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Patiently pending

Posted on Sep 07, 2017 by Chris Littlewood

We recently got the good news that the US Patent Office will accept our application for a patent protecting our Filtering algorithm. As it was the first patent we’d applied for, both as a company and as individuals, it’s been interesting and a learning experience. I wanted to share some of that with you in case you are on a similar path.

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Topics: Technology, Personalization, Business, Algorithms

globalfilter™ for L&D professionals

Posted on Aug 29, 2017 by Marc Zao-Sanders

Next month, we’ll be releasing a technology hosting a small library of resources exclusively for L&D (and HR) professionals. It’s an online recommender system of high-quality learning to read, watch, practice and apply for our industry: globalfilter for L&D professionals. We’ve spent the past two years developing a patent-approved technology to get the right learning to the right learner. This is the version for our industry. It consists of conversational UI (chatbot) + 125 human-curated learning assets + recommendation system to prioritise and personalize it all.

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Topics: Technology, Personalization, Business, Algorithms, Chat Bot, globalfilter

Language processing, AI, and L&D

Posted on Aug 15, 2017 by Chris Littlewood

Redundancy in language I don't know if you tried to read the image at the top of this article - if not, give it a go now. 

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Topics: Technology, Personalization, Business, Chat Bot, Algorithms

LinkedIn is 92% boring

Posted on Jul 13, 2017 by Marc Zao-Sanders

LinkedIn’s feed is boring and could be improved by toning down promos and likes, and introducing an easy model (User-System-Content) for evaluating recommender systems in general. Like 40% of LinkedIn users, I’m on it every day. LinkedIn has a monopoly on public CVs which are useful for lots of reasons. And many of the articles are interesting. But the rest – epitomised by the activity feed – is dull. No wonder LinkedIn is one of the least sticky social media sites.

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Topics: Technology, Personalization, Business, linkedin

Anatomy of a good recommendation

Posted on May 22, 2017 by Chris Littlewood

We’re working on how to personalise training to optimise productivity. In one strand of that project we are trying to understand the characteristics that make a recommendation useful. The recommendation might be for a book, a course, a video, an article, an experience, a mentor, a conversation, a tool, a tip… anything that’s made a difference to the way we work and the results we see.

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Topics: Productivity, Business, Technology, Personalization