We will never really understand learning or intelligence until we can build machines that learn many different things, over years, and become better learners over time. This talk describes our research to build a Never-Ending Language Learner (NELL) that runs 24 hours per day, forever, learning to read the web. Each day NELL extracts (reads) more facts from the web, and integrates these into its growing knowledge base of beliefs. Each day NELL also learns to read better than yesterday, enabling it to go back to the text it read yesterday, and extract more facts, more accurately. NELL has been running 24 hours/day for over two years now. The result so far is a collection of 15 million interconnected beliefs (e.g., servedWtih(coffee, applePie), isA(applePie, bakedGood)), that NELL is considering at different levels of confidence, along with hundreds of thousands of learned phrasings, morphoogical features, and web page structures that NELL uses to extract beliefs from the web. Track NELL's progress at http://rtw.ml.cmu.edu.