A technical guide on using an LLM (Platypus2) with LangChain and pgvector to analyze YouTube's Procella database paper.
A guide to using GPTQ quantization with Hugging Face Optimum to compress open-source LLMs for efficient deployment on smaller hardware.
A critical analysis of the machine learning bubble, arguing its lasting impact will be a proliferation of low-quality, automated content and services, not true AGI.
A developer's weekly learning log covering Power BI data refresh, LLM architectures, Azure OpenAI costs, AI news, Python in Excel, and Azure SQL updates.
A guide to participating in the NeurIPS 2023 LLM Efficiency Challenge, focusing on efficient fine-tuning of large language models on a single GPU.
Introduces EasyLLM, an open-source Python package for streamlining work with open large language models via OpenAI-compatible clients.
A developer shares two summer side projects: an academic paper digest app and a movie selection tool for groups, built to solve personal problems.
Weekly tech digest covering Azure OpenAI architecture, vector databases, AI anomaly detection, and an LLM self-cloning article.
A practical guide outlining seven key patterns for integrating Large Language Models (LLMs) into robust, production-ready systems and products.
Weekly tech roundup covering major Microsoft AI announcements: Bing Chat Enterprise, Microsoft 365 Copilot pricing, Azure AI updates, and new LLM architectures.
A guide on configuring LangChain to connect to and use Azure OpenAI services in Python, covering setup, authentication, and examples.
An overview of LLM-powered autonomous agents, covering their core components like planning, memory, and tool use for complex problem-solving.
A guide to running open-source Large Language Models (LLMs) like LLaMA locally on your CPU using C# and the LLamaSharp library.
A guide to efficiently finetuning Falcon LLMs using parameter-efficient methods like LoRA and adapters to reduce compute costs.
Explores the potential and implications of using AI to automate mathematical theorem proving, framing it as a 'tame' problem solvable by machines.
An AI-generated, alliterative rewrite of Genesis 1 where every word starts with the letter 'A', created using GPT-4.
Explains the intuition behind the Attention mechanism and Transformer architecture, focusing on solving issues in machine translation and language modeling.
Explores user interfaces for LLMs that minimize text chat, using clicks and user context for more intuitive interactions.
The article distinguishes between interactive and transactional prompting, arguing that prompt engineering is most valuable for transactional, objective tasks with LLMs.
A developer explores running LLMs on a Raspberry Pi Pico with memory constraints, creating a witty e-ink display that generates content from news feeds.
