AI MUST READS — W30 2018, by City AI
Artificial Intelligence, Machine Learning and related fields are in a constant state of change. We want to inform but also encourage discussions on well presented topics we think are necessary in the context of putting AI into production. Every week we’re picking applied AI’s best articles plus adding a discussion starter
1. Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
Author — Stefan Kojouharov (Follow on Twitter) via Becoming Human AI
Its a post from last year but it doesn’t make this post any less of a valuable resource. This is one of those articles that you’ll find yourself constantly going back too and stapling to the wall of your desk, the utility of this collection is limited only by your ability to make use of it.
2. China’s AI focus will leave US in the dust, says top university professor
Author — Wataru Suzuki via Nikkei Asia Review
Whilst I find the new band-wagon which has seemingly sprung up within the A.I community in the last couple of months to be wholly unproductive, that being the hype that China is going to beat everyone else, I also think its indicitive of a much bigger problem than that of one country being the leading nation for the development and utilisation of this technology. Instead it shows the current worrying trend of the develoment of A.I being seen as a race similar to that of an arms race.
With a technology this important and with such potential it should instead be seen as a collaboration. If we continue to try and out do one another, focusing on what we can develop and how we can use it, then eventually we will forgo the safety and colloborative potential that we should instead be working towards.
3. DARPA pushes for AI that can explain its decisions
Author — Jon Fingas (Follow on Twitter) via Engadget
One of the first big issues that people considered with Artificial Intelligence was its “Black Box” nature, whether it was because companies wanted to protect the secrets contained within their proprietary technologies or because we didnt even know exactly why A.I was providing the answers it gave (source). When there are Artificial Intelligence systems in places that are making crucial decisions that are effecting peoples lives, then being able to explain why these decisions were made is crucial.
An institution the size of DARPA making its intentions to develop an A.I system that can explain its decision is encouraging and will also hopefully lead the way so that industries that make use of these systems can follow.
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