Deep generative systems that learn probabilistic models from a corpus of existing music do not explicitly encode knowledge of a musical style, compared to traditional rule-based systems. Thus, it can be difficult to determine whether deep models generate stylistically correct output without expert evaluation, but this is expensive and time-consuming. Therefore, there is a need for automatic, interpretable, and musically-motivated evaluation measures of generated music. In this paper, we introduce a grading function that evaluates four-part chorales in the style of J.S. Bach along important musical features. We use the grading function to evaluate the output of a Transformer model, and show that the function is both interpretable and outperforms human experts at discriminating Bach chorales from model-generated ones.

Ellie Goulding's new album opens with the sound of a crowd going wild, recorded at a festival date on the star's 2016/17 Delirium tour. It might have been Glastonbury, it might have been Rock In Rio, but the location isn't important. Wherever she was, Goulding was drained and tired and unhappy. "I'd just become a robot that was able to walk on stage and perform energetically and wildly," she says. "But actually I was just exhausted, and I don't remember any of it. I wasn't really able to enjoy anything properly."

LOLA, the fake news detection platform designed by Dr. David Lopez was recently used to uncover the online bullies of Greta Thunberg Fake news has become a menace that has resulted in bullying of unsuspecting victims. People fall prey to these fake tabloids and the age of social media makes it easier for them to generate hate in a matter of minutes. There are scores of these hoax newsrooms which spread wrong news disguised as authentic information via mediums like Instagram, Twitter, and Facebook. These platforms amplify the news effect manifold and drive traffic to the fake news site. The main agenda behind such sites are generally monetary or political.

Prominent Key Players –Covered in the Global Artificial Intelligence in Healthcare Market report: NVIDIA Corporation; Intel Corporation; IBM; Google …

Well explained SWOT analysis, revenue share and contact information are shared in this report analysis. "Artificial Intelligence (AI) Verticals Market is …

The Artificial Intelligence (AI) Technology Interest Group is your destination for discussions, online resources, education, and networking with …

Machine learning: This is a subset of the field of artificial intelligence that addresses problems that a computer cannot be "programmed" to solve.

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At IBM Research's recent "The Path to More Flexible AI" virtual roundtable, a panel of MIT and IBM experts discussed some of the biggest obstacles they face in developing artificial intelligence that can perform optimally in real-world situations. The solution, they agreed during the July 8 panel, is to embrace an integrated AI paradigm that amplifies the strengths and compensates for the weaknesses found in different approaches, including symbolic programming and deep learning. AI and automation are largely synonymous when you talk about industrial uses, said panelist David Cox, IBM Director of the MIT-IBM Watson AI Lab. "A lot of what people mean when they talk about AI today is automation," he added. "But automation is incredibly labor-intensive today, in a way that really just doesn't work for the problems we want to solve."

To improve how sporting events are covered in the news, a new AI 3D pose estimation model was recently developed by a group of researchers from The New York Times R&D group, and wrnch, an AI-computer vision company and member of the NVIDIA Inception program. The 3D pose estimation model can help extract data the human eye can easily miss and help journalists tell a story with more concrete data. "Traditional motion capture techniques require an athlete to wear physical markers. But this isn't possible during live sporting events. Instead, we built a solution that uses our photographers' cameras, machine learning and computer vision to capture this data as an event unfolds," the researchers stated in their article, Estimating 3D Poses of Athletes at Live Sporting Events.