This week in AI & Machine Learning: eBay taps computer vision, a chatbot that builds long-term memory and searches the internet, ML Innovation in Healthcare, real-world machine learning with Coral in manufacturing, and more!
Author’s Note:
I’ll be teaching Intro to Computer Vision: Building Object Detection Models and Datasets on July 29th at 10:00am PDT. It’ll be a fun fast-paced workshop covering computer vision applications, data annotation, and training an object detection model with python! A great place to learn how to get started building your own AI-powered solution
🤖 Artificial Intelligence News:
- eBay taps computer vision to transform online shopping ← learn how eBay is using computer vision in its online retail application and what’s next for AI in the industry!
- Google CEO Still Insists AI Revolution Bigger Than Invention of Fire
- Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet “Facebook AI Research has built and open-sourced BlenderBot 2.0, the first chatbot that can simultaneously build long-term memory it can continually access, search the internet for timely information, and have sophisticated conversations on nearly any topic.”
🛠️ Developer Tools & Education:
- Real-World ML with Coral: Manufacturing ← Some great examples of using computer vision and edge computing in manufacturing!
- Introduction to Explainable AI (ML Tech Talks)
- Introduction to TorchShard “TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers or huge classes.”
- How to Configure a GPU Cluster to Scale with PyTorch Lightning
- New Hugging Face Hub documentation ← Unified search across everything should make finding what you’re looking for much easier!
- Intro to PyTorch: Training your first neural network using PyTorch ← Beloved Pyimagesearch has started a tutorial series on Pytorch.
📅 Upcoming Online AI & Data Science Events:
- Practical Crowdsourcing for ML at Scale (July 20–10:00 am PDT) “AI stands on three pillars: algorithms, hardware and training data. While the first two have already become commodities on the market, the latter — reliable labelled data — is still a bottleneck in the industry.”
- Intro to Computer Vision: Building Object Detection Models and Datasets (July 29–10:00 am PDT): ← I’ll be teaching this, so come say hi and ask questions!
- Beam Summit for Data and Stream Processing (August 4–8:00 am PDT)
🎤 Interesting Podcasts & Interviews:
- NVIDIA’s Liila Torabi Talks the New Era of Robotics Through Isaac SIm
- ML Innovation in Healthcare with Suchi Saria
- Cross-Device AI Acceleration, Compilation & Execution with Jeff Gehlhaar
- From symbols to AI pair programmers
- Matanya Horowitz explains how AMP Robotics is building a waste free world
📄 Notable Research Papers:
- PonderNet: Learning to Ponder
- ViTGAN: Training GANs with Vision Transformers
- CMT: Convolutional Neural Networks Meet Vision Transformers
- Per-Pixel Classification is Not All You Need for Semantic Segmentation
- Zero-shot Visual Question Answering using Knowledge Graph
🤝 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 & Plainsight:
- Sage Elliott is a Developer Evangelist at Plainsight & passionate about making AI more approachable. Connect with Sage on Twitter or LinkedIn.
- Plainsight provides custom enterprise AI solutions, end-to-end machine learning lifecycle management, and fast data annotation for computer vision.
