Shane Legg, the visionary founder of Deepmind has just dropped a bombshell: he envisions DeepMind achieving Artificial General Intelligence, or AGI, by the year 2028. This announcement comes as a seismic shift in the AI landscape, setting the stage for a future where machines possess human-level cognitive abilities. The implications are nothing short of revolutionary, promising to reshape industries, economies, and the very fabric of our existence!
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.
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TIMESTAMPS:
00:00 AGI By 2028 confirmed
01:10 Deepmind is working towards AGI
05:04 How AGI will be created
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#deepmind #ai #agi

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🚀 Gumroad Link to Assets in the Video: https://markkashef.gumroad.com..../l/agenticdesignpatt

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🎬 Core Video Description

What if you could learn the 20 agentic design patterns the pros actually use—without wading through a 400-page manual? In this practical 63-minute breakdown, I translate a Google engineer’s book into plain English and show you exactly how to apply each pattern in real workflows. You’ll see where each architecture shines, the tradeoffs that matter (cost, latency, failure modes), and quick ways to combine patterns for robust systems—so you can ship reliable agents faster and avoid over-engineering rabbit holes. Expect concise TL;DRs, labeled visuals, and a free repo packed with diagrams, ASCII flows, and Mermaid files to help you implement immediately.

[Main Topic]: A practical, plain-English guide to 20 agentic design patterns

[Key Benefits or Outcomes]: Understand when/why to use each pattern, reduce hallucinations and cost, add safety/quality gates, route work across models/agents, and ship production-ready automations with fewer retries and rollbacks

[Tools or Techniques Covered]: Prompt chaining, routing, parallelization, reflection loops, tool use, planning/orchestration, multi-agent collaboration, memory management, learning/feedback, goal tracking, exception handling, human-in-the-loop, RAG, inter-agent comms, resource-aware model routing, reasoning strategies (CoT/ToT, debate), evaluation & monitoring, guardrails/safety, prioritization, exploration/discovery

⏳ TIMESTAMPS:
00:00 – Intro: Why agentic patterns separate pros from beginners
00:36 – What you’ll get: TL;DRs, visuals, free resources
00:54 – Pattern 1: Prompt Chaining (assembly-line steps & validations)
05:42 – Pattern 2: Routing (smart triage to specialist agents)
09:30 – Pattern 3: Parallelization (split, normalize, merge)
13:16 – Pattern 4: Reflection (critic → revise → pass)
15:51 – Pattern 5: Tool Use (discover, authorize, execute, fallback)
18:19 – Pattern 6: Planning (milestones, dependencies, constraints)
20:49 – Pattern 7: Multi-Agent Collaboration (manager + roles + shared memory)
23:45 – Pattern 8: Memory Management (short/episodic/long-term, retrieval)
26:42 – Pattern 9: Learning & Adaptation (feedback → prompts/policies/tests)
29:17 – Pattern 10: Goal Setting & Monitoring (KPIs, drift, course-correct)
31:34 – Pattern 11: Exception Handling & Recovery (classify, backoff, fallbacks)
34:11 – Pattern 12: Human-in-the-Loop (review cues & approvals)
36:01 – Pattern 13: Retrieval (RAG): parse, chunk, embed, rerank
38:14 – Pattern 14: Inter-Agent Communication (protocols, IDs, expiry)
43:08 – Pattern 15: Resource-Aware Optimization (route by cost/complexity)
46:35 – Pattern 16: Reasoning Techniques (CoT, ToT, self-consistency, debate)
49:57 – Pattern 17: Evaluation & Monitoring (golden sets, SLAs, drift)
52:44 – Pattern 18: Guardrails & Safety (PII, injection, sandboxing)
56:04 – Pattern 19: Prioritization (value×effort×urgency×risk, re-order)
59:29 – Pattern 20: Exploration & Discovery (map space, cluster, probe)
62:17 – Free Repo & Diagrams (ASCII + Mermaid)
63:08 – Final CTA: Share, comment, and join the community

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This Edureka video on "Data Blending in Tableau" talks about a method for combining data when there is related data in multiple data sources, which you want to analyze together in a single view. Tableau has two inbuilt data sources named Sample-superstore and Sample coffee chain.mdb which will be used to illustrate data blending.
We shall discuss the following topics:
00:00:00 Introduction
00:01:10 Objective of data blending
00:03:53 Introduction to Data Blending
00:04:12 Joining vs Blending
00:07:12 Blending in Tableau
00:10:13 Limitations of Data Blending

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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
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Learn more: https://stanford.io/4iHlGQp

Build modern AI agents with Stanford's graduate-level curriculum, adapted for working professionals.

Taught by Stanford Adjunct Professor Chowdhery and Assistant Professor Mirhoseini, this Agentic AI program takes you beyond basic LLM prompting to agents that reason, plan, use tools, and improve themselves through interaction with their environment.

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- Add retrieval and long-term memory to LLMs
- Develop planning and multi-step reasoning
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Drawing on Stanford research and the latest advances in the field.

About the Instructors
Stanford Engineering Adjunct Professor Dr. Aakanksha Chowdhery led end-to-end training of the 540B PaLM model (the largest densely trained language model in the world at the time) and drove pre-training and scaling of Gemini's mixture-of-experts models. Stanford Assistant Professor Azalia Mirhoseini co-developed the MoE architectures now used in nearly every frontier model, created AlphaChip (the RL method behind Google's TPU designs), and pioneered LLM test-time scaling; she worked on both Claude and Gemini.

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Top 20 Most Important Excel Formulas by simplilearn is dedicated to guide the aspiring data analysts and business analysts with the top Excel Formulas For Data Analysis in 2024 and beyond. This Excel tutorial for beginners by Simplilearn will cover the following topics. In this video, we learn into the top 20 to 25 most important Excel formulas every data analyst needs to excel in their role.This excel tutorial will help you to refine your skills, and building a strong foundation in Excel proficiency.

0:00:00 How To Change Lower Case To Upper Case In Excel?
0:01:14 How To Add Rows In Excel?
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0:08:32 How to Compare Two Columns In Excel?
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0:17:28 How to Group Rows in Excel?
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0:25:29 How to Convert Number to Words in Excel?
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0:40:57 How To Calculate Age In Excel From A Date Of Birth?
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0:44:29 DAX In Excel Explained
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Checkout the roadmap: https://www.krishnaik.in/ai-roadmaps
Agentic AI involves creating autonomous systems that use Large Language Models (LLMs) to plan, reason, and act to achieve goals, rather than just generating content. To learn this, focus on mastering frameworks like LangGraph, CrewAI, and AutoGen to build multi-agent workflows, and focus on agentic RAG for data access. Key skills include planning, tool usage, and human-in-the-loop interaction.
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Learn from me and my team
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Learn Agentic AI using a popular framework langgraph. In this agenti ai tutorial for beginners, we will start with agentic AI basics and then we will dive deeper into langgraph by covering a wide range of topics.

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00:00 Introduction
00:40 Agentic AI Basics
00:00 What is Langgraph
07:41 Langchain vs Langgraph
13:08 Installation and Setup
19:00 Simple Graph
31:36 Graph with Condition
36:55 Chatbot in Langgraph
45:38 Chatbot with Tool
56:03 Memory
1:05:05 Tracing with Langsmith
1:10:11 Human in the Loop

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🔥PROMPT ENGINEERING WITH GENERATIVE AI: https://www.edureka.co/prompt-....engineering-generati
Explore the field of artificial intelligence through our Generative AI Tutorial. This video will break down the intricate workings of the generative AI model and give you useful information and pointers for utilizing generative AI in your projects, covering everything from the fundamentals of the technology to its applications, frameworks, and changing the landscape of industries. This course is a crucial place to start, whether you're a professional looking to implement AI-driven solutions or a newcomer excited to learn about AI's creative potential.

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✅ 05:00 - AI Prompt Writing
✅ 06:35 - Text-to-Text Generative AI
✅ 07:42 - Prompt Writing Rules
✅ 08:47 - ChatGPT-3.5
✅ 09:15 - ChatGPT-4
✅ 11:24 - Google Gemini
✅ 12:22 - Text-to-Image Generative AI
✅ 13:41 - DezGo
✅ 13:50- Hands-On Tutorial

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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- - - - - - - - - - - - - -

What is Prompt Engineering?

Prompt engineering involves optimizing artificial intelligence engineering for multiple purposes. It includes refining large language models (LLMs) using specific prompts and recommended outputs. Additionally, it focuses on enhancing input to different generative AI services to make text or images. With advancements in generative AI tools, prompt engineering becomes crucial for generating diverse content, such as robotic process automation bots, 3D assets, scripts, robot instructions, and various digital artifacts.
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What kinds of jobs can you get with Prompt Engineering skills?‎

Here are some potential job roles:

Machine Learning Engineer
Data Scientist
Natural Language Processing (NLP) Engineer
AI Research Scientist
Software Engineer (AI/ML)
Data Engineer
Content Generation Specialist
Conversational AI Developer
AI Product Manager
AI Ethicist

Remember that the job market and the demand for specific skills can change over time, so staying updated on industry trends and job postings is essential.

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Who are the instructors for Prompt Engineering Course?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (toll-free).

🔥Advanced Certification in Agentic AI Engineering: https://www.edureka.co/agentic-ai-training-course
🔥 Integrated MS+PGP Program in Data Science & AI https://www.edureka.co/dual-ce....rtification-programs

In this video, we dive into the exciting developments and advancements that are set to shape the industry in 2025. We will learn what Agentic AI is and how it goes beyond traditional AI by acting with purpose and autonomy. You’ll discover 5 powerful secrets behind Agentic AI—from multi-agent collaboration to real-world tool integration and ethical guardrails. By the end, you’ll understand how Agentic AI is transforming industries and why it’s the future of intelligent systems.

Join us as we discuss the latest trends, innovations, and predictions for Agentic AI in 2025. Whether you're an AI enthusiast, a business leader, or simply curious about the future of technology, this video is for you.

00:00:00 Introduction
00:17:13 What is Agentic AI?
00:36:19 Agentic AI vs Generative AI
00:46:07 Agentic AI Roadmap
00:52:18 Introduction to Artificial Intelligence
00:58:37 Introduction to Deep Learning
02:28:29 Artificial Neural Network
03:08:09 Transformers Explained Using Generative AI
03:09:37 Transformers Neural Networks Explained
03:21:52 What are Large Language Models?
03:38:17 LLM vs SLM
03:41:59 What is LangChain?
03:59:35 What is RAG?
04:22:07 LLMOps: The Future of AI Development
04:29:57 Prompt Engineering
04:42:41 Natural Language Processing (NLP) & Text Mining using NLTK
05:22:21 KNN Algorithm using Python
05:45:23 Alibaba’s Qwen 2.5-Max Just Beat GPT-4 & DeepSeek?
05:49:47 DeepSeek vs OpenAI: Who Wins the AI Race?
06:02:06 Deep Learning Interview Questions

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What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously make decisions, take actions, and pursue goals with minimal human intervention. Unlike traditional AI, which adheres to predetermined rules, agentic AI may dynamically adapt to new situations. It is widely utilized in robotics, virtual assistants, self-driving cars, and sophisticated decision-making processes.

What are the prerequisites for this Agentic AI Training Course?
In order to complete this course successfully, participants need to have a basic understanding of the Python programming language, machine learning, deep learning, natural language processing, generative AI, and prompt engineering concepts.

Who should take this AI Agents Training Course?
The Agentic AI online Training Course is ideal for AI enthusiasts, developers, and professionals looking to build autonomous AI agents. It is best suited for LLM Engineers, Generative AI Engineers, AI Research scientists, AI/ML practitioners, and freshers who want to leverage Agentic AI for automation and decision-making.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18885487823(toll-free).

#agenticai #aiagents #agenticaicourse #generativeai