Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Well, you can go ahead and add foosball to the list of things that humans won't have a chance at once robots get involved: I like the idea of a robot on robot foosball match, although I would guess that it would be far too fast for a human to actually enjoy watching. The project Europa-Explorer is a pilot survey for future missions to Jupiter's moon Europa.

Artificial Intelligence – a technology which has continually broken promises. AI technology has always been the star striker of the technology field, hugely expensive and much hyped. However, AI has never scored the big goals promised by those working on the sidelines, with a Minority Report-esque world remaining in the realms of fiction. However, no one can ignore the renewed enthusiasm that AI is today courting – companies like Salesforce, Intel and Apple are rushing to acquire AI start-ups, bolstering their in-house offerings, while others are creating secretive labs in order to get a jump on competitors. Everyone seems to be throwing their hat into a driverless, smart, self-learning, AI project or company, indicating that the much lauded'Machine Age' may be closer than critics think.

Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the "brain" behind some of the world's smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe. Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the "black box" API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans.

Dataiku, the maker of the all-in-one predictive analytics software platform Dataiku Data Science Studio (DSS), has today announced the release of Dataiku DSS 3.1, which now enables transformations in Apache Spark's Scala, adds additional external integrations, an improved UX interface, and includes 5 machine learning engines in its visual analysis section. Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a single line of code. The blending of visual code-free and free-form code-based transformations is one of the main strengths of Dataiku DSS for the prototyping and production of data applications. In addition to Python, R, SQL, Hive, Impala, and Pig, Dataiku DSS 3.1 now enables Apache Spark users to write transformations and interactive notebooks in Scala, bringing the power of Spark's native and most performant language to the data teams using Dataiku DSS.

Scientists at Stanford University have found a new method in predicting poverty through the use of machine learning and satellite images. The technique could make it easier for organizations to know where across the world their aid is needed most. Also, this could help governments develop a better policy to prevent or fight poverty. Using three data sources namely daytime images, night light images, and survey data, scientists built an algorithm to predict how wealthy or poor an area is. The results of the study have been published in the journal Science. "The idea is that if we train our models right, they help us predict poverty in areas where we don't have the surveys, which will help out aid orgs that are working on this issue," explained Neal Jean, co-author of the study and a doctoral candidate at Stanford.

Until we open our mouths to speak, it is possible for most of us to keep our thoughts to ourselves. But computers could soon be able to predict what you are thinking by looking for distinct patterns of activity in your brain that relate to sentences. Researchers have developed a computer program that is able to search for the brain activity related to certain words and then use this to predict a sentence being thought even it hasn't seen it before. Scientists have created a computer model that can predict unspoken sentences by looking at the neural activity in the brain. They say the system is able to get the predictions right around 70 per cent of the time.

The World Economic Forum recently published its 2016 list of the Top Ten Emerging Technologies that will likely have the greatest impact on the world in the years to come. The list is compiled by the WEF Meta-Council on Emerging Technologies, a panel of global experts led by Dr. Bernard Meyerson, IBM Fellow and Chief Innovation Officer. "Horizon scanning for emerging technologies is crucial to staying abreast of developments that can radically transform our world, enabling timely expert analysis in preparation for these disruptors," said Dr. Meyerson. "The global community needs to come together and agree on common principles if our society is to reap the benefits and hedge the risks of these technologies." The technologies on the list are not new.

The number of CT scans hospitals perform is on the rise, but professionals who actually read these scans can't seem to keep up with increasing demand -- often just looking at images as they come in. But artificial intelligence may be able to help. Chicago startup Realize.ai is launching a pilot study of its AI that identifies certain problems often spotted on CT scans this fall at Northwestern University Medical Center. Many times, these scans can reveal deadly conditions that need immediate attention, which means reading scans efficiently can be a life-or-death situation. "Getting to a scan too late or misreading a scan can cause serious clinical problems and we are trying to alleviate that," said co-founder Alex Risman.

According to a recent Deloitte report, advances in medical science are leading to an increased life expectancy. In 2014, the average life expectancy globally was 72.3 years and that is expected to grow to 73.3 years by 2019. In 2019, 11% of the total population are expected to be aged more than 65 years. Analysts expect that out of the global health spend of nearly 7 trillion, nearly half of the funds are diverted to making sure that this aging population continues to live longer. La Jolla, California,-based Human Longevity (Private:HLONG) is one player that is successfully integrating genomics and technology to help create the world's largest and most comprehensive database of whole genome, phenotype and clinical data that can be used to increase human longevity.

A visualization of a convolutional neural network, which has a color scheme similar to OpenAI's. Since announced in December 2015, Elon Musk and Sam Altman's OpenAI has recruited some of the foremost names in modern artificial intelligence research. Its poached top talent from giants in the field--research director Ilya Sutskever cut his teeth at Google Brain after studying with A.I. veterans Geoff Hinton and Andrew Ng. In their latest round of hires, the company is starting to diversify its staff. OpenAI's newest recruits come from Google Brain (where they have previously tapped), but also from startups and a trading firm.