Using Generative AI & Machine Learning in the Enterprise
September 18, 2024
DSS MIAMI | Schedule
Wednesday, September 18th
8:00 – 9:40am ET
Registration
9:45 – 10:15am ET
Navigating the Evolution: The Present & Future of LLMs in Enterprise Environments
Chalamayya Batchu Veera - Sr. Enterprise Architect at Georgia-Pacific
10:15 – 10:35am ET
Building Advanced AI Systems: Common Challenges & Best Practices
Sidd Seethepalli - Co-Founder & CTO at Vellum.ai
10:35 – 10:55am ET
“AI” for the Enterprise as a Science of Business Processes
Matthew Denesuk - SVP, Data Analytics & AI at Royal Caribbean Group
We need a fundamental shift in how AI is applied to enterprise performance. To rephrase and adapt a statement made by a renowned economist about IT in the 90s: “We see AI everywhere except in Enterprise Performance.” While he was referring to IT, we are focusing on AI, particularly Generative AI (GenAI). Currently, most of the profits from GenAI are going to those providing the tools and infrastructure. I propose that traditional enterprises should concentrate on developing and utilizing a “Science of Business Processes.” This approach often involves leveraging Data Science, Machine Learning, Statistics, and Scientific Reasoning, and it should be closely integrated with the deep business process knowledge held by those who execute these processes. Such a strategy can lead to significant improvements in business performance, fulfilling AI’s promise of autonomous learning and continuous improvement over time. This is the essence of “Enterprise AI.”
11:00 – 11:20am ET
Coffee Break
11:20 – 12:05pm ET
Roundtable: Bridging the Data Gap: Strategies for Powering
Next-Generation AI Applications
Chris Latimer - Co-Founder at Vectorize
We’ll explore the role of Large Language Models (LLMs) across various industries and their general tendency to produce responses that are often too generic for specialized tasks. This is particularly relevant in healthcare, where LLMs must be fine-tuned with medical data to address specific nuances such as clinical relevance, factual accuracy, and specialized vocabulary.
We’ll discuss the advantages of using smaller, domain-specific models that offer greater clinical precision and accuracy. Additionally, we’ll cover the importance of adapting LLMs to evolving medical concepts and the benefits of evaluating these models using domain-specific benchmarks. We’ll also review various methods for tuning LLMs with limited data to better meet industry needs.
11:20 – 12:05pm ET
Roundtable:
Noelle Russell - Chief AI Officer at AI Leadership Institute
12:05 – 12:15pm ET
Lightning Talk:
Michel Lopez - CEO at e2f, inc.
In the evolving landscape of AI and machine learning, monitoring Large Language Models (LLMs) is critical for maintaining app performance and reliability. This presentation explores the significance of model monitoring, emphasizing that success in machine learning is not solely dependent on algorithms but also on continuous data oversight. We delve into the challenges and best practices for effective model monitoring, combining machine and human efforts to ensure ethical compliance, relevance, bias detection, and consistency. Attendees will gain insights into creating robust monitoring frameworks and the importance of collaboration between data scientists and annotation teams to optimize model performance and user satisfaction.
12:15 – 12:25pm ET
Lightning Talk:
Sagar Samanthapudi - Data Engineer at Indiana University Indianapolis
In this talk, We will explore the transformation journey of Community Information Systems into Advanced Intelligent Systems which are enriched with vast amounts of community data within the data lake. A brief highlights on the key challenges of the transition from legacy data models to new, dynamic data models capable of leveraging Generative AI. This transformation opens new endeavors for a data discovery within the intelligent systems, resulting in significant improvements and streamlined processes in curation of data products which serves in enhancing Community Assessment and Planning within the Data Intelligent Systems.
12:25 – 12:55pm ET
Karthik Ilangovan - Head of Business Intelligence at Neiman Marcus
12:55 – 1:15pm ET
Lauren Burke-McCarthy - Senior Data Science Lead, AI Strategy at Further
1:15 – 2:15pm ET
Lunch & Networking
2:15 – 3:00pm ET
Panel: Applying ML/AI to the Enterprise, and the Trends We’re Predicting for 2025
Antonio Ponte - Global Deposits & Investment Product Manger at Citi, Flaviane Peccin - Director of AI & ML at Visa, Perla Sierra - VP of AI Strategy at PM Electrical Contractors Inc., and Sushaanth Srirangapathi - Principal Data Scientist at Deluxe Corporation
As we approach 2025, machine learning and AI are poised to revolutionize enterprise operations. This session will highlight key trends such as AI-driven automation, ethical AI practices, and the integration of advanced analytics into decision-making processes. We’ll explore the opportunities and challenges that lie ahead, offering insights on how to harness ML/AI to drive innovation, efficiency, and competitive advantage in your organization.
3:00 – 3:20pm ET
Preyaa Atri - Senior Data Engineer at L.G. Electronics
3:20 – 3:50pm ET
Rebecca Sharpe - Chief Technology Officer at Miami Waterkeeper
Join us for a thought-provoking roundtable on leveraging AI to create lasting positive change for our planet. This event will explore the transformative potential of artificial intelligence in addressing urgent environmental challenges. We will delve into cutting-edge AI applications that are revolutionizing environmental conservation and sustainability efforts.
The discussion will showcase real-world examples of AI-driven projects, with a special focus on initiatives underway in Miami. These local case studies will demonstrate how global technologies can have significant local impact.
3:50pm – 4:10pm ET
Coffee Break
4:10 – 4:20pm ET
Lightning Talk:
Ana Arias - Geographic Information Systems Analyst at City of Coral Gables
4:20 – 4:30pm ET
Jay Kachhadia - Sr. Data Scientist at Paramount
4:30 – 4:40pm ET
Lightning Talk: The Ways Data Analytics can Improve Healthcare Billing
Aikerim Belispayeva - Data Analyst at MSP Recovery
4:40 – 5:10pm ET
Deploying Machine Learning Models at Scale
Rachita Naik - Machine Learning Engineer at Lyft
5:10pm – 5:40pm ET
Beyond Agile: Revolutionize Your Data Science Workflow
Balaji Dhamodharan - Sr. Principal Data Scientist at NXP Semiconductors
6:40pm – 7:30pm ET
Closing Reception with office hours with Hasham Ul Haq Sr ML Engineer from John Snow Labs