Top 10 ODSC West Sessions You Must Attend in 2023
Xingsheng Qian | October 24, 2023
ODSC West 2023, one of the leading AI conferences, will take place this year from Oct. 30 to Nov. 2, in San Francisco and virtually. This time, 250 speakers will be sharing 300 hours of valuable content. Sessions will be spread across multiple tracks: NLP and LLMs, MLOps, Generative AI, Machine Learning, Responsible AI, and more. Don’t miss this opportunity to hear from top speakers, get hands-on training, see demos from the latest innovators in the field and network with the data science community.
300 hours of content is a lot, which makes it tough to choose the sessions you’d like to attend. To help, we put together a list of our top 10 recommended sessions. We chose them because they provide practical information that can be implemented today in your environments and organizations, along with a forward-thinking approach that discusses ideas, considerations and opportunities for the future. As can be expected, LLMs and Generative AI are attracting a lot of attention this year, and our list includes sessions about those topics as well.
Here are our top recommended 10 sessions:
1. Causality and LLMs
Wed., Nov. 1, 11:20am - 11:50am
Robert Osazuwa Ness, PhD Senior Researcher, Microsoft
Following the rapid development of LLMs, innovative opportunities for causal analysis have emerged. In this workshop, participants will learn how to effectively use LLMs in complex causal models and in the field of causal AI. First, it will explain how to extract and interpret causal knowledge from LLMs. Then, it will cover how to implement the knowledge in causal models and for comprehensive causal analysis. Finally, it will discuss the concept of “causal LLM”, which is when LLMs are designed using foundational causal principles.
Read the full abstract here.
2. Keynote: Human Centered AI
Wed., Nov. 1, 9:00am - 9:40am
Peter Norvig, PhD, Engineering Director, Education Fellow, Google, Stanford Institute for Human-Centered Artificial Intelligence (HAI)
This talk focuses on the human side of AI applications. Peter Norvig will discuss how to ensure applications are fair, just, truthful, beneficial and suitable for users and society.
Read the full abstract here.
3. Generative AI in Enterprises: Unleashing Potential and Navigating Challenges
Wed., Nov. 1, 10:00am - 10:30am
Rama Akkiraju VP AI/ML for IT, NVIDIA
Generative AI is transforming enterprises. Intelligent chatbots, IT service management, and IT operations management are some examples of helpful applications. But this business potential also requires addressing challenges such as costs, data privacy, governance and ethical deployments. This talk will share insights, observations and lessons on these issues based on NVIDIA’s early-phase projects and experience.
Read the full abstract here.
4. Scope of LLMs and GPT Models in Security Domain
Wed., Nov. 1, 3:30pm - 4:15pm
Nirmal Budhathoki, Senior Data Scientist, Microsoft
What is the perfect balance between Data Science and Security? How can generative AI models like ChatGPT and other LLMs help Security Analysts to do their job more effectively and efficiently? What are the required new skills for someone who wants to start a career path in AI and Cyber Security? The answers to these questions and more will be covered in this session, as well as real world use cases about the opportunities and challenges of LLMs in security.
Read the full abstract here.
5. Machine Learning Has Become Necromancy
Thu., Nov. 2, 3:00pm - 3:45pm
Mark Saroufim, Staff Engineer, Meta
In this unique session, the speaker will explore the evolution and destruction of necromancy and compare it to recent proposed regulations in Machine Learning.
Read the full abstract here.
6. Building Using Llama 2
Mon., Oct. 30, 2:00pm - 3:15pm
Amit Sangani, Director of Partner Engineering, Meta
Looking to learn more about Llama 2 models? In this workshop, participants will discover how to use and access them, how to use LangChain and Tools to build core elements of an AI chatbot, what are the core concepts of Prompt Engineering and Fine-Tuning and how to programmatically implement them using Responsible AI principles, and potential use cases.
Read the full abstract here.
7. A Background to LLMs and Intro to PaLM 2: A Smaller, Faster and More Capable LLM
Mon., Oct. 30, 3:45pm - 5:00pm
Andrew Dai, Principal Software Engineer, Google
PaLM 2 is a Transformer-based model that was trained using a mixture of objectives. In this session, the presenter will demonstrate PaLM 2’s capabilities and its improvements compared to PaLM. This includes improved quality on downstream tasks across different model sizes with more efficient inference, robust reasoning capabilities, stable performance, and inference-time control over toxicity without overhead or impact.
Read the full abstract here.
8. Track Keynote: Implementing Gen AI in Practice
Wed., Nov. 1, 9:45am - 10:30am
Yaron Haviv, Co-Founder and CTO, Iguazio (Acquired by Mckinsey)
Generative AI has become extremely popular in a short period of time. However, building Gen AI applications for production poses a unique set of challenges. These include custom performance, risk, simplifying implementation for production, setting guardrails, automation, CI/CD and more.
In this talk, our own Yaron Haviv, CTO and co-founder of Iguazio (acquired by McKinsey), will explain how to build an ‘AI Factory’ that enables streamlining the process of rolling out new Gen AI applications.
The talk will include three real world examples:
- Creating a Virtual SME (Subject Matter Expert)
- Building a Smart Customer Call Center Analysis App (check out demo here
- Building an Intelligent Chatbot with LLMs
The session will include best practices for building a repeatable process for accelerated development, maintaining low costs, addressing modularity and ensuring safety and production readiness.
Read the full abstract here.
9. Hidden Insights in Financial Audio
Wed., Nov. 1, 2:00pm - 2:45pm
Katie Kuzin, Product Lead, Voice to Text, Kensho Technologies, S&P Global Market Intelligence
There is a lot of information that can be derived from financial earnings calls. Since these calls are public information, they are also easily accessible. In this session participants will learn how to use ASR and NLP tools to run analyses and gain insights from financial earnings calls and any audio data. The tools from this session can be applied to all industries that have audio data.
Read the full abstract here.
10. Why Did My AI Do That? Decoding Decision-making in Machine Learning
Wed., Nov. 1, 4:30pm - 5:15pm
Swagata Ashwani, Senior Data Scientist, Boomi
LLMs resemble black boxes, which undermines trust and poses legal and ethical challenges. This session provides a framework for understanding, evaluating and enhancing model interpretability. The session will cover the model explainability landscape, post-hoc methods like Local Interpretable Model-agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), and Integrated Gradients, and practical implementation using Python libraries like sklearn, lime, and shap. In addition, participants will discuss the trade-offs between accuracy and explainability as well as ethical considerations that stem from model opacity.
Read the full abstract here.
Meet Iguazio at ODSC West
If you're planning to be at ODSC West, swing by booth #3 and catch up with the Iguazio team. We'd love to discuss Generative AI and MLOps with you. Interested in a more detailed discussion? Let's schedule a one-on-one session.
