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.
18d ago | birchtree.me
19d ago | theverge.com
18d ago | techcrunch.com
18d ago | flgov.com
18d ago | higashi.blog
18d ago | experimental-history.com
17d ago | mashable.com
21d ago | techcrunch.com
20d ago | thecooldown.com
21d ago | techcrunch.com
18d ago | dolthub.com
18d ago | techcrunch.com
18d ago | dolthub.com
18d ago | techcrunch.com
19d ago | substack.com
19d ago | cnn.com
21d ago | techcrunch.com
21d ago | techcrunch.com
18d ago | techcrunch.com
20d ago | techcrunch.com
18d ago | windowscentral.com
18d ago | techcrunch.com
22d ago | citp.princeton.edu
20d ago | techcrunch.com
21d ago | techcrunch.com
21d ago | techcrunch.com
18d ago | amazon.com
18d ago | techcrunch.com
21d ago | techcrunch.com