In this paper, we learn disentangled representations of timbre and pitch for musical instrument sounds. We adapt a framework based on variational autoencoders with Gaussian mixture latent distributions. Specifically, we use two separate encoders to learn distinct latent spaces for timbre and pitch, which form Gaussian mixture components representing instrument identity and pitch, respectively. For reconstruction, latent variables of timbre and pitch are sampled from corresponding mixture components, and are concatenated as the input to a decoder. We show the model efficacy by latent space visualization, and a quantitative analysis indicates the discriminability of these spaces, even with a limited number of instrument labels for training. The model allows for controllable synthesis of selected instrument sounds by sampling from the latent spaces. To evaluate this, we trained instrument and pitch classifiers using original labeled data. These classifiers achieve high accuracy when tested on our synthesized sounds, which verifies the model performance of controllable realistic timbre and pitch synthesis. Our model also enables timbre transfer between multiple instruments, with a single autoencoder architecture, which is evaluated by measuring the shift in posterior of instrument classification. Our in depth evaluation confirms the model ability to successfully disentangle timbre and pitch.

Following the attacks in Christchurch, New Zealand, in March, social media companies have once again come under growing pressure to "do …

Artificially intelligent systems are slowly taking over tasks previously done by humans, and many processes involving repetitive, simple movements have already been fully automated. In the meantime, humans continue to be superior when it comes to abstract and creative tasks. However, it seems like even when it comes to creativity, we're now being challenged by our own creations. In the last few years, we've seen the emergence of hundreds of "AI artists." These complex algorithms are creating unique (and sometimes eerie) works of art.

The digital video company, which split from Baidu (BIDU), has been seeing losses since going public in the US last March. In this year's first quarter, the company's net loss jumped year-over-year to $270.3 million from $63.1 million as operating costs soared. In contrast, Tencent (TCEHY) made a profit of $4.1 billion in the first quarter, and Tencent Music (TME), a digital music company that split from Tencent and went public in December, posted a profit of $147 million. Chinese e-commerce leader Alibaba (BABA), into the movie and video streaming business through its Alibaba Pictures and Youku units, made a profit of $3.8 billion in the first quarter, and Netflix (NFLX) and Amazon (AMZN) made profits of $344 million and $3.6 billion, respectively. Amazon is also into video streaming, although its main operations are e-commerce.

New technology devices and apps pop up as abundantly as summer weeds here in Silicon Valley. Chip-enhanced products offer to satisfy almost every need imaginable. Prompts from your smart refrigerator tell you to buy more milk. With a voice command, music plays to facilitate meditation, thanks to your smart -- always on -- helper who listens for your next query from a canister on your kitchen counter; you know, the one with a woman's voice and name. In this glut of offerings, how do you select what is truly useful from what is simply the latest "smart" thing?

DENVER, June 17, 2019 (GLOBE NEWSWIRE) -- RLH Corporation (NYSE:RLH) announced today that they have successfully deployed an industry-first Artificial Intelligence Virtual Agent for Central Reservations to support all 1,400 system hotels. This announcement follows the successful completion of a three-month program pilot originally announced on April 24, 2019. "The results of our pilot have been very positive," said RLH Corporation Director of Telephony Optimization & Analytics, April Weatherly. "We're seeing travelers engage with the technology at a rate higher than we anticipated and are very pleased with the Virtual Agent's ability to resolve traveler questions autonomously, reducing the cost of non-revenue related calls." In concert with the systemwide rollout of the Virtual Agent, new features and capabilities have been deployed to further support travelers.

The Bots Next Door follows the domestic lives of Roni and Rana Robot - a pair of sentient, artificial intelligence droids, trying to get on in a world dominated by humans. The Palo Alto treaty has decreed that creative limiters are now mandatory, to ensure artificial intelligence robots remain focused on their programmed function, and not anything else. But before they can be integrated into society to live among us, all bots must be'assigned' a lifelong menial vocation and'unified' into couples... Recently robo-coupled, trainbot R.O.N.I. and carebot R.A.N.A. are moving out of Skid Ro-bot into a home of their own. Things get worse when Roni unexpectedly finds himself both'unassigned' and able to have creative thoughts, putting Rana's social climbing aspirations in jeopardy.

Synthetic Data is fast becoming an essential component of autonomous driving and computer vision AI systems. By bringing together techniques from the movie and gaming industries (simulation, CGI) together with emerging generative neural networks (GANs, VAE's), we are now able to engineer perfectly-labeled, realistic datasets and simulated environments at scale. There is virtually no incremental cost of additional generated images and since the Synthetic Data is created all the attributes are known to pixel-perfect precision. Key labels such as depth, 3D position and partially obstructed objects are all provided by design. Application of this technology could allow important safety features to be brought to market quickly and cost-effectively, from crash prevention software to predictive maintenance, onboard diagnostics, and location insights.

The AI & Big Data Expo Europe, the leading Artificial Intelligence and big data conference and exhibition event, will take place on June 19 – 20, 2019, at the RAI, Amsterdam. It is a showcase of next generation technologies and strategies from the world of Artificial Intelligence and big data -- an opportunity to explore and discover the practical and successful implementation of AI and big data in driving forward your business in 2019 and beyond. The AI & Big Data Expo will bring together 2,000 visitors over the two days, including IT decision makers, developers and designers, heads of innovation, chief data officers, chief data scientists, brand managers, data analysts, start-ups and innovators, tech providers, C-level executives, and venture capitalists. This track covers the full spectrum of AI technologies -- how they are being developed and the real life scenarios where they are being utilized. Expect to hear about chatbots, visual recognition technologies, robotics, and machine learning.

Apps were smart but they are getting smarter with the addition of newer technologies like AI, AR, VR, and ML. With the enterprise and business facing crucial competition, they are striving to add every possible innovative addition that provides them a competitive edge and something extraordinary than the usual Android apps. Looks like AI has some significant impact on the business and enterprise apps. According to the reports of Statista AI is expected to cross $17 Billion by the end of 2020. I bet you want to be a part of this booming industry.