“The Future of Video Codecs: VP9, HEVC & AV1” at Streaming Media East 2018

Perspectives on the digital video world from JW Player’s SVP of Technology

Readers of this blog may have seen my recent posts about the new AV1 video codec from the Alliance for Open Media (see "An Encouraging Development in the HEVC Patent Mess" and "AV1: The Long Road Ahead"). If you are attending Streaming Media East next week, you can watch me and some friends from Bitmovin, Viacom, fuboTV and Littlstar discuss and debate AV1, HEVC and other developments that lie ahead on the video compression horizon.  

“Making 360 Video Easy for Publishers”​ at 7th FOKUS Media Web Symposium

Perspectives on the digital video world from JW Player’s SVP of Technology

My interest in virtual reality started in 3rd grade, when I was obsessed with a book called Danny Dunn, Invisible Boy. It's about a kid who is given a dragonfly robot that can be controlled with a "telepresence helmet" and gloves. He uses his ability to virtually exist in other places to enforce justice, specifically exposing a Spelling Bee cheater and preventing the dragonfly from falling into the hands of people with sinister motives.

An Encouraging Development in the HEVC Patent Mess

Perspectives on the digital video world from JW Player’s SVP of Technology

Earlier this month, HEVC Advance announced changes to their royalty fees for commercial use of the HEVC video compression standard. In short, these changes will make it essentially free to distribute video content on the Internet using the HEVC codec. Previously the content royalty rate was a complex matrix of rates by content type (subscription, title-by-title, etc), but it boiled down to potentially millions of dollars per year.

AV1: The Long Road Ahead

Perspectives on the digital video world from JW Player’s SVP of Product Strategy

Last month, Apple became a founding member of the Alliance for Open Media (AOM), the project that manages development of the emerging AV1 video codec, "a next-generation video format that is . . . interoperable and open,” according to the AOM website

The story originated simply from the word "Apple" suddenly appearing on the AOM website, yet within the video tech community it was seen as a seismic shift in the video tech industry.

Industry View: Reports of the “Dying Web” Are Still Greatly Exaggerated

Perspectives on the digital video world from JW Player’s SVP of Product Strategy

Last month, my ten year-old son showed me a stark message displayed on our Fire TV: "Starting on 2018-01-01, YouTube will not be available on this device."

To my son, YouTube and oxygen are basically the same thing, so the idea of either being "not available" is cause for a crisis. He demanded not only an explanation, but a solution.

A Google search provided us with the explanation: an ongoing spat between Amazon and Google (which owns YouTube). We had to wait a few days for Amazon to provide the solution: open YouTube in a web browser.

Yes indeed, there are two web browsers available on Fire TV. My son and I can verify that YouTube works great in both of them, no app required.

This incident touched on an important technology trend. Despite what people have been saying for the past five years, the web is not 'dying' at the hands of native apps.

Extend Your Insight With JW Player’s New Analytics Endpoint

  JW Player has recently released a brand new Analytics endpoint which allows users to access their Video and Advertising data programmatically! JW Player users are now able to pull JW Player data into their own application, data warehouse, or analytics tools like Looker, Domo, or Tableau.  JW data can be plugged into these tools without users having to implement their own frontend tracking & data processing engine. This is extremely useful for users that are managing multiple analytics platforms in addition to JW Player Analytics, but do not have time to visit each dashboard to pull reports and track individual metrics separately.

Redefining “Batch” in our Analytics Pipeline

  Much like the legendary Gordian Knot, sometimes when a problem becomes too thorny to solve, you just need to approach it from a different perspective. Especially in the fast-paced world of data, it’s tempting to devise complex systems when a simple one works just as well. A few months ago, the analytics team at JW Player started working on breaking apart the usage computation from our larger daily pipeline. This usage data needed to be more timely to help our customers avoid overage charges or unexpected loss of service. We called this new pipeline Usage-Mini because it would run more frequently on smaller batches of data as they arrive. As part of splitting apart the usage aggregation, we redesigned the pipeline, making one key decision that has led to huge improvements in performance, monitoring, and stability. This change was to reformulate our definition of batch from fixed time to fixed size. What’s the big deal about that? Keep reading to understand the impact of this simple choice.

Agile Incident Response for Big Data Systems

How We Increased Uptime and Decreased Engineering Stress

Working in the big data world can be a little chaotic. For us that means a stable flow of 20k events per second can spike to 50k over the course of an hour. It takes only seconds to look through our logs and find a perfect example:   chart   Things move fast and we need to be able to adapt and respond immediately when our systems are under stress. When a system goes “red” most people’s first instinct is to call the engineer who built it. Over time this can create silos of knowledge and an uneven load on the engineers. Another side-effect of this engineer-first thinking is that the priority is focused on fixing the problem, missing the importance of communication.

My Internship at JW Player

This summer I was very lucky to join JW Player as an engineering intern on the Data Team. It has been a fantastic experience. Aside from sailing on the Hudson River, enjoying Ping Pong games, and cycling on the Governors Island, I learned about their state-of-the-art data pipeline, followed Agile practices, and worked with an amazing group of people. I was part of the Discovery squad of the Data Team, worked on evaluating recommendation systems, and was responsible for developing an evaluation tool for our data-driven recommendations. With data-driven recommendations, we want to show our users relevant videos to increase video plays and user engagement. The question is how to evaluate if the recommended content is relevant, and which metrics to use as the measure. Generally there are three methods for evaluating recommendation systems: offline experiments, online trials, and user studies. In this project, we are using the user study approach, by directly asking the opinions of the viewers whether the recommended video is relevant or not.  

Architecture of the evaluation tool danmeng1