This week in AI & Machine Learning: computer vision in e-scooters, gpt-2 training counselors, monitor models in production, PyTorch3d, commercial ML opportunities, and more!
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Sixgill Tip of the Week:
Looking to get started in computer vision? Join our free hands-on workshop this week on March 24th at 10:00am PST. We’ll cover industry computer vision applications, building your own datasets, and how to train models for object detection. Reserve your spot here.
Artificial Intelligence News:
The AI field is growing fast! Here are some of the most interesting or thought provoking AI stories and applications that made the news this week.
This isn’t the first time we’ve seen E-scooter companies using computer vision to help manage how shared scooters are used within crowded cities. But instead of being used to monitor if customers illegally ride or park the scooters, this company aims to prevent pedestrian collisions by detecting pedestrians with computer vision techniques similar to some autonomous vehicles.
It will be interesting to see how much this improves rider safety and potentially increases scooter ride sharing adoption in wary cities.
A crisis hotline is using a chatbot trained with OpenAI’s GPT-2 natural language processing (NLP) algorithm to help train employees for complex situations with teens in crisis. The idea of using NLP as counselors or therapists is a hot topic. This approach of using machine learning to train humans is intriguing and could help save lives!
A restaurant is switching over to speech recognition software to take orders at a drive-thru restaurant. Think about using Alexa or Siri to place your order using your voice. Do you think it will improve order times or end up being more frustrating to customers?
Developer Tools & Education:
Keep up to date with the latest relevant developer tool releases & educational posts.
Checkout how Google AI is using generative machine learning algorithms to improve compression that can allow voice communication even on the slowest networks.
This week’s computer vision tutorial from PyImageSearch you’ll learn how to implement connected component labeling and analysis with OpenCV.
PyTorch3D added some interesting new features: implicit shape rendering, multiple ray sampling implementations, new volumes data structure, and more. I’m excited to see where 3D deep learning libraries take us!
In this workshop, you’ll learn about computer vision applications, labeling your own datasets for object detection, and training models using python.
Upcoming Online AI & Data Science Events:
Live tech events are a great way to learn skills, meet new people, and stay connected to amazing communities around the world!
Mar 02, 06:00PM PST
Learn how to monitor and maintain a model after deployment in productions to ensure performance.
Mar 16, 10:00AM PST
This talk will walk machine learning practitioners through guidelines for efficient hyperparameter optimization based on Oríon, an open source HPO framework
Mar 24, 10:00am PST
Build your own object detection model from start to finish. Includes how to do data annotation and model training on your own dataset.
Interesting Podcasts & Interviews:
Listening to podcasts is a great way to stay updated with the ever changing world of AI, and often provides deeper insights into how brilliant people solve problems.
In this episode of SuperDataScience with Michael Segala (Co-Founder & CEO of SFL Scientific), learn how GPUs can be used to accelerate machine learning, the biggest government policy holding back machine learning, and more.
The hosts of Practical AI discuss low code/no code development and new learning opportunities for machine learning.
Listen to Penousal Machado, Associate Professor and Head of the Computational Design and Visualization Lab in the Center for Informatics at the University of Coimbra discuss Evolutionary Computation and more.
Hear what Arul, a 30-year veteran of Microsoft and a manager of machine translation research at Azure has to say about the evolution of machine translation, including seq2seq and transformer models.
Notable Research Papers:
Every week there are many interesting papers published to arxiv. I highlight some of the ones I find interesting below.
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