This week in AI & Machine Learning: Teaching dogs with ML, Azure in space, TensorFlow 3D, building object detection datasets, Swift for TensorFlow shuts down, and more
Don’t want to miss new articles or tutorials? You can subscribe to our publication on medium to get weekly AI news and more!
Sixgill Tip of the Week:
Save time labeling complex objects by using the track forward and smart polygon selection features in Sense Data Annotation. Label objects in one frame and they will be automatically tracked and labeled in the next! Sign up now and get started today free of charge. No credit card required.
Artificial Intelligence News:
A couple of researchers from Colorado State University used computer vision and a NVIDIA Jetson Nano to automatically reward a dog treats if it followed commands correctly. This fun project does a great job demonstrating the complexity of collecting data, data annotation, machine learning, and edge deployment.
Microsoft Azure’s cloud computing services and Hewlett-Packard Enterprise are attempting to deliver on artificial intelligence and edge computing capabilities to the International Space Station. The new machine learning capabilities can be used to help make predictions across a wide variety of problems that could help with space travel. We won’t be seeing HAL 9000 yet.
The artificial intelligence in agriculture shows no signs of slowing! With recent reports indicating it could be a 11.2 billion dollar industry by 2030. If you’re interested in understanding the agriculture market use cases, checkout Sixgill’s agriculture with artificial intelligence solution page to learn more.
Developer Tools & Education:
We’re at an exciting time where machine learning libraries are making it easier to build 3 dimensional use case solutions. Read about how TensorFlow is bringing 3D capabilities to help understand data from Lidar, depth sensing cameras, and radar.
Development on Swift for TensorFlow officially stops. I know quite a few people were excited about the prospect of using Swift for machine learning, but it seems like that won’t be happening soon, at least not in the TensorFlow ecosystem.
Discover some interesting weak spots of computer vision models, and join a global community of ML researchers and practitioners in a challenge to help better understand these weak spots.
Learn how to perform histogram matching using OpenCV and scikit-image for style transfer.
This blog post provides an overview of changes made in the Hugging Face library, what the PyTorch / XLA library does, an example to get you started training your favorite transformers on Cloud TPUs and some performance benchmarks.
Do you want to MASSIVELY speed up your trainings on TPU?🚀— Hugging Face (@huggingface) February 9, 2021
Transformers has TPU support for all PyTorch training scripts thanks to PyTorch/XLA.
The following joint blog from @GoogleAI x @huggingface showcases the integration and examples.https://t.co/OVyvRW0HlN
Upcoming Online AI & Data Events:
PyCascades is a regional PyCon in the Pacific Northwest, celebrating the west coast Python developer and user community. This year it’s virtual, so everyone can join!
Pedro Domingos will show that deep networks learned by the standard gradient descent algorithm are in fact mathematically approximately equivalent to kernel machines.
Build your own object detection model from start to finish. Learn how fast and easy data annotation accelerates the process and experience model training on your own dataset. Join this free, hands-on workshop to get started with Computer Vision & Object Detection.
Shifting patterns mean that some AI models, which were previously working fine, are now no longer predicting with the same accuracy. Learn how to tackle this problem automatically.
This is part of a global community-led event series for TensorFlow and Machine Learning enthusiasts and developers around the world, powered by the North America Developer Ecosystem at Google.
Interesting Podcasts & Interviews:
Listen to Ya Zu of LinkedIn discuss experiences prior to becoming Head of Data Science, and how to build a sustainable machine learning platform.
Join this conversation with Drago Anguelov of Waymo self-driving cars to hear about autonomous vehicle system design, machine learning use cases, perception, planning, and much more.
Hear Andrew Trister speak about the ways AI is transforming areas of healthcare innovation.
Notable Research Papers:
Connect with AI practitioners of all levels
Stay connected with artificial intelligence and machine learning practitioners around the world!