From left: Professor Brendan Frey (ECE), U of T Engineering alumnus and CEO of Jupiter Networks Rami Rahim, Dean Cristina Amon and ECE Chair Professor Farid Najm. Your computer can identify you in photos, sort your email and keep your money safe online, but like anyone starting a new job, first it needs to learn how. The field of machine learning has exploded in recent years, and researchers are now developing software systems that can "learn" by exposure to training data sets and make "decisions" about real-world problems in ways that approach or exceed human abilities. On Thursday, June 23, alumni of the University of Toronto's Faculty of Applied Science & Engineering, current students and friends of the Faculty gathered at a BizSkule Speaker Series event in California to learn about the next frontier of machine learning from one of the field's experts, Brendan Frey, a professor in The Edward S. Rogers Sr. Hosted by Rami Rahim (ElecE 9T4), CEO of Juniper Networks at the company's headquarters in Silicon Valley, BizSkule showcases engineering leadership by inviting keynote speakers and industry panellists to share their experiences and insights on key issues and hot topics. Professor Frey and his team are working on closing what he calls the genotype-phenotype gap: understanding how a person's genomic make up influences their physical characteristics and traits.

It's not uncommon for large enterprises to have hundreds or perhaps hundreds of thousands of databases -- many out of date, many no longer used, and the vast majority not monitored or properly secured from possible attacks. Unauthorized databases access is increasingly a result of credential theft, and IT personnel are urgently trying to get their arms around the situation. They know they need to not only discover all their own databases, but must figure out how to secure them once they do. An Osterman Research study found nearly 40 percent of enterprises are unable to monitor the majority of their databases in real time. When asked what database security issues are of most concern, compromised credentials was the top concern of the survey respondents.

Finally, you can set your artificial intelligence creations free in Minecraft. Microsoft has announced a public release for Project Malmo, the company's system for testing AI software in Minecraft -- and for the first time, anyone can join in. Microsoft first made the system available to researchers in March under the name AIX, but this release marks the first time the code has been freely available to the public. The code is all available under an open-source license on Github, including a full tutorial on how to deploy your script on the platform, which is embedded below. The result isn't that different from typical AI test, in which code is deployed and observed in a test environment.

In an effort to apply data-driven insights to one of the most fundamental aspects of running a health care system, UPMC announced today that it has formed Pensiamo, an independent company that aims to help hospitals improve supply chain performance through a comprehensive source-to-pay offering, including cognitive analytics with IBM Watson Health technologies. IBM (NYSE:IBM) is a minority owner of Pensiamo. Supply chain costs are the second-largest and fastest-growing expense behind labor costs for health care providers [1]. The Institute of Medicine estimates that nearly one-third of health care spending is waste [2]. In today's dynamic environment, providers face mounting pressure to improve the effectiveness of patient care while controlling costs.

Additionally they used 3-D printing to replicate the body of Alexis Ohanian, infusing it with their proprietary Artificial Intelligence engine. "There's a lack of qualified IT professionals here in Armenia", said Dr. J.P. Hagopian, the CEO of 1AI Solutions. "We need to hire people, but we simply can't find enough good candidates. At some point our HR manager said that we should clone one of the high-performing Silicon Valley guys. She was kidding, but the idea stuck."

The devastating neurodegenerative condition Alzheimer's disease is incurable, but with early detection, patients can seek treatments to slow the disease's progression, before some major symptoms appear. Now, by applying artificial intelligence algorithms to MRI brain scans, researchers have developed a way to automatically distinguish between patients with Alzheimer's and two early forms of dementia that can be precursors to the memory-robbing disease. The researchers, from the VU University Medical Center in Amsterdam, suggest the approach could eventually allow automated screening and assisted diagnosis of various forms of dementia, particularly in centers that lack experienced neuroradiologists. Additionally, the results, published online July 6 in the journal Radiology, show that the new system was able to classify the form of dementia that patients were suffering from, using previously unseen scans, with up to 90 percent accuracy. "The potential is the possibility of screening with these techniques so people at risk can be intercepted before the disease becomes apparent," said Alle Meije Wink, a senior investigator in the center's radiology and nuclear medicine department. "I think very few patients at the moment will trust an outcome predicted by a machine," Wink told Live Science.

Technology giant Nvidia has revealed how one of its engineers has used machine learning at his home to keep cats off his prized lawn. Robert Bond, who has previously used the firm's Jetson TX1 platform to build a laser to take out the ants that appeared on his kitchen floor, used the same machine learning technology to turn his sprinklers into a smart identification system that could spot cats that appeared on or near the lawn before triggering the sprinklers to shoo the feline visitors away. "My wife is a gardener and she likes her garden to be tidy and clean," Robert said. The new Jetson TX1 is really good at running these neural nets." His system, as he explained in an Nvidia blog post, works by detecting motion.

Making a strong push toward enhancing its artificial intelligence (AI) capabilities, the world's leading search engine giant, Alphabet Inc.'s (GOOGL - Analyst Report) Google acquired Moodstocks, a French start-up specialized in instant smartphone image recognition. The financial terms of the deal remain under wraps. Moodstocks' "deep-learning" AI technology, allows computers, including smartphones, to identify and remember objects in the real world. The company said that the on-device image recognition technology was developed in 2012 and has been developing object recognition using deep learning approaches. According to a statement on Moodstocks' site, monthly recurring users can access the services until their subscriptions end.

Flip.to has created an artificial intelligence-led platform that it reckons is the start of "real personalisation at scale" for hotels. Well, the brand advocacy service – which usually incentivises guests to share their upcoming stay with their social networks as soon as they've booked a room – has developed a system whereby it uses two forms of machine learning to identify both human attributes (such as gender, age, etc) and characteristics within content to create new marketing messages for a property. Previously, guest "stories" would be collected and then shared on the Flip.to Now, using the AI processes, between Vision AI and Faces AI (the two new bits of Flip.to tech), a hotel can see all the content from guests automatically fitted with descriptions and tagged during the curation process, essentially saving the marketing team and effort of a manual process. "Amazing tech lets us gather real insight on the guest stories we capture.

Hell, Microsoft issued an Education Edition of the popular PC game earlier this year, s targeted at use in a classroom setting. Turns out the game could also prove a useful tool for helping artificial intelligence be more, well, intelligent. Back in March, Microsoft Research showcased the work it was doing with Project Malmo, a platform designed to leverage Minecraft as a means of helping improve AI problem solving, using machines to accomplish tasks and create items in the blocky game. Now the company is bringing Malmo to the GitHub-using masses, courtesy of an open-source license in a private preview. Katja Hoffman of MS's Cambridge, UK lab highlighted the key of teaching AI fundamental connections that go build simple pattern recognition.