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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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U-Enjoy Stainless Steel Faucet Top Quality Chrome Shampoo Bed Shower Faucets Mixer Taps Salon Punch Bed Mixing Valve Wash Hair (pink)

Honcx Copper Hot and Cold Kitchen Sink Taps Kitchen Faucet Bathroom Led Faucet Copper Waterfall Single Hole Hot and Cold Basin Mixer

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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Lpophy Bathroom Sink Mixer Taps Faucet Bath Waterfall Cold and Hot Water Tap for Washroom Bathroom and Kitchen redating All-Copper Ancient Antique gold-Plated Hot and Cold redation
Quality assurance is durable
Not only household items, but more like a piece of art
Let you drink water and use water more healthily
J.K. Adams Ash Wood American Collection Cutting Board, 20-inches by 15-inches

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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