This presentation explores the integration of generative AI in healthcare and pharmacology, highlighting advancements in prompt engineering and its impact on decision-making. The session will examine the complexities and variability of AI responses and the difficulties in establishing a reliable ground truth, emphasizing the need for structured and reproducible outputs to support clinical and business processes efficiently.
Application & Gen AI Integration (Business Leaders) Track
Healthcare
Pharma
Data Science
AI Technologists
Zoran Krunic
Principal Product Manager
Amgen
Since joining Amgen R&D in 2018, Zoran Krunic has been at the forefront of applying Machine Learning to enhance patient outcomes and streamline clinical trial enrollment processes, utilizing comprehensive Electronic Health Records and clinical datasets. His pioneering work in the Quantum Machine Learning space, in collaboration with IBM's Quantum team, has been instrumental in integrating machine learning with quantum computing through IBM’s Qiskit platform.
Prior to his tenure at Amgen, Zoran developed Machine Learning algorithms at Optum to predict hardware and software failures within complex enterprise architectures. He has a strong background in data engineering and systems development, having contributed significantly to large-scale projects at renowned organizations such as Capital Group and ARCO Petroleum.
In his current full and part-time endeavors, Zoran is leading the efforts in embracing generative AI technologies, with a particular focus on OpenAI's GPT and Anthropic's Claude-2 models. His work is focused on prompt engineering and its application to code generation, advanced document analysis, and process management, with a commitment to ethical AI practices and data privacy.
A recognized voice in quantum computing circles, Zoran is a regular presenter at industry conferences and has served on numerous panels discussing the integration of quantum computing and generative AI within the Health Sciences sector.
With a Master of Science in Electrical Engineering & Computer Science, Zoran continues to explore and contribute to the evolving relationship between quantum computing and artificial intelligence, fostering groundbreaking advancements in healthcare technology.
This engaging panel discussion delves into the critical differences between proprietary and public data, emphasising the distinct advantages and disadvantages associated with each. Explore how the accessibility and vast quantities of public data facilitate robust generalisation within AI models, contrasting with the nuanced strengths of proprietary data.
Public data's accessibility and abundance offer significant advantages, enabling broad generalisation within AI models. Conversely, proprietary data boasts higher quality, enhanced control, and minimal risk of contamination, catering specifically to niche topics with detailed coverage.
Delve into the advantages of public data, its scalability, and the challenges it poses, juxtaposed against the precise and controlled nature of proprietary data. Gain valuable insights into navigating the trade-offs between the two, understanding their impacts on model performance, ethical and regulatory considerations, and innovation within the realm of AI.
Technologist Deep-Dive (Gen AI & Data Science) Track
AI Technologists
Data Science
Digital Infrastructure
MLOps
Moderator
Tom Kersten
R&D Engineer
Royal NLR - Netherlands Aerospace Centre
Tom is a distinguished R&D Engineer specialising in AI within the aerospace sector. Armed with a background in computer science and AI, Tom possesses a comprehensive understanding of AI systems. Within his company, he stands out as a leading visionary delving into the integration of generative AI in space, in particular to support the efforts of the Dutch government and its military in this domain. His pioneering work involves exploring and harnessing the potential of GenAI models to revolutionise satellite operations, mission planning, earth observation and space exploration. Tom's dedication to pushing the boundaries of AI in aerospace extends to leveraging generative AI's capabilities, envisaging transformative applications that could redefine the landscape of space technology.
Application & Gen AI Integration (Business Leaders) Track
AI Implementation
Systems Selection
AI Investment
Brandon Walker
Enterprise AI Strategy Lead
Rocket Companies
Brandon Walker is the Enterprise AI Strategy Lead at Rocket Companies. In this role, he is responsible for driving the strategy and architecture for the technology, data and analytics that power the Rocket Company’s fintech platforms—ensuring a consistent, seamless experience for clients across the Rocket Companies ecosystem and driving its growth from mortgage and real estate to personal finance.
Brandon holds a bachelor’s degree from Georgia College and State University and a master’s degree from Harvard University. He and his family reside in Charleston, South Carolina.
Tom Kersten
R&D Engineer
Royal NLR - Netherlands Aerospace Centre
Tom is a distinguished R&D Engineer specialising in AI within the aerospace sector. Armed with a background in computer science and AI, Tom possesses a comprehensive understanding of AI systems. Within his company, he stands out as a leading visionary delving into the integration of generative AI in space, in particular to support the efforts of the Dutch government and its military in this domain. His pioneering work involves exploring and harnessing the potential of GenAI models to revolutionise satellite operations, mission planning, earth observation and space exploration. Tom's dedication to pushing the boundaries of AI in aerospace extends to leveraging generative AI's capabilities, envisaging transformative applications that could redefine the landscape of space technology.
Austin Vance
CEO
Focused Labs
Austin Vance, the co-founder and CEO of Focused Labs, brings a dynamic blend of technical prowess and leadership to the forefront of the software industry. With a career spanning 24 years in software development, he has a rich history of leading high-performing engineering teams at organizations such as Pivotal and PayPal. This extensive experience has not only honed his expertise in the field but also deepened his commitment to delivering exceptional customer service through innovative software solutions. Under his guidance, Focused Labs excels in providing customers with custom software solutions that drive growth, enhance efficiency, and foster innovation, solidifying its position as a trusted partner in the tech ecosystem.
This talk delves into the forefront of AI reliability, presenting sophisticated strategies that address core challenges in the field. Our focus encompasses the intricacies of hallucination prevention, the refinement of data batching processes, and the criticality of compliance in AI development. Leveraging deep insights from cutting-edge research and practice, we offer a comprehensive perspective on enhancing AI systems' accuracy and ethical integrity. This discourse is designed to equip practitioners and researchers with advanced methodologies, fostering the next wave of AI innovations grounded in robustness and responsibility.
Technologist Deep-Dive (Gen AI & Data Science) Track
Finance
Data Science
AI Technologists
AI Integration
Sai Teja Akula
Senior Director, Data Science
LTX Trading
With over a decade of dedicated experience in the field of Artificial Intelligence, Sai stands at the forefront of implementing and leveraging Data Science within organizations. A respected figure in the AI community, Sai has played an instrumental role in the transformation of traditional business models by seamlessly integrating advanced data-driven solutions. His expertise extends from developing sophisticated machine learning algorithms to strategizing the holistic implementation of AI within organizational infrastructures