On Thursday, Microsoft researchers announced a new text-to-speech AI model called VALL-E that can closely simulate a person's voice when given a three-second audio sample. Once it learns a specific voice, VALL-E can synthesize audio of that person saying anything--and do it in a way that attempts to preserve the speaker's emotional tone. Its creators speculate that VALL-E could be used for high-quality text-to-speech applications, speech editing where a recording of a person could be edited and changed from a text transcript (making them say something they originally didn't), and audio content creation when combined with other generative AI models like GPT-3. Microsoft calls VALL-E a "neural codec language model," and it builds off of a technology called EnCodec, which Meta announced in October 2022. Unlike other text-to-speech methods that typically synthesize speech by manipulating waveforms, VALL-E generates discrete audio codec codes from text and acoustic prompts.

A woman looks at the camera and says, "Knowledge is one thing, virtue is another." Then, she says, "Knowledge is virtue." The same person, with the same voice, says two conflicting statements--but she only said the first in real life. The second statement is the work of an AI system that took audio of her speech and turned it into a video. Researchers from Nanyang Technological University in Singapore, the National Laboratory of Pattern Recognition in China, and artificial intelligence software company SenseTime developed the method for creating deepfakes from audio sources.

A woman looks at the camera and says, "Knowledge is one thing, virtue is another." Then, she says, "Knowledge is virtue." The same person, with the same voice, says two conflicting statements--but she only said the first in real life. The second statement is the work of an AI system that took audio of her speech and turned it into a video. Researchers from Nanyang Technological University in Singapore, the National Laboratory of Pattern Recognition in China, and artificial intelligence software company SenseTime developed the method for creating deepfakes from audio sources.

Beijing firm Megvii, which is being backed by the Chinese government, is expanding the places in which its powerful Face software is rolled out. The company secured a distributor in Thailand after Chinese police were able to use the software in China to locate and arrest more than 3,000 fugitives. The technology works by identifying 106 different features on people's faces, so even if the face is partially covered, by a balaclava for example, it should still work. Face is already worth an estimated £1.5billion, according to Business Insider, and Megvii are in talks with commercial banks and building managers to deploy it for security purposes.

For millions of successful poker players, the key to outwitting other players often rests in the face. The'poker face' -- a blank expression that never gives away a good or a bad hand -- has become one of the most iconic looks associated with professional poker players. A new artificial intelligence system might change that entirely. In a recent TED Conference talk, Dolby Laboratories chief scientist Poppy Crum detailed the company's new innovation that could see right through someone's expressions. Dolby developed a combined sensor and AI system that can tell whether someone is lying, infatuated, or posed for violence, Crum said at a big ideas TED Conference.

In around 60 seconds after opening the sale to the public, it sold out of the whole amount of available tokens (the AGI token), bringing the total raised to $36 million. However, in this day and age, a startup raising a lot of money in an ICO is not really of interest, at least to me. This is part and parcel of the crazy, unregulated, crypto world these days. But was is interesting is what SingularityNET actually plans to become. Dr. Ben Goertzel, the CEO and founder, has a grand vision.

An aspect of artificial intelligence that's sometimes overlooked is just how good it is at creating fake audio and video that's difficult to distinguish from reality. The advent of Photoshop got us doubting our eyes, but what happens when we can't rely on our other senses? The latest example of AI's audiovisual magic comes from the University of Washington, where researchers have created a new tool that takes audio files, converts them into realistic mouth movements, and then grafts those movements onto existing video. The end-result is a video of someone saying something they didn't. It's a confusing process to understand by just reading about it, so take a look at the video below: You can see two side-by-side clips of Barack Obama.

Minecraft, meet bombshell: The promise of a master version of studio Mojang's sandbox builder, identical across all platforms, not just functionally but at the codebase level, is finally happening. Pop some corks and fill those glasses. But when this new version arrives, it also stands to usher in something much grander and subversive. Despite efforts for years to bring Minecraft's many versions into alignment, the game has remained siloed in essential ways. You still have the Java-based PC edition, the franchise elder and a computers-only club (it also supports Mac and Linux) that is still the guiding template and place where new features tend to prove out first--to this version, all others are essentially beholden.

Another day, another fun internet thing that uses neural networks for facial manipulation. This time it's DeepWarp, a demo created by Yaroslav Ganin, Daniil Kononenko, Diana Sungatullina, and Victor Lempitsky, that uses deep architecture to move human eyeballs in a still image. First spotted by Prosthetic Knowledge, DeepWarp is focused on realistic "gaze manipulation." The authors of the demo acknowledge that similar projects already exist (like the smile-manipulator FaceApp), but without such a singular, detailed focus. The authors note that their findings in this study could be applied to solve real-world issues of eye movement, like for "gaze correction in video conferencing."

"We now have a new computing model to power AI and solve what was once unsolvable, with superhuman speed and intelligence." "It's like the Ratatouille movie, but instead of'anyone can cook' it's'anyone can do machine learning.'" "Focus on your company's challenges and what it is that you want to achieve." - Beena Ammanath, General Electric VP Data and Analytics "The biggest constraint is people's ability to understand the potential of what they can do." "Think of AI like a rocketship, where data is the fuel and neural networks are the engine." "Startups, consulting orgs, big players all want and try to do this but it's complex like playing 3D chess, so we have to be an extreme pattern matcher to plan, anticipate, execute many moves ahead to win." - Steve Ardire, Advisor for Software Startups