Impact AI Decoding Pathology for Precision Medicine with Maximilian Alber from Aignostics
Today, I am joined by Maximilian Alber, Co-founder and CTO of Aignostics, to talk about pathology for precision medicine. You’ll learn about Aignostics’s mission, how they are impacting healthcare, and the transformative power of foundational models. Max explains how Aignostics is driven by the belief that machine learning and data science will help improve healthcare before expanding on the role of foundational models. He describes how they built their foundational model, what sets it apart from other models, and why diversity in their datasets is key. He also breaks down how foundational models have allowed them to develop other models more quickly and better navigate explainability with concepts that are challenging for machine learning. We wrap up with Max’s advice for leaders of other AI-powered startups and where he expects Aignostics will be in the next five years. Tune in now to learn all about foundational models and the innovative work being done at Aignostics!
Key Points:
- Insight into Max’s role at Aignostics and how the company is impacting healthcare.
- How they use machine learning to set themselves apart from their competitors.
- A rundown of their models and datasets.
- The definition of a foundation model and how Aignostics built theirs.
- How to use foundation models as a starting point for building machine learning applications.
- What sets Aignostics’ foundation model for histopathology apart from other similar models.
- How their foundation model enables them to develop other models more quickly.
- Top lessons Max has learned from developing foundation models.
- How they navigate explainability with concepts that are challenging for machine learning.
- The positive impact that foundational models have had on explainability.
- Recent advancements that Max is excited about as potential use cases for Aignostics.
- Max’s advice to leaders of other AI-powered startups.
- The impact of Aignostics and where he expects it will be in the next three to five years.
Quotes:
“Our mission is to turn biomedical data into insights.” — Maximilian Alber
“Everything we do is driven by the belief that machine learning and data science will help us improve healthcare.” — Maximilian Alber
“A foundation model is a model that can be used as a starting point for building a machine learning application, with the promise that the foundation model already has a great understanding of the domain.” — Maximilian Alber
“We are in active discussions for licensing our foundation model to other companies in order to enable their development as well. [What’s] important here is that we develop our foundation model along regulatory requirements, which will allow it to be used in medical products.” — Maximilian Alber
“One needs to build a technology that either makes a difference in the long run, or one must be able to innovate at a very fast pace.” — Maximilian Alber
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.
Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
Foundation Model Assessment – Foundation models are popping up everywhere – do you need one for your proprietary image dataset? Get a clear perspective on whether you can benefit from a domain-specific foundation model.