If you knocked on Heaven's door, and God greeted you, what question would you ask? What is the nature of human consciousness, and how can it be expanded? Where does the Universe begin and end? What is time, and why isn't it constant? The Most Unknown, a documentary film in the Simons Foundation Science Sandbox series, takes the viewer on a fantastical journey of nine scientists as they intrepidly knock on Heaven's door.
In a world where the most famous dorm-room-born internet company has developed a reputation as a matrix of fake users and misleading posts, Ash Bhat and Rohan Phadte are hoping that the answer to online disinformation could come out of their own college apartment. Bhat and Phadte, both 21, are the founders of Robhat Labs, which they launched while previously students at the UC Berkeley. Last year, they debuted two misinformation-fighting projects. The first is NewsBot, an app for Facebook Messenger that aims to identify the political leaning of a given news piece. The duo's third project, set to be released next month, is a free browser extension called SurfSafe.
To death and taxes, Benjamin Franklin's binary list of life's certainties, add the expectation that this six-note sequence: Although we ponder ways to avoid or evade Franklin's list of unavoidable events, we generally accept this more benign certainty as immutable. The penultimate note of the tune generates such strong and specific anticipation that you are likely finding it difficult to continue reading without resolving the sequence. That anxious pause is key to composition and music's power. It creates a sense of prophetic certainty that allows musicians to play against expectations by thwarting the expected. The controlled manipulation of certainty and likelihood lurks behind those magical moments in which music has caused a shiver or a tear to fall. By infusing uncertainty or surprise into the mix, musicians literally play on our emotions.
Open any newspaper, on-screen or off, and you'll find that scientific controversy underlies many of the day's most hotly debated issues. The arguments surrounding genetically modified organisms, the threat of artificial intelligence to human existence, and stem cell research are exemplary. Science, a domain that we might naively expect to provide objective knowledge and definitive answers, has always been and will remain forever contested. What is the non-expert--that is, most of us--to do? For most issues, interpreting research findings or parsing the academic debate is infeasible.
In a dank corner of the internet, it is possible to find actresses from Game of Thrones or Harry Potter engaged in all manner of sex acts. Or at least to the world the carnal figures look like those actresses, and the faces in the videos are indeed their own. Everything south of the neck, however, belongs to different women. An artificial intelligence has almost seamlessly stitched the familiar visages into pornographic scenes, one face swapped for another. The genre is one of the cruelest, most invasive forms of identity theft invented in the internet era.
A lot of people don't like the word "moist." Several Facebook groups are dedicated to it, one with over 3,000 likes, New Yorker readers overwhelmingly selected it as the word to eliminate from the dictionary, and Jimmy Fallon sarcastically thanked it for being the worst word in the English language. When you ask people why this might be, there is no shortage of armchair theory: that there's something about the sounds involved, that it puts your face in a position similar to the facial expression of disgust, or that it reminds people of mold or sex.
Emerging anxieties pertaining to the rapid advancement and sophistication of artificial intelligence appear to be on a collision course with historic models of human exceptionality and individuality. Yet it is not just objective, technical sophistication in the development of AI that seems to cause this angst. It is also the linguistic treatment of machine "intelligence." But what is really at stake? Are we truly concerned that we will be surpassed in our capacities as human beings?
Such creative software can be used for autonomous creative tasks, such as inventing mathematical theories, writing poems, painting pictures, and composing music. However, computational creativity studies also enable us to understand human creativity and to produce programs for creative people to use, where the software acts as a creative collaborator rather than a mere tool. Historically, it's been difficult for society to come to terms with machines that purport to be intelligent and even more difficult to admit that they might be creative. For instance, in 1934, some professors at the University of Manchester in the United Kingdom built meccano models that were able to solve some mathematical equations. Groundbreaking for its time, this project was written up in a piece in Meccano Magazine.
A number of approaches have been advanced for taking data about a user's likes and dislikes and generating a general profile of the user. These profiles can be used to retrieve documents matching user interests; recommend music, movies, or other similar products; or carry out other tasks in a specialized fashion. This article presents a fundamentally new method for generating user profiles that takes advantage of a large-scale database of demographic data. These data are used to generalize user-specified data along the patterns common across the population, including areas not represented in the user's original data. The input data most often take the form of samples of the user's interests or preferences in a given area, and the profile is a generalization of these data that can be used generatively to carry out tasks on behalf of the user.