AI and Moore's law, Customer service and negotiating bots, event forecasting at Uber, MobileNets, Human-level AI and more
ARTIFICIAL INTELLIGENCE NEWS #63 June 15th 2017
In the News
New ideas in chip design look likely to keep software getting smarter.
A virtual assistant that can tell you’re frustrated can slow down and help you out.
Also in the news...
- Apple has officially confirmed they work on self-driving technology. More
- Intel predicts $7 trillion self-driving future. More
- Element AI raises $102M for its AI platform. More
Interesting work by Facebook AI Research. They have built a framework to train AI bots on human negotiations. The bots seem to be learning human-like negotiation strategies on their own.
What can NLP learn from the popularity of Convolutional Neural Networks commonly used in Computer Vision? Great run down of convolutional methods applied to NLP.
Companies that rush into sophisticated artificial intelligence before reaching a critical mass of automated processes and structured analytics can end up paralyzed..
Neural spatial models and finite-state transducers power Google's "intelligent keyboard"..
The new Developer Economics survey is a sci-fi adventure, so it is actually fun, plus you will learn about new tools! Talk about your dev habits related to your work and hobbies, whether it’s for your machine learning projects, desktop app development or any other. Start here!
*to be eligible for the prize, you need to complete the survey and submit your email
Software tools & code
For Keras, Numpy, Pandas, Scipy, Scikit-learn, Matplotlib and more
At Uber, event forecasting enables us to future-proof our services based on anticipated user demand. The goal is to accurately predict where, when, and how many ride requests Uber will receive at any given time.
Open-source models trained and designed to be lightweight and faster. They are less accurate than "standard" ResNet and Inception networks but a lot faster and lighter for on-device analysis.
LSTMs are a fairly simple extension to neural networks, and they're behind a lot of the amazing achievements deep learning has made in the past few years.
Ray Kurzweil, Rodney Brooks, and others weigh in on the future of artificial intelligence
While training Imagenet in 2012 took a couple of weeks with a GPU and lots of custom programming, Facebook claims to have trained Imagenet in just 1 hour recently, using 256 GPUs.
This newsletter is a collection of AI news and resources curated by @dlissmyr. If you find it worthwhile, please forward to your friends and colleagues, or share on your favorite network!
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