Deeplearning

Optimize, deploy, and benchmark an open-source LLM with vLLM.

What the DeepLearning.AI vLLM course teaches: optimizing, deploying, and benchmarking LLM inference with LLM Compressor quantization, GuideLLM, KV cache sizing,

Build and train a 20M-parameter LLM from scratch using JAX, the open-source library behind Google's Gemini, and learn the core techniques powering modern AI development.

Connect agents across different frameworks and teams using A2A, the open protocol standardizing agent-to-agent communication.

Build real-world applications from the command line using Gemini CLI, Google's open-source agentic coding assistant that coordinates local tools and cloud services to automate coding and creative workflows.

The Batch AI News and Insights: Many people are fighting the growth of data centers because they could increase CO2 emissions, electricity prices...

The Batch AI News and Insights: As amazing as LLMs are, improving their knowledge today involves a more piecemeal process than is widely...

Build AI agents that write and execute code to accomplish tasks, running safely in sandboxed cloud environments that protect your systems from untrusted code.