This week in AI & Machine Learning: Autonomous Fruit picking robots, AI processing breakthrough, finding optimal ML Models, robot paintings, 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 February 24th at 5:30pm 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.
Hiring enough workers to pick fruit is always hard, but it has been especially difficult during the COVID-19 pandemic. Learn how Tevel Aerobotics Technologies is solving the worker shortage and reducing food waste with its flying autonomous fruit picking robots!
At this year’s Super Bowl, Mountain Dew presented a challenge: count the number of Mountain Dew bottles in its 30-second Super Bowl commercial. Could computer vision be used to help accurately count the bottles even with complicated scene transitions? This fun project highlights the steps for a successful machine learning project and demonstrates how quickly you can from idea to results in the Sense Platform.
There have been a lot of awesome AI generated art pieces, and even robots that paint them, but what makes the Ai-da exhibit a bit more fun is having the humanoid robot artist exhibit her work “in person”.
Samsung announces it has developed “the industry’s first High Bandwidth Memory (HBM) integrated with artificial intelligence (AI) processing power”. Having more powerful AI processing chips from Samsung and other chip manufacturers will greatly affect where AI can be applied in the future! To learn more about the AI microprocessor field, check out the conversation with Jim Keller in the podcast section!
The 2021 Habitat Challenge launched by Facebook AI and Georgia Tech challenges AI researchers to train machines to navigate real-world environments. Navigating real-world environments has been a long running problem in the AI and robotics community. It’s always neat to see more challenges aiming to improve navigation in complex environments.
We're excited to launch the third Habitat Challenge at the Embodied AI workshop with 15 research & academic institutions. The 2021 Habitat Challenge invites AI experts from around the world to teach machines to navigate real-world environments. #CVPR2021 https://t.co/wefO4xXCz0 pic.twitter.com/1Ai3PVyujN— Facebook AI (@facebookai) February 17, 2021
Developer Tools & Education:
Keep up to date with the latest relevant developer tool releases & educational posts.
Google announces its open source domain-agnostic platform to help researchers develop the best ML models, efficiently and automatically with its AutoML solution, Model Search.
Google in collaboration with Deepmind and the University of Toronto introduce DreamerV2, the first deep reinforcement learning (RL) agent based on a world model to achieve human-level performance on the Atari benchmark. Read the arxiv paper here.
Presenting DreamerV2, the first world model-based #ReinforcementLearning agent to achieve top-level performance on the Atari benchmark, learning general representations from images to discover successful behaviors in latent space. Read more at https://t.co/V12CYFPWBy pic.twitter.com/ssS88f8Vsz— Google AI (@GoogleAI) February 18, 2021
PyTorch Lightning V1.2.0 is here! This brings some neat new features such as, PyTorch autograd profiler, DeepSpeed model parallelism, Pruning, quantization, Stochastic weights averaging and more stability improvements.
PyImageSearch announces a new “university” tier of subscription. This is pretty exciting! It will allow a subscriber to pay for content organization, videos, certificates, and code while allowing pyimagesearch to still post free content for everyone to enjoy and learn from.
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!
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.
This is a half-day interactive event with AI and ML leaders from Google, Facebook, Academia, Goldman Sachs and Anthem Insurance. Check out the awesome speaker lineup!
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.
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.
Find out how Pooja Rao is making cutting-edge AI medical care available to communities around the world through her start up, qure.ai!
Get a glimpse at another awesome medical AI startup, AIdoc In this episode with Elad Walach, AIdoc creates AI for radiology.
In this conversation with Sinan Ozdemir, learn how he implements, designs, and integrates conversational AI algorithms and what it takes to be in the natural language processing (NLP) field.
Listen to Luna Dong discuss Amazon’s extensive product knowledge graph and how machine learning plays a role in it.
Listen to Jim Keller and Lex fridman discuss the fascinating world of microprocessor chip design, the role it plays in the future of artificial intelligence and much more.
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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