Arraiy 4.11.19

Category Archives: Machine Learning

AI and deep learning at NAB 2019

By Tim Nagle

If you’ve been there, you know. Attending NAB can be both exciting and a chore. The vast show floor spreads across three massive halls and several hotels, and it will challenge even the most comfortable shoes. With an engineering background and my daily position as a Flame artist, I am definitely a gear-head, but I feel I can hardly claim that title at these events.

Here are some of my takeaways from the show this year…

Tim Nagle

8K
Having listened to the rumor mill, this year’s event promised to be exciting. And for me, it did not disappoint. First impressions: 8K infrastructure is clearly the goal of the manufacturers. Massive data rates and more Ks are becoming the norm. Everybody seemed to have an 8K workflow announcement. As a Flame artist, I’m not exactly looking forward to working on 8K plates. Sure, it is a glorious number of pixels, but the challenges are very real. While this may be the hot topic of the show, the fact that it is on the horizon further solidifies the need for the industry at large to have a solid 4K infrastructure. Hey, maybe we can even stop delivering SD content soon? All kidding aside, the systems and infrastructure elements being designed are quite impressive. Seeing storage solutions that can read and write at these astronomical speeds is just jaw dropping.

Young Attendees
Attendance remained relatively stable this year, but what I did notice was a lot of young faces making their way around the halls. It seemed like high school and university students were able to take advantage of interfacing with manufacturers, as well as some great educational sessions. This is exciting, as I really enjoy watching young creatives get the opportunity to express themselves in their work and make the rest of us think a little differently.

Blackmagic Resolve 16

AI/Deep Learning
Speaking of the future, AI and deep learning algorithms are being implemented into many parts of our industry, and this is definitely something to watch for. The possibilities to increase productivity are real, but these technologies are still relatively new and need time to mature. Some of the post apps taking advantage of these algorithms come from Blackmagic, Autodesk and Adobe.

At the show, Blackmagic announced their Neural Engine AI processing, which is integrated into DaVinci Resolve 16 for facial recognition, speed warp estimation and object removal, to name just a few. These features will add to the productivity of this software, further claiming its place among the usual suspects for more than just color correction.

Flame 2020

The Autodesk Flame team has implemented deep learning in to their app as well. It portends really impressive uses for retouching and relighting, as well as creating depth maps of scenes. Autodesk demoed a shot of a woman on the beach, with no real key light possibility and very flat, diffused lighting in general. With a few nodes, they were able to relight her face to create a sense of depth and lighting direction. This same technique can be used for skin retouch as well, which is very useful in my everyday work.

Adobe has also been working on their implementation of AI with the integration of Sensei. In After Effects, the content-aware algorithms will help to re-texture surfaces, remove objects and edge blend when there isn’t a lot of texture to pull from. Watching a demo artist move through a few shots, removing cars and people from plates with relative ease and decent results, was impressive.

These demos have all made their way online, and I encourage everyone to watch. Seeing where we are headed is quite exciting. We are on our way to these tools being very accurate and useful in everyday situations, but they are all very much a work in progress. Good news, we still have jobs. The robots haven’t replaced us yet.


Tim Nagle is a Flame artist at Dallas-based Lucky Post.

Dell updates Precision 7000 Series workstation line

Dell has updated its Precision 7920 and 7820 towers and Precision 7920 rack workstations to target the media and entertainment industry. Enhancements include processing of large data workloads, AI capabilities, hot-swappable drives, a tool-less external power supply and a flexible 2U rack form factor that boosts cooling, noise reduction and space savings.

Both the Dell Precision 7920 and 7820 towers will be available with the new 2nd Gen Intel Xeon Scalable processors and Nvidia Quadro RTX graphic options to deliver enhanced performance for applications with large datasets, including enhancements for artificial intelligence and machine learning workloads. All Precision workstations come equipped with the Dell Precision Optimizer. The Dell Precision Optimizer Premium is available at an additional cost. This feature uses AI-based technology to tune the workstation based on how it is being used.

In addition, the Precision workstations now feature a multichannel thermal design for advanced cooling and acoustics. An externally accessible tool-less power supply and FlexBays for lockable, hot-swappable drives are also included.

For users needing high-security, remotely accessible 1:1 workstation performance, the updated Dell Precision 7920 rack workstation delivers the same performance and scalability of the Dell Precision 7920 tower in a 2U rack form factor. This rack workstation is targeted to OEMs and users who need to locate their compute resources and valuable data in central environments. This option can save space and help reduce noise and heat, while providing secure remote access to external employees and contractors.

Configuration options will include the recently announced 2nd Gen Intel Xeon Scalable processors, built for advanced workstation professionals, with up to 28 cores, 56 threads and 3TB DDR4 RDIMM per socket. The workstations will also support Intel Deep Learning Boost, a new set of Intel AVX-512 instructions.

The Precision 7000 Series workstations will be available in May with high-performance storage capacity options, including up to 120TB/96TB of Enterprise SATA HDD and up to 16TB of PCIe NVMe SSDs.

Arraiy 4.11.19

Video: Machine learning with Digital Domain’s Doug Roble

Just prior to NAB, postPerspective’s Randi Altman caught up with Digital Domain’s senior director of software R&D, Doug Roble, to talk machine learning.

Roble is on a panel on the Monday of NAB 2019 called “Influencers in AI: Companies Accelerating the Future.” It’s being moderated by Google’s technical director for media, Jeff Kember, and features Roble along with
Autodesk’s Evan Atherton, Nvidia’s Rick Champagne, Warner Bros’ Greg Gewickey, Story Tech/Television Academy’s Lori Schwartz.

In our conversation with Roble, he talks about how Digital Domain has been using machine learning in visual effects for a couple of years. He points to the movie Avengers and the character Thanos, which they worked on.

A lot of that character’s facial motion was done with a variety of machine learning techniques. Since then, Digital Domain has pushed that technology further, taking the machine learning aspect and putting it on realtime digital humans — including Doug Roble.

Watch our conversation and find out more…


GTC embraces machine learning and AI

By Mike McCarthy

I had the opportunity to attend GTC 2018, Nvidia‘s 9th annual technology conference in San Jose this week. GTC stands for GPU Technology Conference, and GPU stands for graphics processing unit, but graphics makes up a relatively small portion of the show at this point. The majority of the sessions and exhibitors are focused on machine learning and artificial intelligence.

And the majority of the graphics developments are centered around analyzing imagery, not generating it. Whether that is classifying photos on Pinterest or giving autonomous vehicles machine vision, it is based on the capability of computers to understand the content of an image. Now DriveSim, Nvidia’s new simulator for virtually testing autonomous drive software, dynamically creates imagery for the other system in the Constellation pair of servers to analyze and respond to, but that is entirely machine-to-machine imagery communication.

The main exception to this non-visual usage trend is Nvidia RTX, which allows raytracing to be rendered in realtime on GPUs. RTX can be used through Nvidia’s OptiX API, as well as Microsoft’s DirectX RayTracing API, and eventually through the open source Vulkan cross-platform graphics solution. It integrates with Nvidia’s AI Denoiser to use predictive rendering to further accelerate performance, and can be used in VR applications as well.

Nvidia RTX was first announced at the Game Developers Conference last week, but the first hardware to run it was just announced here at GTC, in the form of the new Quadro GV100. This $9,000 card replaces the existing Pascal-based GP100 with a Volta-based solution. It retains the same PCIe form factor, the quad DisplayPort 1.4 outputs and the NV-Link bridge to pair two cards at 200GB/s, but it jumps the GPU RAM per card from 16GB to 32GB of HBM2 memory. The GP100 was the first Quadro offering since the K6000 to support double-precision compute processing at full speed, and the increase from 3,584 to 5,120 CUDA cores should provide a 40% increase in performance, before you even look at the benefits of the 640 Tensor Cores.

Hopefully, we will see simpler versions of the Volta chip making their way into a broader array of more budget-conscious GPU options in the near future. The fact that the new Nvidia RTX technology is stated to require Volta architecture CPUs leads me to believe that they must be right on the horizon.

Nvidia also announced a new all-in-one GPU supercomputer — the DGX-2 supports twice as many Tesla V100 GPUs (16) with twice as much RAM each (32GB) compared to the existing DGX-1. This provides 81920 CUDA cores addressing 512GB of HBM2 memory, over a fabric of new NV-Link switches, as well as dual Xeon CPUs, Infiniband or 100GbE connectivity, and 32TB of SSD storage. This $400K supercomputer is marketed as the world’s largest GPU.

Nvidia and their partners had a number of cars and trucks on display throughout the show, showcasing various pieces of technology that are being developed to aid in the pursuit of autonomous vehicles.

Also on display in the category of “actually graphics related” was the new Max-Q version of the mobile Quadro P4000, which is integrated into PNY’s first mobile workstation, the Prevail Pro. Besides supporting professional VR applications, the HDMI and dual DisplayPort outputs allow a total of three external displays up to 4K each. It isn’t the smallest or lightest 15-inch laptop, but it is the only system under 17 inches I am aware of that supports the P4000, which is considered the minimum spec for professional VR implementation.

There are, of course, lots of other vendors exhibiting their products at GTC. I had the opportunity to watch 8K stereo 360 video playing off of a laptop with an external GPU. I also tried out the VRHero 5K Plus enterprise-level HMD, which brings the VR experience to whole other level. Much more affordable is TP-Cast’s $300 wireless upgrade Vive and Rift HMDs, the first of many untethered VR solutions. HTC has also recently announced the Vive Pro, which will be available in April for $800. It increases the resolution by 1/3 in both dimensions to 2880×1600 total, and moves from HDMI to DisplayPort 1.2 and USB-C. Besides VR products, they also had all sorts of robots in various forms on display.

Clearly the world of GPUs has extended far beyond the scope of accelerating computer graphics generation, and Nvidia is leading the way in bringing massive information processing to a variety of new and innovative applications. And if that leads us to hardware that can someday raytrace in realtime at 8K in VR, then I suppose everyone wins.


Mike McCarthy is an online editor/workflow consultant with 10 years of experience on feature films and commercials. He has been involved in pioneering new solutions for tapeless workflows, DSLR filmmaking and multi-screen and surround video experiences. Check out his site.