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

In my talk titled “Navigating the Evolution: The Present & Future of LLMs in Enterprise Environments,” I’ll dive into how Large Language Models (LLMs) are reshaping enterprise operations today and what we can expect in the future. We’ll look at how LLMs are currently enhancing areas like customer service, marketing, and decision-making, using real-life examples to show their impact. Then, we’ll explore what’s on the horizon for LLMs, touching on upcoming research and how enterprises might need to adjust their strategies to keep up with these advances. We’ll also tackle the important topics of ethics, privacy, and security in the context of LLM use. The goal is to give you a clear picture of where LLMs stand today and how they’re set to evolve, helping your organization stay competitive in a fast-changing landscape.

10:15 – 10:35am ET

Building Advanced AI Systems: Common Challenges & Best Practices

Sidd Seethepalli - Co-Founder & CTO at Vellum.ai
This presentation outlines techniques for developing advanced AI systems, focusing on common challenges and best practices. We cover the AI Test Driven Product Development Lifecycle (experiment – evaluate – deploy – monitor), emphasizing experimentation with prompting techniques, testing various architectures, and maintaining a model agnostic approach. The presentation also explores the emerging paradigm of Agentic Workflows, detailing components such as planning, execution, refinement, and interface design. Key takeaways include identifying low-risk use cases, iterating on models and prompting techniques, implementing robust evaluation methods, and maintaining quality through continuous monitoring and edge case identification.

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: Scaling Responsible AI: From Enthusiasm to Execution

Noelle Russell - Chief AI Officer at AI Leadership Institute

Noelle Russell explores the dual phases of AI innovation. Noelle will guide the audience through the journey from initial hype to responsible execution, highlighting the importance of transparency, fairness, and continuous learning in navigating AI’s complexities at scale. Attendees will gain insights on building a robust framework for responsible AI, ensuring long-term benefits and trust.

12:05 – 12:15pm ET

Lightning Talk: Monitoring the Quality of LLM Engines in Production

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: Modernizing Community Information Systems to Intelligent Systems

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

AI for Analytics: Role of AI in Transforming Data into Actionable Insights

Karthik Ilangovan - Head of Business Intelligence at Neiman Marcus

Unlike its deployment in digital realms, applying AI in analytics introduces unique challenges, including data diversity, integrity, bias and ethical concerns. Karthik will discuss overcoming these hurdles with robust governance, ethical AI practices, and user-centric designs. Join him for a concise exploration of AI’s potential to turn data into strategic assets, driving innovation and competitive advantage in the analytics landscape.

12:55 – 1:15pm ET

A Value Playbook for Solo & Siloed Data Practitioners

Lauren Burke-McCarthy - Senior Data Science Lead, AI Strategy at Further

Working as a solitary data practitioner presents both challenges and opportunities. This session will introduce strategies and frameworks for setting expectations, framing problems that align value with organizational needs, and delivering communication and user-focused documentation that improves transparency. Discover how to increase buy-in and enable quick wins with practical approaches to stakeholder engagement, like the road trip method. Attendees will learn to invest in the right use cases, scope projects effectively, and demystify the process while delivering incremental value. This session will highlight best practices for value-first, impact-aligned communication and explore how design thinking fosters successful data projects.

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

Innovative Data, Analytics, and AI Strategies

Preyaa Atri - Senior Data Engineer at L.G. Electronics

In an era where data-driven decision-making is pivotal, the retail sectors are uniquely positioned to leverage advancements in data engineering, analytics, and AI. This presentation explores cutting-edge strategies that integrate these technologies to drive efficiency, enhance customer experiences, and boost profitability. Drawing from my extensive experience as a Senior Data Engineer at LG Electronics and a decade of expertise in data-intensive applications, I will delve into real-world case studies and innovative solutions. Attendees will learn about the development of high-accuracy machine learning systems, the optimization of data warehouses to achieve significant cost reductions, and the deployment of advanced cloud-based data processing workflows. The talk will also highlight the use of big data ecosystems, the integration of diverse cloud services, and the application of robust data protection measures to secure sensitive information. By examining these strategies, participants will gain insights into how to harness data and AI to stay competitive in the dynamic retail landscape.

3:20 – 3:50pm ET

AI and Environmental Sustainability: Innovating for a Greener Future

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: Transforming City Services Using AI

Ana Arias - Geographic Information Systems Analyst at City of Coral Gables

This presentation highlights the significant improvements achieved in Coral Gables through the integration of AI tools in IT projects and their development processes. We have optimized our processes, especially in GIS and IoT, leading to more efficient and accurate outcomes. This implementation using AI technologies has enhanced data analysis, streamlined workflows, provided more insights, and has delivered superior solutions that meet the evolving needs of the City of Coral Gables.

4:20 – 4:30pm ET

Lightning Talk: Making Content Greenlight decisions with Machine Learning at Paramount+

Jay Kachhadia - Sr. Data Scientist at Paramount

In the competitive world of streaming, predicting what content audiences will engage with next is both an art and a science. At Paramount+, we leverage advanced machine learning models to analyze data such as historical viewing patterns and audience demographics, providing us with powerful insights into content demand. However, data alone can’t predict the unpredictable. This talk will explore how we combine data-driven forecasting with human intuition, creativity, and expertise to navigate emerging trends and cultural shifts. By blending these approaches, we ensure that our content strategy is both innovative and responsive to changing viewer preferences. Join us as we discuss how art and science work together to shape the future of entertainment at Paramount+.

4:30 – 4:40pm ET

Lightning Talk: The Ways Data Analytics can Improve Healthcare Billing

Aikerim Belispayeva - Data Analyst at MSP Recovery

In today’s healthcare landscape, data analytics plays a pivotal role in optimizing billing processes, reducing costs, and enhancing overall financial performance. This talk will explore how advanced analytics techniques can be applied to billing in healthcare to uncover inefficiencies, detect fraud, and streamline revenue cycle management. By leveraging data from electronic health records (EHRs), claims, and patient billing histories, healthcare providers can identify patterns that lead to delayed payments, denials, and underpayments. The presentation will cover key strategies for implementing predictive analytics to anticipate billing issues, machine learning models to automate and improve coding accuracy, and data visualization tools to provide real-time insights into financial performance. We will also discuss how data-driven decision-making can lead to more transparent billing practices, improved patient satisfaction, and compliance with regulations. Attendees will gain a deeper understanding of the transformative impact of data analytics in making healthcare billing more efficient and effective.

4:40 – 5:10pm ET

Deploying Machine Learning Models at Scale

Rachita Naik - Machine Learning Engineer at Lyft

The session will explore the complexities of developing and deploying Machine Learning (ML) models at scale in large tech enterprises. The presentation will provide an in-depth examination of the unique challenges faced – ranging from data management and model training to deployment and monitoring, using real-world use cases to illustrate how vast amounts of data are handled and model performance is maintained in dynamic production environments. Attendees will gain practical knowledge and actionable insights, including effective data management strategies, best practices for ML development and deployment, and tips for leveraging advanced tools and frameworks to streamline the ML process, making it more efficient and effective within their own companies.

5:10pm – 5:40pm ET

Beyond Agile: Revolutionize Your Data Science Workflow

Balaji Dhamodharan - Sr. Principal Data Scientist at NXP Semiconductors

Traditional Agile methodologies often struggle to meet the specific demands of data-driven research and development. This presentation introduces the Data Science Lifecycle Process (DSLP), an innovative framework designed to address the distinct challenges of managing data science projects. Balaji will delve into DSLP’s five-step approach—Ask, Data, Explore, Experiment, and Model—and demonstrate how it enhances project management by improving documentation, fostering collaboration, and accelerating value delivery. In a landscape where organizations face growing pressure for tangible results, DSLP stands out as a timely, effective solution. Join Balaji to discover how this transformative framework can revolutionize your data science workflow and drive measurable outcomes.

6:40pm – 7:30pm ET

Closing Reception  with office hours with Hasham Ul Haq Sr ML Engineer from John Snow Labs

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