This week in AI & Machine Learning: Google’s next gen AI chip, Facebook unsupervised speech recognition, pizza robots, TensorFlow Lite for Microcontrollers, and more!
Author’s Note:
I’m teaching a free workshop on May 26th at 5:30pm PDT! Join Intro to Computer Vision: Building Object Detection Models and Datasets to learn how to solve problems using computer vision with your own datasets!
AutoLabel in Action: Try Sense Data Annotation for free!
🤖 Artificial Intelligence News:
- Google Launches the next generation of custom AI chips ← Another huge advancement in computing chips for artificial intelligence! Google had a lot to announce this week at Google IO 2021. You can read a list of the biggest announcements here.
- Facebook AI cuts by more than half the error rate of unsupervised speech recognition
- The Navy sub commanded by artificial intelligence ← We’ve seen a lot of AI examples piloting aircraft, but not many controlling large submarines!
- Why federated learning is the right solution for healthcare AI ← Federated learning seems like it could be the future of data for healthcare applications! Openmined has been doing a lot of work in this field. I welcome you to check them out.
- Artificial Intelligence: How Non-Tech Firms Can Benefit ← This report shows some interesting use cases for AI in “non-tech” spaces. Bringing machine learning and computer vision to industries is something Sixgill happens to be really good at! Contact us to see how we can help.
- Slicing up Pizza Robots
🛠️ Developer Tools & Education:
- Hyperparameter tuning with scikit-learn and Python
- TensorFlow Lite for Microcontrollers ← I’m excited to get these new examples on a raspberry pi pico!
- High Fidelity Pose Tracking with MediaPipe BlazePose and TensorFlow.js
- Building with the Responsible AI Toolkit ← A useful new toolkit from google to explore your datasets.
- TensorFlow Forum ← TensorFlow now officially has a forum!
📅 Upcoming Online AI & Data Science Events:
- A Hybrid Method to Predict Sports Related Concussions with ML (May 24–7:00pm PDT) “Hybrid machine learning model based on the combination of human/knowledge based domains and computer generated feature rankings to improve accuracy of diagnosing SRC.”
- The Ins and Outs of Apache Kafka (May 25–10:00am PDT)
- Intro to Computer Vision: Building Object Detection Models and Datasets (May 26–5:30pm PDT): ← I’ll be teaching this, so come say hi!
- Graph Analytics and Graph-based Machine Learning (May 28–10:00am PDT)
🎤 Interesting Podcasts & Interviews:
- Sam Harris: Consciousness, Free Will, Psychedelics, AI, UFOs, and Meaning
- AI Researcher James Kahn Explains Deep Learning’s Collision Course with Particle Physics
- Using AI to Map the Human Immune System with Jabran Zahid
- Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch
- Peter Chen on building brains for robots in the real world
- Apache TVM and OctoML
📄 Notable Research Papers:
- Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
- Style-Restricted GAN: Multi-Modal Translation with Style Restriction Using Generative Adversarial Networks
- Self-Supervised Learning for Fine-Grained Visual Categorization
- Rethinking the Design Principles of Robust Vision Transformer
- Divide and Contrast: Self-supervised Learning from Uncurated Data
- Omnimatte: Associating Objects and Their Effects in Video
🤝 Connect with AI practitioners of all levels
- Stay connected with artificial intelligence and machine learning practitioners around the world! Slack Group | LinkedIn Group | Meetup Group
🦈 About the Author & Sixgill:
- Sage Elliott is a Developer Evangelist at Sixgill & passionate about making AI more approachable. Connect with Sage on Twitter or LinkedIn.
- Sixgill, LLC provides custom enterprise AI solutions, end-to-end machine learning lifecycle management, and fast data annotation for computer vision.
