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.
991d ago | substack.com
1001d ago | verfassungsblog.de
996d ago | phys.org
990d ago | techcrunch.com
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1002d ago | niemanlab.org
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995d ago | arstechnica.com
1002d ago | phys.org
990d ago | ted.com
990d ago | techcrunch.com
1002d ago | phys.org
993d ago | readwrite.com
995d ago | techcrunch.com
1002d ago | phys.org
1000d ago | jondron.ca
995d ago | substack.com
993d ago | scientificamerican.com
991d ago | ben-evans.com
1029d ago | platformer.news
991d ago | simonwillison.net
994d ago | scientificamerican.com
998d ago | stat.columbia.edu
993d ago | arstechnica.com
994d ago | techcrunch.com
990d ago | theverge.com
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997d ago | pxlnv.com
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997d ago | serokell.io
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999d ago | globalnerdy.com
990d ago | theverge.com
994d ago | techcrunch.com
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997d ago | macstories.net
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990d ago | ted.com
990d ago | techcrunch.com
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993d ago | hbr.org
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990d ago | stratechery.com
994d ago | techcrunch.com
990d ago | theverge.com
1001d ago | readwrite.com
1002d ago | stat.columbia.edu
1008d ago | newatlas.com
993d ago | scientificamerican.com