The most likely reason Uber’s self driving car killed a pedestrian is because of settings designed to increase passenger comfort. While I’m sure Uber would agree that in this case they went too far, it reminds us that autonomous vehicles (and robots in general) live only to the moral code we provide them. An interesting side note in this article highlights Dara Khosrowshahi’s vision that Uber is at the centre of the network of autonomous vehicles – rather than designing specific end nodes, Uber expects to work with others to be the one ring to binding them all together.
https://rob.al/2FTnD6g
Uber has determined that the likely cause of a fatal collision involving one of its prototype self-driving cars in Arizona in March was a problem with the software that decides how the car should…
Over 10% of all randomised controlled trials in education ever, anywhere in the world, have been funded by the UK government. Following the evidence is hard, especially when it challenges the status quo, common practice, or established “knowledge”, so its good to see the UK government putting this money in to establishing a solid evidence base for effective educational practices.
https://rob.al/2HGdWdQ
A third of its schools have taken part in randomised controlled trials. The struggle is getting teachers to pay attention to the evidence
Why is weather unpredictable? The natural world is governed by thousands of factors, and their relationships are intrinsically chaotic, making them hard to model and so to predict – at least for humans. In most systems the number of variables is so massive that even identifying them is impossible – think about the flickering of the flames of a large bonfire, or how topography affects weather formations. Researchers at the University of Maryland have proven that they can train a machine learning model on the existing time-series data, and the model was able to predict future states approximately 8 times further to the future than a human.
https://rob.al/2KmIRwI
In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems.
Very interesting approach by Google’s researchers to the “cocktail party problem”. The team trained a CNN to determine which person is speaking in a video with multiple overlapping sounds, and to amplify that speech while reducing other noise. Applications include better automated subtitles, and improved hearing aids. https://research.googleblog.com/2018/04/looking-to-listen-audio-visual-speech.html
https://research.googleblog.com/2018/04/looking-to-listen-audio-visual-speech.html
Posted by Inbar Mosseri and Oran Lang, Software Engineers, Google Research People are remarkably good at focusing their attention on a par…
Stripe's advances in AI, based on hundreds of billions of data points, have been able to reduce fraud by 25% without materially affecting non-fraud acceptance rates.
https://rob.al/2FsfhCj
I’m loath to use the term, but Stripe is a revolutionary product. It allows pretty much anyone to accept card payments just by adding a few lines of code to their site, without having to deal with…
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://rob.al/2JJoYQa
More and more companies are seeing the benefits of remote work for productivity in the workplace. As Director of Design at Zapier, I frequently get asked the question of how the design process works…
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?
https://rob.al/2KoD1es
Musings on systems, information, learning, and optimization.
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 devices, as the big boys (e.g. Facebook) do.
https://rob.al/2HEhvk7
Intel has been making some interesting moves in the community space recently, including free licenses for its compiler suite for educators and open source contributors can now be had, as can rotating…
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://rob.al/2v5sAZz
Sitting tall gives him the confidence boost he needs.
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://rob.al/2IEbJPA
Tech companies claimed the top five spots again this year.