News stories from Filtered in 2017
Filtered | 26 Oct 2017
US Patent & Trademark Office confirms it has accepted the patent application for Filtered's learning-content filtering algorithm.
Filtered | 01 Sep 2017
Filtered will be unveiling their new product globalfilter for L&D at this year’s Learning Live conference taking place in London on 6-7 September.
Filtered | 03 Jul 2017
CSO of Filtered attends eLN’s Empowering your Digital Learning event this week to discuss how machine learning, algorithms and human curation work together to create useful learning recommendations
Intelligent learning, personalization, and algorithms: Filtered leads workshop for London EdTech Week
Filtered | 16 Jun 2017
Marc Zao-Sanders, CEO of Filtered, will discuss with attendees what makes a Spotify-, Netflix-, Amazon-like personalized user experience at EdTechXEurope
Filtered's CSO discusses the importance of intelligent, personalized learning recommendations at LTSF17
Filtered | 06 Jun 2017
Dr Chris Littlewood, CSO at Filtered, will share with LTSF17 attendees the company's mission to optimise recommendations, boost productivity, and the Innovate UK funded project that will deliver it.
Filtered | 24 May 2017
One of LinkedIn’s first hires outside the US, Richard Ward, is now a new addition to the Filtered team, overseeing all sales and marketing activity.
Filtered | 18 May 2017
Filtered is supporting workers in their personal development endeavours by opening up their learning recommendation engine - as well as their exclusive live classes - to the public for the next two weeks.
Filtered | 19 Apr 2017
The UK's innovation agency, Innovate UK, is co-funding Filtered's algorithm development work to help personalise training, optimise skills and impact productivity of today's knowledge workers.
Filtered | 11 Jan 2017
Award-winning adaptive training provider, Filtered.com, has released globalfilter - a new learning recommendation engine set to become the long awaited missing piece of the Learning Panorama in 2017.
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Filtered is an award-winning online training platform which personalizes learning material for each user. By asking users questions about their role, aspiration and proficiency, the platform’s machine learning algorithm is able to pinpoint skills gaps and filter out material that the user doesn’t need or already knows. This minimises time spent training, maximises the impact of learning and increases productivity. This approach of pinpointing skills gaps across a portfolio of core skills means that 97% of material covered in a Filtered course is relevant to the learner.