The Robust & Responsible AI Summit

Alessya Visnjic

CEO & Co-founder of WhyLabs

Welcome session presented by Alessya Visnjic, CEO & Co-founder of WhyLabs.

Andrew NG

Founder of DeepLearning.AI General Partner at AI Fund

Alessya Visnjic

CEO & Co-founder of WhyLabs

A fireside chat with Andrew Ng, Founder of DeepLearning.AI and Landing AI, and Alessya Visnjic, CEO of WhyLabs, on data's role in driving the development and advancement of artificial intelligence.

With over two decades of experience in the field, Andrew has a unique perspective on the evolution of AI, how organizations can leverage data-centric practices to train and improve their AI systems, and the potential impact it can have on many industries.

Maya Wilson

Director of Data Science at Intuit Mailchimp

AI-driven text generation is top of mind these days, and GPT3 has made content generation exponentially more accessible to everyone, from data scientists to designers. So… are we done? Not quite. Creating a positive user experience with zero-shot models should be top of mind for product teams producing human-like text.

In this talk, Maya Wilson will cover the following:

• Thinking about “accuracy” in the context of AI-generated text
• Building personalized experiences with privacy in mind
• Creating internal visibility through monitoring to ensure the models are working as expected

Whether you are a data scientist, engineer, or product manager, this talk will provide valuable insights and practical strategies for your GPT-driven product development.

Daniel Stahl

Head of Data and Analytic Platforms at Regions Bank

Hear how the Regions team designed and scaled their data science platform using DevOps and MLOps practices to meet the increased demand for machine learning while embedding controls throughout the model lifecycle.

In this talk, Daniel Stahl will discuss:

• Scaling machine learning at a large financial institution
• The role of DevOps and MLOps in enabling the scalability and reliability of ML systems
• Best practices for implementing MLOps in a financial setting

Whether you are a data scientist, engineer, or manager, this talk will provide valuable insights and practical strategies for operationalizing machine learning in your organization.

Ksenia Palke

Head of AI at Airspace

Artificial intelligence (AI) has the potential to transform businesses across a wide range of industries. But how do you introduce AI into your company, and what considerations should you make when hiring the right people?

In this talk, Ksenia Palke will cover the following:

• The benefits of introducing AI into your company and how to get started
• The essential skills and expertise required for an AI team
• Getting the leadership buy-in to ensure success

Whether you are a business leader looking to introduce AI into your company or a professional looking to join an AI team, this talk will provide valuable insights and practical guidance.

Rolland He

Manager, Machine Learning Science, Glassdoor

Linge Lass

Staff Machine Learning Scientist, Glassdoor

Building and maintaining models for production is hard! The advent of large language models (LLMs) has highlighted a number of challenges for how ML teams build out production-scale systems. The nature of these challenges also differ quite a bit based on the maturity of the ML team, which makes it impossible to provide a one-size-fits-all solution for ML teams.

In this talk, you'll learn about how Glassdoor shifted to using LLMs for NLP tasks, and some of the challenges we faced when productionizing and maintaining such models, both from a technical and an organizational standpoint. To do this, we'll be walking through a case study related to how we're able to leverage these LLMs to build out new features for Fishbowl, our social media platform for professionals.

Join this talk to learn about some of the hurdles the Glassdoor ML team overcame to successfully deploy a LLM for use in a production use case!

Greg Coquillo

AI Technology Manager, Amazon

Sarah Floris

Senior Data and ML Platform Engineer at Dutch Engineer

Joe Reis

Co-Founder and CEO of Ternary Data

Bernease Herman

Sr. Data Scientist at WhyLabs

A panel discussion on the latest trends in artificial intelligence for 2023 with experts delving into the current state of AI and discussing its potential future developments.

Topics to be covered include:

• Recent advances in machine learning tools & applications
• The role of AI in industry and society
• The ethics of AI and its impact on employment
• The convergence of AI with other technologies such as the internet of things (IoT) and 5G
• The potential for AI to revolutionize healthcare, transportation, and other sectors
• What to expect in 2023

This panel discussion will provide valuable insights and stimulate thought-provoking debate on the future of AI.

Alicia Bargar

Senior Data Developer, Shopify

Curious about whether feature stores have a place in your ML pipelines? In this talk, we will discuss Shopify's philosophy of mediated data sharing and how this influences our approach to building our in-house feature store.

In particular, Alicia Bargar will discuss: The concept of a 'data marketplace' and role of a feature store as broker How data sharing infrastructure leads to better data science and ML Technical advances to support online inference and data quality monitoring

This talk will provide insight into the role of feature stores in machine learning and practical considerations for planning and implementation.