In Mediterranean waters, off the coast of France, a diver recently visited the shipwreck La Lune -- a vesssel in King Louis XIV's fleet -- which lay untouched and unexplored on the ocean bottom since it sank in 1664. But the wreck's first nonaquatic visitor in centuries wasn't human -- it was a robot. Dubbed "OceanOne," the bright orange diving robot resembles a mecha-mermaid. It measures about 5 feet (1.5 meters) in length and has a partly human form: a torso, a head -- with stereoscopic vision -- and articulated arms. Its lower section holds its computer "brain," a power supply, and an array of eight multidirectional thrusters.

Nobody wants to be fat and men don't often want to be seen as effeminate, but for those in the gay community who live at the intersection of such identities, life can be like the worst case of double jeopardy. For Jamal Lewis however, who is also black and gender deviant, being fat and effeminate is a source of power, and a subject worthy of exploration in a documentary titled "No Fats, No Femmes." "For me, I'm just interested in the spaces that people are afraid to occupy," said Lewis, who uses "he-she" as a gender pronoun. "I think there is something to be learned from what we are most afraid of and so, if that's what I was taught to be afraid of, well [forget] that. I am the Fat Femme." Jamal Lewis, director of "No Fats, No Femmes," poses for a portrait on Third Street and Broadway in Los Angeles, Calif.

Being overweight carries with it a social stigma, as does being a man who embraces the feminine, but for those in the gay community who live at the intersection of such identities, life can be like the worst case of double jeopardy. To Jamal Lewis, however, who is also black and who identifies as "gender deviant," being fat and effeminate is a source of power and a subject worthy of exploration in a documentary titled "No Fats, No Femmes." "For me, I'm just interested in the spaces that people are afraid to occupy," said Lewis, who uses "he-she" as a gender pronoun. "I think there is something to be learned from what we are most afraid of, and so, if that's what I was taught to be afraid of, well [forget] that. I am the Fat Femme."

Distributional (or distribution-valued) data are a new type of data arising from several sources and are considered as realizations of distributional variables. A new set of fuzzy c-means algorithms for data described by distributional variables is proposed. The algorithms use the $L2$ Wasserstein distance between distributions as dissimilarity measures. Beside the extension of the fuzzy c-means algorithm for distributional data, and considering a decomposition of the squared $L2$ Wasserstein distance, we propose a set of algorithms using different automatic way to compute the weights associated with the variables as well as with their components, globally or cluster-wise. The relevance weights are computed in the clustering process introducing product-to-one constraints. The relevance weights induce adaptive distances expressing the importance of each variable or of each component in the clustering process, acting also as a variable selection method in clustering. We have tested the proposed algorithms on artificial and real-world data. Results confirm that the proposed methods are able to better take into account the cluster structure of the data with respect to the standard fuzzy c-means, with non-adaptive distances.

Jamie Metzl is a Senior Fellow for Technology and National Security at the Atlantic Council. After 4 billion years of evolution by one set of rules, our species is about to begin evolving by another. Overlapping and mutually reinforcing revolutions in genetics, information technology, artificial intelligence, big data analytics, and other fields are providing the tools that will make it possible to genetically alter our future offspring should we choose to do so. Nearly everybody wants to have cancers cured and terrible diseases eliminated. Most of us want to live longer, healthier and more robust lives. Genetic technologies will make that possible. But the very tools we will use to achieve these goals will also open the door to the selection for and ultimately manipulation of non-disease-related genetic traits -- and with them a new set of evolutionary possibilities.

After being stranded in the Mediterranean for three days, fear had overcome Alou Sango. "I thought that we would all die, because there was nothing left, the petrol had finished," he says of his journey from Libya. Like thousands before him, Sango boarded an overcrowded boat to escape the country's turmoil after being unable to return to his native Mali. But after days at sea the captain lost his way and, without a GPS position to give to the Italian authorities, the 100 or so passengers were losing hope. Their rubber dinghy was finally spotted by a Chinese vessel, which picked up the migrants and took them to Italy, where Sango, now 24, is studying through a Rome-based charity, Sant'Egidio Community.

Dreams are successions of images, ideas, emotions, and sensations that occur usually involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]

We present algorithms to effectively represent a set of Markov decision processes (MDPs), whose optimal policies have already been learned, by a smaller source subset for lifelong, policy-reuse-based transfer learning in reinforcement learning. This is necessary when the number of previous tasks is large and the cost of measuring similarity counteracts the benefit of transfer. The source subset forms an `$\epsilon$-net' over the original set of MDPs, in the sense that for each previous MDP $M_p$, there is a source $M^s$ whose optimal policy has $<\epsilon$ regret in $M_p$. Our contributions are as follows. We present EXP-3-Transfer, a principled policy-reuse algorithm that optimally reuses a given source policy set when learning for a new MDP. We present a framework to cluster the previous MDPs to extract a source subset. The framework consists of (i) a distance $d_V$ over MDPs to measure policy-based similarity between MDPs; (ii) a cost function $g(\cdot)$ that uses $d_V$ to measure how good a particular clustering is for generating useful source tasks for EXP-3-Transfer and (iii) a provably convergent algorithm, MHAV, for finding the optimal clustering. We validate our algorithms through experiments in a surveillance domain.

Robotics scientists at the US's Stanford University have achieved a remarkable first: they have successfully sent an automated avatar – which they describe as a robo-mermaid – down to an ancient shipwreck to retrieve a vase from the sunken vessel. La Lune, the flagship of Louis XIV of France, sank 20 miles off the south coast city of Toulon in 1664. Only a few dozen of the hundreds of men on board survived. The wreck, which lies at a depth of 100 metres, had never been disturbed until the OceanOne robot craft reached it two weeks ago and recovered the grapefruit-size vase. The humanoid diving robot was piloted, using virtual reality techniques, by Oussama Khatib, professor of computer science at Stanford.

Do they miss you when you're away on business? Can they put on a VR headset without their parents' help? That last one is pretty important. The year is zipping by, but before we launch full-force into next month, there's just about enough time for a quick roundup of the best updates and launches in April. It was recently revealed that Google was testing a new app for travelers, and now we have a better idea of what it might do.