The third annual Festival of Learning, organized by MIT Open Learning and the Office of the Vice Chancellor, highlighted educational innovation, including how digital technologies and shared best practices are enabling educators to drive better learning outcomes for MIT students and global learners via online courses. "As a community, we are energized by all the transformation and innovation happening within the education space right now," said Krishna Rajagopal, dean for digital learning, open learning, as he kicked off the festival. The educator's role: to engage and inspire learners Keynote speaker Po-Shen Loh, Carnegie Mellon University associate professor, founder of online education platform Expii, and coach of the U.S. International Math Olympiad Team, surprised a morning audience of about 400 people in Room 10-250 when he held up a small red die and asked why opposite sides of the die always add up to seven. Loh then began a lively, Socratic interaction with the audience that blended math and physics with engaging humor. What Loh's inquiry consciously didn't include was digital technology.

Google announced on Tuesday that it plans to acquire the cloud migration startup Alooma. The startup is known for its tool that lets enterprises automate data ingestion pipelines into the cloud, as well as for its cloud migration and data cleansing services. Financial terms of the deal were not disclosed. Alooma has been an integration partner for Cloud Spanner, Google's its globally distributed relational database, since 2017, and has also partnered with the company on Google Ads and Analytics. Google's aim with brining the startup in-house is to create a simplified cloud migration path for customers that could eventually lead to them buying more of Google's analytics, security, AI and machine learning products.

BEIJING - The Chinese database Victor Gevers found online was not just a collection of old personal details. It was a compilation of real-time data on more than 2.5 million people in western China, updated constantly with GPS coordinates of their precise whereabouts. Alongside their names, birth dates and places of employment, there were notes on the places that they had most recently visited -- mosque, hotel, restaurant. The discovery by Gevers, a Dutch cybersecurity researcher who revealed it on Twitter last week, has given a rare glimpse into China's extensive surveillance of Xinjiang, a remote region home to an ethnic minority population that is largely Muslim. The area has been blanketed with police checkpoints and security cameras that apparently are doing more than just recording what happens.

The breathless headline caught my eye: "Computer Shows Human Intuition--AI Breakthrough!" (or words to that effect). I was intrigued but skeptical. Reading further, I learned that a computer program, AlphaZero, developed by a team at DeepMind, in London, had beaten other champion chess-playing programs, as well as (of course) humans. That wasn't the interesting news, as we take that kind of dominance for granted these days. What fascinated me was how the program had been constructed.

An incredible optical illusion that'breaks your brain' for 15-milliseconds and causes you to see a circular shape spin has been created by scientists. The geometric pattern, a variation of the Pinna-Brelstaff illusion made up diamond-like shapes, turns clockwise or anti-clockwise, depending on which way you move your head. The small, thick dashes appear to turn clockwise if you move your head towards the image, or anti-clockwise if you pull your head away from it. The reason this happens is due to a communication delay between the regions of your brain that process vision and movement. Scientists have cracked why an optical illusion'breaks your brain' for 15-milliseconds causing you to see a circular shape turn clockwise and anti-clockwise depending on which way you move your head.

Listening to your friends butcher your favourite songs during karaoke nights could become a thing of the past, thanks to software created by scientists. Their AI system can bring your pitch closer to the original artist's, without making it sound overly robotic or artificial (stock image) Most commercial autotuning systems require the user to input a melody score, or instructions to modulate pitch by a particular pitch or scale. Sanna Wager, a PHD candidate and main author of the study at Indiana University, told New Scientist: 'When looking at how to correct the current note, we look at what the singer did over the past few seconds.' The current tool must be applied to recordings after they have been made, but the end product could used to make changes on-the-fly. Her paper, published on the pre-print repository Arxiv.org,

At re:Invent 2018, AWS announced Amazon Elastic Inference (EI), a new service that lets you attach just the right amount of GPU-powered inference acceleration to any Amazon EC2 instance. This is also available for Amazon SageMaker notebook instances and endpoints, bringing acceleration to built-in algorithms and to deep learning environments. In this blog post, I show how to use the models in the ONNX Model Zoo on GitHub to perform inference by using MXNet with Elastic Inference Accelerator (EIA) as a backend. Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75 percent. Amazon Elastic Inference provides support for Apache MXNet, TensorFlow, and ONNX models.

The customer has grown rapidly, delivering farm-fresh fruit across the country with customers ranging from stealth mode startups to large enterprises. It's common to see their boxes in office cafeterias, meeting rooms and company micro kitchens. Successful micro package distribution of perishable products depends on multiple factors: reaching the customer on time, avoiding congestion on routes and precise location delivery. Selecting the best route and the right local delivery carrier in the distribution network involves a lot of complexity, and rule-based logic must be updated continuously to reflect the constant changes in patterns. This is a classic problem that Machine Learning and Artificial Intelligence based solutions can solve.

You may have heard the news already: the AI bubble is getting ready to burst. You can find recent articles about it on the Financial Times, Popular Science, TNW, CapX, HackerNews and plenty of other sites. In fact, you only have to google AI winter or AI bubble for the evidence to start leaping off the screen. You might wonder why I'm so enthusiastic. After all, the rise of AI has been hugely beneficial for technologists who understand the tech driving the boom.

Whether through chatbots or voice assistants, bank customers are beginning to experience Banking AI and are responding favourably. Initially, the focus of these interfaces is similar to the task-oriented nature of channels that banks already provide. Though conversational interfaces have yet to attain the level of adoption expected in the banking space and has not yet matured as mobile has, there are already a variety of approaches for establishing a conversational banking capability. Going forward, I believe there will be at least four distinct banking models supported by apps and conversational interfaces. The majority of banks will begin their journey in the conversational banking space by implementing a conversational interface as an additional channel with a task-based focus.