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.
298d ago | newslttrs.com
302d ago | arstechnica.com
322d ago | platformer.news
298d ago | theconversation.com
297d ago | manton.org
298d ago | gizmodo.com
306d ago | gizmodo.com
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310d ago | overcomingbias.com
327d ago | newatlas.com
299d ago | arstechnica.com
297d ago | wired.com
305d ago | newscientist.com
299d ago | techcrunch.com
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298d ago | openculture.com
306d ago | ieee.org
301d ago | wheresyoured.at
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305d ago | greenspun.com
304d ago | citizenlab.ca
321d ago | arstechnica.com
299d ago | techcrunch.com
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303d ago | livescience.com
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298d ago | birchtree.me
312d ago | platformer.news
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297d ago | theverge.com
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300d ago | patatas.ca
299d ago | eff.org
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300d ago | scripting.com
297d ago | theverge.com
304d ago | arstechnica.com
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300d ago | nature.com
300d ago | ben-evans.com
297d ago | techcrunch.com
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302d ago | 512pixels.net
297d ago | ieee.org
300d ago | allthingsopen.org
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298d ago | sciencebusiness.net
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300d ago | techcrunch.com
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298d ago | github.com
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298d ago | ycombinator.com
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298d ago | ycombinator.com