Applied AI Lunch Talks

About Applied AI Lunch Talks

Applied AI Lunch Talks is an initiative designed to share insights on how AI is leveraged across various organizations to address significant challenges and create value in both business and society. Our guest speakers, who come from startups, SMEs, and large corporations, bring hands-on experience and practical knowledge about applying AI to solve complex problems within their organizations.

Talk 1

Building Enterprise AI Before the Hype
From real-world use case to enterprise adoption

Before ChatGPT brought generative AI into the mainstream, Pernille started building AI Content Creator at Novo Nordisk to solve a real communication need. Today, it is a hyper-personalised GenAI tool designed to help create communication and content that is on-brand and compliant across cultures and markets. In this talk, Pernille will share the journey from use case to enterprise adoption, including stakeholder buy-in, governance and implementation. She will share practical learnings from building and introducing AI in a global organisation balancing technology with people and demonstrate the tool in action.

Speaker

Pernille Kjæmpe, AI Enablement Lead, Global Corporate Affairs, Novo Nordisk

Pernille is AI Enablement Lead in Global Corporate Affairs at Novo Nordisk, where she drives the implementation and adoption of generative AI in communications. She is responsible for Novo Nordisk’s brand guidelines for AI and leads initiatives that bring together technology, communication, brand and compliance.

Talk 2

How Do You Build a Chip - and where can AI help?

How does an idea make its way into a silicon chip? In this talk, Maxim will take you on an accessible tour of the chip-development process - from the first design choices and verification to tape-out, manufacturing, and testing. Along the way, he will explain where Normal Computing fits into the picture, combining custom IP for energy-efficient computing with AI-powered tooling for chip development. From there, the talk will turn to lessons from working with LLMs in a highly technical domain, where mistakes can be subtle and expensive to miss. Maxim will share some of the practical challenges involved in evaluating and improving these systems, where standard approaches tend to fall short, and some of the methods Normal Computing is exploring to make AI more reliable and useful in practice.

Speaker

Maxim Khomiakov, Senior AI Engineer at Normal Computing

Maxim Khomiakov is a Senior AI Engineer at Normal Computing. He studied at DTU and Imperial College London and holds a PhD in Machine Learning from DTU Compute. Before joining Normal Computing, he worked at Apple. Earlier, he co-founded Sunmapper, a greentech venture that was acquired by Otovo. His work spans computer vision, generative models, and applied machine learning, with a recent focus on language models for engineering applications.