Latest bookmarks (page 1 of 2)

"La intérprete, que abandonó la vida pública en 1978 y no volvió a pisar un escenario, sigue lanzando discos, y hasta un vídeo con su imagen reproducida con inteligencia artificial. “Nunca ha tomado decisiones dictadas por otros, o el dinero”, dice su hija"

"El director del Instituto de Biología Tumoral de Hamburgo habla de las posibilidades de la biopsia líquida para detectar el cáncer en etapas tempranas o saber si alguien está curado tras una cirugía "

"La celebración del centenario del autor revela la enorme estatura literaria e intelectual de un hombre que siempre supo decir no ante las grandes líneas rojas"

"A community version of the "common API" for how the GitHub Engineering organization communicates - GitHub - github/how-engineering-communicates: A community version of the "common AP..."

"Completed in 1982 in Dhaka, Bangladesh. Modernist architecture is traditionally understood to be utilitarian, sleek, and most of all without context, such that it can be placed in any..."

"Listen to this episode from The Gradient: Perspectives on AI on Spotify. In episode 92 of The Gradient Podcast, Daniel Bashir speaks to Kevin K. Yang.Kevin is a senior researcher at Microsoft Research (MSR) who works on problems at the intersection of machine learning and biology, with an emphasis on protein engineering. He completed his PhD at Caltech with Frances Arnold on applying machine learning to protein engineering. Before joining MSR, he was a machine learning scientist at Generate Biomedicines, where he used machine learning to optimize proteins.Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pubSubscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (02:40) Kevin’s background* (06:00) Protein engineering early in Kevin’s career* (12:10) From research to real-world proteins: the process* (17:40) Generative models + pretraining for proteins* (22:47) Folding diffusion for protein structure generation* (30:45) Protein evolutionary dynamics and generative models of protein sequences* (40:03) Analogies and disanalogies between protein modeling and language models* (41:45) In representation learning* (45:50) Convolutions vs. transformers and inductive biases* (49:25) Pretraining tasks for protein structure* (51:45) More on representation learning for protein structure* (54:06) Kevin’s thoughts on interpretability in deep learning for protein engineering* (56:50) Multimodality in protein engineering and future directions* (59:14) OutroLinks:* Kevin’s Twitter and homepage* Research* Generative models + pre-training for proteins and chemistry* Broad intro to techniques in the space* Protein structure generation via folding diffusion* Protein sequence design with deep generative models (review)* Evolutionary velocity with protein language models predicts evolutionary dynamics of diverse proteins* Protein generation with evolutionary diffusion: sequence is all you need* ML for protein engineering* ML-guided directed evolution for protein engineering (review)* Learned protein embeddings for ML* Adaptive machine learning for protein engineering (review)* Multimodal deep learning for protein engineering Get full access to The Gradient at thegradientpub.substack.com/subscribe"

"Una nueva herramienta logra por primera vez clasificar los laberínticos ladrillos de la vida en grupos con estructuras similares"

"Artificial intelligence foundation for therapeutic science"

"A from scratch GPU-free introduction to modern machine learning. Many tutorials exist already of course, but this one aims to really explain what is going on, from the ground up. Also, we’ll develop the demo until it is actually useful on real life data which you can supply yourself.
Other documents start out from the (very impressive) PyTorch environment, or they attempt to math it up from first principles. Trying to understand deep learning via PyTorch is like trying to learn aerodynamics from flying an Airbus A380."