Learn how watsonx helps you utilize AI → https://ibm.biz/BdMpXV

The recent interest in AI as meant a lot of people have been encountering new vocabulary. Martin Keen is to help you sort it out. This video runs through key terms like machine learning, deep learning, foundation models, and large language models and how they're related to each other.

While much of the world is focused on large language models, our Salesforce AI Research teams are looking at smaller models that offer unique advantages in speed, cost, and accessibility. In this episode, learn what Small Language Models are, how they work and how they can be used for task-specific situations like personal agents on wearable devices like smart watches and robotics.

Learn more about Agentforce: https://www.salesforce.com/agentforce/
Learn more about AI Agents: https://www.salesforce.com/agentforce/ai-agents/

The AI Research Lab - Explained gives you a sneak peak of cutting-edge AI techniques developed by Salesforce’s very own AI Research group. Along the way, we’ll demystify complex concepts and share real-world insights—all from the forefront of research.

#Salesforce #Agentforce

Subscribe to Salesforce’s YouTube Channel: http://bit.ly/SalesforceSubscribe

Learn more about Salesforce: https://www.salesforce.com
Facebook: https://www.facebook.com/salesforce
Twitter: https://www.twitter.com/salesforce
Instagram: https://www.instagram.com/salesforce
LinkedIn: https://www.linkedin.com/company/salesforce

About Salesforce:
Improve customer relationships with Salesforce, the #1 AI CRM where humans with agents drive customer success together. Our integrated platform pairs your unified customer data with trusted agents that can assist, take action autonomously, and hand off seamlessly to your employees in sales, service, marketing, commerce, and more.

Disclaimer: This video is for demonstration purposes only. All account data depicted is fictional and does not contain personally identifiable information (PII). This content is intended solely to illustrate product functionality in a simulated environment.

🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6

Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs.

🎯 What You'll Learn:
• AI Fundamentals - LLMs, tokens, embeddings, and context windows
• LangChain - Simplify AI development with pre-built components
• Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques
• Vector Databases - Semantic search with ChromaDB and Pinecone
• RAG (Retrieval Augmented Generation) - Build intelligent document search
• LangGraph - Create multi-step AI workflows and agents
• MCP (Model Context Protocol) - Connect AI to external tools

🔧 Hands-On Labs Include:
✓ Making your first OpenAI API calls
✓ Building semantic search engines
✓ Creating RAG systems for document retrieval
✓ Developing multi-agent workflows
✓ Integrating external tools with MCP

Perfect for developers, data scientists, and anyone wanting to understand modern AI development. Follow along with free labs and build a real-world AI assistant that searches 500GB of documents in under 30 seconds.

🚨Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX

⏰ TIMESTAMPS:
00:00 - Introduction to AI Agents
00:40 - How LLMs work in real time?
04:56 - Embeddings & Vector Representations
05:56 - How LangChain works?
10:12 - Practice Labs - Your First AI API Call
14:57 - Practice Labs - LangChain
17:57 - Prompt Engineering Techniques
21:21 - Practice Labs - Master Prompt Engineering
24:46 - Vector Databases Deep Dive
31:27 - Practice Labs - Build Semantic Search Engine
35:15 - RAG (Retrieval Augmented Generation)
38:14 - Practice Labs - RAG Implementation
42:14 - LangGraph for AI Workflows
45:51 - Practice Labs - Build Stateful AI Workflow
48:51 - Model Context Protocol (MCP)
51:56 - Practice Labs - Advanced MCP Concepts
55:21 - Conclusion

🔔 Subscribe to KodeKloud for more AI development tools and tutorials!

#AiAgents #AI #Aifundamentals #LangChain #MCP #LLMs #RAG #Langgraph #vectordb #promptengineering #VectorDatabases #Tutorial #kodekloud

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

December 5, 2025
This lecture covers:
• Recap
• Trending topics
• Closing thoughts

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:01:12 Transformer
00:06:35 Transformer-based models & tricks
00:11:17 Large Language Models
00:15:05 LLM training
00:24:09 LLM tuning
00:29:41 LLM reasoning
00:38:37 Agentic LLMs (RAG, tool calling)
00:44:09 LLM evaluation
00:48:57 Vision Transformer
01:04:02 Diffusion-based LLMs
01:23:38 Closing thoughts
01:50:16 Thank you!

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

View the course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

This is a complete course on learning Generative ai and agentic with Langchain and Langgraph. We have included all the topics from RAG, vectorless rag, Deep agents, Guardrails, LLM Evaluation and LLM Gateways Techniques
Github Links
Langchain : https://github.com/krishnaik06..../Langchain-V1-Crash-
Langgraph: https://github.com/krishnaik06..../Agentic-LanggraphCr
RAG: https://github.com/krishnaik06/RAG-Tutorials
Vectorless RAG: https://github.com/krishnaik06/RAG-Tutorials/blob/main/PageIndex_Vectorless_RAG_CrashCourse%20(1).ipynb
Deep Agents: https://drive.google.com/file/....d/1SVjvgqvKfF-FPAIqp
Guardrails : https://github.com/krishnaik06..../Langchain-V1-Crash-/blob/main/updatedlangchain/langchain_guardrails_crash_course.ipynb
LLM Evals : https://github.com/krishnaik06/RAG-Tutorials/blob/main/1-rag_evaluation.ipynb
LLM Gateways: https://github.com/krishnaik06..../Langchain-V1-Crash-/blob/main/llm_gateway_tutorial.ipynb

Timestamp
00:00:00 Introduction
00:02:31 Langchain Course
02:35:12 Langraph Course
05:02:29 RAG Course
07:10:43 Vectorless RAG
08:02:11 Deep Agents
08:45:43 Guardrails
09:22:55 LLM Evaluation
10:30:25 LLM Gateways
-------------------------------------------------------------------
Learn from us visit https://krishnaik.in/liveclasses