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Robots That Learn Across Tasks!
MIT, Meta, and FAIR are leading the way in robot learning! They’ve introduced Heterogeneous Pre-trained Transformers (HPT), a breakthrough allowing robots to apply skills across different tasks and settings—like a universal "language" for robots!
Key Highlights:
20% boost in task performance
Success across 52 datasets
Effective in both simulations and real-world
By leveraging HPT, robots can build on previous knowledge instead of starting from scratch each time. Just imagine how much faster and adaptable robots will become!
Where do you see this technology heading in the next 5 years?
MIT, Meta, and FAIR are leading the way in robot learning! They’ve introduced Heterogeneous Pre-trained Transformers (HPT), a breakthrough allowing robots to apply skills across different tasks and settings—like a universal "language" for robots!
Key Highlights:
20% boost in task performance
Success across 52 datasets
Effective in both simulations and real-world
By leveraging HPT, robots can build on previous knowledge instead of starting from scratch each time. Just imagine how much faster and adaptable robots will become!
Where do you see this technology heading in the next 5 years?
🤖 Robots That Learn Across Tasks!
MIT, Meta, and FAIR are leading the way in robot learning! They’ve introduced Heterogeneous Pre-trained Transformers (HPT), a breakthrough allowing robots to apply skills across different tasks and settings—like a universal "language" for robots! 🦾✨
🔹 Key Highlights:
20% boost in task performance
Success across 52 datasets
Effective in both simulations and real-world
By leveraging HPT, robots can build on previous knowledge instead of starting from scratch each time. Just imagine how much faster and adaptable robots will become! 🌐🤖
Where do you see this technology heading in the next 5 years?
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