SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign
Apple Machine Learningen
Apple Machine Learning
AI Global WireProteins are fundamental to biological processes, with their function determined by the complex interplay between the amino acid sequence and the three-dimensional structure. Developing generative models capable of understanding this intrinsically multi-modal relationship is crucial for fields like drug discovery and protein engineering. Existing models often rely on a multi-stage training process where autoencoders that tokenize data into latent representations are trained in a first stage. Secondly, a generative model is trained on the latent representation of the autoencoder(s), i.e…
This is a short summary published by AI Global Wire. The full article is owned and hosted by Apple Machine Learning — open it there to read it in full.
Read the full story at Apple Machine LearningRelated AI news
- DiscoSign: Discourse-Aware Text to Sign Language Gloss TranslationApple Machine Learning · September 11, 2026
- ToolGrad: Efficient tool-use dataset generation with textual "gradients"Google Research · September 10, 2026
- DeepSeek AI Released DeepSeek-V4.1-Flash with 1M Context, FP4 KV Cache, and Cross-Layer Attention ReuseMarkTechPost · September 10, 2026
- Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic TasksarXiv cs.AI · September 10, 2026
- ContractEval: Query-Conditioned Execution Matching for Procedural Instruction ConformancearXiv cs.AI · September 10, 2026
- Decision Shifts, Lost Label Functionality, and an Inconclusive Grounding Audit in Correctness-Gated Multi-Teacher DistillationarXiv cs.AI · September 10, 2026