Tag: ChatGPT

Abstract home lab operations wall showing separate workflow lanes for AI managers and operator approval.

Smaller Keys, Clearer Lanes: How I Split Work Across My AI Managers

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HGG682 was the first time my AI operations model started to feel less like an experiment and more like a production workflow. ChatGPT helped shape the writing, OpenClaw handled the guarded WordPress work, Hermes managed the YouTube side, and I stayed in the approval and publishing seat. It was not one AI assistant doing everything. It was a set of narrower managers working in clearer lanes.

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LEPRO Lights Revisited, DIY Storm Guard and Safer AI Agents – HGG683

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Jim revisits the LEPRO permanent outdoor lights after six months, then walks through two OpenClaw projects in depth: a DIY Home Assistant Storm Guard for EcoFlow and BLUETTI batteries — tested during a real severe-weather event — and an Amazon Affiliate Manager for TheAverageGuy.tv. He shares what he has learned about AI agent authority, batch… Click for more / Podcast Player>
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Should You Trust OpenClaw on Your Network? with Christian Johnson – HGG676

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What happens when a practical conversation about AI tools turns into a deeper discussion about autonomy, cybersecurity, local models, and the future of the internet? This week, Christian Johnson joins me to talk about OpenClaw, the rapid rise of open-source AI agents, and why this new generation of tools feels very different from traditional chat-based… Click for more / Podcast Player>
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From Ice Fishing to Home Labs: Catching up with Mike Wieger – HGG637

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Mike Wieger joins me this week. We explore tech gadgets and personal experiences together, starting with a light-hearted chat about Nebraska's cold weather. Mike shares updates on his board game development challenges and growing passion for ice fishing, discussing how technology enhances the experience. We catch up on setting up home servers, focusing on Unraid… Click for more / Podcast Player>
natural language processing, ChatGPT, machine learning, AI, language models, chatbots, deep learning, neural networks.

The Evolution of ChatGPT: A Comparison of v3.5 and v4 for the Average Guy

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First, let’s start with some background. ChatGPT is a large language model developed by OpenAI, based on the GPT-3.5 architecture. It is designed to generate human-like responses to text-based prompts, and it has been used for a variety of applications, including chatbots, question-answering systems, and language translation. Now, the latest version, ChatGPT v4, builds upon the foundation of v3.5 and includes a number of improvements and upgrades. One of the most significant changes is the increase in the number of parameters, from 175 billion in v3.5 to 6 trillion in v4. This increase in parameters allows ChatGPT v4 to generate

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