On October 23, 2024 at 9 am PT (noon ET), the Edge AI and Vision Alliance will deliver the free symposium “Your Next Computer Vision Model Might be an LLM: Generative AI and the Move From Large Language Models to Vision Language Models” in partnership with BenchSci and Camio. Here’s the description, from the event registration page:
The past decade has seen incredible progress in practical computer vision. Thanks to deep learning, computer vision is dramatically more robust and accessible, and has enabled compelling capabilities in thousands of applications, from automotive safety to healthcare.
But today’s widely used deep learning techniques suffer from serious limitations. Often, they struggle when confronted with ambiguity (e.g., are those people fighting or dancing?) or with challenging imaging conditions (e.g., is that shadow in the fog a person or a shrub?). And, for many product developers, computer vision remains out of reach due to the cost and complexity of obtaining the necessary training data, or due to lack of necessary technical skills.
Surprisingly, recent advances in large language models (and their close cousins, vision language models, which comprehend both images and text) hold the key to overcoming these challenges. Join us for this exciting expert-led 90-minute online symposium where you will learn:
- What are vision language models, and how do they combine language and vision to create a unified representation?
- What enables vision language models to generalize more effectively compared with classical vision models?
- How can product developers leverage vision language models to reduce the need for training data for new vision applications?
The symposium will feature brief presentations from three expert speakers—István Fehérvári, Director of Data and ML at BenchSci, Carter Maslan, CEO of Camio, and Jeff Bier, Founder of the Edge AI and Vision Alliance and President of BDTI—followed by a Q&A session.
To register for this free webinar, please see the event page. For more information, please email [email protected].
