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July is almost over and on 7 August we’d like to invite you to our meetup hosted by Artefact at their office in Utrecht, directly next to the Utrecht central train station! The meetup theme is centered around how to bring GenAI to production, but not just production, production to the next level. More specifically, the Artefact team will demonstrate how they use GenAI for the generation of customized, production-ready marketing images and the Phospho team will illustrate how to integrate robust ML best practices on scales of quality metrics for GenAI products. See you there!

SCHEDULE

• 18:00-19:00: Welcome with food and drinks! 🙌
• 19:00-19:45: Talk 1 - "GenAI Image Interaction: a next step beyond LLM text chatbots"
• 19:45-20:00: Break
• 20:00-20:45: Talk 2 - "Emerging best practices in Analyzing Usage Patterns and Quantifying Quality Metrics for GenAI Products"
• 20:45-22:00: Networking / drinks!

TALKS

[Talk 1]: “GenAI Image Interaction: a next step beyond LLM text chatbots" by Arthur Lambert & Priya Sarkar We've all experienced the capabilities of GenAI chatbots for data interaction. Now, it's time to explore the new GenAI innovations that Artefact is developing. Discover how GenAI is transforming marketing by accelerating asset creation and reducing costs. In this talk, we'll demonstrate how we're using GenAI to generate customized, production-ready marketing images. You'll also gain insights into automating the processes, enhancing efficiency for creativity based applications and learn about the quality metrics essential for monitoring and enhancing model performance.

[Talk 2]: “Emerging best practices in Analyzing Usage Patterns and Quantifying Quality Metrics for GenAI Products" by Paul-Louis Venard & Pierre-Louis Biojout Discover how to apply machine learning (ML) emerging best practices to Generative AI (GenAI) applications, specifically focusing on Large Language Models (LLMs) and diffusion models. This talk targets ML engineers and developers aiming to enhance their GenAI products through a quantified evaluation of model quality and user interaction analysis. Learn to implement rigorous, measurable standards to improve and understand GenAI applications.

The rapid advancement in Generative AI technologies, including LLMs and diffusion models, has empowered ML engineers and developers to build new and powerful products. However, the integration of robust ML best practices into the development of these products is still nascent. This session aims to bridge that gap by introducing established methodologies from traditional ML to enhance the reliability and effectiveness of GenAI applications.

DIRECTIONS Directly next to the Utrecht central train station, you’ll find the Artefact office in the Creative Valley building. The address is: Stationsplein 32, 3511 ED, Utrecht.

** Important RSVP here (Due to room capacity and building security, you must pre-register at the link for admission)

Description: Welcome to our in-person AI meetup in New York. Join us for deep dive tech talks on AI, GenAI, LLMs and ML, hands-on workshops, food/drink, networking with speakers and fellow developers.

Tech Talk: Using Generative AI and Diffusers with Cloudera Machine Learning (CML) and Posit Speaker: Kenton Davis (Cloudera), Rika Gorn (Posit) Abstract: In this session, we will explore the architecture of Diffusers models and discuss components such as VAE and UNet. An example will be presented of how to combine text-to-image and image-to-image into one data pipeline with the Cloudera Data Platform (CDP). Specific emphasis will be placed on using ControlNet, PyTorch, and metadata persistence within CDP for editing images.

Tech Talk: Next-Gen AI for Developers Speaker: Allen Firstenberg (Objective) Abstract: In this session, we'll learn how developers of all skill levels can use the Gemini API to build cutting-edge AI applications, regardless of programming language. Discover how to leverage Gemini's unique features for responsible AI, Google Search integration, custom data grounding, and more and the benefits and trade-offs for each model.

Tech Talk: Testing LLMs in web applications Speaker: Haldun Anil (Braze) Abstract: In this talk I will go over how I think about testing applications that integrate LLMs. I will go over what the challenges of writing such applications are and go over a few tools that are out there to overcome these challenges.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsor. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 20,000+ AI developers in New York or 350K+ worldwide.

Community on Slack/Discord

• Event chat: chat and connect with speakers and attendees
• Sharing blogs, events, job openings, projects collaborations

When: July 3, 2024 – 9 AM Eastern / 2 PM BST / 6:30 PM IST

Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-july-3-2024/

Performance Optimization for Multimodal LLMs

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

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

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.

When: July 3, 2024 – 9 AM Eastern / 2 PM BST / 6:30 PM IST

Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-july-3-2024/

Performance Optimization for Multimodal LLMs

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

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

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.

When: July 3, 2024 – 9 AM Eastern / 2 PM BST / 6:30 PM IST

Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-july-3-2024/

Performance Optimization for Multimodal LLMs

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

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

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.

When: July 3, 2024 – 9 AM Eastern / 2 PM BST / 6:30 PM IST

Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-july-3-2024/

Performance Optimization for Multimodal LLMs

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

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

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.