This post will summarize the current state of Artificial Intelligence (AI) applications for video in 2024, including recent progress and announcements. We’ll also take a closer look at AI video research and collaboration between Bitmovin and the ATHENA laboratory that has the potential to deliver huge leaps in quality improvements…
AI has been the hot buzz word in tech the past couple of years and we’re starting to see more and more practical applications for video emerging from the hype, like automatic closed-captioning and language translation, automated descriptions and summaries, and AI video Super Resolution upscaling. Bitmovin has especially focused on how AI can…
Globo’s content and reach When it comes to content scale and audience reach, Globo is on par with Hollywood and the big US broadcasters with over 3,000 hours of entertainment content being produced each year. The viewership numbers are equally impressive with forty-nine million Brazilians watching the daily, one-hour newscast and Globo’s Digital Hub attracting…
Encoding a feature-length film used to take hours, sometimes days. Split-and-stitch encoding changed all of that. By breaking a video file into smaller chunks, encoding them simultaneously across parallel cloud compute resources, and reassembling the final output, Bitmovin’s VOD Encoder can achieve speeds of over 92x real-time, and was the first in the industry to reach 100x.
Video analytics data is only valuable if you can act on it, and that’s easier said than done when you’re sifting through bitrate logs, error events, and ABR switches for thousands of sessions. Bitmovin’s Analytics AI Session Interpreter was designed to solve exactly that. Built during an internal hackathon and powered by Google’s Vertex AI, it automatically reads session data, identifies what went wrong, explains why it matters for the viewer experience, and tells you what to do about it.
Video streaming has grown rapidly over the past few years and is the prominent content people engage with online. This puts a lot of pressure on streaming companies as they now have to support a wide range of devices to maximize their viewer reach. Additionally, depending on the device type and the user’s network connectivity,…
The post will explain how Per-Title Encoding works and the advantages of using Per-Title Encoding compared to using the same bitrate ladder for all your content. Per-Title often requires fewer ABR ladder renditions and lower bitrates that translate into storage, egress and CDN cost savings. It also improves QoE with less buffering and quality…
Over the past 3-4 years, each industry that streams video has changed significantly. Depending on the company’s size, cloud adoption for streaming workloads before 2020 was driven by leading-edge “builders” with the technical expertise and in-house resources to experiment. Now, we’re in an era of early mainstream adoption led by “buyers” looking for comprehensive, reliable,…
Bitmovin was founded on research and that commitment to innovation never stopped. This post spotlights the ATHENA Lab, a joint research program between Bitmovin and the University of Klagenfurt, as its first cohort of PhD students completed their dissertations. Covering four major projects across edge computing, machine learning-based video encoding, adaptive bitrate streaming, and multi-access edge computing, the research tackles some of the streaming industry’s hardest problems.
As video workflows get more detailed, companies face numerous challenges in delivering a seamless viewing experience to their audiences. One of the biggest hurdles is the ability to make sense of disjointed sets of information from different points in the video delivery workflow. When a client experiences buffering or other playback issues, it can be…
The Bitmovin Blog. Keeping you informed.