The New York Times
The Great A.I. Awakening
Summary · · Writing for The New York Times Magazine, Gideon Lewis-Kraus’s article breaks down a complex, multilayered story of artificial intelligence into an absorbing, detailed read. The story of Google Translate involves many prestigious players, who all worked together to create an impressively improved translation tool in far less time than originally expected. This is a tale of the meeting of many minds to create a single truly powerful artificial one that will have future uses beyond translating from one language to another. · Shared by 1053, including Aleyda Solis 🇺🇦, Diogo Mónica, Kenneth Kalmer, Andy Weissman, Pete Skomoroch, Gideonro, Thomas Power, #bottish, Data Science Renee, Rachel Miller | #InfluencerMarketing, Call Me ❝MICKEY❞, Jane, Mathew Ingram, Christoph Magnussen, Howard Getson, Claudia Sommer, Fabricio Teixeira, Chris Messina, Josep M. Ganyet, Stowe Boyd
Tim Urban
The Artificial Intelligence Revolution: Part 1
20+ min · · Part 1 of 2: "The Road to Superintelligence". Artificial Intelligence — the topic everyone in the world should be talking about. · Shared by 3337, including Marko Saric, Thomas Power, Paul Roetzer, Josep M. Ganyet, #bottish, Courtney Bolton ★, Fanzo, Aleksandra Wisniewska, Mark Birch AWS Startup Advocate, Christoph Magnussen, Lord Travis Wright, Herbert Bay, Casey Smith, Parin Vachhani, Gideonro, Chris Messina, Ian M Calvert, Ron McIntyre, Mark Kaigwa, Max Roser
r2d3.us
A visual introduction to machine learning
5 min · · What is machine learning? See how it works with our animated data visualization. · Shared by 3948, including hardmaru, wahalulu@fosstodon.org Marck Vaisman, Mara Averick, designshard, Parin Vachhani, Rand Fishkin, Stowe Boyd, Gideonro, Justin Wolfers, Mike Tamir, PhD, Elijah Meeks, Data Science Renee, Kenneth Kalmer, Aleyda Solis 🇺🇦, Helen Yu, hakan, Chris Messina, 🇺🇦Evan Kirstel #B2B #TechFluencer, Kevin_Indig, Daniel Boos
machinelearnings.co
The Non-Technical Guide to Machine Learning & Artificial Intelligence
20+ min · · Machine learning and artificial intelligence (ML and AI) have seized Tech mindshare in a way few topics have in recent memory. · Shared by 8217, including Gabriele, Tibor Martini 🇺🇦 @tibor@mastodon.social, Pete Skomoroch, Thomas Power, Brent Summers, Kris Fannin, Chris Messina, Lord Travis Wright, Klaus Eck, Frank, Werner Vogels, Kenneth Kalmer, Harpreet Singh, Herbert Bay, Lluís Codina, Fabricio Teixeira, Antonio Vieira Santos, DonDahlmann, Howard Getson, Mike Ivars
BBC News (World)
How artificial intelligence may be making you buy things
5 min · · Retailers are increasingly using AI to try to predict and encourage what customers purchase. · Shared by 229, including James Gingerich #B2B #Technology #Influencer, ipfconline in vacation mode :) will be back Sept.4, Ferit (at 🏠) 🌙, Terence Mills, Andres Saldarriaga, IronBrigade - Gaming/Vlogs, Nicolas Babin, Andreas Staub, Iain Brown, PhD, John Nosta, Harold Sinnott
MIT Technology Review
AI godfather Geoff Hinton: “Deep learning is going to be able to do everything”
4 min · · Nearly 30 years ago, Hinton’s belief in neural networks was contrarian. Now it’s hard to find anyone who disagrees, he says. · Shared by 630, including Eric Topol, James Gingerich #B2B #Technology #Influencer, Gerd Leonhard, 🇺🇦Evan Kirstel #B2B #TechFluencer, AI, Marc R Gagné MAPP, Bill Slawski ⚓ 🇺🇦, Carla Gentry 🎶, Gideonro, Nige Roberts-Willson, Martin Ford, John Hagel, Theodora (Theo) Lau - 劉䂀曼 🌻, Harold Sinnott, John Nosta, Bob E. Hayes, Nicolas Babin, Helen Yu, Dr. Ganapathi Pulipaka 🇺🇸, Vaughan Bell
TNW
How I’d study machine learning — if I’d be starting out today
8 min · · I’m underground, back where it all started. Sitting at the hidden cafe where I first met Mike. I’d been studying in my bedroom for the past 9-months and decided to step out of the cave. Half of me was… · Shared by 214, including Andres Saldarriaga, Matthias Lampe, Theodora (Theo) Lau - 劉䂀曼 🌻, Merkstatt@troet.cafe 📯
WIRED
AI Can Help Diagnose Some Illnesses—if Your Country Is Rich
3 min · · Algorithms for detecting eye diseases are mostly trained on patients in the US, Europe, and China. This can make the tools ineffective for other racial groups and countries. · Shared by 114, including Andres Saldarriaga, Andreas Staub, 🇺🇦Evan Kirstel #B2B #TechFluencer, Marcus Borba, Jose Luis Calvo, Glen Gilmore #MWC23, Theodora (Theo) Lau - 劉䂀曼 🌻, Harold Sinnott, Berci Meskó, MD, PhD, Backchannel, Yves Mulkers, LARRY ELKAN, Nicolas Babin, Terence Mills, Nige Roberts-Willson, rogerverhoeven, Brian Ahier, Chris Heilmann codepo8@toot.cafe, Helen Yu