Abstract: This paper demonstrates emergence of computational creativity in the field of music. Different aspects of creativity such as producer, process, product and press are studied and formulated. Different notions of computational creativity such as novelty, quality and typicality of compositions as products are studied and evaluated. We formulate an algorithmic perception on human creativity and propose a prototype that is capable of demonstrating human-level creativity. We then validate the proposed prototype by applying various creativity benchmarks with the results obtained and compare the proposed prototype with the other existing computational creative systems. I. INTRODUCTION Computational creativity is the modeling or replicating human creativity computationally. Traditionally computational creativity has focused more on creative systems' products or processes, though this focus has widened recently. Research on creativity offers four Ps of creativity (Rhodes, 1961; MacKinnon, 1970; Jordanous, 2016). These four P's are: 1. Person/Producer: a creative agent 2. Process: an activity done by the creative agent 3. Product: the product of the creative process 4. Press/Environment: the overall environment of creativity 110 The proposed methodology addresses all the four P's of creativity unlike most of recent works, which focus on these individually (Saunders, 2012; Gervas & Leon, 2014; Misztal & Indurkhya, 2014; Sosa & Gero, 2015; Besold & Plaza, 2015; Harmon, 2015). Figure 1 gives a simplified view of proposed computational creative system in the context of four P's of creativity.

When people think of Artificial Intelligence (AI), the major image that pops up in their heads is that of a robot gliding around and giving mechanical replies. There are many forms of AI but humanoid robots are one of the most popular forms. They have been depicted in several Hollywood movies and if you are a fan of science fiction, you might have come across a few humanoids. One of the earliest forms of humanoids was created in 1495 by Leonardo Da Vinci. It was an armor suit and it could perform a lot of human functions such as sitting, standing and walking.

In China, blockchain technology is increasingly employed to settle court cases, local news outlet Global Times reported on April 25. Speaking at the 2019 Forum on China Intellectual Property Protection, Zhang Wen, president of the Beijing Internet Court -- which was established in September 2018, and has since processed 14,904 cases -- reportedly said that the court employs technologies such as artificial intelligence (AI) and blockchain to render judgement. Zhang reportedly told the Global Times that "of the 41 cases concluded [with blockchain technology] so far, parties chose to settle out of court rather than litigate in 40 cases with compelling evidence from blockchain. He also noted that the court had deployed blockchain in 58 cases to collect and provide evidence. "In the current use of AI as an assistant to make rulings, efficiency is prioritized over accuracy.

A long user history inevitably reflects the transitions of personal interests over time. The analyses on the user history require the robust sequential model to anticipate the transitions and the decays of user interests. The user history is often modeled by various RNN structures, but the RNN structures in the recommendation system still suffer from the long-term dependency and the interest drifts. To resolve these challenges, we suggest HCRNN with three hierarchical contexts of the global, the local, and the temporary interests. This structure is designed to withhold the global long-term interest of users, to reflect the local sub-sequence interests, and to attend the temporary interests of each transition. Besides, we propose a hierarchical context-based gate structure to incorporate our \textit{interest drift assumption}. As we suggest a new RNN structure, we support HCRNN with a complementary \textit{bi-channel attention} structure to utilize hierarchical context. We experimented the suggested structure on the sequential recommendation tasks with CiteULike, MovieLens, and LastFM, and our model showed the best performances in the sequential recommendations.

Artificial intelligence has been used to generate an endless stream of death metal music which will play on YouTube for 24 hours a day. The creation comes from two US programmers who built a virtual band known as'Dadabot'. It creators are now letting the technology play forever via a live stream called'Relentless Doppelganger' on the video-sharing platform. An AI system has been programmed to generate heavy metal music on YouTube 24 hours a day, with the aim to do so until'infinity'. Dadabot, and its continual supply of music, was trained using a large amount of music from Canadian death metal band Archspire.

AI expert and Sinovation Ventures CEO Dr. Kai-Fu Lee took the stage at the TIME 100 Summit in New York on Tuesday to discuss the current state of artificial intelligence, arguing that it will do as much for society's well-being as electricity. In his talk, Lee also touched on how governments and businesses can take advantage of artificial intelligence to improve nearly everything from infrastructure to the relationship between individuals and the companies handling their data. Lee showcased examples of AI applications, like warehouse machines that use computer vision to move and sort boxes, and an AI-powered rapper capable of generating rhymes based on any topic. Lee also highlighted an AI technique known as deep learning, and how it could be and has been used to generate false information, demonstrating with a fabricated audio clip of President Donald Trump. New machine learning techniques, like generative adversarial networks, have created real images of nonexistent people, as well as legit-looking news stories full of false information.

Don Draper and his crew of alpha males all trying to innovate and stay atop the cutthroat world of advertising. These stories of advertising greatness have been played out in AMC's award-winning drama series Mad Men. But the glory days of advertising have come and gone, yet the space has never been more significant, more influential, and powerful. Advertising is one of the biggest industries in the world and accounts for a lot of influence and direction. Advertising can stay up to date and on the cutting edge, evolving at every turn; that is what has helped it explode exponentially since the 60s.

Remember last week when Samsung unveiled its "foldable" phone? Well, it appears there are still a few wrinkles to iron out. Meanwhile, Google walkout organizers say they're facing retaliation from the company, a new Game of Thrones episode has come, and John Legend is putting Siri to shame. Here's the news you need to know in two minutes or less. Two Google employees who worked to organize a walkout of thousands of employees last November say the company is now retaliating against them.

In a project called "Relentless Doppelganger," a neural network is grinding out the blast beats, super-distorted guitars, and bellowing vocals of death metal. The best part of all: it's streaming its brutal creations 24 hours a day on YouTube -- an intriguing and public example of AI that's now able to generate convincing imitations of human art. The neural network is the work of Dadabots, a research duo that experiments with creating music using artificial intelligence tools. The death metal project, which they trained using tracks by death metal band Archspire, is the first that they've livestreamed instead of releasing as an album, and the change in format had everything to do with the quality of the neural network's output. In Dadabots' previous experiments, which dabbled in black metal and Beatles-inspired tracks, only about 5 percent of the AI-generated tracks were usable, co-creator CJ Carr told Futurism, and the programmers had to curate it.

For nearly a month, Dadabots has been streaming death metal nonstop on its YouTube channel. While that may sound like a huge undertaking for a typical four-piece metal band, Dadabots is actually an AI generating its own approximations of what death metal sounds like. Dadabots--a fake band powered by deep learning software--was developed by CJ Carr and Zack Zukowski, two musicians and technologists who met while they were going to Berklee College of Music in Boston they told The Outline. It's based on a recurrent neural network--computing architecture that "learns" patterns in a large amount of input data (in this case, death metal) in order to predict what musical elements and sequences are most common and recreates them. They broke down their process in a 2017 paper posted to the arXiv preprint server.