Detection Transformers (DETR)

Transformer networks have gained a lot of popularity in the recent years. But mostly in the sequence modeling space like NLP, not much used in the computer vision space.

Recently Facebook AI research team has successfully used transformer networks for object detection making the end-to-end detection pipeline much simpler. (paper | code | blog)

Nvidia Jetson Xavier NX DevKit

Nvidia announced Jetson Xavier Nx last November but it wasn’t available to buy right away. After the wait, the devkit has finally arrived.

What’s new ?

Nvidia announced Jetson Nano last year as entry level edge device for AI at $99. Nano was really well received in the market. Now Nvidia is upping the game with Xavier NX for heavy compute applications on edge which Nano can’t handle. In fact, Nvidia calls it “the World’s Smallest AI Supercomputer”. It comes at the same form factor as Nano but with way better compute capability at $399.

Google opensources Big Transfer (BiT)

Researchers at Google have found that pre-training computer vision models on very large scale datasets (way bigger than ImageNet) helps the model to learn quickly and generalize better when finetuned using transfer learning for other tasks even with vey small training data. This approach has been found useful in the language domain in recent times. This work in computer vision shows the need for very large scale open datasets (one of the datasets with 300M images used in the research was an internal dataset). (paper | code | blog)

AI for Healthcare Nanodegree

Following Coursera, Udacity has also launched “AI for Healthcare” nanodegree, a specialized course focusing on applying machine learning to medical data. With everything going on currently, applying AI to healthcare has gained more importance than ever. Checkout the curriculum to learn more.

CVPR 2020

CVPR this year was conducted as a virtual conference due to the pandemic. Featured two special keynotes from Satya Nadella, CEO of Microsoft and Charlie Bell, SVP of AWS. Many tutorial and workshop organizers have generously posted the video recordings online. Checkout the individual websites for the tutorial / workshops you are interested in.

Deep learning lectures from DeepMind

DeepMind in collaboration with UCL has shared a series of deep learning lectures by research scientists at deepmind. 10 out of 12 planned lectures are available on YouTube. Probably the course is affected due to the pandemic. Nevertheless, the available lectures are definitely worth checking out.

Fei-Fei Li on Exponential View Podcast

Dr.Fei-Fei Li, creator of ImageNet was featured on Exponential View podcast. She discussed the early days of ImageNet, the impact it has created, her current work on healthcare and the vision of Human centered AI Lab (HAI) she has cofounded at Stanford. Checkout the full episode here or wherever you generally consume podcasts.

AI fun :)