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.
236d ago | ieee.org
234d ago | pluralistic.net
238d ago | livescience.com
234d ago | theverge.com
233d ago | theverge.com
238d ago | niemanlab.org
274d ago | platformer.news
236d ago | arstechnica.com
233d ago | flgov.com
236d ago | nature.com
259d ago | arstechnica.com
247d ago | arstechnica.com
236d ago | sciencebusiness.net
233d ago | experimental-history.com
236d ago | platformer.news
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236d ago | techcrunch.com
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237d ago | stratechery.com
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235d ago | thecooldown.com
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237d ago | sciencebusiness.net
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237d ago | arstechnica.com
238d ago | nature.com
252d ago | newatlas.com
233d ago | cnn.com
264d ago | platformer.news
233d ago | substack.com
253d ago | newatlas.com
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236d ago | techcrunch.com
236d ago | techcrunch.com
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235d ago | theverge.com
238d ago | arstechnica.com
236d ago | arstechnica.com
237d ago | nature.com
235d ago | techcrunch.com
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235d ago | spyglass.org
235d ago | mit.edu
271d ago | platformer.news
236d ago | citp.princeton.edu
235d ago | techcrunch.com
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237d ago | design-milk.com
237d ago | amazon.com