London AI, ML & Computer Vision Meetup – Sept 4

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London AI, Machine Learning and Computer Vision Meetup

Sept 4, 2024 | 6:00 to 8:00 PM 

Register for the event at The Counting House!. RSVPs are limited!

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Date, Time and Location

Date and Time

Sept 4 from 6 PM to 8 PM

Location

The Meetup will take place at The Counting House, EC3, 50 Cornhill, London, EC3V 3PD

Talks and Speakers

Accelerating Machine Learning Research and Development for Autonomy

Guillaume Rochette
Oxa (MetaDriver)

At Oxa (Autonomous Vehicle Software), we designed an automated workflow for building machine vision models at scale from data collection to in-vehicle deployment, involving a number of steps, such as, intelligent route planning to maximise visual diversity; sampling of the sensor data w.r.t. visual and semantic uniqueness; language-driven automated annotation tools and multi-modal search engine; and sensor data expansion using generative methods.

About the Speaker

Guillaume Rochette is a Staff Engineer at Oxa MetaDriver, a suite of tools that combines generative AI, digital twins and simulation to accelerate machine learning and testing of self-driving technology before and during real-world use. Prior to that, he did a PhD. in Machine Vision at the University of Surrey on “Pose Estimation and Novel View Synthesis of Humans”. He is currently working on Machine Vision and 3D Geometric Understanding for autonomous driving.

RGB-X Model Development: Exploring Four Channel ML Workflows

Daniel Gural
Sr. Machine Learning Engineer and Developer Relations

Machine Learning is rapidly becoming multimodal. With many models in Computer Vision expanding to areas like vision and 3D, one area that has also quietly been advancing rapidly is RGB-X data, such as infrared, depth, or normals. In this talk we will cover some of the leading models in this exploding field of Visual AI and show some best practices on how to work with these complex data formats!

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.

Performance Optimization for Multimodal LLMs

Neha Sharma
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.