Last year, graphics processing chip manufacturer NVIDIA released a new AI platform for video calls. The AI platform, Maxine, offers several intriguing features, including the game-changing ability to make it look like you're paying attention when you're not. Now, NVIDIA scientists have come up with another video-conferencing AI; one that'll let people use what are essentially deepfake versions of themselves for calls. The company's obviously building out Maxine, and looking for ways to make video conferencing better in general. The purpose of this particular AI is to lessen the amount of information that needs to be transmitted through the network in order to have clear video calls.

Nvidia AI researchers have introduced AI to generate talking heads for video conferences from a single 2D image. The team says they are capable of achieving a wide range of manipulation, from rotating and moving a person's head to motion transfer and video reconstruction. The AI uses the first frame in a video as a 2D photo and then uses an unsupervised learning method to gather 3D keypoints within a video. In addition to outperforming other approaches in tests using benchmark datasets, the AI achieves H.264 quality video using one-tenth of the bandwidth that was previously required. Nvidia research scientists Ting-Chun Wang, Arun Mallya, and Ming-Yu Liu published a paper about the model Monday.

Artificial Intelligence or popularly known as AI, has been the main driver of bringing disruption to today's tech world. While its applications like machine learning, neural network, deep learning have already earned huge recognition with their wide-ranging applications and use cases, AI is still in a nascent stage. This means, new developments are simultaneously taking place in this discipline, which can soon transform the AI industry and lead to new possibilities. So, some of the AI technologies today may become obsolete in the next ten years, and others may pave the way to even better versions of themselves. Let us have a look at some of the promising AI technologies of tomorrow.

Last month, Nvidia announced a new platform called Maxine that uses AI to enhance the performance and functionality of video conferencing software. The software uses a neural network to create a compact representation of a person's face. This compact representation can then be sent across the network, where a second neural network reconstructs the original image--possibly with helpful modifications. Nvidia says that its technique can reduce the bandwidth needs of video conferencing software by a factor of 10 compared to conventional compression techniques. It can also change how a person's face is displayed.

Indeed, it's now possible to impersonate practically anybody with astonishing verisimilitude, thanks to the artificial intelligence technology known as generative adversarial networks (GANs). Fortunately, deepfakes have not shown their ugly side in the US presidential election campaign that is now drawing to a close. No one has been able to point to any significant use of GANs to produce deceptive videos and thereby manipulate public opinion. Instead, GANs are increasingly popping up in socially beneficial applications, such as for photorealistic animation and live-action video post-production. As evidenced by several recent industry announcements, next-generation remote collaboration services are using GANs and other AI techniques to improve the quality of rendered streams while improving the productivity of participants on these calls.

This article is part of "Deconstructing artificial intelligence," a series of posts that explore the details of how AI applications work. One of the things that caught my eye at Nvidia's flagship event, the GPU Technology Conference (GTC), was Maxine, a platform that leverages artificial intelligence to improve the quality and experience of video-conferencing applications in real-time. Maxine used deep learning for resolution improvement, background noise reduction, video compression, face alignment, and real-time translation and transcription. In this post, which marks the first installation of our "deconstructing artificial intelligence" series, we will take a look at how some of these features work and how they tie-in with AI research done at Nvidia. We'll also explore the pending issues and the possible business model for Nvidia's AI-powered video-conferencing platform.

It's no secret that global Internet traffic has dramatically increased thanks to a pandemic forcing everyone to work and learn from home. It's difficult to find exact, comprehensive figures, but it's clear that as a result of COVID-19, Internet traffic is up generally by 30% to 50%. And video conferencing is likely a major culprit. After all, Zoom's revenues jumped by an unbelievable yearly 355% in the second quarter, to $663.5 million, after COVID-19 made the videoconferencing platform part of many people's daily routine. Zoom says it now has over 300 million daily users.

It can adjust your camera's focus to place you in the center of the frame, reorientate your face and add virtual backgrounds. You can also have an AI avatar replace your face on calls, while Maxine offers real-time closed captioning and translation through NVIDIA Jarvis. The company says Maxine's video compression can reduce the bandwidth needed for calls by 90 percent versus H.264 compression. As such, video calls could vacuum up much less of your data in the near future. Maxine uses NVIDIA Tensor Core GPU acceleration and it runs in the cloud. So, you won't exactly need one of NVIDIA's latest graphics cards to harness these features if your video calling app of choice enables them. They should work on any device. Zoom, Skype, Microsoft Teams and Google Meet have some of these features already, but tapping into the Maxine platform could help them improve those functions. AI developers, startups, its software partners and makes of video calling apps can now apply for early access to Maxine.

Nvidia today launched Nvidia Maxine, a platform that provides developers with a suite of GPU-accelerated AI conferencing software to enhance video quality. The company describes Maxine as a "cloud-native" solution that makes it possible for service providers to bring AI effects -- including gaze correction, super-resolution, noise cancellation, face relighting, and more -- to end users. Developers, software partners, and service providers can apply for early access to Maxine starting this week. Videoconferencing has exploded during the pandemic, as it offers a way to communicate while minimizing infection risk. In late April, Zoom surpassed 300 million daily meeting participants, up from 200 million earlier in the month and 10 million in December. According to a report from App Annie, business conferencing apps topped 62 million downloads during the week of March 14-21.

Nvidia has announced a new videoconferencing platform for developers named Nvidia Maxine that it claims can fix some of the most common problems in video calls. Maxine will process calls in the cloud using Nvidia's GPUs and boost call quality in a number of ways with the help of artificial intelligence. Using AI, Maxine can realign callers' faces and gazes so that they're always looking directly at their camera, reduce the bandwidth requirement for calls by up to 90 percent by only transmitting "key facial points," and upscale the resolution of videos. Other features available in Maxine include face re-lighting, real-time translation and transcription, and animated avatars. Not all of these features are new of course.