🤖Figure’s Voice-Controlled Robot Showcase

Today we will discuss:

• Sponsored: Anonysis—Unlock feedback, spot trends instantly, and turn insights into action through AI-driven analysis

• Figure’s Robot Follows Voice Commands—Figure’s new Vision-Language-Action model, Helix, helps robots follow voice commands and perform task

• Nvidia Launches AI Tool for ASL—A free AI-powered platform designed to support sign language learners and boost accessibility

• In other AI news today—OpenAI rolls out its AI agent, Operator, in several countries, DeepSeek to open-source 5 code repositories next week for ‘full transparency’, Pika AI launches Pikaswaps, letting users swap objects in videos with anything, and Google’s AI video model Veo 2 goes live on Freepik

• Don’t miss this week’s Workflow Wednesday—AI optimization for content, ads, and videos; now available at only $20/month! 

• Saved the best for last—9 must-try AI tools

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Figure showcases robot completing tasks on voice command

Key Points 

• Figure unveiled Helix, a new Vision-Language-Action model designed for humanoid robots.

• Helix combines visual data and natural language prompts, enabling real-time control of robots for various tasks.

👨‍💻News – Figure founder and CEO Brett Adcock has introduced Helix, a new machine learning model designed for humanoid robots. Helix is described as a “generalist” Vision-Language-Action (VLA) model, aimed at helping robots better interpret and respond to their environment through a combination of vision and language processing.

📖For context – VLAs are a relatively new development in robotics, using visual input and language commands to help machines understand and carry out tasks. One of the most recognized examples so far is Google DeepMind’s RT-2, which trains robots by combining video data with large language models (LLMs) to improve their ability to perform various actions.

🤖In action – Helix works in much the same way, using visual data alongside language prompts to guide a robot’s actions in real time. According to Figure, Helix can recognize and handle thousands of unfamiliar household items, regardless of shape, size, color, or material, all through simple natural language instructions. The goal is to make interactions intuitive—say a command, and the robot gets it done.

🦾A case in point – Figure demonstrates this with examples like, “Hand the bag of cookies to the robot on your right,” or, “Receive the bag of cookies from the robot on your left and place it in the open drawer.” These tasks involve two robots working together, with one assisting the other to complete an action.

However, the technology is still in its early stages, and much of what’s seen in polished demonstration videos requires significant behind-the-scenes effort to achieve.

Read the full story here.

Nvidia debuts Signs, an AI platform to improve ASL accessibility

Key Points 

• Nvidia’s Signs platform is creating a validated ASL dataset with 400,000 video clips of 1,000 signs.

• The platform offers real-time feedback through AI analysis of webcam footage, supporting learners at all skill levels.

☕News – Nvidia has launched Signs, a new AI platform designed to support American Sign Language (ASL) learning and development. 

The platform is focused on building a validated dataset for both learners and developers working on ASL-based AI applications. Nvidia aims to expand this dataset to 400,000 video clips, covering 1,000 signed words. Each sign is reviewed by fluent ASL users and interpreters, ensuring accuracy and creating a reliable visual dictionary and learning tool.

🙌Why this matters – ASL is the third most widely used language in the United States, yet AI tools built with ASL data remain limited compared to those for English and Spanish. The Signs platform aims to support ASL education while encouraging the development of more accessible AI technologies.

🤓How it works – Learners can access a library of validated ASL signs demonstrated by a 3D avatar. The platform also features an AI tool that analyzes webcam footage, offering real-time feedback on signing. Users of all levels can contribute by signing specific words, helping expand the open-source dataset.

👏What’s more? Nvidia plans to use this dataset to develop AI applications that help bridge communication between deaf and hearing communities. The data will also be made publicly available, offering a valuable resource for building accessible technologies such as AI agents, digital human applications, and video conferencing tools.

Read the full story here.

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