Guardian Platinum Series Indoor Wiper Floor Mat, Rubber with Nylon Carpet, 4'x16', Grey

Flannel Cushion Makeup Seat Change shoes Bench Modern Dining Room Chairs Seat Nordic Metal Dressing Stool HENGXIAO (color Pink)

orange B-48x48x80cm CAIJUN Chair Solid Wood Elastic Sponge Multipurpose Assembly Non-Slip Breathable Comfortable, 2 Styles, 200kg Load-Bearing (color orange, Size B-48x48x80cm)

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

Standing Flower Stand Wooden Flower Rack Indoor Plant Stand Wooden Plant Flower Display Stand Wood Pot Shelf Storage Rack Outdoor Decorative Frame (Size 80cm)

Modern Adjustable Swivel Pub Style Bar Stools Barstools Black 2 Counter rnlkyb5044-Furniture

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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Geometric Semicircle Doormat Vintage Sixties Circles with Squares Disc Vibrant Symmetric Motif Halfmoon doormats H 35.4 xD 53.1 Cream Red Maroon Marigold

JIAYING Coat Racks Coat Rack, Wall-Mounted Hook Coat Rack 38 Slidable Hook Bedroom Porch Wall Hanger 2 color Optional Single Hook Can Bear Weight 3kg Multifunction (color White, Size 61.1cm)

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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Mats Kitchen Doormat The Door Bathroom Bedroom Toilet Toilet Door Bedside Water Absorption Anti-Skid Foot Pad (color Green)

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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