Nov 7-8, 2024
Nov 7-8, 2024
Presenter:
Gon Rappaport, Solution Architect, Aporia
About the Speaker:
I’m a solution architect at Aporia. I joined just over two years ago. I’ve spent over eight years in the tech industry, starting from low-level programming and cybersecurity and transitioning to AI&ML.
Talk Track: Virtual Workshop
Talk Technical Level: 3/7
Talk Abstract:
During the session, we’ll explore the challenges of adopting GenAI in production use-cases. Through focus on the goal of using language models to solve more dynamic problems, we’ll address the dangers of “No-man’s-prod” and provide insights into safe and successful adoption. This presentation is designed for engineers, product managers and stakeholders and aims to provide a roadmap to release the first GenAI applications safely and successfully to production.
What You’ll Learn:
Presenter:
Anish Shah, ML Engineer, Weights & Biases
About the Speaker:
Join Anish Shah for an in-depth session on fine-tuning and evaluating multimodal generative models. This talk will delve into advanced methodologies for optimizing text-to-image diffusion models, with a focus on enhancing image quality and improving prompt comprehension.
Learn how to leverage Weights & Biases for efficient experiment tracking, enabling seamless monitoring and analysis of your model’s performance.
Additionally, discover how to utilize Weave, a lightweight toolkit for tracking and evaluating LLM applications, to conduct practical and holistic evaluations of multimodal models.
The session will also introduce Hemm, a comprehensive library for benchmarking text-to-image diffusion models on image quality and prompt comprehension, integrated with Weights & Biases and Weave. By the end of this talk, you’ll be equipped with cutting-edge tools and techniques to elevate your multimodal generative models to the next level.
Talk Track: Virtual Workshop
Talk Technical Level: 3/7
Talk Abstract:
Join Anish Shah for an in-depth session on fine-tuning and evaluating multimodal generative models. This talk will delve into advanced methodologies for optimizing text-to-image diffusion models, with a focus on enhancing image quality and improving prompt comprehension.
Learn how to leverage Weights & Biases for efficient experiment tracking, enabling seamless monitoring and analysis of your model’s performance.
Additionally, discover how to utilize Weave, a lightweight toolkit for tracking and evaluating LLM applications, to conduct practical and holistic evaluations of multimodal models.
The session will also introduce Hemm, a comprehensive library for benchmarking text-to-image diffusion models on image quality and prompt comprehension, integrated with Weights & Biases and Weave. By the end of this talk, you’ll be equipped with cutting-edge tools and techniques to elevate your multimodal generative models to the next level.
What You’ll Learn:
Advanced Fine-Tuning Techniques: Explore methods for fine-tuning text-to-image diffusion models to enhance image quality and prompt comprehension.
Optimizing Image Quality: Understand the metrics and practices for assessing and improving the visual fidelity of generated images.
Enhancing Prompt Comprehension: Learn how to ensure your models accurately interpret and respond to complex textual prompts.
Utilizing Weights & Biases: Gain hands-on experience with Weights & Biases for tracking experiments, visualizing results, and collaborating effectively.
Leveraging Weave: Discover how Weave can be used for lightweight tracking and evaluation of LLM applications, providing practical insights into model performance.
Introduction to Hemm: Get acquainted with Hemm and learn how it facilitates comprehensive benchmarking of text-to-image diffusion models.
Holistic Model Evaluation: Learn best practices for conducting thorough evaluations of multimodal models, ensuring they meet desired performance standards across various metrics.
Presenter:
Vinay Kumar Sankarapu, Founder & CEO, Arya.ai
About the Speaker:
Vinay Kumar Sankarapu is the Founder and CEO of Arya.ai. He did his Bachelor’s and Master’s in Mechanical Engineering at IIT Bombay with research in Deep Learning and published his thesis on CNNs in manufacturing. He started Arya.ai in 2013, one of the first deep learning startups, along with Deekshith, while finishing his Master’s at IIT Bombay.
He co-authored a patent for designing a new explainability technique for deep learning and implementing it in underwriting in FSIs. He also authored a paper on AI technical debt in FSIs. He wrote multiple guest articles on ‘Responsible AI’, ‘AI usage risks in FSIs’. He presented multiple technical and industry presentations globally – Nvidia GTC (SF & Mumbai), ReWork (SF & London), Cypher (Bangalore), Nasscom(Bangalore), TEDx (Mumbai) etc. He was the youngest member of ‘AI task force’ set up by the Indian Commerce and Ministry in 2017 to provide inputs on policy and to support AI adoption as part of Industry 4.0. He was listed in Forbes Asia 30-Under-30 under the technology section.
Talk Track: Virtual Workshop
Talk Technical Level: 4/7
Talk Abstract:
In highly regulated industries like FSIs, there are more stringent policies regarding the use of ‘ML Models’ in production. To gain acceptance from all stakeholders, multiple additional criteria are required in addition to model performance.
This workshop will discuss the challenges of deploying ML and the stakeholders’ requirements in FSIs. We will review the sample setup in use cases like claim fraud monitoring and health claim processing, along with the case study details of model performance and MLOps architecture iterations.
The workshop will also discuss the AryaXAI MLObservability competition specifications and launch details.
What You’ll Learn:
In this workshop, you will gain a comprehensive understanding of the expectations of FSIs while deploying machine learning models. We’ll explore the additional criteria beyond model performance essential for gaining acceptance from various stakeholders, including compliance officers, risk managers, and business leaders. We’ll delve into how AI explainability outputs must be iterated for multiple stakeholders and how alignment is implemented through real-world case studies in claim fraud monitoring and health claim processing. You’ll also gain insights into why the iterative process of developing MLOps architectures is needed to meet performance and compliance requirements.
Presenters:
Roy Derks, Technical Product Manager, IBM watsonx.ai | Alex Seymour, Technical Product Manager, IBM watsonx.ai
About the Speaker:
Roy Derks is a lifelong software developer, author and public speaker from the Netherlands. His mission is to make the world a better place through technology by inspiring developers all over the world. Before jumping into Developer Advocacy and joining IBM, he founded and worked at multiple startups. His personal mission is making the world better through technology.
Talk Track: Virtual Workshop
Talk Technical Level: 5/7
Talk Abstract:
In today’s world, developers are essential for creating exciting AI applications. They build powerful applications and APIs that use Large Language Models (LLMs), relying on open-source frameworks or tools from LLM providers. In this session, you’ll learn how to build your own AI applications using the watsonx and watsonx.ai ecosystem, including use cases such as Retrieval-Augmented Generation (RAG) and Agents. Through live, hands-on demos, we’ll explore the watsonx.ai developer toolkit and the watsonx.ai Flows Engine. Join us to gain practical skills and unlock new possibilities in AI development!
What You’ll Learn:
By attending this session, you’ll acquire essential skills for effectively leveraging Large Language Models (LLMs) in your projects. You’ll learn to use LLMs via APIs and SDKs, integrate them with your own data, and understand Retrieval-Augmented Generation (RAG) concepts while building RAG systems using watsonx.ai. Additionally, this session will cover Agentic workflows, guiding you through their creation with watsonx.ai. Finally, you’ll explore how to work with various LLMs, including Granite, LLama, and Mistral, equipping you with the versatility needed to optimize AI applications in your development work.
Presenter:
Remi Cadene, ML for Robotics, Hugging Face
About the Speaker:
I build next-gen robots at Hugging Face. Before, I was a research scientist at Tesla on Autopilot and Optimus. Academically, I did some postdoctoral studies at Brown University and my PhD at Sorbonne.
My scientific interest lies in understanding the underlying mechanisms of intelligence. My research is focused on learning human behaviors with neural networks. I am working on novel architectures, learning approaches, theoritical frameworks and explainability methods. I like to contribute to open-source projects and to read about neuroscience!
Talk Track: Virtual Talk
Talk Technical Level: 3/7
Talk Abstract:
Learn about how LeRobot aims to lower the barrier of entry to robotics, and how you can get started!
What You’ll Learn
1. What LeRobot’s mission is.
2. Ways in which LeRobot aims to lower the barrier of entry to robotics.
3. How you can get started with you own robot.
4. How you can get involved in LeRobot’s development.
Presenter:
Dan Adamson, Interim Chief Executive Officer & Co-Founder, AutoAlign AI
About the Speaker:
Dan Adamson is a co-founder of AutoAlign, a company focused on AI safety and performance. He has also co-founded PointChain (developing a neo-banking platform using AI for high-risk and underserved industries) and Armilla AI (a company helping enterprises manage AI risk with risk transfer solutions). He previously founded OutsideIQ, deploying AI-based AML and anti-fraud solutions to over 100 global financial institutions. He also previously served as the Chief Architect at Medstory, a vertical search start-up acquired by Microsoft. Adamson holds several search algorithm and AI patents in addition to numerous academic awards and holding an M.Sc. from U.C. Berkeley and B.Sc. from McGill. He also serves on the McGill Faculty of Science Advisory Board.
Talk Track: Business Strategy or Ethics
Talk Technical Level: 2/7
Talk Abstract:
Many enterprise pilots with GenAI are stalling because of a lack of consistent performance as well as compliance, safety and security concerns. Comprehensive GenAI safety must continually evolve to mitigate critical issues such as hallucinations, jailbreaks, data leakage, biased content, and more.
Learn how AutoAlign CEO and co-founder Dan Adamson leveraged over two decades building regulated AI solutions to launch Sidecar — to ensure models are powerful AND safe. Learn how weak-to-strong controls work to put decisions directly in users’ hands — improving model power while ensuring Generative AI is safe to use.
What You’ll Learn:
During this session, participants will have the opportunity to learn about common approaches to protect GenAI against jailbreaks, bias, data leakage and hallucinations and other harms. We’ll discuss the unique requirements of bringing LLMs to production in real-world applications, the critical importance of ensuring a high level of robustness and safety, and tools for solving these problems.
We’ll then discuss a new approach: weak supervision with a sidecar that can not only increase safety but can also make models more powerful. Finally, we’ll show some of our latest benchmarks around accuracy and discuss these state-of-the-art results.
