This week in AI & Machine Learning: Saving elephants, AI in the classroom, Tensorflow 2.4, mitigating unfair bias, get started in Computer Vision, and more!
Artificial Intelligence News:
I sure hope so! Who doesn’t love elephants? Learn how large tech companies and open source developers have partnered together to create advanced tracking technologies. The device, opencollar contains multiple sensors and runs tinyML models to help keep track of animals and detect anomalies that can help alert the right people to help.
If this project sounds interesting to you, check out their github.
This isn’t the first time we’ve talked about AI in the classroom. A couple months ago we saw how a machine learning grading system caused all sorts of problems. But this proposed use isn’t about assigning scores with AI. Instead, it can be used to gain a better understanding of how students are learning and can be used to make sure that no student gets left behind.
Learn how AI impacts neurosurgical progress across many applications, from gaining more knowledge with fewer inputs, to classifying tumors more easily, to assisting with spine care, and much more. AI has the potential to drastically change the way we apply new methods of medical treatment.
Zapata’s mission: “Delivering quantum advantage for customers through real business use cases.” With $38 million to help build its enterprise quantum computing platform, Zapata stands poised to deliver!
Developer Tools & Education:
Check out the cool new features in TF 2.4.0: asynchronous training of Keras models, NumPy-compatible API, Keras mixed precision API, CUDA11, and more.
nbdev is an online environment tool built by github and fastai to help with Automated generation of docs. Continuous integration, and a jupyter notebook hosted on github codespaces.
If you’ve ever talked to me about deep learning I’ve probably brought up GANs at some point! This is a great tutorial to get acquainted with them and start building your own.
Deeplearning.ai released a new advanced course on coursera covering advanced techniques in tensorflow, including custom models, distributed training, computer vision, and GANs.
Upcoming Online AI & Data Events:
Welcome to the “Deep Learning in Practice” learning series, presented by Allegro AI. This series is focused on methodologies and tools for machine and deep-learning(ML/DL) projects.
In the 4th session, we will focus on practical experiences and practices on hyperparameter optimization.
Discuss chapter 7 of “Deep Learning” book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
Get started with computer vision and object detection. I, Sage Elliott, will walk through how to build your own object detector to locate objects in images and videos with Facebook detectron2 and cover practical data labeling methods for you to use in your own projects.
This introductory workshop will get you started with computer vision and walk you through how to build your own object detection system to locate objects in images and videos.
Interesting Podcasts & Interviews:
Charlie Boyle: Pushing the Envelope of Super Computing, NVIDIA DGX A100, Hardware Engg at NVIDIA | Chai Time Data Science
Learn about how the new DGX A100 systems and GPUs are made from Charlie Boyle, the VP of DGX Systems at NVIDIA.
Hear how Sushil thinks COVID-19 is happening in the future enterprise decision making, and gain insights on how to scale machine learning.
Join this conversation with Devin Singh to learn about deploying machine learning models, the current state of academic research, and building automated pipelines.
Notable Research Papers:
Some of the interesting machine learning papers published this week.