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The future of robotics

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Manage episode 418721723 series 2712286
Content provided by Stanford Engineering & Russ Altman and Stanford Engineering. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stanford Engineering & Russ Altman and Stanford Engineering or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Guest Jeannette Bohg is an expert in robotics who says there is a transformation happening in her field brought on by recent advances in large language models. The LLMs have a certain common sense baked in and robots are using it to plan and to reason as never before. But they still lack low-level sensorimotor control — like the fine skill it takes to turn a doorknob. New models that do for robotic control what LLMs did for language could soon make such skills a reality, Bohg tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

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Chapters:

(00:00:00) Introduction

Russ introduces guest Professor Jeannette Bohg, an expert in robotics from Stanford University.

(00:01:58) AI's Impact on Robotics

How AI is transforming robotics and the use of AI in high-level planning and reasoning in robotics.

(00:04:26) Challenges of Applying Language Models in Robotics

The challenges and potential of using large language models for robotic task planning and interaction between humans and robots.

(00:07:06) Data Shortages in Robotics

The scarcity of training data in robotics compared to other AI fields and its impact on development.

(00:10:43) Human-Robot Interaction and Augmentation

The potential for robots to augment human capabilities rather than replace them and different approaches to autonomy in robotics.

(00:16:41) The Future of Robotic Hardware

The current state of robotic hardware, its limitations, and what the future might hold for robotic development.

(00:19:53) The Financial and Practical Realities of Robotic Research

Cost and maintenance challenges associated with robotic research platforms, as well as practical applications of robotics in everyday life.

(00:25:11) Humanoid Robots vs. Practical Robots

The practicality and implications of designing robots that mimic human appearance and capabilities.

(00:27:55) Future Outlook and Commercial Viability

The future outlook for robotic platforms and when they might become commercially available.

(00:29:08) Conclusion

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads or Twitter/X

Connect with School of Engineering >>> Twitter/X

  continue reading

272 episodes

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The future of robotics

The Future of Everything

142 subscribers

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Manage episode 418721723 series 2712286
Content provided by Stanford Engineering & Russ Altman and Stanford Engineering. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stanford Engineering & Russ Altman and Stanford Engineering or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Guest Jeannette Bohg is an expert in robotics who says there is a transformation happening in her field brought on by recent advances in large language models. The LLMs have a certain common sense baked in and robots are using it to plan and to reason as never before. But they still lack low-level sensorimotor control — like the fine skill it takes to turn a doorknob. New models that do for robotic control what LLMs did for language could soon make such skills a reality, Bohg tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

Connect With Us:

Chapters:

(00:00:00) Introduction

Russ introduces guest Professor Jeannette Bohg, an expert in robotics from Stanford University.

(00:01:58) AI's Impact on Robotics

How AI is transforming robotics and the use of AI in high-level planning and reasoning in robotics.

(00:04:26) Challenges of Applying Language Models in Robotics

The challenges and potential of using large language models for robotic task planning and interaction between humans and robots.

(00:07:06) Data Shortages in Robotics

The scarcity of training data in robotics compared to other AI fields and its impact on development.

(00:10:43) Human-Robot Interaction and Augmentation

The potential for robots to augment human capabilities rather than replace them and different approaches to autonomy in robotics.

(00:16:41) The Future of Robotic Hardware

The current state of robotic hardware, its limitations, and what the future might hold for robotic development.

(00:19:53) The Financial and Practical Realities of Robotic Research

Cost and maintenance challenges associated with robotic research platforms, as well as practical applications of robotics in everyday life.

(00:25:11) Humanoid Robots vs. Practical Robots

The practicality and implications of designing robots that mimic human appearance and capabilities.

(00:27:55) Future Outlook and Commercial Viability

The future outlook for robotic platforms and when they might become commercially available.

(00:29:08) Conclusion

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads or Twitter/X

Connect with School of Engineering >>> Twitter/X

  continue reading

272 episodes

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