Rapid TV News reports that Ooyala and Jinni have joined up to deliver advanced video discovery technology. The article states, “The two personalisation leaders are targeting media companies, broadcasters and pay-TV operators with their new proposition that will integrate Ooyala’s machine-learning big-data analytics systems with Jinni‘s semantic discovery to deliver what the two companies call a powerful new level of video personalisation for all screens. The two companies will work together to develop and deploy what they claim will be a new level of machine learning powered by semantic discovery that will allow TV providers to tailor programming and video viewing experiences to each individual user. This will include personalised channels, custom programming guides, mood-based browsing and search, and viewer recommendations for both live and video-on-demand (VOD) content.” Read more
Posts Tagged ‘Jinni’
TEL AVIV, Israel–(BUSINESS WIRE)–Jinni, the creators of the world’s first and only semantic video discovery engine, announced its taste-and-mood based recommendations will reach TV audiences across Spain on CANAL+/YOMVI network. This is the first Spanish language Set-top box deployment of the multilingual Jinni solution and represent a further penetration of the next-generation user experience into the TV market in Europe with linear TV and on demand content recommendations. Read more
CHICAGO, Dec. 4, 2013 /PRNewswire/ – TMS, the international leader in entertainment navigation, and Jinni, the first and only taste-and-mood based semantic discovery engine for video, have announced that Jinni is using TMS’ world-class On®Entertainment metadata to provide availability information for linear TV and OTT content on its new ‘My TV & Movie Guide’ iPad app and web service. As a result, once consumers find something great to watch using Jinni’s taste and mood based recommendation engine, they can easily find when and where to watch it. Jinni’s superior recommendations are seamlessly integrated into the viewing experience and deliver the most personalized and relevant TV and movie options to end users. Read more
Darrell Etherington of Tech Crunch recently reported, “After a successful pilot project, Tel Aviv startup Jinni [a company we have covered multiple times over recent years], a provider of natural language processing-based video content recommendations, has been chosen by Xbox to power its Xbox content catalog recommendations over the course of a multi-year licensing agreement. Jinni wouldn’t reveal the terms of the deal, but it will bring their tech front and center to the Xbox and its show and movie library.” Read more
Yosi Glick, co-Founder and CEO of semantic taste engine Jinni, recently wrote a post about the technology and engineering Emmy award that is to be given to Amazon’s Instant Video for its personalized recommendation algorithms.
The basis for awarding the honor, he writes, lies with Amazon’s early item-to-item collaborative filtering (CF) algorithms that analyze consumer data to find statistical connections between items and then uses that as the basis for recommendations. But, says Glick, the company may be soon heading toward a fundamentally different approach.
“Amazon,” Glick explains, “is using the Emmy award to flaunt its latest Video Finder service, that seems to leave CF behind and embrace a new semantic approach to recommendation.”
Amazon is embracing semantics for its video content because it realizes that video is different than regular consumer items. TV and movies are “entertainment that is consumed based on personal tastes and our particular mood at the moment. The types of content each of us enjoy is not based on what ‘other people have also watched’, rather it has to do with the plots, moods, style and pace,” he writes. “So content has to be described and discovered the same way we choose and experience it.”
Categories in Amazon’s Video Finder service include classifications that describe the mood, plot, style and pace of titles — meaningful classifications that Glick says are the basis for semantic discovery. You can read the entire piece here.
Starting today, if you’re a customer of Singapore Telecommunications Ltd. in Malaysia, you’re going to be able to expand your notions of a more personalized web experience.
The company’s SingTel Digital Life Division has partnered with Nara to integrate its proprietary cloud-based neural network technology into its products. Nara today is best known for providing personalized restaurant recommendations: Its “digital DNA” algorithm adds up the sum of what it learns of what each person likes and doesn’t like regarding dining venues in order to serve up restaurant choices (see our story here).
Personalized experiences for SingTel customers will start at the restaurant level, too, with the Malaysia rollout followed by the debut of these services in Australia and Singapore. Nara always has said that its technology can expand beyond the restaurant domain, however, and a spokesperson for the company says such plans are still in the works, though she can’t provide a more definitive timeline.
The deal is not the first semantic matchup for SingTel, south-east Asia’s largest telecom operator.
Sunday night’s the big stroll down the red carpet for Hollywood’s elite — for the 85th time. But no need to wait until then to have some fun with old Oscar.
Some services with semantics and sentiment analytics in their genes have already begun. Here are a few examples:
Jinni, the semantic movie and TV Taste engine, has created a detail-filled graphic, based on analysis and cross-referencing it did according to its own Jinni Entertainment Genome (see its blog post here for a look at the entire graphic and more info on its creation):
Michael Grotticelli of Broadcast Engineering reports, “Jinni, the maker of a new kind of ‘semantic’ video guide that spans television, tablets, smart phones and the Web, has signed content distributors Time Warner Cable and Vudu among seven new licensees on four continents. It replaces old grid-style video guides with a new intuitive, personalized user experience. The company’s new “natural language understanding” (NLU) discovery engine supports voice-activated video guides that understand natural human language. The Jinni NLU engine leverages the company’s ‘Entertainment Genome’ to interpret natural human speech and derives the underlying meaning to enable intuitive interaction between users and their TVs.” Read more
According to an article out of the company, Jinni launched a “radically new NLU (natural language understanding) discovery engine to power the first voice-activated video guides that understand natural human language. Until now, the voice-activated TV experience was limited to basic commands because that was all the guide could process. The Jinni NLU engine leverages the company’s unique Entertainment Genome™ to interpret natural human speech and derive the underlying meaning to enable rich, intuitive interaction between users and their TVs. Now users will be able to simply tell their TV what they are in the mood to watch and Jinni will find the most fitting content from live TV, VOD and any other available video catalog.” Read more
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