AYLIEN Text Analysis API is a package of easy to use Natural Language Processing, Information Retrieval and Machine Learning tools that will help you extract meaning and insight from text and images. The Basic plan allows you to make 1,000 calls/day for free, forever. Use our Text Analysis API to analyze documents, news articles, Tweets and URL's.

Facebook is looking to revolutionise the way brands interact with customers through sophisticated software known as bots that can hold elaborate conversations. These pieces of code that emulates artificial intelligence (AI) will spearhead the company's monetisation strategy for its Messenger app which has over 900 million users as of today. Mark Zuckerberg introduced chatbots for Messenger at the recent F8 developer conference, giving us a broad idea of what they will be able to do. For starters, users will be able to get weather and other updates from within the Messenger app, but more sophisticated uses include receiving invoices and facilitating customer care queries. Bots have been active on the beta version of Messenger for the past two days and the verdict by early users has been that there's still a long way to go to make the interactions more human.

I built deepjazz in 36 hours for HackPrinceton, Spring 2016. It uses Keras & Theano, two deep learning libraries, to generate jazz music. Specifically, it builds a two-layer LSTM, learning from the given MIDI file. It uses deep learning, the AI tech that powers Google's AlphaGo and IBM's Watson, to make music -- something that's considered as deeply human. This project develops a lot of preprocessing code (with permission) from Evan Chow's jazzml.

A microscope, invented by a professor at the University of California, uses artificial intelligence in order to locate cancer cells more efficiently than ever before. The device uses photonic time stretch and deep learning to analyze 36 million images every second without damaging the blood samples. This new technique for identifying problematic cells is faster and more accurate than standard methods currently in practice. Commonly, doctors will add biochemicals to blood samples in order to check for cells containing cancer. The biochemicals attach what scientists call "biological labels" to damaged cells, which enables instruments to both locate and identify differences.

Ratnesh Pandey, Co-Founder, Healthkhoj.com worked in multi cultural International business environments in Europe and US. He has executed complex engagements with globally distributed teams and vendors. He possesses domain knowledge on B2B IT marketing, Lead progression, Campaigns, Branding and Promotions. Healthkhoj is changing the way healthcare services are delivered and consumed. We are doing this by bringing different service providers in the patient care cycle together, which means that the people will be able to access everything they need through healthkhoj.

Like many hospitals, Advocate was struggling to reduce 30-day hospital readmissions, a key benchmark for Medicare reimbursement. An earlier risk-stratification model developed in-house at Advocate had yielded a model with little predictive power, a result that has been typical for attempts to use administrative data alone to classify patients. The model automated the process, identifying patients deemed at high risk of readmission and embedding the information within the EHR. The first iteration of the model yielded only modest predictive value. But after only a year of use, readmissions from all causes had dropped by 20 percent among the highest-risk patients in the Advocate system when comparing outcomes in the first half of 2013 with the same period in 2014.

Google Calendar has launched a feature called Goals that uses machine learning to help you figure out when you have time to pencil in stuff like spending time with your family or exercise. The feature is now available for Calendar's Android and iOS apps. Goals are set up by clicking into a category (which currently include Exercise, "Build a Skill," and "Me Time," though they can also be customized) and selecting a specific activity. Then Calendar will automatically find open slots, fill them in with your goal, and send reminders. If you schedule something else during those times, Google Calendar will find another window for your goal--but, in a tool that will surely be chronically abused by procrastinators, they can also be deferred.

Using an EPOC headset from Emotiv, I have captured 14 channels of EEG (brain waves) while subjects lied and answered truthfully to a series of questions. I fed this labelled dataset into Azure Machine Learning to build a classifier which predicts whether a subject is telling the truth or lying. In this session, I will share my results on this "lie detector" experiment. I will show my machine learning model, data cleaning process, and results, along with discussing the limitations of my approach and next steps/resources. Attendees will gain exposure to the Emotiv EPOC headset and Azure Machine Learning.

Many would jokingly describe their smartphone as a fifth limb, but developments in wearable technology are hinting that one day our devices will actually be part of us. In some cases, they already are. Cyborgs are organisms with enhanced abilities thanks to the integration of an artificial component or technology, and many of us already fall under this category. We tend to associate the word cyborg with science fiction representations of super humans like Robocop or Roy Batty from the film Blade Runner, but our present day cyborgs tend to be those with health complications. Those suffering from irregular heartbeats rely on cardiac pacemakers and implantable defibrillators to maintain consistent heart function. Most of know at least one person with more common augmentations, like hearing aids or contact lenses -- two of our most popular biological enhancements.

In the age of ultra-high-frequency trading, financial institutions are turning to artificial intelligence to improve their stock trading performance and boost profit. One such company is Japan's leading brokerage house Nomura Securities. The company has been pursuing one goal: to simulate the insights of experienced stock traders with the help of computers. After years of research, Nomura is set to introduce a new stock trading system for institutional investors in May. The new system stores vast amounts of price and trading data in its computer.