TensorFlow World; Microsoft Azure Kinect; Google Coral out of beta

Vision Week Issue #2

O’Reilly TensorFlow World

TensorFlow team has teamed up with O’Reilly to host their first TensorFlow World conference earlier this month. If you are wondering how does this differ from TensorFlow Dev Summit, well, the key difference is in Dev Summit mostly people from the TensorFlow team will present their work. But TensorFlow World is a place for everyone in the community to learn and share what they are building with TensorFlow.

That means you can see talks and sessions from diverse set of people including TensorFlow team. All the sessions from TensorFlow team is up on TensorFlow YouTube channel. Other talks are on the O’Reilly online learning platform. O’Reilly says all the recorded sessions will be available on the platform after three weeks from the conference. They have a 10 day free trial. No credit card required. Give it a try to watch all the sessions.

Azure Kinect

Microsoft has released a new version of Kinect called ‘Azure Kinect DK’. DK stands for developer kit. Original version of Kinect was released almost a decade ago for Xbox. It was mainly intended for gaming use with Xbox. But people also used it for computer vision research because of the depth sensing capability it had.

This time Azure Kinect is solely intended for developers and companies to build things and not intended for regular consumers and this is not meant to replace the existing kinect for Xbox. Microsoft says they have put together their best sensors to build AI applications. It has a 12 MP RGB camera, 1 MP depth sensing camera and microphone arrays. It doesn’t have onboard processor but it can be connected to a CPU to process the wealth of information it captures to build vision and speech applications.

Real time video gesture recognition

Researchers at MIT have developed a new technique “Temporal Shift Module (TSM)” to do video classification efficiently on low compute devices. Generally doing video activity recognition in real time on edge devices is hard because of the high compute. In video classification we look at sequence of frames to predict the class as opposed to looking at a single frame at a time for image classification or object detection. The demo runs in real time on Nvidia Jetson Nano under 10 Watts. (Paper | GitHub | Site)

CVPR 2019

Computer Vision and Pattern Recognition (CVPR) is one of the premier conferences in computer vision. CVPR 2019 was over earlier this year. Not all of us can afford to travel and attend the conference in person. Luckily there is this thing called ‘internet’. Computer Vision foundation has made lot of the sessions available online. You can find the video recordings (if available) on YouTube and slides under each session page on the conference website. This really helps to get a sense of what’s going on in the research frontier.

Ancient Secrets of Computer Vision

Joseph Redmon (the author of YOLO/DarkNet) teaches a computer vision course at the University of Washington. He has generously posted the video lectures on YouTube. It’s definitely one of the good introduction to CV courses available online. Feel free to check it out.

Google Coral TPU graduates out of beta

Google launched it’s new hardware Coral Edge TPU earlier this year in March for AI at the edge. After six months now its stable and out of beta. It runs models in a specific TensorFlow Lite edgetpu format very efficiently for low latency real time applications. AI on the edge is off to a good start. Long way to go though !

3Blue1Brown on Siraj Raval Podcast

You might know Grant Sanderson from his awesome YouTube channel “3Blue1Brown”. He was recently interviewed by Siraj on his podcast where they discussed about doing math animations, Grant’s recent visit to India and more. Listen to the episode to learn more. It is available on Google Podcasts, Spotify and possibly wherever you consume your podcasts.

AI fun :)

XKCD Comic@xkcdComic
Tasks
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RL Specialization; Tesla acquires DeepScale; OpenAI at TC DisruptSF

Vision Week Issue #1

RL Specialization from UAlberta on Coursera

University of Alberta and Alberta Machine Intelligence Institute (AMII) have come together to launch a specialization (4 courses) on Reinforcement Learning on Coursera. If you have been trying to learn RL, you might already know that there are not a lot of well structured go-to courses out there. There are some really good resources like Sutton & Barto’s text book, David Silver’s course lectures and UC Berkeley RL course lectures on YouTube, OpenAI’s spinning up in deep RL. But they lack well structured assignments or proper beginner-friendly MOOC setup.

Why this matters:

The reason this course looks promising is, it’s from the people who work directly with the great minds in RL like Prof. Sutton. In fact Sutton himself is involved in the creation of this course. I kind of feel like these courses might be the video version of Sutton’s text book. But it’s definitely worth checking out. Give it a try and let me know your thoughts if you manage to finish any of the courses in the specialization.

OpenAI at TechCrunch Disrupt SF

Sam Altman (CEO) and Greg Brockman (CTO) from OpenAI were at TechCrunch Disrupt San Francisco and discussed some of the company’s earlier decisions (forming capped for profit OpenAI LP, partnership with Microsoft, GPT-2 etc) and future roadmap for OpenAI. Greg also showed a demo of their recent experiment with multi-agent RL and how the agents discovered tool usage.

Tesla acquires DeepScale

Tesla has acquired DeepScale (the company behind SqueezeNet paper). SqueezeNet was one of the first attempts in creating smaller models without losing too much accuracy. This acquisition clearly shows the need for efficient models that can run on edge devices with smaller footprint. AI on edge is definitely booming.

Introduction to TensorFlow Lite on Udacity

TensorFlow Lite team has launched a course on Udacity covering deploying TFLite models to mobile and edge devices. Google also released their Coral Edge TPU earlier this year to advance AI applications on the edge. The course may not be advanced in-depth course. But it can definitely serve as a good comprehensive introduction to TensorFlow Lite.

PyTorch Mobile

Until now, if you want to deploy a model to mobile, your best bet was TensorFlow Lite. PyTorch has added support for mobile (Android and iOS) with their 1.3 release. (PyTorch is upping it’s game!)

DeepMind Podcast

DeepMind has completely restructured the organization recently. They have released a limited series podcast with mathematician Hanna Fry hosting the show and giving us an insider look. All the eight episodes are out. You can find it on Spotify, Google Podcasts or wherever you consume your podcasts.

PyTorch official YouTube channel

PyTorch gets it official YouTube Channel (finally!). I have been waiting for this. Earlier the videos were scattered among Facebook Developers YouTube channel and facebook pages. Now we can watch all the content in one place. Go ahead and watch the videos (PyTorch Developer Conference, Summer Hackathon etc) when you are free.

AI fun :)

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