Ruslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two postdoctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an assistant professor in the Departments of Statistics and Computer Science. In 2016 he joined the Machine Learning Department at Carnegie Mellon University as an associate professor. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data.

In the advertising and marketing industry, event marketing has proved to be the fastest growing approach. Event marketers have adopted various new methods of marketing today, and video or live streaming is perhaps the trend which organizations are embracing willingly and promptly. Sharat Saran, Co-Founder and Chief Executive Officer at ON24, analyzes the shape of things to come, "Following from its rise in 2016, next year we'll start to see marketers in both the B2B and B2C worlds really leverage live video for their initiatives – particularly those types of solutions that can provide tangible insights and data on the back end. Video had long been a black hole for data – where you don't know how long someone watched and what they engaged in – but the latest technology shifts make it a gold mine of stats. Savvy marketers will make the move to glean invaluable intelligence from this channel, and helping transform how they engage with consumers."

Creating a new mobile app used to begin with a simple question: iOS or Android? And if you believe the hype about chatbots (intelligent helpers that users can summon via instant message), the decision is about to get much more complicated. Tech companies like Facebook, Microsoft, and Slack are all opening up bot platforms within their messaging services, letting users read the news, shop online, hail an Uber, and get customer service within a messaging window. The idea is to allow for quick interactions that don't require installing a full-blown app. But even as these companies build up their chatbot armies, we're probably not headed for another bitter ecosystem war, like the one that led to the dominance of iOS and Android.

There's a new era of social self-expression and mobile entertainment happening, enabled by always-on cameras, real-time computer vision, social media, and other tech. Several of these phenomena -- from emoji to stickers to filters to cultural memes -- emerged in Asia or were popularized in messaging apps there before they made their way into global products. Well, livestreaming is currently exploding in China. And while it's been around in the U.S. for years in various forms, it hasn't really taken off at mainstream scale… yet. So what can we learn as livestreaming evolves in China (and perhaps here too)?

Thanks to the wonders of AI, it's possible to ask a robot to help you figure out the best way to deal with a difficult situation. One of the greatest hits as far as Christmas gift-giving was a gizmo called an Echo Dot I gave my nephew, Nathan. It was a hit despite the obligatory annoying learning curve that comes when any Southerner tries to talk to an artificial intelligence device ("Alexer, G-darnit, stop giving me the temperature in Celsius, I want it in American!") I had arrived in Chapel Hill weary from a verbal battle with Siri who, based on the convoluted traffic pattern she recommended, is a huge Duke fan. Artificial intelligence is a big buzzword for 2017.

This demo trains a Convolutional Neural Network on the CIFAR-10 dataset in your browser, with nothing but Javascript. The state of the art on this dataset is about 90% accuracy and human performance is at about 94% (not perfect as the dataset can be a bit ambiguous). I used this python script to parse the original files (python version) into batches of images that can be easily loaded into page DOM with img tags. This dataset is more difficult and it takes longer to train a network. Data augmentation includes random flipping and random image shifts by up to 2px horizontally and verically.

The next BriefingsDirect technology innovation thought leadership discussion explores how rapid advances in artificial intelligence (AI) and machine learning are poised to reshape procurement -- like a fast-forwarding to a once-fanciful vision of the future. Whereas George Jetson of the 1960s cartoon portrayed a world of household robots, flying cars, and push-button corporate jobs -- the 2017 procurement landscape has its own impressive retinue of decision bots, automated processes, and data-driven insights. We won't need to wait long for this vision of futuristic business to arrive. As we enter 2017, applied intelligence derived from entirely new data analysis benefits has redefined productivity and provided business leaders with unprecedented tools for managing procurement, supply chains, and continuity risks. To learn more about the future of predictive -- and even proactive -- procurement technologies, please welcome Chris Haydon, Chief Strategy Officer at SAP Ariba. The discussion is moderated by BriefingsDirect's Dana Gardner, Principal Analyst at Interarbor Solutions. Gardner: It seems like only yesterday that we were content to gain a common view of the customer or develop an end-to-end bead on a single business process.

It is unclear what key symptoms differentiate Myalgic Encephalomyelitis (ME) and Chronic Fatigue syndrome (CFS) from Multiple Sclerosis (MS). The current study compared self-report symptom data of patients with ME or CFS with those with MS. The self-report data is from the DePaul Symptom Questionnaire, and participants were recruited to take the questionnaire online. Data were analyzed using a machine learning technique called decision trees. The best discriminating symptoms were from the immune domain (i.e., flu-like symptoms and tender lymph nodes), and the trees correctly categorized MS from ME or CFS 81.2% of the time, with those with ME or CFS having more severe symptoms.

Machine learning is a subfield of computer science. In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".[2] Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to (and often overlaps with) computational statistics; a discipline which also focuses in prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field.

My speech will be about the most important about the grand theme of the 1st century which is the rise of artificial intelligence which is going o transform every aspect of our civilization and before we will look at the content rillettes have a brief look at the previous century what was the most important thing in the previous century the journal nature in 1999 made a list of the most influential inventions after twenty century and number one of class once the invention from 1908 which made the 20th century stand out among our centuries ever in the history of mankind because it was the one that drove the population explosion from 1.6 billion people in the year nineteen hundred too soon 10 billion it's a chemical thing and a high pressure and high temperature nitrogen is extracted from thin air to make still 500 million tons of artificial fertilizer for a year now without that stuff half of humankind would not even exist this planet could sustain at most four billion people without that one invention billions and billions and billions would never have lived without it and soon two out of three people on this planet will depend on this one single mention nothing else was remotely as influential as an however the way I explosion of the present century is going to be much more impactful and grander than that because that we are not talking about smaller numbers such as for or 10 but we are talking about trillions of trillions and this has a lot to do with the fact that computers are getting faster by a factor of 10 per euro per five years and this trend has held at least since nineteen forty one man cannot souza built the first working program controlled computer and nineteen forty one seventy five years gone every five years since then computers became roughly 10 times cheaper which means that now we have a factor of a million billions and this trend has been running for a long time but only recently we have approached the computational power of a small animal brain and in the near future for the first time for a thousand euros.