EP 266: Stop making these 7 Large Language Model mistakes. Best practices for ChatGPT, Gemini, Claude and others

In today's episode, we're diving into the 7 most common mistakes people make while using large language models like ChatGPT. Newsletter (and today's click to win giveaway): Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIRelated Episodes:Ep 260: A new SORA competitor, NVIDIA’s $700M acquisition – AI News That MattersEp 181: New York Times vs. OpenAI – The huge AI implications no one is talking aboutEp 258: Will AI Take Our Jobs? Our answer might surprise you.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [email protected] with Jordan on LinkedInTopics 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:00:00 ChatGPT.com now the focal point for OpenAI.04:58 Microsoft developing large in-house AI model.09:07 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trained with fresh, quality data crucial.10:30 Daily use of large language models poses risks.14:59 Free chat GPT has outdated knowledge cutoff.18:20 Microsoft is the largest by market cap.21:52 Ensure thorough investigation; models have context limitations.26:01 Spread, repeat, and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.38:53 Future work: leverage language models, prompt constantly.40:47 Please rate, share, check out youreverydayai.com.Keywords:Large language models, training data, outdated information, knowledge cutoffs, OpenAI's GPT 4, Anthropics Claude Opus, Google's Gemini, free version of Chat GPT, Internet connectivity, generative AI,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chatbot model, Microsoft's MAI 1, common mistakes with large language models, offline vs online GPT, Google Gemini's outdated information, memory management, context window, unreliable screenshots, public URL verification, New York Times, AI infrastructure.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist.