A discovery call with a global specialty chemicals company revealed that the real AI bottleneck isn't models â it's data. Here's what enterprise chemistry teams actually need versus what the hype promises.
What TFLOPS actually measures, why FP16 matters for LLMs, and why the most important GPU bottleneck for inference isn't compute at all.
A practical walkthrough of how large language models are aligned with human values â from collecting feedback to PPO optimization and the reward hacking pitfalls.
Understand how LLM fine-tuning works, when to use it, and how to choose between full fine-tuning, LoRA, soft prompts, and other PEFT methods.
Building a production forecasting application without the complexity of traditional ML model training and feature engineering.