The results are in! Last month, our engineers experimented with new ideas and projects over a five-day Hackweek competition. With the goal to “provide an outlet to ideate, innovate, and create cool stuff in a self-organized way,” Hackweek encouraged novel approaches to problem solving—regardless of how directly they were tied to current JW Player products. Our product and engineering staff, including the top 3 winning teams, certainly didn’t disappoint.
- Grow audiences by seamlessly publishing videos to Facebook
- Reduce playback errors and viewer abandonment with standardized playback errors
- Deliver a broadcast-quality viewing experience on the web
- Create a consistent viewing experience and improve monetization on mobile
You have a teenage daughter. For the first time, she’s dating. Guy #1 tells you he’s taking her to see a 3D screening of The Incredibles 2, grab cherry slushies and hot dogs at 7-Eleven, and get gas at Chevron. Guy #2 simply tells you it’s going to be dinner and a movie. In both cases, you gave the go-ahead for the guys to take her out. But which one do you trust more to date your daughter? According to expert panelists at JW Insights, under GDPR, the clear winner in this scenario would be Guy #1.
After the launch of Video Player Bidding earlier this year, we’ve seen great adoption and some impressive benefits, including faster time-to-first-frame for ads and a great supplemental boost of ad demand for publishers’ ad stacks. As with any great new product comes great learning experiences. With months of data and the associated on-going analysis, our goal is to educate our customers on best practices to optimize Video Player Bidding setups to maximize revenue potential.
Rooted in the idea that machines can be as smart as humans, machine learning applies the concept of artificial intelligence to learn from data and autonomously improve performance based on that information. At JW Insights 2018, industry experts, including JW Player’s SVP of Technology, John Luther, shared their thoughts on what machine learning can—and can’t—do in our rapidly evolving digital age. Here are three takeaways.
At our annual JW Insights conference, we announced the final piece of the story that makes up the Buffer-Free Player—ad preloading. Since the first part of the story was released back in JW 7.2, we want to take a moment to remind you of everything that goes into reducing buffering. Understanding fully how it works is key to ensuring your player is optimized for improved user engagement and monetization.
Last week was Hackweek here at JW Player. Every six months we put aside all non-critical engineering work for one week so that our engineers and technical staff can experiment with new ideas. In some cases, these projects are not even directly related to their everyday work.