EP 348: Large Language Model Best Practices - 7 mistakes to fix
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Win a free year of ChatGPT or other prizes! Find out how.)In today's episode, we're diving into the 7 most common mistakes people make while using large language models like ChatGPT.Newsletter: Sign up for our free daily newsletter)**More on this Episode: **Episode Page)**Join the discussion: **Ask Jordan questions on AI))Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup)Website: YourEverydayAI.com)Email The Show: [email protected])**Connect with Jordan on **LinkedIn)**Topics Covered in This Episode:1. Understanding the Evolution of Large Language Models2. Connectivity: A Major Player in Model Accuracy3. The Generative Nature of Large Language Models4. Perfecting the Art of Prompt Engineering5. The Seven Roadblocks in the Effective Use of Large Language Models6. Authenticity Assurance in Large Language Model Usage7. The Future of Large Language ModelsTimestamps:**02:30 LLM knowledge cut-off09:07 Models trained with fresh, quality data crucial.10:30 Daily use of large language models poses risks.14:59 Free chat GPT has outdated knowledge cutoff.18:20 Microsoft is the largest by market cap.21:52 Ensure thorough investigation; models have context limitations.26:01 Spread, repeat, and earn with simple actions.29:21 Tokenization, models use context, generative large language models.33:07 More input means better output, mathematically proven.36:13 Large language models are essential for business survival.**Keywords:**Large language models, training data, outdated information, knowledge cutoffs, OpenAI's GPT 4, Anthropics Claude Opus, Google's Gemini, free version of Chat GPT, Internet connectivity, generative AI, varying responses, Jordan Wilson, prompt engineering, copy and paste prompts, zero shot prompting, few shot prompting, Microsoft Copilot, Apple's AI chips, OpenAI's search engine, GPT-2 chatbot model, Microsoft's MAI 1, common mistakes with large language models, offline vs online GPT, Google Gemini's outdated information, memory management, context window, unreliable screenshots, public URL verification, New York Times, AI infrastructure.