A free online session for 30 to 45 minutes.
Use case specific questions
- Should I train a single global model or consider multiple models? What are the pros and cons? How can I do it?
- How do I run large-scale experiments tailored to my specific use cases? What will be important to report?
- How does FL help in the process of fine-tuning Large Language Models (LLMs)?
- What is a model trail, and what advantages does it offer for my use case?
Broader FL related R&D questions
- I'm interested in investigating cyberattacks on FL systems. Where should I begin? What can be realistic attack scenarios? What are the main mitigation strategies available?
- How does FL help in the process of fine-tuning Large Language Models (LLMs)?
- Blockchain and FL appear to complement each other well. What key considerations should be taken into account when building systems that integrate these two technologies?
- For edge devices with varying capacities, what are the options to allow the maximum number of clients to participate effectively?
Product or business related questions
- How much changes will be required in the current production line when transitioning from centralized to federated learning?
- We are an electronics manufacturing company. What benefits can FL bring to our products?
- What competitive advantage will my company gain if we invest in FL?
- Are FL frameworks mature enough to be used in production environments?
- If data privacy is not the primary concern for a business, what other benefits can FL bring to a company?
The session is designed for focused discussions on questions like those mentioned above. It’s not about debugging code. Also you may not get the exact answer to your problem. But rather exploring potential options that can provide clarity and accelerate progress.
