Dexa/Kyle Polich

Published Nov 4, 2024

Graphs and ML for Robotics

Explore how graph-based methods and neural networks can revolutionize robot behavior, as PhD student Abhishek Paudel discusses modeling, decision-making, and the future of robotics, highlighting the crucial transition from simulation to real-world applications.

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Questions from this episode

- Tell me something about artificial intelligence
  Asked by 129 people
- What are the implications for artificial intelligence?
  Asked by 81 people
- What are the current trends in artificial intelligence?
  Asked by 60 people
- How is machine learning evolving?
  Asked by 35 people
- How do you leverage different models in machine learning?
  Asked by 27 people
- What are some key topics discussed in recent episodes of the Practical AI podcast?
  Asked by 19 people
- How can robots affect the future?
  Asked by 13 people
- Can AI lead to rapid advancements?
  Asked by 7 people
- How do we explain neural networks?
  Asked by 5 people
- Teach me about neural networks
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- Why is behavior important in artificial intelligence?
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- How does one understand the underlying data?
  Asked by 4 people
- How is machine learning used in robots?
  Asked by 4 people
- What is the magic in robotics?
  Asked by 3 people
- Tell me more about incremental improvement in the development of AI web agents
  Asked by 3 people

Episode Highlights

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