Noah Weber
Geometric deep learning for drug discovery
#1about 2 minutes
Why many common diseases remain untreatable
Over 80% of pathogenic proteins are considered 'undruggable' because traditional inhibition methods are ineffective for them.
#2about 4 minutes
Introducing targeted protein degradation technology
This biotechnology shifts the paradigm from inhibiting symptoms to eliminating the cause of disease by degrading pathogenic proteins.
#3about 7 minutes
Using geometric deep learning for molecular data
Graphs provide a native, non-Euclidean way to represent complex molecular structures and interactions, which is essential for effective machine learning models.
#4about 11 minutes
An overview of the AI drug discovery pipeline
The process involves predicting protein-ligand interactions, generating molecular conformations, and using Bayesian optimization to find optimal candidates.
#5about 1 minute
Optimizing molecular poses with a fitness function
Bayesian optimization and active learning are used to efficiently search the high-dimensional space of molecular rotations and translations to find the best interaction.
#6about 3 minutes
Generating novel molecules with generative models
Generative models create entirely new linker molecules de novo, optimizing for properties like low toxicity and minimal energy during generation.
#7about 3 minutes
Building a cloud architecture for large-scale ML
A custom cloud architecture using AWS spot instances and persistent storage is necessary to handle the immense computational cost of geometric deep learning.
#8about 3 minutes
The key enablers for AI-driven drug discovery
Success requires a combination of high-quality data, advanced algorithms like geometric deep learning, cloud computing power, and an interdisciplinary team of domain experts.
#9about 9 minutes
Q&A on team collaboration and technical choices
The discussion covers the challenges of communication in interdisciplinary teams, the rationale for a multi-cloud strategy, and specific technical questions about the models.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
01:57 MIN
The future of ML in quantum computing and biology
Getting Started with Machine Learning
Unlock full access
Log in or set up an account to access this feature and more.
05:05 MIN
Inspiring real-world applications of AI and machine learning
Machine Learning for Software Developers (and Knitters)
Unlock full access
Log in or set up an account to access this feature and more.
03:46 MIN
Transforming healthcare with predictive diagnostics and regeneration
AI is the Future of Accessibility - Karl Groves
Unlock full access
Log in or set up an account to access this feature and more.
00:56 MIN
Empowering engineers with accessible machine learning tools
Solving the puzzle: Leveraging machine learning for effective root cause analysis
Unlock full access
Log in or set up an account to access this feature and more.
00:51 MIN
Using AI for deeper and holistic data analysis
Valven Atlas: Engineering Intelligence That Delivers
Unlock full access
Log in or set up an account to access this feature and more.
01:11 MIN
Advancing AI with specialized open source projects
Harnessing the Power of Open Source's Newest Technologies
Unlock full access
Log in or set up an account to access this feature and more.
15:40 MIN
Q&A on graph databases for cybersecurity
Cyber Sleuth: Finding Hidden Connections in Cyber Data
Unlock full access
Log in or set up an account to access this feature and more.
02:02 MIN
The challenge of analyzing terabyte-scale microscopy data
Using Containers to deploy AI Models across our microscopy platform
Unlock full access
Log in or set up an account to access this feature and more.
Featured Partners
Related Videos
Getting Started with Machine Learning
Alexandra Waldherr
What comes after ChatGPT? Vector Databases - the Simple and powerful future of ML?
Erik Bamberg
Building Products in the era of GenAI
Julian Joseph
Debugging Machine Learning Code
Svetlin Penkov
The pitfalls of Deep Learning - When Neural Networks are not the solution
Adrian Spataru & Bohdan Andrusyak
Multimodal Generative AI Demystified
Ekaterina Sirazitdinova
How Machine Learning is turning the Automotive Industry upside down
Jan Zawadzki
Data Science in Retail
Julian Joseph
Related Articles
View all articles



From learning to earning
Jobs that call for the skills explored in this talk.



Neural Concept
Lausanne, Switzerland
DevOps
Continuous Integration

Nomitri
Berlin, Germany
DevOps
Gitlab
Docker
Ansible
Grafana
+6


Proclinical Limited
NumPy
Pandas
PyTorch
Core Data
Tensorflow
+1



Mindpeak
Hamburg, Germany
Intermediate
Linux
Docker
TypeScript
Machine Learning