This week in AI & Machine Learning: How AI influences your purchases, Alexa gets better, Pytorch updates, AI privacy, A/B testing for machine learning, and more!
Artificial Intelligence News:
How artificial intelligence may be making you buy things
You’re probably already somewhat aware of how artificial intelligence plays a role in influencing product consumption in the form of recommendation engines. Read this article to learn more about how brick and mortar and online retailers are using data to discover what you may want to purchase before you even know it.
Amazon adds more machine learning features in Alexa to predict goals that aren’t directly expressed
Read about how Amazon is using machine learning to amp up Alexa’s conversational features to predict requests the user doesn’t explicitly ask for. This could be a big step in making AI voice assistants better at understanding what you’re actually asking for and reducing the number of times you hear the response, “I’m sorry, I don’t understand”.
AI Is Bringing The World Together, and not just through social networks
Learn how some companies are using AI and “Digital Twin” technology to help engineers design better for physical environments and how one company is using it to disrupt the private aircraft manufacturing industry.
Developer Tools & Education:
Pytorch Developer Day brings updates to the library
Read a list of the updates here.
I thought The Private AI Series in partnership with Andrew Trask and OpenMined sounded really neat! Also, check out the new Pytorch mobile features for supporting GPU and the Android Neural Networks APIs (NNAPI).
Google 3D Objectron Dataset for Computer Vision
Most datasets for computer vision today are 2D which makes it harder to research 3D capabilities in the industry. Google is making this problem easier to tackle by releasing the Objectron Dataset which contains 15000 annotated videos and 4M annotated images with 3D labels.
Super Resolution with Deep Learning
This week’s tutorial from Pyimagesearch explores how to perform super resolution on images with OpenCV and deep learning.
Interesting Podcasts & Interviews:
Elizabeth Spears on Modern CTO
Listen to this podcast featuring Plainsight’s own Elizabeth Spears discussing AI ecosystems, the future of AI, finding the signal in the noise, and much more!
Pixels to Concepts with Backpropagation w/ Roland Memisevic on TWiML
Listen to Roland Memisevic of Twenty Billion Neurons explain how they train deep neural networks to understand exercise and physical movements.
Fighting Global Health Disparities with AI w/ Jon Wang on TWiML
Explore different ways AI can be used in public health to prevent disparities and what it takes to build out digital infrastructures in lower resource areas.
Accessibility and Computer Vision on TWiML
Learn how AI and computer vision can be used to increase accessibility to digital assets.
Notable Research Papers:
Some of the interesting machine learning papers published this week.
- Scaling Hidden Markov Language Models
- When Do You Need Billions of Words of Pretraining Data?
- Prediction problems inspired by animal learning
- GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts
- Transformers for One-Shot Visual Imitation
- Real-Time Decentralized knowledge Transfer at the Edge
- Audrey: A Personalized Open-Domain Conversational Bot
- DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
- Offline Learning of Counterfactual Perception as Prediction for Real-World Robotic Reinforcement Learning