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How does Prompt Chaining work?
Prompt Chaining breaks one big task into smaller prompts, where the output of one prompt becomes the input of the next. It solves bigger tasks reliably.
How does PyTorch work?
PyTorch is an open-source library to build and train machine learning models. It uses tensors, a computation graph, and autograd, and runs fast on the GPU.
How does Semantic Caching work?
Semantic Caching is a cache that matches questions by their meaning instead of their exact words, so an AI app can reuse past answers for similar questions.
How does Hybrid Search work?
Hybrid Search combines keyword search and semantic search, and merges their results into one final ranked list, so that we get the best of both.
How does HyDE work in RAG?
HyDE (Hypothetical Document Embeddings) is a RAG technique where the AI first writes a fake answer to the question, and then we search using that fake answer.
Prefill vs Decode: LLM Inference Optimization
Prefill reads the whole prompt in one pass and produces the first token, whereas Decode generates the rest of the tokens one at a time using the KV cache.
How does a GPU work for Deep Learning?
A GPU is a chip that does a huge number of simple calculations at the same time. Deep learning is mostly matrix multiplication, so GPUs make it very fast.
How does LangGraph work?
LangGraph is a framework to build LLM applications where the work is organized as a graph of steps, with nodes, edges, and a shared state.
How does LangChain work?
LangChain is a framework that helps us build LLM applications by connecting the LLM with our data, tools, and logic through chains, memory, and agents.