"This cross-functional collaboration with world leaders in machine learning and AAV gene therapy technologies gives us the potential to dramatically …

We have spent our childhood watching Star Wars where we had witnessed the introduction of the emergence of Artificial Intelligence. Certain robot-centric movies and hi-tech sci-fi movies have created curiosity in our minds to know more about Artificial Intelligence and its impact on human society. Are you confused about which book to read for gaining some perspectives on the Philosophy of the Artificial Intelligence world, which is dominating different fields in human society? Here is our recommendation list of five books that provide an overall perspective on the topic. In this book, you will learn details on some important philosophical issues in the theoretical framework of Artificial Intelligence.

At the start of the year, Spotify secured a patent for a voice recognition system that could detect the "emotional state," age and gender of a person and use that information to make personalized listening recommendations. As you might imagine, the possibility that the company was working on a technology like that made a lot of people uncomfortable, including digital rights non-profit Access Now. At the start of April, the organization sent Spotify a letter calling on it to abandon the tech. After Spotify privately responded to those concerns, Access Now, along with several other groups and a collection of more than 180 musicians, are asking the company to publicly commit to never using, licensing, selling or monetizing the system it patented. Some of the individuals and bands to sign the letter include Rage Against the Machine guitarist Tom Morello, rapper Talib Kweli and indie group DIIV.

Welcome to our April 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent conferences and events, and much more. In this edition we cover a diverse range of topics including AI ethics, education, music, GPT-Neo, and Westworld. Marija Slavkovik wrote this very interesting retrospective on the AAAI symposium on implementing AI ethics. The aim of the symposium was to "facilitate a deeper discussion on how intelligence, agency, and ethics may intermingle in organizations and in software implementations." Another ethics conference on the horizon is the AAAI/ACM conference on artificial intelligence, ethics, and society, scheduled for 19-21 May.

Apple is once again betting on a Tom Hanks movie to attract viewers and awards. Deadline has learned that Apple TV has bought the rights to Finch (formerly Bios), a sci-fi movie that stars Hanks as the namesake character who builds a robot to take care of his dog once he's gone. The three set out into a post-apocalyptic American West where Finch teaches his robot the "joy and wonder" of being alive. The tech giant won a "very competitive" bidding war between streaming services, according to Deadline. Finch was originally meant as a Universal release.

What is new is how quickly malicious actors can spread disinformation when the world is tightly connected across social networks and internet news sites. We can give up on the problem and rely on the platforms themselves to fact-check stories or posts and screen out disinformation--or we can build new tools to help people identify disinformation as soon as it crosses their screens. Preslav Nakov is a computer scientist at the Qatar Computing Research Institute in Doha specializing in speech and language processing. He leads a project using machine learning to assess the reliability of media sources. That allows his team to gather news articles alongside signals about their trustworthiness and political biases, all in a Google News-like format. "You cannot possibly fact-check every single claim in the world," Nakov explains. Instead, focus on the source. "I like to say that you can fact-check the fake news before it was even written." His team's tool, called the Tanbih News Aggregator, is available in Arabic and English and gathers articles in areas such as business, politics, sports, science and technology, and covid-19. Business Lab is hosted by Laurel Ruma, editorial director of Insights, the custom publishing division of MIT Technology Review. The show is a production of MIT Technology Review, with production help from Collective Next. This podcast was produced in partnership with the Qatar Foundation. "Even the best AI for spotting fake news is still terrible," MIT Technology Review, October 3, 2018 Laurel Ruma: From MIT Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Exploiting the power of new technologies and new capabilities often demands that we deny something equally forceful--human nature. Our natural approach to problem-solving is additive: stir in more data, layer in more sophisticated modeling, think through solving the problem for every contingency. It's our tendency to puzzle out what we think is missing, solve every edge case, add those pieces and give ourselves a pat on the back. While that's the first instinct, it's not necessarily the best course to follow when leveraging AI to solve business problems. A recent Washington Post article, based on research published in the scientific journal Nature, explores this phenomenon and demystifies why humans are wired to add complexity, even when doing so runs counter to our best interests, our goals and aspirations.

Hopefully you notice a shorter commute, but you might not notice why. "If you are looking closely, you can probably see the fisheye camera, but other than that it'll look like all the other intersections," said Pima County Department of Transportation's Assistant Division Manager of Maintenance and Operations Michelle Montagnino. The new system will use cameras, sensors and artificial intelligence to better estimate traffic volumes, arrivals on red and side-street delays. But she says privacy issues are not a concern. "Maybe you can make out a make and a color, definitely not a model, you're not going to tell license plate information, driver, or any of that information," she said.

Influenced by the field of Computer Vision, Generative Adversarial Networks (GANs) are often adopted for the audio domain using fixed-size two-dimensional spectrogram representations as the "image data". However, in the (musical) audio domain, it is often desired to generate output of variable duration. This paper presents VQCPC-GAN, an adversarial framework for synthesizing variable-length audio by exploiting Vector-Quantized Contrastive Predictive Coding (VQCPC). A sequence of VQCPC tokens extracted from real audio data serves as conditional input to a GAN architecture, providing step-wise time-dependent features of the generated content. The input noise z (characteristic in adversarial architectures) remains fixed over time, ensuring temporal consistency of global features. We evaluate the proposed model by comparing a diverse set of metrics against various strong baselines. Results show that, even though the baselines score best, VQCPC-GAN achieves comparable performance even when generating variable-length audio. Numerous sound examples are provided in the accompanying website, and we release the code for reproducibility.

Last week, the United States Senate played host to a number of social media company VPs during hearings on the potential dangers presented by algorithmic bias and amplification. While that meeting almost immediately broke down into a partisan circus of grandstanding grievance airing, Democratic senators did manage to focus a bit on how these recommendation algorithms might contribute to the spread of online misinformation and extremist ideologies. The issues and pitfalls presented by social algorithms are well-known and have been well-documented. So, really, what are we going to do about it? "So I think in order to answer that question, there's something critical that needs to happen: we need more independent researchers being able to analyze platforms and their behavior," Dr. Brandie Nonnecke, Director of the CITRIS Policy Lab at UC Berkeley, told Engadget. Social media companies "know that they need to be more transparent in what's happening on their platforms, but I'm of the firm belief that, in order for that transparency to be genuine, there needs to be collaboration between the platforms and independent peer reviewed, empirical research."