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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.
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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 / Bluesky / Mastodon
Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
By Stanford Engineering4.8
127127 ratings
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 / Bluesky / Mastodon
Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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