Alexandra Diem, Head of Cloud Analytics & MLOps at Gjensidige, discusses challenges of generative AI in sensitive data environments, specialized chatbots, data governance, enabling teams through MVP development, transitioning analysts into data scientists, and the importance of collaboration. Her journey from academia to being a consultant in Norway is also explored.
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Quick takeaways
Efficient code development and collaboration are crucial for delivering valuable AI solutions in sensitive data environments.
The use of agile methodologies and scoping minimum viable products can ensure efficient project delivery and customer satisfaction.
Data governance, cloud-native solutions, and internal optimization are key considerations when implementing AI tools and techniques for internal processes.
Deep dives
Enabling Data Teams and Applying Software Engineering Practices
The podcast episode features a conversation with Alexandra Dean, the Head of Cloud Analytics and Machine Learning Operations at a Norwegian insurance company. Alexandra discusses her role in enabling data teams and applying software engineering practices to the data science process. She emphasizes the importance of collaboration and efficient code development in delivering valuable solutions. Alexandra also highlights the significance of hypothesis testing and delivering minimum viable products to ensure quick and effective outcomes. She shares examples of projects that have successfully implemented these principles, such as building chatbots for internal use and using generative AI in improving internal processes.
Balancing Scope and Prioritizing Use Cases
In the discussion, Alexandra explains the process of scoping and prioritizing use cases. She highlights the importance of focusing on minimum viable products and delivering end-to-end solutions from the start. Alexandra mentions the use of agile methodologies to ensure efficient project delivery and customer satisfaction. She emphasizes the value of rotating team members and allocating time to work on both interesting and impactful projects. Alexandra also mentions the challenge of managing change and convincing teams to adopt new tools and approaches, especially when there is existing code or solutions in place.
Navigating the Landscape of AI Tools and Solutions
Alexandra explores the challenges and considerations surrounding AI tools and solutions. She discusses the need to ensure data governance, especially when dealing with sensitive customer data. Alexandra mentions the value of leveraging cloud-native solutions, like feature stores, to reduce code maintenance and improve efficiency. She also highlights the importance of evaluating and recommending external tools while considering factors such as data privacy and ownership. Alexandra emphasizes the principle of building internal capabilities and optimizing internal processes before incorporating AI solutions in customer-facing interactions.
The Role of AI in Internal Process Optimization
The podcast episode touches on the use of AI to optimize internal processes. Alexandra explains how AI tools and techniques can be applied internally to improve efficiency and automate repetitive tasks. She mentions examples of using generative AI to enhance search capabilities for customer advisors and employing chatbots to assist business developers. Alexandra discusses the principle of delivering impactful solutions within the constraints of data governance and risk management. She highlights the importance of achieving a balance between AI advancements and the organization's commitment to data privacy and security.
Lessons from Sports and Gastronomy
Towards the end of the episode, Alexandra shares interesting aspects of her personal life. She mentions her friend's involvement in the Tour de France as a chef and her own experience with owning and operating a restaurant. The discussion sheds light on the challenges and dynamics of the restaurant business and the importance of resilience in the face of unexpected circumstances. The conversation concludes with a recognition that life often guides individuals toward the areas where their skills and passions are most valuable and fulfilling.
Alexandra Diem, PhD, has extensive experience in the field of AI, machine learning, and cloud analytics. Alexandra currently holds the position of Head of Cloud Analytics and MLOps at Gjensidige.
Large Language Models have taken the world by storm. But what are the real use cases? What are the challenges in productionizing them? In this event, you will hear from practitioners about how they are dealing with things such as cost optimization, latency requirements, trust of output, and debugging. You will also get the opportunity to join workshops that will teach you how to set up your use cases and skip over all the headaches.
Join the AI in Production Conference on February 22 here: https://home.mlops.community/home/events/ai-in-production-2024-02-15
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MLOps podcast #212 with Alexandra Diem, Head of Cloud Analytics & MLOps at Gjensidige, Data Governance and AI.
// Abstract
This recent session featuring the incredibly talented Alexandra Diem delves into the challenges of generative AI in sensitive data environments, the emergence of specialized chatbots, and data governance. Balancing high-tech projects with those offering significant business value, using agile methods, is also discussed. Alexandra's journey from academia to being a consultant in Norway is truly inspiring. The discussion explores the function of enabling and R&D in tech roles, the shift towards self-serve solutions, and the integration of AI into existing workflows. Stimulating conversations about future-oriented technologies married with sound data science and industry practices make this session a must-listen for anyone interested in machine learning operations!
// Bio
Former academic turned data scientist with a passion for data mesh architectures.
🔬 Background in applied mathematics and statistics, adept at leveraging data-driven insights to solve complex problems. Experienced in diverse domains spanning the private and public sectors.
🧠 Made significant contributions to research in physiological modeling, successfully debunking a leading biomedical hypothesis on Alzheimer's disease during my PhD. Developed innovative approaches to quantify blood supply to the heart.
💡 Solution-oriented thinker with a track record of efficiently tackling challenging problems and adapting to novel scenarios.
⚙️ Expertise: Data Science | Mathematical Modeling | Statistical Analysis | Problem Solving
In my spare time, you'll find me exploring the great outdoors—whether it's pedaling through scenic landscapes on a bike or riding down the slopes on a pair of skis.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
// MLOps Swag/Merch
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// Related Links
AI in Production Conference: https://home.mlops.community/home/events/ai-in-production-2024-02-15
Website: https://github.com/alexdiem
Talk "DevOps revolutionised software engineering, it's time to revolutionise data" https://vimeo.com/861721829 from JavaZone 2023
Zilliz Cloud: https://zilliz.com/
--------------- ✌️Connect With Us ✌️ -------------
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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Alexandra on LinkedIn: https://www.linkedin.com/in/dralexdiem/
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