-
Remote Design: How Zapier Is Building a Distributed Design Culture
A fascinating set of guidelines for making complex work which we typically say "has" to be done face to face (like designing) effective when the team works remotely. I particularly like the emphasis on using a spectrum of tools to support "stepping up" the "bandwidth" of a conversation from asynchronous text (e.g. email, slack) to…
-
The Ethics of Reward Shaping
Choosing an effective loss function is a critical part of training ML models. This thought provoking article reminds us to be critical in the choice of this function, especially as in many models the reward function itself is unclear – does a recommendation system (e.g. promoting new articles, or songs) simply create an echo chamber,…
-
Is Open Source The AI Nirvana for Intel?
While at first Intel appears to be catching up in the race to develop chips optimised for AI, looking deeper reveals a broader, longer term strategy to develop open code allowing any competing or complimentary framework (Tendorflow, Caffe, MXNet, etc.) to run at optimum efficiency on their hardware. Back to those chips (and the dodgy…
-
The Science Behind Mark Zuckerberg’s Booster Seat
A practical example of the importance of appearance: “appearing tall … is linked to increased social status across cultures, which researchers hypothesize has an evolutionary origin: If you were a taller caveman, you were probably better at taking down megafauna.” https://www.inverse.com/article/43535-mark-zuckerberg-booster-seat-explanation Sitting tall gives him the confidence boost he needs.
-
Amazon spent nearly $23 billion on R&D last year — more than any other U.S. company
Pouring resources in to Alexa, AWS and experiments like Amazon Go, Amazon invested nearly $23bn on R&D last year, nearly 1/3 of the total spend of the top 5 (next come Alphabet, Intel, Microsoft, and Apple). https://www.recode.net/2018/4/9/17204004/amazon-research-development-rd Tech companies claimed the top five spots again this year.
-
IBM outlines the 5 attributes of useful AI
IBM's 5 properties of effective AI? 1 Managed (durable infrastructure, effective data pipelines, data and model governance) 2 Resilient (automatic alerts when model drift is excessive) 3 Performant (runs in reasonable time on cost effective infrastructure) 4 Measurable (model accuracy, data volume, value released) 5 Continuous (evaluate and retrain models as needed) https://venturebeat.com/2018/04/21/ibm-outlines-the-5-attributes-of-useful-ai/ A few…
-
The economics of artificial intelligence
As the cost of AI drops, things which aren't currently thought to be solvable through prediction will suddenly be viable – and this will primarily be complimented with human judgement. Computers predict better than people can, but then these predictions will be "handed off" to a human to use judgement to determine the response (such…
-
Surviving The Retail Apocalypse: The Technologies And Trends That Can Help Brick-And-Mortar Thrive Again
The demise of the retail store may have been (greatly) exaggerated. Yes, many big box stores are disappearing, being unable to compete on cost or selection with online vendors, many companies are turning to technology to survive the change by inviting themselves directly in to customers' homes, or optimising their supply chain and product ranges…
-
Popular Apps Are Leaving the Apple Watch. Is That a Bad Sign?
“That some big-name apps have removed their Apple Watch apps isn’t a sign that the Apple Watch is failing as a platform: It’s a sign that the platform is evolving [as developers learn what the new form factor is truly useful for]” https://slate.com/technology/2018/04/apple-watch-popular-apps-are-leaving-the-platform-is-that-a-bad-sign.html It joined Twitter, Amazon, Google Maps, and Slack, among others.
