These days everything is done with computers. They’re all around us all the time. You can love them or hate them, but you HAVE to live with them. There are some people who like their computers a bit more than the average Joe. They’re looking at them fondly, touching them in a delicate way and deep in their hearts they wish their computers would come to life. This sort of unlikely relationship is the center of one of the most Oscar-buzzed films of the season – “Her“, an offbeat sci-fi romantic comedy about a lonely writer who falls in love with his new operating system designed to meet his every need (which is kind of how Jinni is, and if you love us, the feeling is mutual).
So due to Her’s (limited) release this weekend, here is our take on unlikely couples including a few tips for seducing and building a healthy relationship with your computer. Let the romantic algorithm shine on…
So let’s begin. In order to form a successful relationship one must understand the person/artifact in front of him/her. So for you to understand your computer better, we recommend watching Start-Ups: Silicon Valley (2012)
This reality show follows prodigies in the computers and web world as they try to rise to the top and fulfill their ambitions. With a captivating and sincere approach, the show combines the big brother with science and technology. It’s a great opportunity for you to learn how to communicate with computers from the people who do It best.
After communicating with the computer, it’s time to seduce it and what’s better than a feel good sitcom?
My Hero (2000 – 2006)
The plus side of watching a TV show with your computer is that it’s long term, so your computer can see your intentions are real, not a one-time thing. My Hero describes another fantastic romance between a superhero and a young nurse. An imaginary show that shows love can conquer evil aliens and villains as long as you have some superhuman powers.
Your computer should know love transcends everything, so maybe you should show it an example of a supernatural romance.
Spirited (2010 – 2011)
In this semi-fantastic comedy series from Australia, we see what happens when a divorced dentist moves to an old apartment where the ghost of 80s rock n roll star resides. Of course, she’s the only one who can see him (kind of romantic in it’s own supernatural way…). This humorous fantasy presents some rock tunes, along with paranormal activities and an offbeat love story that’s sure could convince your computer love transcends human limits…
Wilfred (2011 – )
An unlikely relationship such as this, deserves an unusual dog. Wilfred is a comedy series about a dog who thinks he’s human. Elijah wood plays an ordinary guy, about to kill himself, who gets to know this human-dog and as time goes by they become one of the most odd couples in TV history (Not a couple – couple, more buddies-like couple). From dark jokes, through grossout humor to plain old silly humor, Wilfred can help you form a healthier relationship with your computer.
Splash is a good choice ’cause it’s another example of impossible love, and in that case, true love. Tom Hanks, 29 years younger, and Daryl Hanna, approximately 29 bad movies earlier, starred in this critically acclaimed Cinderella story. A young man falls in love with a fish (actually, a mermaid) out of water. Both sentimental and humorous, Splash should set the mood for the rest of the evening. And now, why not take your computer out for a nice dinner? Just be ready to get some odd looks like Ryan Gosling got in…
Lars and The Real Girl (2007)
Lars’s new girlfriend is the extremely shy and quiet Bianca. actually, Bianca is quiet because Bianca is a doll but no one wants to tell Lars and risk making his already unstable personality even more fragile. In every relationship there comes the point you introduce your spouse to your family and friends, so in this movie you can prepare yourself for the moment they’ll see your dating a computer. One can only hope they’ll be supportive and sentimental as the characters in this wonderful dramedy.
Now after dinner, grab a cup of coffee, and invite over…
Coffee Samurai (2011)
Many people like coffee. Many people buy coffee machines. But just a few fall in love with their coffee machine. Not that we’re judging anyone. Coffee Samurai is an anime short about a college student who falls in love with coffee vending machine named Jin. Jin was a Samurai who experienced a reincarnation and got back as a vending machine due to a miss interpreted wish come true… Jin could probably make you and your computer some miraculous coffee . Which may lead to a magical event such as the one in…
Ruby Sparks (2012)
a young writer’s wish comes true when the protagonist of his novel, and the girl of his dreams, comes to life. But when he finds out he can write her actions and characteristics he starts losing his mind and his relationship. A clever and bittersweet tale about what we want from love and what we think we want.
Ruby Sparks shows the ups and downs of love, and if after a while you realize your computer and you have more downs then ups maybe you should erase it’s memory like they did in…
Now remember, this is just in case things went horribly bad and you and your computer decide there’s no turning back and breakup. In that case use the services of doctor Mierzwiak (Tom Wilkinson) in order to erase yours and your computer’s memory like he did in this original and essential film. A couple (Jim Carrey and Kate Winslet) decides to breakup and erase their memory in order to forget each other. As we go inside their minds we see a non linear presentation of their relationship in a captivating and mind bending way. We hope you wouldn’t have to take such extreme measure but sometimes love can make you do things you’d have never believed you’d do before.
And just a clarification before we breakup, though we only mentioned your relationship with your computer, it doesn’t mean Jinni is prejudice about other relationships such as with your smart phone, your car or your Ipad. in fact we encourage it, have you downloaded out new app? It’s here to provide your every entertainment need, feel free to fall in love….
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Technorati Tags: Computers, her, sci-fi, romantic comedy, Start-Ups: Silicon Valley, My Hero, Spirited, Wilfred, Splash, Tom Hanks, Daryl Hanna, Lars and the Real Girl, Coffee Samurai, Ruby Sparks, Eternal Sunshine of the Spotless Mind, Tom Wilkinson, Jim Carrey, Kate Winslet
Popularity: 3% [?]
Today is Human Rights Day. With all due respect to the rights of equality, free speech, etc., let’s talk about the really important rights: our entertainment rights! Without further ado, here’s Jinni’s bill of entertainment rights (and if by any remote chance you’re using another entertainment service, check if you get these rights, and then switch to Jinni :).
We have the right to mobility!
We have the right to get personalized recommendations!
We have the right to explore by mood!
We have the right to know if a movie will suit us before even watching it!
We have the right to use a customized, personalized TV guide!
We have the right to tune our search and discovery!
We have the right to find something to watch together without fighting over it!
We have the right to explore only relevant providers!
One for the future – we have the right to talk to our app!
>> To comment on this blog post, or to share your own insight on entertainment, join us on Facebook:www.facebook.com/JinniDotCom
Popularity: 3% [?]
With the announcement of the 2013 Oscar winners right around the corner, we’ve decided to crack the genetic code of an Oscar winning movie. We’ve compiled the Oscar winning titles of the main categories throughout the 21st Century (best picture, actor, actress and director, from 2000 until today), analyzed and cross referenced their genes according to the Jinni Entertainment Genome, and compared them with the genes of this year’s nominees. The following infographic displays our findings:
Popularity: 3% [?]
After sixty years in hibernation, the TV guide is finally awakening to innovation. The static grid of shows and airing times that granny loved getting in the mail each week is crumbling under the strain of hundreds of linear channels, DVR, VOD and over-the-top internet streaming services and a new generation of consumers who expect a fast, personalized discovery experience. Providers can feel the winds of change brewing and are investing top talent to develop the next generation of guides. The following are 10 challenges and opportunities the industry must master if it wants to continue to keep customers happy.
1) The Couch Potato is Here to Stay
This is not an insult, simply a fact. When we sit down in front of the TV we want to watch something good and we expect it to be easy to find. After all, we’re not in the mood to work. Users want the act of finding something to watch to be as effortless and enjoyable as watching it is.
2) The Paradox of Choice Requires Personalization
Too much choice is overwhelming and is a barrier to consumption. The guide must give quality, personalized recommendations to help users overcome the fear of regret and so the guide becomes your best salesperson.
3) Content Selection is Meaning Driven
What do you want to know about a movie before you decide to watch it? Basic metadata isn’t much help. A rich, human description of the mood, style and plot elements gives us a real feeling for the movie and allows us to overcome the fear of regret and decide if we want to see it.
4) Future-proof the guide for an on-demand world
On-demand video is growing fast and now is the time to future-proof the guide. Service providers that don’t move quickly are at risk of choking future consumption with an antiquated guide.
5) Building Trust Between Man and Machine
Trust is what fuels recommendations to spur action. How can humans learn to trust machine-made recommendations? A discovery engine must be able to explain, in human terms, everything it does.
6) There is No Such Thing as ‘Average Taste’
Our tastes are as distinct and varied as we are. Sometimes I enjoy a witty humorous movie about couple relations, other times I’m in the mood for stylized, exciting movies about space travel and saving the world with androids and alien. You can’t average out things like ‘aliens’ and ‘couple relations’ to get a mathematical estimation of my taste. Yet this is exactly what most so-called ‘personalized discovery’ engines do; bunch everything a user likes together. If we are going to deliver a truly personalized experience that will help consumers find content they will enjoy, first we must recognize that each individual is unique and his or her tastes include several distinct types of content.
7) Keeping Content Fresh is a Challenge
Movies and TV are special, that’s why we love them so much. But that’s also why finding and choosing the right content is such a difficult process. We expect endless fresh programming, to fit our specific preferences and to match the exact mood we’re in at that moment. If the guide fails to lead users quickly to content that suits their taste and mood, they will blame the provider and come to the conclusion that there is ‘nothing good to watch’.
8) Humans seek meaning, not data
We have all been trained by web browsers to think in keywords, but human communication is more than a collection of key words wound into a Boolean string. Just try asking Google to recommend a ‘ feel good witty movie about couple relations’ – you won’t get useful results. The next generation of guides needs to speak in casual human language and deliver relevant and accurate results.
9) ‘Lingua Franca’ of Video Content
The only way guides will be able to communicate with users in a meaningful language is by adopting a normalized unified language or ‘Lingua Franca’ for describing entertainment content. This Lingua Franca will allow the breadth of entertainment content to be described in a single descriptive language irrespective of the producer, director or script writers. From the consumer perspective, all content can be understood in the same natural metaphor.
10) Separating the Social Wheat from the Chafe
Our entire industry seems caught up in the latest Social TV buzz. All the tweets, updates, ‘likes’ and ‘+’s have created massive amounts of TV and movie related social media data. But this kind of random chatter doesn’t drive consumption and it doesn’t enhance the television experience. Why? Because most of your friends don’t share your taste in TV and movies. If Social TV is going to truly enhance the discovery experience, we must be able to identify those few friends that have similar tastes and use them as a source of high quality social recommendations. THAT is social TV.
*An abbreviated version of this article first appeared in Multichannel Magazine
Technorati Tags: Next Generation TV Guide, Next Generation, TV Guide, Social TV, DVR, VOD, Linear channels, on demand, personalized discovery, personalized tv, couch potato, paradox of choice, content, video content, TV, movies, future proof, on-demand, recommendations, movie recommendations, Lingua Franca, Yosi Glick, Jinni, discovery engine
Popularity: 4% [?]
It’s open season on recommendation engines. In an article last month in Time focused on Pandora, Lev Grossman offered up this dire analysis of the impact of recommendation engines:
Just the other day, Shane Richmond responded in an article in The Telegraph titled “Relax. Recommendation engines won’t replace humans.” He (reasonably) predicts that engines will never be our only basis for choosing what to listen to, who to date, etc. In fact, new technology can also foster “human-driven connectivity” of the kind seen on Twitter: “a massive source of unexpected connections and serendipitous links.”
Is that the best we can say for recommendation engines – that at least they’ll never entirely dominate our decision-making process? Since even the smartest recommendation engine can’t speak in its own defense, we’d like to chip in with a word or two.
Our Lives Aren’t an Endless Series of Happy Accidents
Lev Grossman writes –
A recommendation engine isn’t the spouse who drags you to an art film you wouldn’t have been caught dead at but then unexpectedly love. It won’t force you to read the 18th century canon. It’s no substitute for stumbling onto a great CD just because it has cool cover art.
This is all true. But the vision of our lives as non-stop serendipity (if not for algorithms) seems a little overly optimistic. Let’s say you want to watch TV. If you’re like the average viewer, you have access to hundreds of channels, thousands of VOD titles, and you might be considering web and DVR content too. Faced with that much choice, you’re likely to end up flipping to a show you’ve watched before or selecting from a “most popular” list online. Recommendation engines can actually help you out of this rut, by suggesting shows you might not have even heard of, but catch your interest because they fit your tastes.
Recommendation Engines Don’t (Necessarily) Care What’s Popular
People usually gravitate to popularity, not diversity. That’s because we’re overwhelmed by too many options (the Paradox of Choice). Much, though certainly not all, “human-driven connectivity” is likely to expose you over and over to the same short tail of content. As the “Trending” list shows, the majority of movie and TV talk on Twitter is about blockbusters and new releases (seen today: Karate Kid).
Admittedly, recommendation engines that use collaborative filtering – the familiar “People who liked X also liked Y” – also tend to recommend already-popular content (because that’s what most people like). But recommendation engines like Pandora’s and Jinni’s, which focus on understanding content, can make recommendations based on attributes you enjoy, factoring in popularity to a limited extent or not at all.
Algorithms Come in All Shapes and Sizes
Not all recommendation engines create the same experience, as noted above. For example, Jinni acknowledges that people have varied tastes, depending on mood and context, by creating a multifaceted taste model for each user (we call it “Entertainment Personality”), so recommendations will always take users in several directions.
And recommendation engines don’t necessarily exclude human-driven recommendations; they can actually facilitate them. Jinni identifies “taste neighbors,” people whose tastes overlap with yours. Viewing content your neighbors have enjoyed takes you beyond the comfort zone of your circle of friends to get recommendations from a wider variety of people who share some of your interests.
Happily, we don’t expect people will ever live blindly by algorithms. But recommendations engines can play a part in making our lives a little more serendipitous.
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