Just what i find

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 synchronous, real-time, visual methods (e.g. video chat). Others, such as drop in sessions for constructive feedback on work items, look equally useful, and i look forward to testing some of these out with the team. https://zapier.com/blog/remote-design-culture/ More and more companies are seeing the benefits of… Continue reading →

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, or does it broadly converge on the mean? Which of these should score higher? If we penalise the system when users don't click on articles which violate their confirmation bias – are we acting ethically? http://www.argmin.net/2018/04/16/ethical-rewards/ Musings on systems, information, learning, and optimization. Continue reading →

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 performance charts) – the authors of this article point out that you get better single chip performance from hardware 3 generations old compared to the newest silicone – although the real measure isn't single chip, but how to scale out complex models across "farms" of… Continue reading →

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. Continue reading →

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. Continue reading →

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 weeks ago, a dejected CTO told me it took his team three weeks to build a machine learning model. I told him a model in just three weeks sounded great, and he agreed. So why the long face? Be… Continue reading →

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 as whether or how to act, or to ignore). Ultimately, the authors recommend that companies develop a "thesis" outlining what you plan to "predict" (e.g. what is "best"), the time until AI becomes so embedded that investments without it are not viable, recognising that progress… Continue reading →

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 using AI and small, local, relevant locations. Others are making the retail store the place you go to try out a physical product which you then buy online, creating "showroom destinations" for customers. One thing's clear – this battle is not yet lost. https://www.cbinsights.com/research/retail-apocalypse-survival-technology-trends/ We… Continue reading →

“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. Continue reading →

An innovative saving product: “With myAgro’s Mobile Layaway platform, farmers save for seeds, fertiliser and specialised training via scratchcards – in the same way they might buy phone credit” https://www.theguardian.com/social-entrepreneurs-solving-problems-around-the-world/2018/apr/04/developing-mobile-technology-manage-funds-farmers-poverty-myagro-anushka-ratnayake-skoll-social-entrepreneurship-awards Skoll Awards for Social Entrepreneurship winner: Anushka Ratnayake, myAgro Continue reading →