We have seen a rise of AI technologies for image and video processing. Even though things tend to take a little while longer making it to the world of audio, here we have also seen impressive technological advances. In this article, I will summarize some of these advances, outline further potentials of AI in audio processing as well as describe some of the possible pitfalls and challenges we might encounter in pursuing this cause. The kicker for my interest in AI use cases for audio processing was the publication of Google Deepmind's "WaveNet" -- A deep learning model for generating audio recordings [1] which was released during the end of 2016. Using an adapted network architecture, a dilated convolutional neural network, Deepmind researchers succeeded in generating very convincing text-to-speech and some interesting music-like recordings trained from classical piano recordings.

In November, the news website Quartz unveiled a bold idea: a studio, funded by the Knight Foundation, dedicated to reporting the news using machine learning techniques. Today, the Quartz AI Studio's first story dropped -- and it's an intriguing peek at how advancements in artificial intelligence could provide journalists with new tools for digging into public documents. For the story, Quartz reporters trained an algorithm to examine the section of ride-hailing app Lyft's Initial Public Offering (IPO) that lists risks the company anticipates -- and to identify the most "distinctive," or unusual, things that rattle Lyft's executives. The resulting list of Lyft's unusual concerns range from the fairly obvious to the moderately surprising. In addition to having concerns about "public perception," the company's leaders are also worried about how healthcare privacy laws will affect customers who use its service to catch rides to medical appointments.

If you've ever used a customer support livechat service, you've probably experienced that vague, sneaking suspicion that the "person" you're chatting with might actually be a robot. Like the endearingly stiff robots we've seen in countless movies – tragic, pitiful machines tortured by their painfully restricted emotional range, futilely hoping to attain a greater degree of humanity – chatbots often sound almost human, but not quite. Their speech is awkward, the cadence somehow off. It's the online equivalent of the "Uncanny Valley," a mysterious region nestled somewhere between the natural and the synthetic that offers a disturbing glimpse at how humans are making machines that could eventually supplant humans, if only their designers could somehow make their robotic creations less nightmarish. Love them or hate them, chatbots are here to stay. Chatbots have become extraordinarily popular in recent years largely due to dramatic advancements in machine learning and other underlying technologies such as natural language processing.

Chinese technology company Huawei has not had particularly good press recently. Countries including Australia have excluded it from construction of a 5G network, while the U.S. Justice Department recently laid criminal charges against the firm and its chief financial officer. It is understandable that in the midst of such woes, one might turn toward something harmless like classical music to wallow in sophisticated creativity, cultural tradition, and human mystery. In time for the Year of the Pig, Huawei recently presented a completion of Franz Schubert's "Unfinished Symphony" in performance at London's Cadogan Hall. It was accomplished by "pairing technological innovations of Huawei's artificial intelligence" from its smartphone with the human expertise of film composer Lucas Cantor. What was the division of labor here?

A lot has changed since Engadget was born, both in the gadgets we use and what we do with them on a regular basis. When the site started in 2004, fitness trackers, voice assistants and electric cars were the stuff of fiction. Now most of these are commonplace, so much so that we put our trust in them on a daily basis. To celebrate Engadget's 15th birthday, here are 15 things that didn't exist 15 years ago. In the past, mobile phones could do mostly two things: Make calls and send (and receive) text messages. If you had a fancier model, you could also play a little game. Features were added over the years, including music playback and photography. Smartphones like the BlackBerry and the Palm Treo that combined the functionality of PDAs and phones eventually came about, but were mostly designed for business users.

For years, YouTube, the world's most popular video network, has been battling issues with "bad actors" wreaking havoc with the system. The Google-owned property wants to be a safe haven for advertisers to reach young viewers, primarily, with its mix of original videos and a library with virtually anything ever recorded on video. Yet once again, YouTube found itself under scrutiny this week for more abuses. Seemingly innocent videos of young girls doing gymnastics were hijacked by adult viewers commenting with time stamps and links to child pornography videos elsewhere on the web. So after being outed by YouTuber Matt Watson expressing his rage and losing top advertisers like Disney, AT&T, Epic Games and others in response, YouTube said it would change its ways, and disable commenting on any video involving children.

Our industry has a duty to discuss the dark side of technology. Yet many organisations -- including some that wield enormous power and influence -- are reluctant to acknowledge that their platforms are used to spread disinformation, foster hatred, facilitate bullying, and much else that makes our world a worse place in which to live. Disinformation -- what is sometimes called "fake news" -- is a prime example of the unintended consequences of new technology. Its purpose is purely to create discord; it poisons public discourse and feeds festering hatreds with a litany of lies. What makes disinformation so effective is that it exploits characteristics of human nature such as confirmation bias, then seizes on the smallest seed of doubt and amplifies it with untruths and obfuscation.

This blog is syndicated from The New Rules of Privacy: Building Loyalty with Connected Consumers in the Age of Face Recognition and AI. To learn more click here. Since the invention of face recognition in the 1960s, has any single technology sparked more fascination for public safety officials, companies, journalists and Hollywood? When people learn that I'm the CEO of a face recognition company, they commonly reference its fictional use in shows like CSI, Black Mirror or even films such as the 1980s James Bond movie A View to a Kill. Most often, however, they mention Minority Report starring Tom Cruise. For the uninitiated, the film is based on a futuristic Phillip K. Dick short story and is set in the year 2054.

Looking to leverage AI in your organization? Don't miss the Business Summit at the AI Conference in New York, April 15–18, 2019. Register before March 1 to save with Early Price. In a recent post, we described what it would take to build a sustainable machine learning practice. By "sustainable," we mean projects that aren't just proofs of concepts or experiments. A sustainable practice means projects that are integral to an organization's mission: projects by which an organization lives or dies. These projects are built and supported by a stable team of engineers, and supported by a management team that understands what machine learning is, why it's important, and what it's capable of accomplishing. Finally, sustainable machine learning means that as many aspects of product development as possible are automated: not just building models, but cleaning data, building and managing data pipelines, testing, and much more. Machine learning will penetrate our organizations so deeply that it won't be possible for humans to manage them unassisted. Organizations throughout the world are waking up to the fact that security is essential to their software projects. Nobody wants to be the next Sony, the next Anthem, or the next Equifax.

When a news article revealed that Clarifai was working with the Pentagon and some employees questioned the ethics of building artificial intelligence that analyzed video captured by drones, the company said the project would save the lives of civilians and soldiers. "Clarifai's mission is to accelerate the progress of humanity with continually improving A.I.," read a blog post from Matt Zeiler, the company's founder and chief executive, and a prominent A.I. researcher. Later, in a news media interview, Mr. Zeiler announced a new management position that would ensure all company projects were ethically sound. As activists, researchers, and journalists voice concerns over the rise of artificial intelligence, warning against biased, deceptive and malicious applications, the companies building this technology are responding. From tech giants like Google and Microsoft to scrappy A.I. start-ups, many are creating corporate principles meant to ensure their systems are designed and deployed in an ethical way.