London AI, Machine Learning and Computer Vision Meetup
Nov 19, 2024 | 5:30 to 8:30 PM
Register for the event at Fora Space
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Date, Time and Location
Date and Time
Nov 19, 2024 from 5:30 PM to 8:30 PM
Location
The Meetup will take place at Fora Space SOHO located at 33 Broadwick St in London.
Understanding Memory in AI Agents and Agentic Systems
Richmond Alake
MongoDB
Agentic Systems and extensible compound AI systems are revolutionizing LLM applications, positioning themselves as critical tools in modern AI development. These advanced systems go beyond traditional automation, offering capabilities that drive significant productivity and efficiency gains in enterprise and commercial workflows. However, adopting AI Agents and Agentic Systems at scale poses unique challenges, particularly in ensuring consistent performance, reliability, and scalability.
Central to overcoming these challenges is the role of memory. Memory within AI systems is not only essential for retaining operational data but also for enabling adaptive learning, entity profiling, and customized interactions. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent’s functionality. This talk will delve into the architecture of Agentic Systems and examine how various forms of memory—working memory, data stores, profilers, and toolboxes—contribute to creating robust, efficient, and scalable AI solutions. Attendees will gain insight into how memory is leveraged to enable learning from past executions, personalize interactions, and enhance system capabilities in complex AI applications.
About the Speaker
Richmond Alake is an AI/ML Developer Advocate at MongoDB, where he creates high-quality technical learning content for Developers and MongoDB customers building AI applications. In this role, he provides expert guidance on best practices for developing AI solutions that leverage Large Language Models (LLMs) and MongoDB, as well as offering insights on integrations and other critical aspects of AI development.
How to Unlock More Value from Self-Driving Datasets
Dan Gural
Voxel51
AV/ADAS is one of the most advanced fields in Visual AI. However, getting your hands on a high quality dataset can be tough, let alone working with them to get a model to production. In this talk, I will show you the leading methods and tools to help visualize as well take these datasets to the next level. I will demonstrate how to clean and curate AV datasets as well as perform state of the art augmentations using diffusion models to create synthetic data that can empower the self driving car models of the future,
About the Speaker
Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.
Benchmarking and Optimization of LLMs
Ciera Fowler
Ori
In this session, we’ll focus on the critical role benchmarking plays in optimizing the use of large language models. We’ll dive into how to measure performance across different hardware setups, frameworks, and optimizations such as quantization and attention mechanisms.
About the Speaker
Ciera Fowler is the ML Engineering Lead at Ori, an AI native GPU cloud provider, and an MBA Student at London Business School. Ciera’s works on thought leadership pieces for Ori’s blog and speaking engagements focused on benchmarking and analysis of LLMs. She also posts tutorials and presents at tech meetups around London to help others start building their own LLM powered agents and applications.
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Join the AI and ML enthusiasts who have already become members
The goal of the AI, Machine Learning, and Computer Vision Meetup network is to bring together a community of data scientists, machine learning engineers, and open source enthusiasts who want to share and expand their knowledge of AI and complementary technologies. If that’s you, we invite you to join the Meetup closest to your timezone.
