Practical AI One algorithm to rule them all?
Feb 15, 2022
Exciting advancements in AI take center stage as researchers harness deep learning to predict protein interactions. The conversation shifts to cutting-edge self-supervised algorithms at Facebook, which unify tasks across speech, vision, and text. Ethical implications of AI in robotic surgeries spark debate, alongside reflections on the evolution of human-machine collaboration. The hosts explore the creative limits of narrow AI, drawing parallels with Tolkien's work, and promote engaging resources for mastering machine learning fundamentals.
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Protein Attachment and AI
- COVID-19 antibodies attaching to virus spike proteins illustrate protein binding's importance.
- AI accelerates drug and vaccine development by quickly predicting protein interactions.
3D Graphs for Protein Structures
- This protein-attaching model uses 3D graphs of protein structures, processed by a neural network.
- This reflects the growing trend of using graph-structured data in AI.
Data2vec: Multi-Modality Embeddings
- Meta AI's data2vec creates vector representations from various data types (images, speech, text).
- This contrasts with single-modality models and may improve performance across modalities.
