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Google just showed how AI engineers are moving from simple "RAG" to "graphs", memory and multimodal agents • 15:32 - setting up the production agent stack • 28:00 - turning disconnected data into a knowledge graph • 41:00 - Graph RAG with semantic + hybrid search • 58:00 -...

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Morlex

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74,134 views • 1 month ago •via X (Twitter)

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Morty

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Google just released a 1-hour course on building agentic knowledge Graphs from scratch: • 00:00 - Introduction to AI agents • 08:09 - Foundations of multi-agent systems • 13:25 - Introduction to Graph engineering • 23:27 - Environment setup for agentic Graphs • 47:43 - Building Graph RAG agents • 1:25:14 - Agent memory bank with graphs Worth more than 10 articles on loop engineering. Watch it today, then read how to become a graph engineer in the article below.
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196,755 views • 2 months ago

Andrew Ng just released a 1-hour course on what comes after RAG. How to turn raw documents into agent memory: 00:00 - Why larger context windows are not enough 02:18 - Extract entities, relationships, and sources 14:31 - Coordinate specialized agents inside one graph 30:43 - Build it with Google ADK and Neo4j 47:25 - Turn knowledge graphs into persistent memory Most people are still learning RAG. Andrew Ng is already teaching the layer that comes after it. Documents → Entities → Relationships → Agents → Knowledge Graph More context is the old workflow. Persistent graphs are the new memory layer. This 1-hour watch is worth more than most paid GraphRAG courses. Bookmark and watch it today Then read the full graph engineering roadmap below
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Lunar

42,118 views • 2 months ago

Ex-Google engineer just compressed the shift from AI agents to "graphs" and "loops" into one 2h47m lecture: • 00:00 - understanding the different layers of AI memory • 30:00 - moving from simple LLM calls to AI agents • 50:00 - why agent systems are becoming a graph engineering problem • 1:12:00 - connecting context, tools and agent state • 1:24:00 - building a minimal agent harness from scratch • 1:46:00 - breaking down the architecture behind Hermes Agent • 2:08:00 - turning agent concepts into working systems 167-minute deep dive, and one of the clearest ways to understand how AI engineering is moving beyond prompts The progression: Prompt → Context → Memory → Agent → Loop → Graph → Agent Harness Watch it today, then read the full roadmap below
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Google Senior Engineer Annie Wang just dropped a free hands-on course on Graph RAG agents, from scratch: Setup → Graph Schema → Embeddings → Hybrid Search (RRF) → ADK Agent → Deploy 0% → 0:00 – a Graph RAG agent with ADK 25% → 13:01 – Build the graph schema and visualize your data 77% → 39:16 – Hybrid search + RRF 84% → 43:05 – Wiring up the ADK agent: runner, session service, memory service 100% → 51:06 – Final demo and deploying the agent with FastAPI This is one of the few guides that walks through real code and architecture, from an empty project to a working agent. Watch it, then build it yourself
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IBM just turned five of its best graph lectures into a 50-minute course on building AI systems around connected knowledge: • 00:00 - How knowledge graphs represent entities and relationships • 05:36 - Why vector-based RAG misses connections between facts • 09:53 - GraphRAG, precision retrieval and context engineering • 20:43 - How graph neural networks learn from connected data • 37:30 - Building GraphRAG with knowledge graphs and Cypher The progression is simple: Text chunks → entities → relationships → graph retrieval → graph intelligence Vector search finds information that looks similar. Graphs recover the structure behind that information. This 50-minute course will teach you more about modern graph engineering than most paid AI programs. Watch it today, then read how to become a knowledge graph engineer in the article below.

Morlex

12,053 views • 2 months ago

Still the best hour on graph engineering ever recorded, Andrew Ng breaking down how to build agentic knowledge graphs from scratch: 00:00 - what agentic knowledge graphs actually are 03:05 - building a graph from scratch 13:58 - the architecture behind multi-agent systems 22:57 - building a real one with Google ADK 01:06:02 - why graphs are the future of AI agents I've seen $500 courses that teach less. Watch it, then take it further with my step-by-step guide on graph engineering below.
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Still the best hour on graph engineering ever recorded, Andrew Ng breaking down how to build agentic knowledge graphs from scratch: 00:00 - what agentic knowledge graphs actually are 03:05 - building a graph from scratch 13:58 - the architecture behind multi-agent systems 22:57 - building a real one with Google ADK 01:06:02 - why graphs are the future of AI agents I've seen $500 courses that teach less. Watch it, then take it further with my step-by-step guide on graph engineering below.

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265,874 views • 2 months ago

Google just released free 1-hour course on building agentic knowledge Graphs from 0% to 100%: 10% → 4:01 - how to build a GraphRAG agent 30% → 15:00 - Graph Engineering explanation 55% → 30:00 - Agentic search Engineering 80% → 35:48 - Graph Engineering practice 100% → 47:06 - self-improving agents in graphs this free Google course mass replaces a $500 graph engineering bootcamp - learn it in 60 min to 100% watch it today - then read the full graph playbook in the article below ↓
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Google just released free 1-hour course on building agentic knowledge Graphs from 0% to 100%: 10% → 4:01 - how to build a GraphRAG agent 30% → 15:00 - Graph Engineering explanation 55% → 30:00 - Agentic search Engineering 80% → 35:48 - Graph Engineering practice 100% → 47:06 - self-improving agents in graphs this free Google course mass replaces a $500 graph engineering bootcamp - learn it in 60 min to 100% watch it today - then read the full graph playbook in the article below ↓

codila

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Anthropic Engineer Andrej Karpathy just broke the entire premise of modern AI: "Agents aren't magic. They're distillation at scale." RAG → Graph RAG → Memory → Multimodal Agent Graphs. 99.99% of your LLM's capacity is wasted on garbage data it never needed. In a 20-minute conversation, Karpathy reveals the full reasoning stack Worth more than any $500 AI course you've seen this year.
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Anthropic Engineer Andrej Karpathy just broke the entire premise of modern AI: "Agents aren't magic. They're distillation at scale." RAG → Graph RAG → Memory → Multimodal Agent Graphs. 99.99% of your LLM's capacity is wasted on garbage data it never needed. In a 20-minute conversation, Karpathy reveals the full reasoning stack Worth more than any $500 AI course you've seen this year.

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IBM just released a 1-hour course on building agentic knowledge graphs from scratch: • 00:00 - Introduction to knowledge graphs • 05:35 - Building your first agentic graph • 19:59 - Agentic memory powered by graphs • 30:39 - Graphs for multi-agent orchestration This 1-hour watch will replace 10 paid courses on agentic engineering. Watch it today, then learn how to become a knowledge graph engineer in the article below.
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277,296 views • 2 months ago

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Andrew Ng just released a 1-hour course on building agentic knowledge Graphs from scratch: • 00:00 - Introduction to agentic knowledge Graphs • 03:07 - Construction of agentic Graphs • 14:00 - Architecture of multi-agent systems • 23:00 - Building agentic graphs with Google ADK • 01:06:03 - Why Graphsare the future of agentic AI Worth more than 10 articles on loop engineering. Watch it today, then read how to become a graph engineer in the article below.

Codez

468,039 views • 2 months ago

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!
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Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

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244,435 views • 2 years ago

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to an agent graph that builds itself: 10:16 - Build your first AI agent 41:05 - Master prompt engineering 54:45 - Turn agents into graphs 1:20:10 - Run loops inside agent graphs 1:43:33 - Build a graph that builds itself Most people ship one agent and stop there. Google is teaching everything after: Prompt → Agents → Graphs → Loops → Self-Building Systems Single agents are the old workflow. Graphs that evolve themselves are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read how to run 1,000 agents from one prompt below ↓
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Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to an agent graph that builds itself: 10:16 - Build your first AI agent 41:05 - Master prompt engineering 54:45 - Turn agents into graphs 1:20:10 - Run loops inside agent graphs 1:43:33 - Build a graph that builds itself Most people ship one agent and stop there. Google is teaching everything after: Prompt → Agents → Graphs → Loops → Self-Building Systems Single agents are the old workflow. Graphs that evolve themselves are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read how to run 1,000 agents from one prompt below ↓

Lunar

52,359 views • 1 month ago

Andrew Ng just dropped the best 1-hour course on Graph Engineering: from zero to full automation 00:00 - What is graph engineering 03:05 - Building a graph 13:58 - Multi agent architecture 22:57 - Live build: Google ADK 01:06:02 - Why graphs are the future This 1-hour watch replaces any $500 course you could pay for Watch it, then try your first graph with the step-by-step guide below
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Andrew Ng just dropped the best 1-hour course on Graph Engineering: from zero to full automation 00:00 - What is graph engineering 03:05 - Building a graph 13:58 - Multi agent architecture 22:57 - Live build: Google ADK 01:06:02 - Why graphs are the future This 1-hour watch replaces any $500 course you could pay for Watch it, then try your first graph with the step-by-step guide below

Mahax

69,050 views • 2 months ago

This is the best 1 hour on graph engineering ever recorded, just released by Google how to go from a single agent to a full 24/7 system from scratch: 00:00 - what graphs actually are 09:16 - your first working agent 21:15 - graph engineering explained 41:03 - graph engineering in practice 52:21 - graphs that improve themselves I've seen $500 courses that teach less than this video alone. Watch it, then take it further with my step-by-step guide on graph engineering below.
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This is the best 1 hour on graph engineering ever recorded, just released by Google how to go from a single agent to a full 24/7 system from scratch: 00:00 - what graphs actually are 09:16 - your first working agent 21:15 - graph engineering explained 41:03 - graph engineering in practice 52:21 - graphs that improve themselves I've seen $500 courses that teach less than this video alone. Watch it, then take it further with my step-by-step guide on graph engineering below.

Anatoli Kopadze

122,494 views • 22 days ago

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓
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Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

403,431 views • 1 month ago