From market manipulation detection to customer satisfaction and business value, Generative AI technology is experiencing remarkable growth and adoption; transforming the way enterprises operate and compete. The constantly changing business landscape means that staying on top of its advancements is crucial to thrive and avoid being left behind in today's competitive environment. Kicking off Generative AI Online is an overview of the current state of this booming trend, its challenges, and specific use cases that you find in regulated industries.

• New developments in generative AI and its future trajectory.
• Data curation and computation for specific use cases.
• Addressing the challenges of trust and accuracy in the financial industry.

Suresh Ande

Director, Head of Engineering - Global Markets Risk Analytics
Bank of America Merrill Lynch

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Generative AI presents an exciting opportunity to explore new horizons in healthcare, potentially enhancing diagnosis, treatment, and patient care. Analyzing medical data and personalizing interventions offers avenues to improve outcomes. Yet, it is accompanied by its own set of complexities. Data privacy, transparency, and interpretability cannot be overstated for responsible and ethical implementation. In discussing the labyrinth of regulatory compliance and fostering trust in AI-driven healthcare solutions are persistent challenges, Stefan will guide us through strategies to:

• Unlock the potential of Generative AI in healthcare: enhancing patient care, empowering healthcare professionals, and optimizing patient adherence and journey
• Navigate challenges in implementing Large Language Models (LLMs) in regulated industries: addressing data ownership, privacy, transparency, and interpretability to ensure compliance and responsible innovation

Stefan Miljkovic

Global Director Next Gen Web
Novartis Pharmaceuticals

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Choosing the right model is crucial for implementing generative AI technology successfully. In this session, attendees will learn key strategies for designing effective generative AI models, including considerations for model size, training data, and API usage.

• Understand the impact of model size on generative AI performance
• Select the right training data to improve model accuracy
• Evaluate the benefits and challenges of using APIs for generative AI applications vs. training them on internal data
• Explore the range of generative AI applications and use cases

Nikhil Sukhtankar

Head of Product, Conversational AI & Messaging Platforms
PayPal

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The storm of generative AI has mainly been focused on text, but where images and text intertwine, we see even greater innovation possibilities. With the potential of generative AI in visual content, Massimo explores innovative use cases and advanced pixel-level detection capabilities, while highlighting ethical use to protect privacy, prevent bias, and maintain trust in the rapidly evolving landscape.

• Delve into advanced techniques of content detection and moderation.
• Discover the industry's call for standardized approaches and traceability.
• Understand the impact of generative AI on user engagement and consumer trends.

Massimo Belloni

Data Science Manager (Integrity & Safety, MLOps)
Bumble

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Learn about the unique challenges and considerations that product teams and software developers must take into account when using generative AI. Join Andreas Welsch in this session to discover essential strategies to prepare for generative AI, the key differences in building generative AI products, and effective ways for developers to upskill and navigate this dynamic field.

Andreas Welsch

Chief AI Strategist
Intelligence Briefing

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