10:00 - 10:20am: Opening Remarks - Designing Responsible AI Infrastructure

• High Availability Systems: Strategies for creating AI systems that ensure continuous operation and minimal downtime, even under heavy workloads.
• Optimizing High-Density Workloads: Techniques for efficiently managing AI workloads to balance performance with sustainability.
• Balancing Responsibility and Performance: Discussing the trade-offs and best practices in designing AI infrastructure that meets both ethical and operational standards.

10:20 - 10:50am: Sustainable AI Computing

• Understanding the Environmental Impact: Exploring how AI model training and deployment contribute to the carbon footprint.
• Best Practices for Sustainability: Techniques to reduce energy consumption and carbon emissions in AI workflows.
• ·Real-World Examples: Case studies of AI initiatives that have successfully prioritized environmental sustainability.

10:50 - 11:20am: Compliance in AI: Navigating Global Data Privacy Laws

• Overview of Global Regulations: An in-depth look at EU GDPR, UK Data Protection Act, and US data privacy laws, focusing on their implications for AI.
• Strategies for Compliance: Ensuring AI model training processes align with data privacy regulations across different jurisdictions.
• Case Studies: Examples of AI training practices that adhere to international data privacy standards.

11:30am: Roundtable - A comprehensive discussion on the essential elements of responsible AI infrastructure.

12:15 - 12:55pm: Panel: The Future of Responsible Computing

• The Evolution of Responsible AI: Exploring how AI can evolve to be more compliant, sustainable, and resilient.
• Emerging Trends: Insights into the latest developments in AI ethics, sustainability, and regulatory compliance.
• Lessons Learned: Success stories and challenges faced by industry leaders in adopting responsible computing practices.

13:00pm: Closing Remarks

Kristján Hafsteinsson

CEO
Responsible Compute

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2.00pm: Opening Remarks - Accelerating Innovation, Discovery and R&D Transformation with Azure Quantum Elements

Microsoft's latest advancements for R&D transformation empower scientists to make groundbreaking progress in chemistry and materials science by integrating high-performance computing, artificial intelligence and quantum computing. From the ability to rapidly screen lab experiment candidates, to the ease of simulations, and the ability to accurately model and design new molecules, these capabilities enable researchers to accelerate the next 250 years of chemistry and materials sciences progress into the next 25. Join Nick McQuire, Microsoft’s Executive Director of Incubation Management, to learn how to transform your organization into a hub of accelerated innovation. Gain insight on how to adapt to today’s evolving pressures and lead the development of tomorrow's pioneering products. Discover actionable strategies for co-innovating with Microsoft, leveraging state-of-the-art digital solutions to empower your R&D teams and drive substantial business transformation.

2.10pm: Roundtable Discussion: Challenges and Questions in Adopting AI Approaches in R&D

• The session will kick off with an interactive roundtable discussion where executives and thought leaders will explore the current challenges and pressing questions associated with integrating AI approaches in R&D. This will be an open forum for participants to share their experiences, concerns, and aspirations, setting the stage for a collaborative and insightful briefing. Key topics will include data integration, scaling AI infrastructure, talent acquisition, and aligning AI initiatives with business goals.

2.55pm: (Microsoft) Strategising for AI Infrastructure in R&D

• This address will focus on the strategic considerations essential for building and optimizing AI infrastructure to support R&D. The speaker will discuss the importance of a robust data foundation, investment in computational resources, and fostering a culture of innovation. Practical insights on aligning AI strategy with organizational objectives and navigating the evolving landscape of AI technologies will be highlighted.

3.20pm: Material Informatics – Revolutionizing Material Discovery

• This session will delve into the realm of material informatics, emphasizing how AI and machine learning are transforming the discovery and development of new materials. The talk will cover key methodologies, case studies of successful implementations, and the potential for accelerating innovation cycles. Attendees will gain a deep understanding of how AI-driven models can predict material properties and identify novel compounds with unprecedented efficiency.

3.55pm: AI-Driven Drug Discovery

4.20pm: Energy Materials – AI’s Role in Sustainable Innovation

• This session will address the critical role of AI in the development of advanced energy materials, which are essential for sustainable innovation. The talk will highlight how AI is enabling breakthroughs in battery technology, photovoltaics, and other energy storage solutions. Participants will learn about the latest advancements and how AI is driving efficiency and performance improvements in energy materials.

4.45pm: Panel Discussion: Future of AI in R&D – Opportunities and Strategies

• The briefing will conclude with a dynamic panel discussion where experts will discuss the future trajectory of AI in R&D. Topics will include emerging trends, ethical considerations, and long-term strategies for maintaining a competitive edge. The panellists will share their perspectives on the next frontier of AI applications and the collaborative efforts needed to harness AI's full potential in R&D.

Nicholas McQuire

Executive Director of Incubation Management, AI and Quantum
Microsoft

See Bio