🤗 Kernels: Major Updates
In our previous post (From Zero to GPU), we introduced the 🤗 Kernels project, which aims at standardizing how custom kernels are packaged, distributed, and consumed. We want the project…
The Powerhouse GPU Revolutionizing Deep Learning
Introduction The rise of Large Language Models (LLMs) has marked a significant advancement in the era of Artificial Intelligence (AI). During this period, Cloud Graphic Processing Units (GPUs) offered by…
Handling Class Imbalance in ML: Better Alternatives to SMOTE
Most real-world classification problems are imbalanced. Fraud, disease, churn, and defects are rare by nature. Standard classifiers chase accuracy, so they quietly ignore the very class you care about. For…
10 Probability Concepts for Machine Learning Explained Simply
 # Introduction to Probability Concepts  For a long time I treated probability as the vegetables of machine learning. The boring stuff you choke down before you get to the good…
NVIDIA BioNeMo Agent Toolkit Brings Accelerated AI to Life Sciences Researchers in Claude Science
Life sciences has entered an era of computational scale, and for more than a decade, NVIDIA has built the full GPU-accelerated computing stack — spanning hardware, frameworks, libraries, models, microservices…
Context Windows Are Not Memory: What AI Agent Developers Need to Understand
In this article, you will learn why a large context window is not the same thing as agent memory, and how techniques like retrieval, compression, and summarization fit together in…
Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work
I’ve worked on, conversation state tends to grow quickly over time. It’s common to resend large portions of the history on each turn—including older tool outputs, repeated RAG retrievals, and…
Mira Murati’s Thinking Machines Lab Makes The Technical Case For Human-Centered AI Built On Customizable Model Weights
Thinking Machines Lab published a report to build AI that extends human will and judgment. Most AI in use today is trained in a handful of places, then frozen. The…
PRX Part 4: Our Data Strategy
Welcome back! This is Part 4 of the PRX series. Parts 1 to 3 covered model architectures, training design, and a 24-hour speedrun. This time we’re pulling back the curtain…
FLUX Image Generation with DigitalOcean
We have talked a lot about the capabilities and potential of Deep Learning Image Generation here on the Paperspace by DigitalOcean Blog. Not only are image generation tools fun and…
