors. While the program was designed to only scrape audio uttered after a wake-word, contractors hired by Microsoft report that some recordings were taken accidentally without provocation. The practice, reports Motherboard, has been ongoing for several years since the early days of Xbox One and predates Xbox's integration with its voice assistant, Cortana. Xbox users were being recorded by Microsoft in a listening program that scraped audio from Cortana and its augmented reality hardware, Kinect.