Articles: Hacker Noon Pieces on AI
Can’t post just one, too many great reads here
I find that Hacker Noon and Back Channel articles seem to pop up in recommended articles on the bottom of my posts, so naturally I’ve browsed both. I’ll start with Hacker Noon…
In the past year, I’ve become convinced that machine learning is not hype. Strong AI/AGI is no longer a requirement for…hackernoon.com
Harper Maddox’s (harpermaddox) short piece caught my attention, as it spoke to my ‘starting from scratch’ mentality. In the article, he breaks down the Stanford Machine Learning Class on Coursera frequently reco’d by experts, references a few podcasts (like TWiML which I’ve posted here as well) and the Technically Sentient newsletter. I haven’t received a newsletter yet, but the archives are a jackpot of useful links.
🚀 This is issue #103 of THE EXPONENTIAL VIEW. Sign-up for the newsletter here.hackernoon.com
This is actually an issue of Azeem Azhar’s (azeem) The Exponential View newsletter; seems Hacker Noon now posts these regularly. While these aren’t entirely on the topic of AI, Azeem does have a section dedicated to it in each issue called the ‘Dept of artificial intelligence’. He packs this section with a bit of commentary and several links to interesting content and call-outs for particularly worthwhile reads/listens. Warning: these are filled with emojis, so if that’s not your thing, it may be a little much for you.
(Editor’s note: this is a guest post from Ha Duong, a former associate at Techstars, product marketing professional…hackernoon.com
Quite simply a Google Sheet of 606 European AI startups with description, website link, funding raised, city of origin, date started and category. The link to the Hacker Noon piece itself is above, but you probably just want to browse the Google Sheet, so linking directly here.
The compiler of the list, Ha Duong, also recommends these three AI firms lists:
GANs or Generative Adversarial Networks are a kind of neural networks that is composed of 2 separate deep neural…hackernoon.com
I recently mentioned GANs in a previous post, having heard Ian Goodfellow speak about their prevalence and current applications. This post by Chanchana Sornsoontorn, is a plain English explanation with plenty of examples. He’s got a massive list of resources stashed here on GitHub as well.
For all of Hackernoon’s AI-tagged articles, see here.