Modern Tech Stacks
Deep dives into modern frameworks, libraries, and best practices.
Learn how native video understanding differs from frame-sampling AI methods, why "stitched photo" analysis misses motion and context, and how to choose the right approach for your video AI project.

A clear breakdown of how State-Space Models (SSMs) like Mamba work, how they differ from Transformers, and whether they can realistically replace attention-based AI models in 2026.

Learn what GRPO (Group Relative Policy Optimization) is, how it differs from PPO, and why it powers efficient reasoning models like DeepSeek-R1, with code examples using Hugging Face TRL.

Liquid Neural Networks (LNNs) are continuous-time AI models that keep learning after deployment. Learn how they work, how they differ from regular neural networks, and where they are used.

Learn how LLM gateways protect AI applications from provider outages using automatic failover, retries, and load balancing, with config examples using LiteLLM.

Learn what test-time compute means, how it differs from traditional AI training, and why this shift from memorizing to reasoning is changing the way large language models solve hard problems.
