Physical AI Brings Vision-Language Models Into Robotics

Physical AI Brings Vision-Language Models Into RoboticsPhysical AI Brings Vision-Language Models Into Robotics

The network for creativity

Join 1.25M professional creatives like you

Connect with clients, get discovered, and run your business 100% commission-free

Creatives on Contra have earned over $150M and we are just getting started

Back to feedPost

Vishnu Kumawat

• 6h

🤖 AI IS LEARNING TO WORK IN THE REAL WORLD - NOT JUST ON SCREENS.

For years, we've measured AI progress by how well models write, code, answer questions, and generate images.

But a new frontier is emerging: Physical AI.

Google DeepMind recently introduced Gemini Robotics 2.5, a vision-language-action model designed to help robots understand their surroundings, follow instructions, and perform complex physical tasks.

Some of the reported results are fascinating:

🏭 1. Real factory applications Apptronik's Apollo 2 humanoid robots achieved a 96% success rate in a proof of concept sorting automotive parts on Mercedes-Benz production lines.

🧩 2. More advanced dexterity The model was tested across 200+ tasks, from handling delicate objects to using tools and manipulating flexible materials.

⚡ 3. Faster task execution Google reports 30–100% higher success rates across different task types and 20–30% faster completion compared with previous baselines.

🛡️ 4. Safety matters as much as intelligence Robots must recognize obstacles, operate around people, and avoid unsafe actions - not simply follow instructions.

My perspective as an AI Engineer & Full Stack Developer:

The next generation of intelligent products won't exist only inside websites and mobile apps.

AI will increasingly connect software intelligence with physical systems - robotics, sensors, automation, and real-world operations.

That creates exciting engineering challenges around perception, decision-making, APIs, real-time systems, and safety.

The big question:

Where do you think Physical AI will create the biggest impact first - manufacturing, healthcare, logistics, or everyday life?

#PhysicalAI #Robotics #ArtificialIntelligence #GoogleDeepMind #GeminiRobotics #AIEngineering #Automation #HumanoidRobots #FutureOfWork #SoftwareEngineering #TechInnovation #Contra

Nirav Joshi

• Nov 8

Building a robotics startup? Meet Torq Robot, a new template on shadcnspace ⚡

Completed work

AI Development AI Engineer Web Design Claude Framer Next.js

Vansita Addanki

pro

• Nov 9

Cool template for robotics.

Johannes Specht

• Nov 7

This year’s YC Fall batch is for us creatives. 🎯

As a product designer, I’ve never felt like our field was changing as rapidly as it is right now. Tools emerge, you adapt, they disappear. 🫩 Processes that took hours can now be largely automated, and overall, I feel like a big part of the fun gets lost because of a communication issue: I struggle to tell the tools exactly what I want in enough detail. 🫯

I recently stumbled across a few interesting and promising startups that might bring some of that joy back and take the pain out of parts of our work.

Proto is building an IDE specifically for product designers, bringing design and AI workflows closer together. 👩🏻‍💻

Simulithic uses AI agents to test your app across devices, browsers, and account types, automating test creation and maintenance. 🤳🏼

Composal uses swarms of AI agents to explore product flows and edge cases, finding what breaks before release. 🕵🏻‍♂️

Native helps marketers decide what to create by ranking ideas based on brand context, performance, trends, and creative feedback. 🦖

Product Design AI Automation Design Engineering