← Back to articles
Engineer explains how Vision Language Actions work as natural extensions of sequence modeling to enable robots to understand and execute complex tasks.
r/robotics · April 13, 2026
AI Summary
- •VLMs are being repurposed into control policies that can enhance existing robots with open models like openVLA and gr00t
- •Action tokenization versus continuous control represents a fundamental architectural choice in VLA development
- •The real bottlenecks in VLA development are data collection and embodiment challenges, not just model scaling
- •VLAs function as sequence models similar to GPT but extended to control robotic outputs like torque and acceleration
Related Articles
Large Language Models
Moonshot AI launches open-weight Kimi K2.6 model to rival closed proprietary AI systems while supporting massive agent swarms
THE DECODER·Apr 20, 2026
Large Language Models
Noetik uses transformer AI models like TARIO-2 to address the 95% failure rate in cancer drug trials by reframing the problem as one of patient-treatment matching.
Latent Space·Apr 20, 2026
Robotics
Heven AeroTech's Bentzion Levinson demonstrates breakthrough drone navigation solutions for GPS-denied environments at 2026 AI Summit
The Robot Report·Apr 20, 2026
Large Language Models
Connie Ballmer's $80 million donation bolsters NPR as federal public broadcasting funding faces $1.1 billion cuts under Trump administration.
Fortune AI·Apr 20, 2026
Large Language Models
Researchers investigate whether models trained to avoid deceptive behavior can maintain alignment when deployed in different environments.
LessWrong AI·Apr 20, 2026
Stay ahead with AI news
Get curated AI news from 200+ sources delivered daily to your inbox. Free to use.
Get Started Free