Virtual | Nov 9 | 10:00 AM – 3:00 PM PT

LLMs in the Enterprise:
From Theory to Practice

Watch the recordings of AI Forward 2023, a one-day, dual-track virtual summit, bringing together industry leaders and practitioners from data science, machine learning, risk and compliance, and AI policy.

Watch on-demand recordings

Virtual • Thursday, November 9, 2023 • dual-track • Watch on-demand • Thank you for joining us • Virtual • Thursday, November 9, 2023 • dual-track • Watch on-demand • Thank you for joining us • Virtual • Thursday, November 9, 2023 • dual-track • Watch on-demand • Thank you for joining us •

Generative AI is being rapidly deployed across industries to unlock business benefits, but there are everyday challenges in working with, operationalizing, and productizing LLMs that need to be addressed first. From evaluating LLM robustness and continuous monitoring to using safety metrics, organizations are deploying cutting edge ways to get the most out of their models.

We will discuss how to maximize the value of AI investments, and you can see the Fiddler AI Observability solutions for predictive and generative AI in action.

Watch to learn:

LLMOps challenges and opportunities in pre- and post-production

Addressing the infrastructure challenges of LLMs

Enterprise use cases that are delivering valuable business impact

The core capabilities of the Fiddler AI Observability platform and Fiddler Auditor

All Recordings

Journey of LLMs in the Enterprise

Krishna Gade highlights the transformative potential and rapid growth of generative AI applications, and their capability to revolutionize industries.

The Science and Engineering Behind LLMs

In this keynote presentation, Hanlin Tang discusses the science and engineering behind LLMs in enterprise applications.

Everyday Challenges and Opportunities with LLMs Pre- and Post-Production

In this panel, AI experts delved into the dynamic realm of generative AI within enterprise settings, highlighting key aspects such as the critical need for enhancing model efficiency, personalization strategies, and addressing the challenges confronting developers entering the AI domain.

LLM POC to Production: Insights From an Infrastructure Viewpoint

In this panel, the AI experts discuss on the advancements and challenges in LLMs from proof-of-concept to production, focusing on infrastructure, model management, and regulatory compliance.

How is ChatGPT’s Behavior Changing Over Time?

In this presentation, Stanford Associate Professor James Zou discusses the dynamic changes in ChatGPT's behavior over time, highlighting substantial alterations in its ability to follow instructions and improvements in safety measures.

Fireside Chat: CEOs in Conversation

In this fireside chat, Lukas and Krishna discussed the rising potential of search, summarization, and chatbot applications in leveraging LLMs, emphasizing their transformative impact on business operations.

Can LLMs be Explained?

In this session, Joshua Rubin shares the importance of explainability in AI, emphasizing that understanding a model's behavior is crucial for identifying weaknesses, ensuring robustness, and aiding human decision-making.

Leadership Perspectives: Use Cases and ROI of LLMs

In this panel, industry leaders shared their insights on LLM implementation and their significant impact on business ROI in their respective fields.

Immersive Gen AI Experience

In this workshop, Joshua Rubin deep dives into an immersive GenAI experience to see how generative AI models, particularly those handling unstructured data like natural language or multimodal inputs, differ from traditional machine learning models.

Evaluating LLMs with Fiddler Auditor

In this workshop, Amal Iyer discussed the importance of evaluating LLMs using Fiddler Auditor, the open-source robustness library for red-teaming of LLMs, designed for testing and ensuring the reliability of LLMs in various applications.

Effective Enterprise Compliance: Make a Leap of Trust with FRoG (Fiddler Report Generator)

In this workshop, Bashir Rastegarpanah shows how Fiddler users can use the Fiddler Report Generator (FRoG) to create customizable reports for model risk management (MRM) and periodic model health reviews.

Fiddler AI Observability Platform for ML and LLMOps

In this workshop, Sabina Cartacio and Barun Halder demonstrate how the Fiddler AI Observability platform offers comprehensive support for MLOps and LLMOps, enabling data scientists, AI practitioners, business stakeholders, auditors, and regulators to validate, monitor, analyze, and improve predictive and generative models.

Chat on Chatbots: Tips and Tricks

In this workshop, Murtuza Shergadwala shares his experiences in building the RAG-based Fiddler Chatbot, and provides tips and tricks on prompt engineering, document chunking, managing hallucinations in responses, improving user trust through UI/UX design, and improving the chatbot with evolving documentation and user feedback.