Artificial Intelligence with Python: Libraries, Uses and Tools
Discover how to use Python for AI: libraries, examples, tools and real applications explained clearly and in depth.
Pytorch
AI Hallucinations: Why Smart Models Still Make Things Up
Discover why AI hallucinations happen, real examples, their risks and the best current techniques to detect and reduce them.
Open‑Source Language Model Evaluation Platforms Explained
Discover the key open‑source and enterprise platforms to evaluate, monitor and govern modern language models and LLM agents.
How to Host Language Models on a Low Budget
Learn how to host powerful language models on a tight budget, comparing APIs, cloud GPUs and local setups to cut costs without losing performance.
Google teams up with Meta’s PyTorch to challenge Nvidia’s AI dominance
Google boosts PyTorch support on TPUs with TorchTPU and a Meta alliance, seeking to loosen Nvidia’s grip on the AI computing market.
Sesgo y varianza en aprendizaje automático: guía completa y práctica
Qué son sesgo y varianza, su descomposición, ejemplos, k-NN, regularización y equidad. Aprende a equilibrarlos y a medirlos con rigor.
Overfitting vs Underfitting: guía completa con señales, causas y soluciones
Overfitting vs underfitting en ML: señales, causas y técnicas para evitarlos. Ejemplos claros y consejos prácticos para mejorar tus modelos.
PyTorch enters a new phase as Soumith Chintala joins Thinking Machines and education efforts ramp up
Soumith Chintala joins Thinking Machines as PyTorch grows in industry and education, including a new Coursera certificate. Latest updates and context.
La trampa de dependencia de los LLM: límites, sesgos y riesgos
¿Son los LLM una trampa de dependencia? Datos, sesgos, costes y estudios que revelan sus límites y riesgos para educación y sociedad.