Artwork

Innhold levert av Everyday AI. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Everyday AI eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
Player FM - Podcast-app
Gå frakoblet med Player FM -appen!

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

43:24
 
Del
 

Manage episode 416961367 series 3470198
Innhold levert av Everyday AI. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Everyday AI eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Send Everyday AI and Jordan a text message

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 newsletter
More on this Episode: Episode Page
Join the discussion: Ask Jordan questions on AI
Related Episodes:
Ep 260: A new SORA competitor, NVIDIA’s $700M acquisition – AI News That Matters
Ep 181: New York Times vs. OpenAI – The huge AI implications no one is talking about
Ep 258: Will AI Take Our Jobs? Our answer might surprise you.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn
Topics Covered in This Episode:
1. Understanding the Evolution of Large Language Models

2. Connectivity: A Major Player in Model Accuracy

3. The Generative Nature of Large Language Models

4. Perfecting the Art of Prompt Engineering

5. The Seven Roadblocks in the Effective Use of Large Language Models

6. Authenticity Assurance in Large Language Model Usage

7. The Future of Large Language Models

Timestamps:
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14:59 Free chat GPT has outdated knowledge cutoff.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 verificat

Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

  continue reading

308 episoder

Artwork
iconDel
 
Manage episode 416961367 series 3470198
Innhold levert av Everyday AI. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Everyday AI eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Send Everyday AI and Jordan a text message

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 newsletter
More on this Episode: Episode Page
Join the discussion: Ask Jordan questions on AI
Related Episodes:
Ep 260: A new SORA competitor, NVIDIA’s $700M acquisition – AI News That Matters
Ep 181: New York Times vs. OpenAI – The huge AI implications no one is talking about
Ep 258: Will AI Take Our Jobs? Our answer might surprise you.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn
Topics Covered in This Episode:
1. Understanding the Evolution of Large Language Models

2. Connectivity: A Major Player in Model Accuracy

3. The Generative Nature of Large Language Models

4. Perfecting the Art of Prompt Engineering

5. The Seven Roadblocks in the Effective Use of Large Language Models

6. Authenticity Assurance in Large Language Model Usage

7. The Future of Large Language Models

Timestamps:
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 verificat

Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

  continue reading

308 episoder

Όλα τα επεισόδια

×
 
Loading …

Velkommen til Player FM!

Player FM scanner netter for høykvalitets podcaster som du kan nyte nå. Det er den beste podcastappen og fungerer på Android, iPhone og internett. Registrer deg for å synkronisere abonnement på flere enheter.

 

Hurtigreferanseguide

Copyright 2024 | Sitemap | Personvern | Vilkår for bruk | | opphavsrett