In summary, I had a blast at my first GTC. The only downside was that I wasn't on-site long enough to totally absorb everything, certainly not even a fraction of all the great talks on Deep Learning and AI. But no worries, I treated my attendance as a learning experience and I fully intend to drill down on many areas of interest after-the-fact (starting with this field report). As I sat in the conference press room watching the frenetic activity of the attendees passing by, I anticipated hours of fun digesting all that I saw. Look for many future articles here on insideBIGDATA that cover GPU technology, NVIDIA, the vendors I met, as well as leading-edge research taking place in this space. I'm excited, and I hope you are too!

Weird Of The Week: This is part of a series of articles that looks at some of the most bizarre and niche business ideas we see here at Springwise. Advertising and media are often at the forefront of new technology, and we have already seen augmented reality platforms showing content in the real world and a virtual reality advertising network for brands. Now an artificial intelligence robot, AI-CD?, developed by Japanese advertising and marketing agency McCann Japan, is set to work on providing new creative direction for commercials. The AI will give input on projects, mining and analyzing creative databases of adverts to find the best commercials for products and messages. But the robot is also being treated as somewhat part of the team at McCann, taking the title of "creative director" and attending the opening ceremony for new company employees.

While Apple's annual iPhone unveiling is undoubtedly the company's biggest event each and every year, WWDC is clearly a close second. As the event where Apple showcases its latest advancements in user design and iOS and OS X technologies, Apple's annual worldwide developers conference typically provides us with a fascinating sneak peak at the future of mobile and desktop computing. This year, WWDC is slated to take place from June 13 and June 17 in San Francisco at the Moscone West convention center. Interestingly enough, word of Apple's WWDC schedule this year was initially leaked by Siri. Earlier today, a number of sites noted that when you ask Siri when WWDC is, Apple's intelligent personal assistant responds with the following: The Worldwide Developers Conference (WWDC) will be held June 13 through June 17 in San Francisco.

Apple's Worldwide Developers Conference may be taking place June 13-17 this year, if Siri is to be believed. The digital assistant acted as a spokeswoman Monday to reveal the dates to inquisitive users who asked, "When is WWDC?" Apple has not updated the WWDC website, but the announcement and dates line up with the company's announcement history. Siri was enthusiastic for WWDC 2016, which will take place in San Francisco. The exact location was not revealed, but 9to5 Mac speculates that the city's Moscone West convention hall will once again host the huge conference. When Siri was asked about WWDC 2016 earlier in the day, it stated the dates were not announced yet. WWDC 2015, which took place June 8-12, was announced April 14, 2015.

Universities have in recent years awakened to the fact that students can help them make money through more than just tuition and board. Stanford University started investing in students' start-ups in 2013. Harvard University does the same through its Xfund. Last year, the University of California launched a 250-million venture fund to invest in companies that grow out of the UC system. Now, UC Berkeley is getting in on the game -- through a new fund led by 24-year-old Los Angeles native Jeremy Fiance.

Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, will discuss how research has demonstrated the value of Machine Learning in delivering next generation analytics to improve safety, performance, and reliability in today's modern wind turbines. Speaker Bio Stuart Gillen is the Director of Business Development at SparkCognition. In this role, he is responsible for driving business engagements, partner development, marketing activities, and go-to market strategy.

Researchers at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) have developed a cybersecurity system that combines human and machine-learning approaches to reduce cyber attacks and false positives. Named AI2 to signify that it merges artificial intelligence with "analyst intuition," the system was developed by Kalyan Veeramachaneni, a research scientist at CSAIL, and Ignacio Arnaldo, a former postdoctoral researcher at CSAIL who is now a chief data scientist at PatternEx. In tests, the researchers demonstrated that "AI2 can detect 85 percent of attacks, which is roughly three times better than previous benchmarks, while also reducing the number of false positives by a factor of five," according to a news release from CSAIL. Most modern cybersecurity systems use either analyst-driven solutions or machine-learning approaches. Analyst-driven systems rely on rules created by people and consequently can't detect attacks that don't adhere to those rules, whereas machine-learning systems rely on anomaly detection, which tends to generate false positives that have to be investigated by people.

The revolution in GPU computing started with games, and spread to the HPC centers of the world eight years ago with the first "Fermi" Tesla accelerators from Nvidia. But hyperscalers and their deep learning algorithms are driving the architecture of the "Pascal" GPUs and the Tesla accelerators that Nvidia unveiled today at the GPU Technical Conference in its hometown of San Jose. Not only did the hyperscalers and their AI efforts help drive the Pascal architecture, but they will be the first companies to get their hands on all of the Tesla P100 accelerators based on the Pascal GP100 GPU that Nvidia can manufacture, long before they become generally available in early 2017 through server partners who make hybrid CPU-GPU systems. As was the case with the prior generations of GPU compute engines, Nvidia will eventually offer multiple versions of the Pascal GPU for specific workloads and use cases, but Nvidia has made the big bet and created its high-end GP100 variant of Pascal and making other big bets at the same time, such as moving to a 16 nanometer FinFET process from chip fab partner Taiwan Semiconductor Manufacturing Corp and adding in High Bandwidth Memory from memory partner Samsung at the same time. Jen-Hsun Huang, co-founder and CEO at Nvidia, said during his opening keynote that Nvidia has a rule about how many big bets it can make.

Researchers with MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that can offer the security world a huge boost in incident response and preparation with a new artificial-intelligence platform it believes can eventually become a secret weapon in squeezing the most productivity from security analyst teams. Dubbed AI2, the technology has shown the capability to offer three times more predictive capabilities and drastically fewer false positive than todays analytics methods. CSAIL gave a sneak peek into AI2 in a presentation to the academic community last week at the IEEE International Conference on Big Data Security, which detailed the specifics of a paper released to the public this morning. The driving force behind AI2 is its blending of artificial intelligence with what researchers at CSAIL call "analyst intuition," essentially finding an effective way to continuously model data with unsupervised machine learning while layering in periodic human feedback from skilled analysts to inform a supervised learning model. "You can think about the system as a virtual analyst," says CSAIL research scientist Kalyan Veeramachaneni, who developed AI2 with former CSAIL postdoc Ignacio Arnaldo, who is now a chief data scientist at PatternEx.

CkBot is a reconfigurable modular robot that is able to reassemble itself after being kicked apart - the Self-Assembly After Explosion problem. Mark Yim, a professor of mechanical engineering at the University of Pennsylvania Modular Robotics Lab (ModLab), describes the ideas behind CkBot.