Creating Tomorrow is the first and the only recommender as service in Iran. I developed it three years ago.

It was around two years that was working and surprisingly, I was looking for a website which accepts using it! I had to explain, what a recommender system is and how it works. During the past three years, I’ve met many business owners.  Unfortunately they almost weren’t motivated to accept the risk of migrating a new technology. They just wanted their business working up. There wasn’t any reason to accept new challenges. The comfort zone looks awesome! At those time, GoodCo, a small innovative startup, just became interested in our solution. Parisa one of GoodCo co-founders just got it, when I mentioned it, in one of my BigData workshops at SBU. We made an easy deal soon.

Right 8 months ago something interesting happened.  At the time I was trying to convince some, It was Aparat, the biggest dotcom in Iran, who came with a great knowledge and solid experience in this area!

Nima just emailed me. He mentioned that the CEO of Aparat is interested to give our solution a try.

M.J. Shakouri Moghadam, the CEO/CTO of Sabavision, is an intellectual leader with a great resume in creating big startups from scratch. He is a target oriented entrepreneur, who believes in tech. His company, Sabavision, leads the content sharing, providing and streaming market in Iran.

During the first meeting, I noticed, they already have their own matured, well working recommender system! Nevertheless M.J. accepted the risk of replacing something working, with something new! They are pretty passionate. His company, started using in one of their awesome projects, Filimo.

Our first tries on Aparat were doomed to fail. While was working pretty good at Filimo scale, it wasn’t able to serve Aparat. Aparat provides ten million contents to tens of million users. It is growing dramatically as well.

After it, I’ve spent a sensible time to improve and make it an Aparat scale, reliable solution. I started it by developing an Aparat simulator project. It simulates the behavior of thousands online user. Now I can shape different situations at development time. Hasan, an Aparat highprofile technical guy, helped me a lot. He shared his rare experience handsomely. Frankly they are the most knowledgeable WWW team that I’ve ever seen. They are master in agility either. now works much faster than ever. It also provides more processing power, on cheaper machines. I’ve tried all tricks in the book, such as; different kinds of hashing, sketching, matrix factorization, Kohonen network, approximation and multithreading to make it a superfast realtime solution. Through a graph, containing tens of million user/item, It just takes a few micro seconds (10 −6) to predict, who looks for what. We know this is just a start. So we are working on designing and developing some extensions to our solution.

Some guys have collaborated in development. Saeid just developed a WordPress plugin. He also developed the project websiteArghavan has helped us in using matrix factorization technique. Some other talented guys just started helping us as well.

There are hackers who create awesome solutions, beyond the majority demands. And there are rare star companies, who stand ahead, by accepting the risk of creating tomorrow.

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One Response to Creating Tomorrow

  1. Recommender systems are a useful alternative to search algorithms since they help users discover items they might not have found by themselves. Interestingly enough, recommender systems are often implemented using search engines indexing non-traditional data.

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