Five Powerful Robots You Shouldn’t Miss

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SyncedReview

4 min readMay 26, 2019

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Facebook’s Robotic Arms and Legs Are Learning Faster than Ever
Although Facebook Inc. doesn’t sell robots, its researchers use plenty of them — and the company said its machines are getting a lot smarter, a lot faster. The social media giant announced that its engineers, working with computer scientists from New York University, have reduced the time it takes to teach a robotic arm how to grasp objects to tens of tries, rather than hundreds or thousands.
(Bloomberg)

This Robot Helps You Lift Objects — by Looking at Your Biceps
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) recently showed that a smoother robot-human collaboration is possible through a new system they developed, where machines help people lift objects by monitoring their muscle movements.
(MIT News)

Meet Doggo: Stanford’s Cute Open-Source Four-Legged Robot
Students from Stanford University have welcomed a new addition to their campus: Doggo, a four-legged robot that hopes to find a home in research labs around the world. Doggo follows similar designs to other small quadrupedal robots, but what makes it unique is its low cost and accessibility.
(The Verge)

Watch the HyQReal Robot Pull An Airplane
The Italian Institute of Technology (IIT) is announcing a brand new and massively upgraded quadruped called HyQReal. It’s designed to be big, powerful, and rugged, and to demonstrate its capabilities, IIT figured that they might as well see if it could pull a three-ton airplane.
(IEEE Spectrum)

Ford Self-Driving Vans Will Use Legged Robots to Make Deliveries
The automaker is announcing today that its fleet of autonomous delivery vans will carry more than just packages: Riding along with the boxes in the back there will be a two-legged robot. Digit, Agility Robotics’ humanoid, is designed to move in a more dynamic fashion than regular robots do, and it’s able to walk over uneven terrain, climb stairs, and carry 20-kilogram packages.
(IEEE Spectrum)

Technology

Parallel Neural Text-to-Speech
Researchers propose a non-autoregressive seq2seq model that converts text to spectrogram. It is fully convolutional and obtains about 17.5 times speed-up over Deep Voice 3 at synthesis while maintaining comparable speech quality using a WaveNet vocoder. Interestingly, it has even fewer attention errors than the autoregressive model on the challenging test sentences.
(Baidu)

Deep Compressed Sensing
Researchers propose a novel framework that significantly improves both the performance and speed of signal recovery by jointly training a generator and the optimisation process for reconstruction via meta-learning. They explore training the measurements with different objectives, and derive a family of models based on minimising measurement errors.
(DeepMind)

Moving Camera, Moving People: A Deep Learning Approach to Depth Prediction
Google AI has introduced a deep learning based approach that generates depth prediction from videos where both camera and subject are in motion. Researchers focused on depth prediction for humans as humans tend to feature prominently in related applications such as augmented reality, and human motion is relatively difficult to model.
(Synced) / (Google AI)

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Facebook Open-Sources Pythia for Vision and Language Multimodal AI Models
Facebook announced today that it is open-sourcing Pythia, a deep learning framework for vision and language multimodal research framework that enables researchers to “more easily build, reproduce, and benchmark AI models.”
(Synced)

Microsoft Pumps $100M into African AI Centres
Last week Microsoft announced a US$100 million investment in its Africa Development Centres (ADC), with initial software development sites slated to open in Nairobi, Kenya and Lagos, Nigeria later this year. Microsoft will hire 100 full-time developers to work on artificial intelligence, machine learning, and mixed reality innovation.
(Synced)