Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.

Whether you’re watching a YouTube video, streaming media, or playing games, the sync signal associated with buffering can unload some severe existential dread.

Nothing takes you out of the experience faster than a continuously animated buffer circle that seems to extend to infinity. If you’ve fallen victim to buffering in the middle of an important moment in your favorite show or game, you’re not alone. More than 500 million hours of video are streamed per day, which means the audiences of streaming services likely encounter a metric ton of buffering.

Buffer haters everywhere will rejoice to learn that MIT researchers may have come up with a solution that could end slow load times once and for all. They have developed a unique artificial intelligence system that can optimize video streaming, making the process more reliable.

To understand how it works, first you must understand what buffering is and why it happens.

VB Event

The AI Impact Tour

Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you!


Learn More

The tech behind the annoyance

Internet traffic or data is sent in units called packets, also referred to as chunks.

When it comes to video, streaming or loading of said data happens in segments.

Over time, fragments come in as sequential portions of a whole file and are then stitched together — that’s why you can often start watching a video with little to no interruptions but run into problems soon after. When you start, the content is being played back to you at the same time it’s being downloaded.

During the process, if your connection drops or lessens, those chunks may stop flowing in, resulting in reduced performance for the entire file or video.

The idea is to continuously download these pieces and stitch the footage together in the background as you watch. But when the process is interrupted for whatever reason, you encounter buffering and the dreaded spinning circle.

This is exacerbated depending on the strength of a wireless signal, internet connection, or nearby traffic. Watching a video on a crowded public network, for instance, could result in significant buffering and performance issues.

Services like YouTube, Vimeo, and even social media platforms rely on algorithms called Adaptive Bitrate, or ABR. They initially measure the connection speeds, total bandwidth availability, and the resolution of the content to deliver a constant flow or stream of media.

Higher resolutions, obviously, require more resources, so sometimes you can offset buffering by lowering the quality or resolution of the content — that’s also why Netflix sometimes seems blurrier or worse than usual. The service or app has toned down the resolution of the content to match a higher-connection demand.

So, how can AI solve this issue?

MIT’s solution

The team at the MIT Computer Science and Artificial Intelligence Lab (CSAIL) rely on an automated intelligence system to swap between the appropriate algorithms. The neural network — digital, of course — can analyze the data and decide when a connection requires one particular algorithm over another.

The team trained the AI system through a reward- and penalty-based system.

Over the course of a month, they played streams of video content and left the system to do its thing. Failures resulted in a penalty, while successes were rewarded.

This eventually allowed the AI system to work out which algorithms work best for various scenarios, and when it’s time to swap between them.

Even more promising is the fact that the system can be adjusted and tweaked depending on what a service, connection, or media type calls for.

Content providers such as Netflix could opt to always select quality over performance or vice versa. The system would take this input into account and make the corresponding choices through automation and regular monitoring.

MIT professor Mohammad Alizadeh, who worked on the project, says the system can be completely customized. This solution would allow users to personalize “their own streaming experience based on whether they want to prioritize rebuffering versus resolution.”

The implications for other areas of media streaming are also exciting. Imagine being able to stream a high-resolution and intense gaming experience over VR, for example.

But the idea of putting an end to buffering is pretty cool in itself. Finally, streamers everywhere can say goodbye to that dreaded spinning circle.

Kayla Matthews is a technology writer interested in AI, chatbots, and tech news. She writes for VentureBeat, MakeUseOf, The Week, and TechnoBuffalo.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.