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Conteúdo fornecido por Robert Bosch GmbH. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Robert Bosch GmbH ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.
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HOW GENERATIVE AI CAN HELP DRIVING A CAR

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Manage episode 418347486 series 3272453
Conteúdo fornecido por Robert Bosch GmbH. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Robert Bosch GmbH ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.
From Know-how to Wow - the Bosch Global Podcast

Prompt battle! We've all tried giving generative AI chatbots instructions that yield useful results. Recently, GenAI has rapidly expanded across various industries. But can it help drive a car? Dr. Liu Ren, Vice President and Chief Scientist for scalable and assistive AI at Bosch Research, is confident it can. He and his team are at the forefront of integrating foundation models such as large language models or vision-language models with advanced driver assistance systems (ADAS). In this episode, Liu explains to our hosts, Shuko and Geoff, how the extensive knowledge contained in foundation models can enhance the perception, prediction, and planning capabilities of ADAS. What's even more impressive is that Bosch Research’s approach works despite the constrained resources typical in vehicle environments. As Liu shares his cutting-edge research, Shuko and Geoff go head-to-head in a challenge: Who can craft the cleverest prompts for GenAI?

Credits:

  1. Chenbin Pan, Burhan Yaman, Tommaso Nesti, Abhirup Mallik, Alessandro G Allievi, Senem Velipasalar, Liu Ren. “VLP: Vision Language Planning for Autonomous Driving”, The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024).
  2. Xiaoqi Wang, Wenbin He, Xiwei Xuan, Clint Sebastian, Jorge Henrique Piazentin Ono, Xin Li, Sima Behpour, Thang Doan, Liang Gou, Han Wei Shen, Liu Ren. “USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation” , The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024). 3.Chenbin Pan, Burhan Yaman, Senem Velipasalar, Liu Ren. “CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow”, The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024).

More Bosch podcasts: From Know-how to Wow with Liu Ren, all about “Visual Analytics”: https://www.youtube.com/watch?v=CmR97fW_B3I Beyond Bosch: https://podtail.com/de/podcast/beyond-bosch/

  continue reading

72 episódios

Artwork
iconCompartilhar
 
Manage episode 418347486 series 3272453
Conteúdo fornecido por Robert Bosch GmbH. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Robert Bosch GmbH ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.
From Know-how to Wow - the Bosch Global Podcast

Prompt battle! We've all tried giving generative AI chatbots instructions that yield useful results. Recently, GenAI has rapidly expanded across various industries. But can it help drive a car? Dr. Liu Ren, Vice President and Chief Scientist for scalable and assistive AI at Bosch Research, is confident it can. He and his team are at the forefront of integrating foundation models such as large language models or vision-language models with advanced driver assistance systems (ADAS). In this episode, Liu explains to our hosts, Shuko and Geoff, how the extensive knowledge contained in foundation models can enhance the perception, prediction, and planning capabilities of ADAS. What's even more impressive is that Bosch Research’s approach works despite the constrained resources typical in vehicle environments. As Liu shares his cutting-edge research, Shuko and Geoff go head-to-head in a challenge: Who can craft the cleverest prompts for GenAI?

Credits:

  1. Chenbin Pan, Burhan Yaman, Tommaso Nesti, Abhirup Mallik, Alessandro G Allievi, Senem Velipasalar, Liu Ren. “VLP: Vision Language Planning for Autonomous Driving”, The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024).
  2. Xiaoqi Wang, Wenbin He, Xiwei Xuan, Clint Sebastian, Jorge Henrique Piazentin Ono, Xin Li, Sima Behpour, Thang Doan, Liang Gou, Han Wei Shen, Liu Ren. “USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation” , The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024). 3.Chenbin Pan, Burhan Yaman, Senem Velipasalar, Liu Ren. “CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow”, The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024).

More Bosch podcasts: From Know-how to Wow with Liu Ren, all about “Visual Analytics”: https://www.youtube.com/watch?v=CmR97fW_B3I Beyond Bosch: https://podtail.com/de/podcast/beyond-bosch/

  continue reading

72 episódios

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