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. Sadly, not everyone can afford a lab full of robots to experiment with. We'll be checking back in with the Robotarium just as soon as the rest of the world starts using it for research.

With threats, bribes, diplomacy and sanctions, American presidents of both parties have sought for 25 years to try to halt, or at least slow, North Korea's quest for a nuclear arsenal -- to no avail. Though the brinksmanship of the last few weeks has subsided, President Trump still faces the prospect of a madman -- Kim Jong Un -- in control of a nuclear arsenal. What the United States and its allies must now do is find options between conventional war, or even nuclear holocaust, on the one hand, and appeasement on the other. The answer could be robotic, cyber, and space weapons -- if we have the will to deploy them. They already have been used for pinpoint strikes on terrorist leaders and insurgent forces in the Mideast.

Facebook's intelligent assistant M is now available for Facebook Messenger users in Australia, Canada, South Africa, and the U.K. M in Facebook Messenger first became available in April. M uses machine learning to scan words used in conversations to recommend actions or services. Tell someone good night and M may suggest a good night sticker. Chat about a plan and M may suggest you create a calendar event. M also suggests you do things like share your location, save a URL or video, initiate a voice or video call, or send best wishes when you're speaking to someone on their birthday.

The response to Musk's comments about the need for Artificial Intelligence (AI) regulation by experts in has been almost like a knee-jerk reaction. The reaction has been prevalently along the lines of not being able to identify areas that require regulation. I suspect that most AI researchers have not really made a serious effort with regards to the big picture. I am deliberately avoid discussing here the "Why?" of AI regulation. Rather I will discuss the questions of "What?" and "How?".

A video that shows an automatic bathroom soap dispenser failing to detect the hand of a dark-skinned man has gone viral and raised questions about racism in technology, as well as the lack of diversity in the industry that creates it. The now-viral video was uploaded to Twitter on Wednesday by Chukwuemeka Afigbo, Facebook's head of platform partnerships in the Middle east and Africa. He tweeted: 'If you have ever had a problem grasping the importance of diversity in tech and its impact on society, watch this video.' The video begins with a white man waving his hand under the dispenser and instantly getting soap on his first try. Then, a darker skinned man waves his hand under the dispenser in various directions for ten seconds, with soap never being released.

Stephen Colbert kicks up his feet at the Ed Sullivan Theater, where he tapes "The Late Show With Stephen Colbert." Stephen Colbert kicks up his feet at the Ed Sullivan Theater, where he tapes "The Late Show With Stephen Colbert." (Carolyn Cole / Los Angeles Times) Stephen Colbert's desktop computer monitor is ringed with reminders -- Post-it notes ("Joy is the most infallible sign of the presence of God," Pierre Teilhard de Chardin), keepsakes (cards from musicians Regina Spektor and Jack White), directives ("Ask yourself this question: Is my attitude worth catching?"), When not in use, Colbert's computer screen defaults to a live feed of the Earth taken from the International Space Station. Right now, the view has just crossed the Nile, the sun is setting and clouds are casting long shadows across the Red Sea. Colbert looks at these images whenever he's feeling anxious. There's the whole world, he tells himself.

There is a huge amount of pressure on healthcare services today with much written about the resulting impact on patient care. You only need to reflect on the recent election campaign to see what an emotive issue it remains throughout the UK. What's also true is that advanced technology is taking a bigger role in healthcare than ever before, looking to alleviate some of the burdens on our health systems and provide greater support for our wellbeing. One clear theme underpinning this shift is applications. Whether being used by organisations to adapt and streamline processes to improve data access and patient care or by patients themselves looking at ways to better understand and manage their health, the sector is set to be transformed by the evolution of apps.

Every day we hear about Machine Learning and Big Data Analytics... 'United Parcel Service saves 39 million gallons of fuel after using Big Data Analytics to optimise fleet operations'; 'PayPal uses Machine Learning on Customer, Financial and Network data to combat fraud'; 'Amazon uses Machine Learning to discover'lowest price' for over 20 million products'... Machine learning, a subset of Artificial Intelligence (AI) is a method of data analysis that uses algorithms to iteratively learn from data and derive insights without being explicitly programmed. We can find examples of how Machine Learning is already a part of our daily lives -- like Google Maps, using location data from smartphones, analyses the speed of movement of traffic at any given time. Or like Amazon makes recommendations for products -- "customers who bought this item also bought". Behind all these lie complex algorithms that are continuously learning new data and refining outcomes. In banking for example, using client's financial data, risk preferences and desired target return, 'Robo-Advisers' provide personalised, algorithm driven portfolio management services without human supervision.

Messenging app'Messenger' launched a range of new artificial intelligence (AI) features in Australia on Wednesday. The AI, called'M', works almost like a prompting service, where it recognises words and phrases used in a conversation and then suggests relevant content and actions based on the chat between the two users. For example, if you're speaking to someone on their birthday, 'M' will recognise either through a phrase used or their Messenger profile when their birthday is and then prompt you to send a birthday message. Similarly, if you are chatting about making plans or struggling to come to a group decision about something, the AI will suggest you make a plan or start a group poll respectively. If you are chatting in a one-on-one conversation, and one person rises the idea of making a call, 'M' will prompt you to start a video or voice chat.

About this course: How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters. In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data. In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data.