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TV Tech
TV Tech
George Winslow

Streaming Video Technology Alliance Convenes in New Orleans

STVA

FREMONT, Calif.—The Streaming Video Technology Alliance (SVTA) is welcoming new members CDN77, ITV, Microsoft, and Mux to its Q2 Member Meeting in New Orleans at the Hilton St. Charles. 

The May 17 and 18 meeting includes Working Group sessions, industry presentations, and networking events. 

“Q2 has been a quarter of exciting developments at SVTA, including the launch of SVTA University and the first SEGMENTS conference, held yesterday, where we announced the 2023 Fellow Program honorees,” said Jason Thibeault, executive director at the Streaming Video Technology Alliance. “This is our first time holding an SVTA member meeting in beautiful New Orleans, and we’re looking forward to a productive two days of industry discussions, debates, and networking. On the Working Group front, we have a number of openings for Working Group chairs, which creates new opportunities for our members to participate and make a positive impact on the industry.”

The group also announced that it had moved all of its web properties to Qwilt’s CDN. Qwilt’s Open Caching-based solution enables edge cloud services to be deeply embedded in service provider networks, and by tapping directly into the service provider network edge, content publishers can get closer to their users than ever before.

“We’re proud to report that all of the SVTA sites are running faster now, thanks to Qwilt’s CDN, which is built on Open Caching,” Thibeault stated. “We felt it was a good signal to the industry to utilize a service provider built on SVTA specifications.”

In addition, the group reported that SVTA Streaming Video Wiki, which was launched earlier this year, is now available in multiple languages and that ChatGPT Integration to be released next quarter. 

Users can click on one of the language links at the top of each page to translate the page in real time. The SVTA is also working on the integration of a ChatGPT engine, based on a large language model (LLM) generated specifically from the Wiki content, to provide a more natural way for visitors to interact with the Wiki. The Wiki can be accessed here

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