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5bn people have a mobile phone now, and 4bn have a smartphone. Time to stop making charts.

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Notes on AI Bias

Machine learning is the new centre of tech, and like all big new things there are issues. ‘AI bias’ is much-discussed right now: machine learning finds patterns but sometimes it finds the wrong one, and it can be hard to tell. This is a real concern, but it’s also manageable as long as we pay proper attention to it, and will probably look much like similar issues in previous waves of automation.

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YAWEDA Kitchen Tap Copper Washbasin Kitchen Sink Tap Cold and Hot Water Mixer Into The Wall Type Single-Handled Lead-Free Double-Lift Type

Chrome-Plated Adjustable Temperature-Sensitive Led Faucet304 Stainless Steel Basin Single Cold

Internet platforms are mechanical Turks - they can only understand things by finding a way to leverage vast numbers of humans. They’re distributed computers where all of us are the CPUs. How does that affect how we think about abuse, and how might machine learning change this? 

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Apple Plus - brand versus subscription

Apple’s talk about services got specific with a bunch of news subscription services. Most of them are sensible and worthy iteration, but the company still hasn’t explained exactly what it plans with its push into commissioning billions of dollars of premium TV (Spielberg! Oprah!). Maybe all of this is about trust: the old Apple promise was that you don't have to worry if the tech works, and the new promise is you don't have to worry if the tech is scamming you. 

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Smart home, machine learning and discovery

Smart home today looks a lot like the world of kitchen gadgets a few generations ago - and so does machine learning. We have a bunch of cheap commodity components (DC motors! Cameras! Wifi chips! Voice recognition!) and we’re trying to work out how to bolt them together into things that makes sense. There are lots of experiments - some things will be the toasters or benders of the future, and some will be the electric can-opener.

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