Bridging The Gap Between Machine Learning and the Life Sciences with Artur Yakimovich - #411
Published:Sep 21, 2020 18:43
•1 min read
•Practical AI
Analysis
This article from Practical AI features an interview with Artur Yakimovich, focusing on the intersection of machine learning and life sciences. It highlights the challenges of bridging the gap between life science researchers and computer science tools. Yakimovich's transition from viral chemistry to computational biology is discussed, along with his application of deep learning and neural networks to research. The article also emphasizes his efforts in building the Artificial Intelligence for Life Sciences community, a non-profit aimed at fostering interdisciplinary collaboration. The interview provides insights into the practical applications of AI in the life sciences and the importance of community building.
Key Takeaways
- •The article highlights the challenges of integrating AI tools in life sciences research.
- •Artur Yakimovich's work focuses on applying deep learning to biological problems.
- •The Artificial Intelligence for Life Sciences community aims to foster collaboration between different scientific fields.
Reference
“We explore the gulf that exists between life science researchers and the tools and applications used by computer scientists.”