by CPI Staff | Sep 15, 2025 | AI, Blog, LLM, PyTorch
In this blog post Best Practices for Loading and Saving PyTorch Weights in Production we will map out the practical ways to persist and restore your models without surprises. Whether you build models or manage teams shipping them, understanding how PyTorch saves...
by CPI Staff | Sep 15, 2025 | AI, Blog, LLM
In this blog post Practical ways to fine-tune LLMs and choosing the right method we will walk through what fine-tuning is, when you should do it, the most useful types of fine-tuning, and a practical path to ship results. Large language models are astonishingly...
by CPI Staff | Sep 15, 2025 | AI, Blog, LLM, RAG
In this blog post Use Text2Cypher with RAG for dependable graph-based answers today we will show how to turn natural-language questions into precise Cypher queries and reliable answers over your graph data. Before diving into code, let’s clarify the idea. Text2Cypher...
by CPI Staff | Sep 15, 2025 | Blog, LLM, RAG
In this blog post Architecture of RAG Building Reliable Retrieval Augmented AI we will unpack how Retrieval Augmented Generation works, what to build first, and how to run it reliably in production. Retrieval Augmented Generation (RAG) combines a large language model...
by CPI Staff | Aug 29, 2025 | AI, Blog, LLM
In this blog post Step-back prompting explained and why it beats zero-shot for LLMs we will explore a simple technique that reliably improves reasoning quality from large language models (LLMs) without adding new tools or data. At a high level, step-back prompting...
by CPI Staff | Aug 27, 2025 | AI, Blog, LLM
In this post “What Are Tensors in AI and Large Language Models (LLMs)?”, we’ll explore what tensors are, how they are used in AI and LLMs, and why they matter for organizations looking to leverage machine learning effectively. Artificial Intelligence (AI)...
