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.
1029d ago | blog.google
1022d ago | newscientist.com
1021d ago | readwrite.com
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1024d ago | diginomica.com
1023d ago | scientificamerican.com
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1024d ago | 3quarksdaily.com
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1036d ago | arstechnica.com
1099d ago | overcomingbias.com
1024d ago | diginomica.com
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1023d ago | mattermost.com
1020d ago | innovationnation.blog
1052d ago | platformer.news
1026d ago | disassociated.com
1085d ago | overcomingbias.com
1020d ago | 3quarksdaily.com
1021d ago | venturebeat.com
1021d ago | scientificamerican.com
1024d ago | techcrunch.com
1021d ago | honest-broker.com
1025d ago | newscientist.com
1021d ago | phys.org
1029d ago | platformer.news
1022d ago | scientificamerican.com
1023d ago | techcrunch.com
1022d ago | understandingai.org
1021d ago | arstechnica.com
1029d ago | diginomica.com
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1021d ago | readwrite.com
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1021d ago | fast.ai
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1025d ago | phys.org
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1021d ago | disassociated.com
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1080d ago | platformer.news
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1021d ago | phys.org
1023d ago | techcrunch.com