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New York AI, ML, and Computer Vision Meetup
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Orchestrating AI Pipelines: GenAI and LLOps in Action
Shihan He
Novo Nordisk
Anubhav Srivastava
Novo Nordisk
The increasing adoption of Generative AI (GenAI) is transforming decision-making across industries, making robust Large Language Model Operations (LLOps) and governance strategies critical. This presentation examines technical approaches for leveraging pre-trained transformer models to extract actionable insights and explores the implementation of secure and compliant LLOps pipelines. It will address the challenges and solutions for establishing safe GenAI practices, particularly within regulated sectors like pharmaceuticals, emphasizing the crucial role of governance and risk mitigation in ensuring responsible data-driven decision-making.
Trading on Vision: The Role of VLMs in Market Insights
Daniel Gural
Voxel51
Financial markets move at the speed of information, and traders are increasingly looking beyond traditional text-based data for an edge. Vision-Language Models (VLMs) offer a revolutionary approach by analyzing both visual and textual financial data – from satellite imagery and corporate filings to stock charts and social media trends. This talk explores how VLMs can extract alternative trading signals, interpret financial reports beyond text, and analyze sentiment from news images, all in real time. We’ll also discuss the challenges of accuracy, bias, and regulation when applying VLMs to financial decision-making. By integrating multimodal AI into trading strategies, investors can see the markets like never before.
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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.
Shihan He
Novo Nordisk
Shihan He is a Machine Learning Engineer at Novo Nordisk, focus on developing and implementing advanced AI solutions to drive valuable decision-making throughout the healthcare value chain. She is passionate about applying AI to improve patient outcomes, particularly for those with chronic diseases. Shihan is particularly interested in exploring the potential of GenAI and LLOps to build robust and scalable AI systems.
Anubhav Srivastava
Novo Nordisk
Anubhav Srivastava is the Associate Director of the AI Center of Excellence at Novo Nordisk, leading the development and deployment of AI-powered solutions across the organization. He possesses extensive experience in building and managing high-performing AI teams and is passionate about fostering a culture of innovation and collaboration. Anubhav is committed to driving the adoption of cutting-edge AI technologies, such as GenAI and LLOps, to address critical business challenges and improve patient outcomes.
Shihan He
Novo Nordisk
Shihan He is a Machine Learning Engineer at Novo Nordisk, focus on developing and implementing advanced AI solutions to drive valuable decision-making throughout the healthcare value chain. She is passionate about applying AI to improve patient outcomes, particularly for those with chronic diseases. Shihan is particularly interested in exploring the potential of GenAI and LLOps to build robust and scalable AI systems.
Anubhav Srivastava
Novo Nordisk
Anubhav Srivastava is the Associate Director of the AI Center of Excellence at Novo Nordisk, leading the development and deployment of AI-powered solutions across the organization. He possesses extensive experience in building and managing high-performing AI teams and is passionate about fostering a culture of innovation and collaboration. Anubhav is committed to driving the adoption of cutting-edge AI technologies, such as GenAI and LLOps, to address critical business challenges and improve patient outcomes.
Daniel Gural
Voxel51
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.