Understanding LLM Poisoning
Discover how LLM poisoning works, why even 0.01% poisoned data can compromise AI systems, and the steps to prevent backdoor attacks in models.
How to Choose the Right GPU for vLLM Inference
Size and configure GPUs for vLLM inference. Master memory requirements, KV cache, quantization, and tensor parallelism for LLM deployment.
Writing ResNet from Scratch in PyTorch
In this continuation on our series of writing DL models from scratch with PyTorch, we learn how to create, train, and evaluate a ResNet neural network for CIFAR-100 image classification.
Next Generation AI Development with the AMD MI300X
In this tutorial, we discuss the effectiveness of AMD GPUs for Deep Learning tasks. In particular, we focus on the powerful MI300X, now available for the cloud provider’s GPU Droplets, examine the specs of these potent machines in depth.
Understanding the BART Model for Accurate Text Summarization
Explore BART (Bidirectional and Auto-Regressive Transformers), a powerful seq2seq model for NLP tasks like text summarization and generation.
Learn How to Build a RAG Application using GPU Droplets
Learn how to create a Retrieval-Augmented Generation (RAG) application using the cloud provider’s GPU Droplets.
What’s New with Claude Sonnet 4.6
‘In this tutorial, we examine the powerful, new Claude Sonnet 4.6 model, and show how you can access Sonnet 4.6 today with Gradient!’
Create and Implement Data Secure AI Workflows
Learn how to build secure AI workflows with added protections to prevent attacks, data leaks, and meet compliance requirements like HIPAA, COPPA, and GDPR.
Devstral: An Open-Source Agentic LLM for Software Engineering
‘An overview and implementation details of Devstral, a 24B parameter agentic LLM excelling in software engineering tasks.’
Expert Parallelism: Scaling Mixture-of-Experts Models
Learn how Expert Parallelism boosts Mixture-of-Experts model efficiency and GPU scalability for faster, more optimized large-scale deep learning training.
