What is the future of AI? Some say it is bright and shiny, others see a dark dystopia. But who is really right or wrong and how can we tell the difference? There is so much noise in the media that the reader easily gets lost. I get lost too, because I apply emotion and personal bias.
To help myself, I decided to let a machine do it for me (how ironic). I trained one of our text classifiers to distinguish betwen three categories (concerned, curious, and excited) and let it get fed with the latest content on AI that appears online. The result is the constantly updated list you will see below. The model is not perfect, but is slowly getting better, as I train it with more and more data.
For feedback and suggestions, feel free to get in touch on Mastodon and Twitter.
290d ago | ieee.org
287d ago | pluralistic.net
291d ago | livescience.com
288d ago | theverge.com
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292d ago | niemanlab.org
328d ago | platformer.news
290d ago | arstechnica.com
287d ago | flgov.com
290d ago | nature.com
313d ago | arstechnica.com
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287d ago | experimental-history.com
290d ago | platformer.news
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290d ago | techcrunch.com
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290d ago | stratechery.com
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290d ago | sciencebusiness.net
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292d ago | nature.com
306d ago | newatlas.com
287d ago | cnn.com
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287d ago | substack.com
306d ago | newatlas.com
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292d ago | arstechnica.com
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291d ago | nature.com
289d ago | techcrunch.com
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289d ago | spyglass.org
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325d ago | platformer.news
290d ago | citp.princeton.edu
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291d ago | design-milk.com
291d ago | amazon.com