ChatGPT

How I Created a Custom ChatGPT Trained on the CXL Specification Documents

If you’re working with Compute Express Link (CXL) and wish you had an AI assistant trained on all the different versions of the specification—1.0, 1.1, 2.0, 3.0, 3.1… you’re in luck.

Whether you’re a CXL device vendor, a firmware engineer, a Linux Kernel developer, a memory subsystem architect, a hardware validation engineer, or even an application developer working on CXL tools and utilities, chances are you’ve had to reference the CXL spec at some point. And if you have, you already know: these documents are dense, extremely technical, and constantly evolving.

I Turned Myself Into an Action Figure

Part of being in tech, especially in emerging memory technology, is constantly switching between the serious and the surreal. One day you’re in kernel debug mode, the next you’re explaining complex system architectures on a whiteboard, and then suddenly you’re jumping on the latest craze such as making yourself into an action figure.

It’s fun. It’s human. And honestly? It’s a reminder not to take yourself too seriously. (Even if your job title suggests differently)

Running Open WebUI and Ollama on Ubuntu 22.04 for a Local ChatGPT Experience

Introduction

Open WebUI and Ollama are powerful tools that allow you to create a local chat experience using GPT models. Whether you’re experimenting with natural language understanding or building your own conversational AI, these tools provide a user-friendly interface for interacting with language models. In this guide, we’ll walk you through the installation process step by step.

Ollama is a cutting-edge platform designed to run open-source large language models locally on your machine. It simplifies the complexities involved in deploying and managing these models, making it an attractive choice for researchers, developers, and anyone who wants to experiment with language models1. Ollama provides a user-friendly interface for running large language models (LLMs) locally, specifically on MacOS and Linux (with Windows support on the horizon).

An Introduction to Generative Prompt Engineeering

Introduction

Over the past few years, there has been a significant explosion in the use and development of large language models (LLMs). An LLM is a language model consisting of a neural network with many parameters (commonly multi-billions of weights), trained on large quantities of text. Some of the most popular large language models are: GPT-3 (Generative Pretrained Transformer 3) – developed by OpenAI ; BERT (Bidirectional Encoder Representations from Transformers) – developed by Google; RoBERTa (Robustly Optimized BERT Approach) – developed by Facebook AI; T5 (Text-to-Text Transfer Transformer) – developed by Google. Many others exist and continue to emerge. These language models are designed to understand and generate natural language text, allowing for a wide range of applications such as chatbots, content creation, language translation, and more.