AI systems with an embodiment, such as autonomous cars, have an important function in society. We look closer at the special needs of such systems.
SwissCognitive Guest Blogger: Hedvig Kjellström , Lead AI Scientist, Silo AI
In my research at KTH, I am interested in embodied AI systems – systems with a location in the world that are able to move around and also change the state of the world by means of their embodiment. An example of this is autonomous vehicles.
An embodied AI system can actively perceive the world around them in order to gather information through sensors such as vision, process this information on different cognitive levels, both autonomously and in interaction with a human, and finally make plans or decisions based on the outcome. In the autonomous vehicle case, the internal processing consists in planning future driving actions in interaction with the surrounding world and possibly also with a driver.
Modern learning-based AI systems are extremely data-hungry; this is an issue that has to be addressed in the near future, steering development towards more data-efficient methods. An additional challenge with autonomous vehicles is that they constantly meet new situations and surroundings, which means that visual data acquisition for training the vehicle’s perception for all possible eventualities becomes infeasible. A solution is to simulate a wide variety of surroundings and generate synthetic photorealistic data; for an example of such a method from my KTH lab, see https://arxiv.org/pdf/2012.05846.pdf.
In my role Lead AI Scientist at Silo AI I help bring these ideas to use in industrial development projects. We are the leading private AI laboratory in the Nordics, and have a broad and deep competence in real-world AI applications with a strong focus on Computer Vision, Natural Language Processing and Machine Learning. We arrange regular workshops about various AI topics: relevant to this article is an upcoming Autonomous Vehicles webinar; for information and registration see https://learn.silo.ai/webinar-autonomous-vehicles.
About the author – in her own words:
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
I am a Professor in the Division of Robotics, Perception and Learning, KTH. I am also a Lead AI Scientist at Silo AI and an affiliated researcher in the Perceiving Systems Department, Max Planck Institute for Intelligent Systems in Tübingen, Germany. I do research in Computer Vision and Machine Learning. The general theme of my research is methods for enabling artificial agents to interpret the behavior of humans and other animals, and also to behave in ways interpretable to humans. These ideas are applied in Performing Arts, Healthcare, Veterinary Science, and Smart Society. In my free time I like to play the classical double bass, and of course also spend time with the family outdoors, skiing or hiking.
AI systems with an embodiment, such as autonomous cars, have an important function in society. We look closer at the special needs of such systems.
SwissCognitive Guest Blogger: Hedvig Kjellström , Lead AI Scientist, Silo AI
In my research at KTH, I am interested in embodied AI systems – systems with a location in the world that are able to move around and also change the state of the world by means of their embodiment. An example of this is autonomous vehicles.
An embodied AI system can actively perceive the world around them in order to gather information through sensors such as vision, process this information on different cognitive levels, both autonomously and in interaction with a human, and finally make plans or decisions based on the outcome. In the autonomous vehicle case, the internal processing consists in planning future driving actions in interaction with the surrounding world and possibly also with a driver.
Modern learning-based AI systems are extremely data-hungry; this is an issue that has to be addressed in the near future, steering development towards more data-efficient methods. An additional challenge with autonomous vehicles is that they constantly meet new situations and surroundings, which means that visual data acquisition for training the vehicle’s perception for all possible eventualities becomes infeasible. A solution is to simulate a wide variety of surroundings and generate synthetic photorealistic data; for an example of such a method from my KTH lab, see https://arxiv.org/pdf/2012.05846.pdf.
In my role Lead AI Scientist at Silo AI I help bring these ideas to use in industrial development projects. We are the leading private AI laboratory in the Nordics, and have a broad and deep competence in real-world AI applications with a strong focus on Computer Vision, Natural Language Processing and Machine Learning. We arrange regular workshops about various AI topics: relevant to this article is an upcoming Autonomous Vehicles webinar; for information and registration see https://learn.silo.ai/webinar-autonomous-vehicles.
About the author – in her own words:
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
I am a Professor in the Division of Robotics, Perception and Learning, KTH. I am also a Lead AI Scientist at Silo AI and an affiliated researcher in the Perceiving Systems Department, Max Planck Institute for Intelligent Systems in Tübingen, Germany. I do research in Computer Vision and Machine Learning. The general theme of my research is methods for enabling artificial agents to interpret the behavior of humans and other animals, and also to behave in ways interpretable to humans. These ideas are applied in Performing Arts, Healthcare, Veterinary Science, and Smart Society. In my free time I like to play the classical double bass, and of course also spend time with the family outdoors, skiing or hiking.
Hedvig Kjellström
Professor in the Division of Robotics, Perception and Learning, KTH
Lead AI Scientist, Silo AI
CognitiveVirtual by SwissCognitive
Global Online AI Event Series
07. April 2021
Event Recording – Panel Discussion with Hedvig Kjellström
Global Online AI Event Series
07. April 2021
CognitiveVirtual
CognitiveVirtuals are regular worldwide-reaching online events bringing dozens of global AI leaders and experts together to share their views, experiences and expertise in the development of AI to the benefit of business and society. These 3 hour-long events are transparently addressing the development of cognitive technologies – including successes and challenges – while reaching and connecting a global online community of over ½ million followers.
All the sessions and formats are strictly content-driven with a non-sales approach, allowing focused and open discussions with content only. These events provide not only a platform to brainstorm and network but also to position experts, leaders, organisation, research developments, the current status and future outlook of AI.
Check out our upcoming CognitiveVirtual HERE
Share this: