In this video I look at the foundations of generative AI and then provide guidance on which AI technology applies best to different use cases.

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▬▬▬▬▬▬ C H A P T E R S ⏰ ▬▬▬▬▬▬
00:00 - Introduction
00:29 - What is AI
01:59 - Generative AI
03:33 - GPT and the model
06:12 - Why don't I always use the newest
07:42 - How models are created
14:57 - Gaps to be really useful
18:42 - Solving the gaps
23:11 - How we use GPT
25:37 - Copilots
26:41 - GitHub Copilot
29:38 - Microsoft product copilots
33:39 - Data governance considerations
37:01 - Bing Chat
37:36 - Copilot Studio
40:00 - Custom copilot
42:16 - Topics
44:13 - Generative AI
44:33 - Adding custom data
48:32 - Actions
52:37 - Entities
52:49 - Publish
54:28 - Licensing
55:14 - Extend first-party copilot
56:26 - Pro-code with Azure AI Studio
1:04:56 - Orchestrators
1:06:34 - LangChain
1:10:08 - Semantic Kernel
1:12:32 - AutoGen
1:13:37 - Windows AI Studio
1:14:46 - Summary

▬▬▬▬▬▬ K E Y L I N K S 🔗 ▬▬▬▬▬▬
► Whiteboard:
🔗 https://github.com/johnthebrit/Random...
► Key complementary videos:
📽️ Use your own data -    • Using Your Own Data with Large Langua...  
📽️ RAG -    • RAG, semantic search, embedding, vect...  
► Tokenizer
🔗 https://platform.openai.com/tokenizer
► Microsoft Copilot
🔗 https://copilot.microsoft.com/
► Copilot Studio
🔗 https://copilotstudio.microsoft.com/
► Azure AI Studio
🔗 https://ai.azure.com/
► Azure OpenAI Studio
🔗 https://oai.azure.com

▬▬▬▬▬▬ Want to learn more? 🚀 ▬▬▬▬▬▬
📖 Recommended Learning Path for Azure
🔗 https://learn.onboardtoazure.com
🥇 Certification Content Repository
🔗 https://github.com/johnthebrit/Certif...
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🎓 Certification Cram Videos
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