Metaculus Help: Spread the word
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Will DeepMind Publish at least 450 articles by mid-2019?
This is a short-fuse question, which might be followed by a similar long timeline quesions depending on interest.
As of March 6 2019, DeepMind has published 390 articles in many subfields of machine learning, focussing on a wide range of both theoretical issues in deep learning, neural networks, reinforcement learning, pattern recognition, natural language procession, episodic curiosity approaches, memory and more. Other publications include research on various applied issues related to medical diagnostics, neuroscience, biochemistry and more. Most of these articles were published after 2012.
Will DeepMind's number of publications, as declared on their website, be >= 450 by July 1st, 2019?
Metaculus help: Predicting
Predictions are the heart of Metaculus. Predicting is how you contribute to the wisdom of the crowd, and how you earn points and build up your personal Metaculus track record.
The basics of predicting are very simple: move the slider to best match the likelihood of the outcome, and click predict. You can predict as often as you want, and you're encouraged to change your mind when new information becomes available.
The displayed score is split into current points and total points. Current points show how much your prediction is worth now, whereas total points show the combined worth of all of your predictions over the lifetime of the question. The scoring details are available on the FAQ.
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Metaculus help: Community Stats
Use the community stats to get a better sense of the community consensus (or lack thereof) for this question. Sometimes people have wildly different ideas about the likely outcomes, and sometimes people are in close agreement. There are even times when the community seems very certain of uncertainty, like when everyone agrees that event is only 50% likely to happen.
When you make a prediction, check the community stats to see where you land. If your prediction is an outlier, might there be something you're overlooking that others have seen? Or do you have special insight that others are lacking? Either way, it might be a good idea to join the discussion in the comments.