Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the "disruptive" potentials of new AI technologies. Designed as a comprehensive evaluation, this paper analyzes and compares these guidelines highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems - and how the effectiveness in the demands of AI ethics can be improved.

We introduce the new task of Acoustic Question Answering (AQA) to promote research in acoustic reasoning. The AQA task consists of analyzing an acoustic scene composed by a combination of elementary sounds and answering questions that relate the position and properties of these sounds. The kind of relational questions asked, require that the models perform non-trivial reasoning in order to answer correctly. Although similar problems have been extensively studied in the domain of visual reasoning, we are not aware of any previous studies addressing the problem in the acoustic domain. We propose a method for generating the acoustic scenes from elementary sounds and a number of relevant questions for each scene using templates. We also present preliminary results obtained with two models (FiLM and MAC) that have been shown to work for visual reasoning.

There is tremendous buzz about artificial intelligence (AI) and its power to transform business. AI is associated mostly with online selling at companies such as Amazon and Netflix. Lately articles have reported sky-high ROI from AI designed to boost field and inside sales force performance. From all the success stories, one might conclude that most sales forces are well on their way to realizing value from AI, and that the going is easy. The truth is that only a small number of sales forces are using AI successfully.

GAN, a technique in unsupervised ML that pits two neural networks against each other in a zero-sum game framework, has a variety of applications including autonomous driving, text generation, video generation and digital image repair. Machine-learning ethicists and practitioners have begun to raise concerns over their application however, as computer-generated images, video and audio become more realistic, while still stressing that the tools could open up vital new areas of research for the ML community. Already, GANs are able to generate pictures of faces that look convincingly real to the untrained eye, Tamir explained. Earlier this month, OpenAI made a decision to not open-source their GAN based GPT-2 text-generation model, citing ethical concerns over the possible misuse of such technology in generating fake news articles. Already, GANs are able to generate pictures of faces that look convincingly real to the untrained eye.

Who needs the Russians to run a disinformation campaign when there are American leftists creating "deepfake" news? After the 2018 midterms, a wealthy Democrat became embroiled in controversy when it was reported that he had heavily bankrolled a false-flag operation in Alabama. Back in December, Internet billionaire Reid Hoffman apologized for his part in funding a high-tech disinformation campaign that sought to undermine support for Republican Roy Moore and boost Democrat Doug Jones. Just after Christmas, The Washington Post reported, "Hoffman invested $750,000 in one group, American Engagement Technologies, or AET, according to a person close to the matter but not authorized to discuss Hoffman's spending. Hoffman's statement Wednesday referred to AET, which has been linked to a campaign to spread disinformation targeting Moore."

Spotify has finally launched in India, following a long wait and a whole variety of legal arguments. The company will now let people sign up and get access to a version of Spotify that is "tuned to Indian music fans' personal tastes", including special features that have been created for the country. Spotify has been rumoured to be on its way into India for months. But it has been hit by a number of fallouts with record labels and other important companies that have threatened to derail the release. Those problems appear now to have been solved and the company's catalogue includes more than 40 million songs, which it said include "the hottest Indian and international music".

To say the entertainment industry has changed since Kevin Tsujihara became chief executive of film and TV studio Warner Bros. in 2013 would be an understatement. Netflix Inc. has become a disruptive force in film and television. Walt Disney Co. is about to become an even bigger giant when it absorbs much of 21st Century Fox and launches its own streaming service. Warner Bros. itself, at nearly a century old, is adjusting to new ownership under Dallas telecom behemoth AT&T Inc., which bought Time Warner Inc. (now called WarnerMedia) for $85.4 billion last year. The studio is coming off a strong year at the box office, grossing $5.6 billion globally with hits including "A Star Is Born" (which won the Oscar for best original song) and "Crazy Rich Asians."

Rotten Tomatoes is no longer allowing people to post comments about films before they come out, to try to stop trolling. The site announced the change in a blog post, saying some comments are "a disservice to our general readership". It says there's been an "an uptick in non-constructive input, sometimes bordering on trolling". But the movie site assured fans they would still be able to review films once they're released. "We have decided that turning off this feature for now is the best course of action," the blog said.

Spotify has finally launched in India, following a long wait and a whole variety of legal arguments. The company will now let people sign up and get access to a version of Spotify that is "tuned to Indian music fans' personal tastes", including special features that have been created for the country. Spotify has been rumoured to be on its way into India for months. But it has been hit by a number of fallouts with record labels and other important companies that have threatened to derail the release. Those problems appear now to have been solved and the company's catalogue includes more than 40 million songs, which it said include "the hottest Indian and international music".

I've seen a lot articles about people switching from TensorFlow to PyTorch, but not the other way around. We can have a good understanding about the strengths and weaknesses of the two frameworks if we could hear stories from both sides. I'm one of the people who are slowly moving towards PyTorch, I would like to know more before rewriting tens of thousands lines of old code. Even if both frameworks are similar, there should be far less people switching from PyTorch to TensorFlow because PyTorch came later. So, to have a good discussion are there at least people who are on PyTorch that are considering TensorFlow or people who are regretting switching to PyTorch?