Ethan B. Holland

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a middle school art project showcasing robotics, a small written sign says: "Robots" --chaos 20 --ar 4:3 --style raw --personalize x3p86jc --v 6.1

Robotics and Embodiment News: Week Ending 07/19/2024

a middle school art project showcasing robotics, a small written sign says: “Robots” –chaos 20 –ar 4:3 –style raw –personalize x3p86jc –v 6.1

“Skild AI came out of stealth with the goal to develop a ‘general-purpose brain’ for robots Most interestingly, the company plans to operate similarly to OpenAI, allowing customers to fine-tune its foundational robot model for specific use cases 

“Thrilled to announce @SkildAI! Over the past year, @gupta_abhinav_ and I have been working with our top-tier team to build an AI foundation model grounded in the physical world. Today, we’re taking Skild AI out of stealth with $300M in Series A funding, led by @lightspeedvp,”

“Grasping Diverse Objects with Simulated Humanoids We present a method for controlling a simulated humanoid to grasp an object and move it to follow an object trajectory. Due to the challenges in controlling a humanoid with dexterous hands, prior methods often use a disembodied 

Skild AI Is Building A ‘General Purpose Brain’ For Robots

https://www.forbes.com/sites/rashishrivastava/2024/07/09/this-15-billion-ai-company-is-building-a-general-purpose-brain-for-robots

“Code released for Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing! Project page: 

“Researchers open-sourced the code for ‘Robot Synthesia’ It’s an approach to achieving in-hand object rotation using visual/touch inputs The policy is trained in simulation and then transferred to the robot hand without real-world training”

China proposes guidelines for future humanoid development – The Robot Report

China proposes guidelines for future humanoid development

China’s Laws of Robotics: Shanghai publishes first humanoid robot guidelines | South China Morning Post

https://www.scmp.com/tech/policy/article/3269500/chinas-laws-robotics-shanghai-publishes-first-humanoid-robot-guidelines

“Exciting new work! Fast, robust, reactive, direct-from-sensor grasp-anything policies. RL really works, and it’s going to transform the entire robotics economy. DextrAH-G: Dexterous Arm-Hand Grasping 

“Researchers introduced DextrAH-G, a dexterous arm-hand grasping policy trained in simulation using RL It enables a 23-motor arm-hand robot to safely and continuously grasp and transport objects using multimodal inputs 

“Introducing Surgical Robot Transformer (SRT): Automating surgical tasks with end-to-end imitation learning. On the da Vinci robot, we automate: – Knot tying – Needle manipulation – Soft-tissue manipulation Collaboration between @JohnsHopkins & @Stanford. 

https://twitter.com/jwbkim/status/1813263637429297381

“Duke presented ClutterGen, a RL method to generate cluttered scenes to assist robot learning According to the researchers, the idea is that we can look at scene generation as a reinforcement learning problem Interesting work 

“We present ClutterGen that tackles two important research problems in robotics: 1) how to generate physically compliant cluttered scene for robot learning? 2) how to stably place objects instead of the current “pick and drop” paradigm? Our key idea is to formulate physically 

Google

“Next, we provided more multimodal instructions, such as: 📝 Map sketches on a whiteboard 🗣️ Audio requests referencing places from the tour 🎲 Visual cues, like a box of toys. With these acting as inputs, the robot could carry out various actions for different people. 

“We took the robots on a tour of specific areas in a real-world setting, highlighting key places to recall – such as “Lewis’s desk” or “temporary desk area”. Then, they were asked to lead us to these locations. 🏢 Watch more. ↓ 

“Google DeepMind published new research on robot navigation by leveraging Gemini 1.5 Pro’s long context “Mobility VLA” combines 1M token context with a map-like representation of spaces to create frameworks to navigate environments from human instructions 

“Google DeepMind’s robots responded to multimodal instructions, including sketches, audio requests, and visual cues – like a box of toys It also allows for natural language commands, as shown in this demo 

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Be Sure To Read This Week’s Main Post:

This week’s executive overview and top links are here:

AI News #42: Week Ending 07/19/2024 with Executive Summary and Top 58 Links 

The post you just read is an deep dive extension of my weekly newsletter, This Week In AI, an executive summary of the top things to know in AI. Each week, I create an accessible overview for laypeople to feel confident they are conversant with the week’s AI developments. I include a curated list of must-click links of the week, to offer everyone a hands-on opportunity to explore the most intriguing updates in artificial intelligence across various categories, including robotics, imagery, video, AR/VR, science, ethics, and more. Beyond the overview, I post these topic-based deeper dives (below). If you haven’t read this week’s overview, I recommend starting there.

Credits/Sources

Most of these weekly links come from just a few prolific oversharing sources. Please follow them, as they work hard to find the news each week and they make it a lot easier for me to compile.

For previous issues, please visit the archives!

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