AI, Machine Learning and Computer Vision Meetup
July 3, 2024 at 2 PM London / 6:30 PM India
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Performance Optimisation for Multimodal LLMs
Neha Sharma
Technical PM at Ori Industries
In this talk we’ll delve into Multi-Modal LLMs, exploring the fusion of language and vision in cutting-edge models. We’ll, highlight the challenges in handling diverse data heterogeneity, its architecture design, strategies for efficient training, and optimization techniques to enhance both performance and inference speed. Through case studies and future outlooks, we’ll illustrate the importance of these optimizations in advancing applications across various domains.
About the Speaker
Neha Sharma has a rich background in digital products and technology services, having delivered successful projects for industry giants like IBM and launching innovative products for tech startups. As a Product Manager at Ori, Neha specializes in developing cutting-edge AI solutions by actively engaging on various AI-based use cases centered around latest/popular LLMs, demonstrating her commitment to staying at the forefront of AI technology.
5 Handy Ways to Use Embeddings, the Swiss Army Knife of AI
Harpreet Sahota
Hacker-in-Residence
Discover the incredible potential of vector search engines beyond RAG for large language models! Explore 5 handy embeddings applications: robust OCR document search, cross-modal retrieval, probing perceptual similarity, comparing model representations, concept interpolation, and a bonus—concept space traversal. Sharpen your data understanding and interaction with embeddings and open source FiftyOne.
About the Speaker
Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.
Deep Dive: Responsible and Unbiased GenAI for Computer Vision
Daniel Gural
Machine Learning Engineer at Voxel51
In the rapidly evolving landscape of artificial intelligence, the emergence of Generative AI (GenAI) marks a transformative shift in the field. But can too fast of an adoption lead to some costly mistakes? In this talk, we’ll delve into the pivotal role GenAI will play in the future of computer vision use cases. Through an exploration of image datasets and latest diffusion models, we will use FiftyOne – the open source data management tool for visual datasets – to demonstrate the leading ways GenAI is being adopted into computer vision workflows. We will also address concerns about how GenAI can potentially poison data, emphasizing the importance of vigilant data curation to ensure dependable and remarkable datasets.
About the Speaker
Daniel Gural is a seasoned Machine Learning Evangelist with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data. Currently serving as a valuable member of Voxel51, he takes a leading role in efforts to bridge the gap between practitioners and the necessary tools, enabling them to achieve exceptional outcomes. Daniel’s extensive experience in teaching and developing within the ML field has fueled his commitment to democratizing high-quality AI workflows for a wider audience.
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