Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.
- Google launches an end-to-end AI platform
At the core of all of these new tools and services is the company’s plan to democratize AI and machine learning with pre-built models and easier to use services. - Google to pull plug on AI ethics council (and another article)
We thought this paired well with the article above… “Alphabet Inc’s Google said on Thursday it was dissolving a council it had formed a week earlier to consider ethical issues around artificial intelligence and other emerging technologies. The council had run into controversy over two of its members, according to online news portal Vox, which first reported the dissolution of the council.” - YouTube Executives Ignored Warnings, Letting Toxic Videos Run Rampant
Proposals to change recommendations and curb conspiracies were sacrificed for engagement, staff say. - Introducing Activation Atlases
Modern neural networks are often criticized as being a “black box.” Despite their success at a variety of problems, we have a limited understanding of how they make decisions internally. - Open Questions about Generative Adversarial Networks
What we’d like to find out about GANs that we don’t know yet. - How AI will enable Predictive Design in creatives
Predictive Design in Creatives will soon become available and will eventually become a part of every designer’s and marketers toolkit in the upcoming years. - How IBM Watson Overpromised and Underdelivered on AI Health Care
After its triumph on Jeopardy!, IBM’s AI seemed poised to revolutionize medicine. Doctors are still waiting - AI pioneer: ‘The dangers of abuse are very real’
Yoshua Bengio, winner of the prestigious Turing award for his work on deep learning, is establishing international guidelines for the ethical use of AI. - Researchers successfully trick @Tesla autopilot into driving into opposing traffic
… via “small stickers as interference patches on the ground” - Our Misplaced Fear of Job-Stealing Robots
At a Future of Work forum, experts say demographic shifts, not artificial intelligence, create the biggest challenges for today’s workplace. - The Wrong Kind of AI? Artificial Intelligence and the Future of Labor Demand (pdf)
- Machine Learning In The Judicial System Is Mostly Just Hype
ML algorithms in the judicial system are increasingly used to predict pre-trial flight risk and appropriate bail rates, as well as assessing a person’s recidivism risk when handing down a prison sentence. But as things stand, ML predictions of the risk of re-offending perform abysmally. - How India’s data labellers are powering the global AI race
“It’s in this village that Mujeeb Kolasseri, a high-school dropout, commands a team of over 200 employees working on artificial intelligence solutions for clients across America, Europe, Australia and Asia. At 28, Kolasseri is the oldest member of Infolks, a company he founded three years ago.” - The grim reality of life under Gangs Matrix, London’s controversial predictive policing tool
AI and machine learning software was meant to make policing fairer and more accountable – but it hasn’t worked out that way - The Intuition behind Adversarial Attacks on Neural Networks
Are the machine learning models we use intrinsically flawed? - Teaching machines to reason about what they see
Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency. - ‘Worse than doing time’: life on the wrong side of China’s social credit system
“As one of 13 million officially designated “discredited individuals,” or laolai in Chinese, 47-year-old Kong is banned from spending on “luxuries,” whose definition includes air travel and fast trains.” - Mistakes, we’ve drawn a few: Learning from our errors in data visualisation
Great post by The Economist in which they go over some of their previous visualizations and explain how they could be improved. - Kicking neural network design automation into high gear
Algorithm designs optimized machine-learning models up to 200 times faster than traditional methods. - K-means clustering: unsupervised learning for recommender systems
On Magic: The Gathering decks. - Artificial intelligence group DeepMind readies first commercial product
DeepMind, the British synthetic intelligence group, has constructed a working prototype of a tool that may diagnose advanced eye ailments in actual time, in a serious step in the direction of the Alphabet-owned firm’s first medical gadget. - MIT is using AI to invent new flavor combinations and foods – and it suggested a shrimp, jelly, and sausage pizza
If you’re tired of four-cheese pizzas or barbecue sauce has become a little samey, have you ever considered trying out a sweet potato, bean, and brie pizza? - Alexa AI scientists reduce speech recognition errors up to 22% with semi-supervised learning
Amazon’s Alexa Speech group scientists today announced they have used what they believe to be one of the largest unlabeled data sets ever assembled to train an acoustic model and improve the intelligent assistant’s ability to understand the human voice. - Personalized Recommendations for Experiences Using Deep Learning
TripAdvisor explains how their newly-developed ‘Recommended For You’ (RFY) model generates personalized recommendations on their website using users’ browsing history and deep learning. - A Visual Exploration of Gaussian Processes
How to turn a collection of small building blocks into a versatile tool for solving regression problems. - The Illustrated Word2vec
“In this post, we’ll go over the concept of embedding, and the mechanics of generating embeddings with word2vec. But let’s start with an example to get familiar with using vectors to represent things. Did you know that a list of five numbers (a vector) can represent so much about your personality?” - A visualization of different optimization techniques in the browser
From SGD to ADAM - rosshow: Visualize ROS topics in a terminal
Have you ever SSH’ed into a robot to debug whether sensors are outputting what they should? - Red pepper chef— from new training data to deployed system in a few lines of code
