Let's face it: traditional TV is fading. Viewing habits have totally changed, with spectators now favoring online video. In this competitive market where big players like Netflix and Hulu are racing for most eyeballs it might be rather difficult to encourage audiences to stay tuned to your video content. According to NewVantage Venture Partners, big data and machine learning (ML) deliver true value to enterprises. The marriage of these techs allows getting advanced customer intelligence, automating mission-critical workflows, and, in turn, significantly improving viewer experience.

Sequence-to-Sequence (seq2seq) models have become overwhelmingly popular in building end-to-end trainable dialogue systems. Though highly efficient in learning the backbone of human-computer communications, they suffer from the problem of strongly favoring short generic responses. In this paper, we argue that a good response should smoothly connect both the preceding dialogue history and the following conversations. We strengthen this connection through mutual information maximization. To sidestep the non-differentiability of discrete natural language tokens, we introduce an auxiliary continuous code space and map such code space to a learnable prior distribution for generation purpose. Experiments on two dialogue datasets validate the effectiveness of our model, where the generated responses are closely related to the dialogue context and lead to more interactive conversations.

People feel emotions when listening to music. However, emotions are not tangible objects that can be exploited in the music composition process as they are difficult to capture and quantify in algorithms. We present a novel musical interface, Mugeetion, designed to capture occurring instances of emotional states from users' facial gestures and relay that data to associated musical features. Mugeetion can translate qualitative data of emotional states into quantitative data, which can be utilized in the sound generation process. We also presented and tested this work in the exhibition of sound installation, Hearing Seascape, using the audiences' facial expressions. Audiences heard changes in the background sound based on their emotional state. The process contributes multiple research areas, such as gesture tracking systems, emotion-sound modeling, and the connection between sound and facial gesture.

The movie was made through a collaboration with science fiction writer Arthur C. Clarke and film director Stanley Kubrick, inspired by Clarke's novel Childhood's End and his lesser-known short story The Sentinel. A striking work of speculative fiction, it depicts–in terms sometimes hopeful and other times cautionary–a future of alien contact, interplanetary travel, conscious machines, and even the next great evolutionary leap of humankind. The most obvious way in which 2018 has fallen short of the vision of 2001 is in space travel. People are not yet routinely visiting space stations, making unremarkable visits to one of several moon bases, nor traveling to other planets. But Kubrick and Clarke hit the bull's-eye when imagining the possibilities, problems and challenges of the future of artificial intelligence.

Marketers have plenty of ways to measure video campaign success, but artificial intelligence is uncovering new methods for determining whether the dollars you're spending are being applied optimally. That's what video insights company YouFirst is offering, and a recent study of one of its clients, spanning 13 video campaigns over two years, is revealing. Even with the latest and greatest analytics tools at the brand's disposal, AI and emotion tracking are opening up new insights. More importantly, AI is showing where to make changes to a campaign so it hits its exact target market -- and when to pull the plug. YouFirst works by allowing a focus group of video viewers access to the content through its player, which -- with permission -- monitors the facial expressions of the consumer via a webcam.

Last December, the world ushered in a new era of popular music: human and artificial intelligence (A.I.) collaboration. Musical eras are often defined by their dominant modes of production -- analog, electronic, digital -- each bringing about new styles and ways of listening. This era is marked by the release of the first A.I.-human collaborated album, Hello World, by the music collaborative Skygge. Skygge, led by composer and producer Benoît Carré and musician and tech researcher François Pachet, translates to "shadow" in Danish and was inspired by the Hans Christian Andersen story of the same name. We now know that algorithms can learn human bias, but can they also create highly creative and emotionally engaging music?

Growing up, one of my favorite movies was Steven Spielberg's Minority Report. I was fascinated by the idea that a crime could be prevented before it occurred. More interesting to me at the time was the futuristic role that'super intelligent' technology – something depicted as more sophisticated and advanced than humans – could play in doing this accurately. Recently, the role that pre-crime and artificial intelligence can play in our world has been explored in episodes of the popular Netflix TV show Black Mirror, focusing on the debate between free will and determinism. Working in counter-terrorism, I know that the use of artificial intelligence in the security space is fast becoming a reality. After all, decisions and choices previously made by humans are being increasingly delegated to algorithms, which can advise, and decide, how data is interpreted and what actions should result.

When in industry more than 50% of new roles are driven towards a specific skill set and when projections from various recruiting companies shows the world being short of certain skilled people and employers are scrambling to find certain type of resources in the market and are willing to pay a premium to get them on-board then it is a clear sign that we're in a hype cycle. The skill here is Data Science and resources Data Scientists. Those who have been in the industry long enough can recognize this. A decade back industry was going crazy for a similar skill known as Business Analysts, who are now found dime a dozen in the market (apologies if I've hurt someone's sentiments, but you can't escape the truth). I know certain organizations where the certain preference is being given to Data Modelers, Data Analysts & data Scientists instead of sitting Business Analysts.

Say you're staring at the image of a small circle in the center of a larger circle: The larger one looks green, but the smaller one appears gray. Except your friend looks at the same image and sees another green circle. So is it green or gray? It can be maddening and fun to try to decipher what is real and what is not. In this instance, your brain is processing a type of optical illusion, a phenomenon where your visual perception is shaped by the surrounding context of what you are looking at.

Keeping in mind the overall trustworthiness of the website itself--and checking its Wikipedia page, if it has one--is a good step for regular people, too. For example, in August, Facebook and a cybersecurity firm announced they'd uncovered "inauthentic" news coming out of Iran. One of the websites associated with Iran was called the Liberty Front Press; they called themselves "independent" but appeared to actually be pro-Iran. And tellingly, the site does not appear to have a Wikipedia page. Of course, the MIT research group aren't the only ones using AI to analyze language like this: a Google-made AI system called Jigsaw automatically scores the toxicity of reader comments, and Facebook has turned to AI to help augment its efforts to keep hate speech at bay in Myanmar.