Samsung is developing AI ScaleNet capability, enabling seamless, high-resolution 8K streaming

As the world enters the era of 8K TVs with sales of 8K displays steadily increasing, TV manufacturers are constantly adding more offerings to the mix, the 8K market is expected to continue to grow. 

There are, however, a few challenges that need to be addressed before viewers around the world will be able to enjoy 8K’s stunning visuals in their entirety. First, more 8K content will need to be produced, and second, network connections need to be made capable of supporting the seamless streaming of 8K movies and shows.

To address these issues, researchers from Samsung Research, an advanced R&D hub within Samsung Electronics’ SET Business, have developed an AI Codec known as AI ScaleNet. First introduced at SDC19, this capability enables delivery of 8K content on networks that typically support only 4K speeds, without the need for additional infrastructure.

To learn more about AI ScaleNet’s development process and potential applications, Samsung Newsroom interviewed Kwangpyo Choi and Youngo Park – researchers from Samsung Research’s Visual Technology team, and the first individuals to suggest and develop this type of innovative technology.

AI ScaleNet utilizes deep learning technology to minimize data loss during compression and enable 8K content to be streamed on networks with lower bandwidth capabilities.

Here’s how it works, in a nutshell: 8K content is compressed to 4K quality using an AI downscaler and transmitted to the user’s TV, which utilizes AI to upscale the content back to 8K quality. When asked to describe the inspiration for the technology, Kwangpyo Choi, a researcher from Samsung Research’s Visual Technology, specified a need for a new video compression and transmission technology in order to accommodate the evolving media landscape, and to address related technical challenges.

“Multimedia content is rapidly moving online, so figuring out how to overcome bandwidth limitations for UHD content transmission has become a major task,” said Choi.

“With AI ScaleNet, users will be able to enjoy 8K-quality content, even at lower bandwidths,” added Youngo Park, another Samsung researcher. “In fact, during periods of high network traffic, when speeds tend to drop, viewers can still expect content to be presented at a relatively higher quality.”

AI ScaleNet addresses bandwidth limitations within modern network infrastructures with what’s known as an adaptive AI Codec. “AI Adaptive Bit Rate Streaming refers to AI technology that adapts to various bandwidths and adjusts the resolution to enable seamless streaming,” said Choi.

The difference the technology makes is especially clear when using over-the-top (OTT) services, where viewers typically notice changes in picture quality. As Choi explained, however, Samsung’s AI Codec and AI ScaleNet technology utilize AI that adapts to changes in bandwidth and optimizes quality, so users enjoy the highest-quality streaming experience possible.

Samsung Research Centers earn top places in leading AI challenges

Samsung Electronics’ Global Research & Development (R&D) centers play a key part in developing artificial intelligence (AI) capabilities for real-world usage. A credit to the work this advanced R&D branch of Samsung undertakes, both Samsung R&D Institute Poland and Samsung Research America AI Center have recently won two prestigious global challenges.

2019 marks the third year in a row that Samsung R&D Institute Poland, in partnership with the U.K.’s University of Edinburgh (UEDIN), has received accolades at the International Workshop on Spoken Language Translation (IWSLT), one of the top two global workshops on automatic language translation, along with the Workshop on Machine Translation (WMT). 

This year, Samsung R&D Institute Poland won first place in two categories, the first being text-to-text translation from English to Czech and the second – an end-to-end system translating English speech into German text.

For the text-to-text translation category, researchers worked to develop a model to translate the transcript of a spoken English-language TED Talk into Czech. Developing their winning model required the Samsung team to develop large, filtered corpora from which to work and generate as much synthetic data as possible. 

The work done by the Samsung R&D Institute Poland team, together with additional modeling help from UEDIN, was selected as the best in the challenge by human evaluators. This means that the translations produced by Samsung R&D Institute Poland’s system scored the highest both in fluency and adequacy.

Samsung R&D Institute Poland’s participation in their second winning category this year, the end-to-end translation system from English to German, was a first for the team. 

The task was to produce a German-language transcription of an English-language TED Talk audio recording. This task required the development of a single model that could take an audio file input and subsequently produce a translated transcription. It was made more difficult by the deficiency of the provided audio sources, compared to typical speech recognition task. 

Samsung R&D Institute Poland proposed several innovative methods for end-to-end speech translation that mitigated this source paucity, obtaining a state-of-the-art result with their final system that won them first place in the challenge.

This October, researchers from Samsung Research America’s AI Center received first place in the International Conference on Computer Vision (ICCV)’s challenge: Linguistic Meets Image and Video Retrieval (Fashion IQ). ICCV is a premier international computer vision conference that took place in Seoul, Korea, this year.

The challenge Samsung Research America AI Center took part in, sponsored by IBM research, aims to develop conversational shopping assistants that are more natural and real-world applicable. The task given to Samsung Research America AI Center‘s team, the ‘Superraptors’, belonged to the domain of image retrieval. 

In the task, an input query was specified in the form of a candidate image as well as in two natural language expressions that describe the visual differences of the search target. The goal of this challenge was to gather opinions and experience from researchers on the emerging space of visual content retrieval with a natural language interface.

Samsung Research America AI Center’s submission to the challenge, “Multimodal Ensemble of Diverse Models for Image Retrieval Using Natural Language Feedback”, blended the given data in different modalities with multiple deep learning models. 

The team’s win marks the first time a Samsung Research team has won a multimodal (language and vision) challenge; previously, Samsung AI Center Moscow, Samsung R&D Institute Poland and Samsung R&D Institute China-Beijing have received awards in single modality challenges.

Cloudinary releases AI-enabled video management platform to deliver engaging, dynamic video at scale in minutes

Cloudinary announced Tuesday key enhancements to its video management solution, including new AI capabilities to accelerate the entire video workflow process and help companies improve customer experience and engagement. 

Cloudinary’s modern approach to video management eliminates traditional limitations and pain-points, enabling brands to enhance and deliver dynamic video experiences quickly and cost effectively at scale, no matter where their content is viewed.

Nearly 90 percent of consumers rely on videos to help make their purchasing decisions, and landing pages with video see higher conversion rates of 80 percent or more. Video has long been a favorite of marketers for its storytelling power and effectiveness, but traditional video platforms weren’t built to support the volume and scale of today’s digital experience needs.

Cloudinary’s new video capabilities allow users to automate for format and quality at scale. It also eliminates the time-consuming work traditionally required to select the right codecs, formats and quality. This allows any user – marketer or developer – to deliver each video optimally for any browser, device and location. 

Deep learning capabilities dynamically re-frame landscape mode videos to any aspect ratio requested on-the-fly with intelligent content-aware cropping to automatically focus on the most engaging story in the frame.

By utilizing a single media platform, Cloudinary users can seamlessly create engaging product pages that include both video and images without the hassle that come from working across two or more disparate systems. 

The platform also simplifies search, improves team workflows and optimizes storage. AI-based auto-tagging, structured metadata, and advanced search capabilities let users more easily manage, store and search video libraries. Streamlined media workflows help ensure that all asset stakeholders are in sync. 

By creating a single source of truth, Cloudinary helps users manage a single video asset, no matter how many derived assets they create, which greatly streamlines storage management and discoverability.

Cloudinary further simplifies the process of moderating, optimizing and delivering many thousands of user-generated videos at scale by automating functions like cropping, resizing, branding, overlays, quality and more.