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The Artificial Intelligence Course video by Simplilearn mainly focuses on the Artificial Intelligence Tutorial for Beginners 2023, which covers an introduction to artificial intelligence, the definition of artificial intelligence, the basics of artificial intelligence, the types of artificial intelligence, applications, and examples of artificial intelligence. This AI Tutorial video reveals the full Artificial Intelligence Course for beginners.

✅ 00:00 Artificial Intelligence Tutorial For Beginners 2023

✅ 00:01 - What is Artificial Intelligence?
This phase of the video picturizes the basics of Artificial Intelligence and its role in problem-solving.

✅ 05:28 - Introduction to Artificial Intelligence
This part of the video phase uncovers the definition of Artificial Intelligence and the relationship between Artificial Intelligence and Data Science.

✅ 19:14 - Future of Artificial Intelligence
This part of the video covers statements of great personalities about the future of AI and upcoming projects on Artificial Intelligence.

The term artificial intelligence was first coined by John McCarthy in the 1950s.McCarthy established a lab for artificial intelligence at Stanford University, where he developed the first iterations of a self-driving car.

Artificial intelligence is a technique of turning a computer-based robot to work and act like humans.
Siri, Alexa, recommendations from companies like Flipkart and Amazon, and self-driving cars like Tesla. All this work is based on AI.

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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AI is evolving towards human-level intelligence at breakneck pace – or have we already reached it? ChatGPT is very powerful in its own right though it may not reach full human level intelligence or AGI levels. Still, if that's what's available to the public, is it possible that powerful government agencies or tech giants have created full AGI in secret?

Several people have asked me this question so this video dives into some arguments for why AGI may or may not have been created in secret. Some of the discussion is based on my experience as a PhD student at an Ivy League institution.

This video also defines various tests for AGI and artificial intelligence. This helps answer the question, is there a Turing test for AGI? We also discussed briefly what might be left before AGI is created in the public sphere.

#agi #ai #secret


What's Left Before AGI? PaLM-E, 'GPT 4' and Multi-Modality
https://www.youtube.com/watch?v=EzEuylNSn-Q

Has GPT-4 Ignited the Fuse of Artificial General Intelligence?
https://www.datanami.com/2023/....03/30/has-gpt-4-igni

Morgan Stanley note on GPT-4/5 training demands, inference savings, Nvidia revenue, and LLM economics
https://www.reddit.com/r/mlsca....ling/comments/11pnhp

AGI: What, When and Why
https://blogs.perficient.com/2....023/04/03/agi-what-w

0:00 Intro
0:20 Contents
0:27 Part 1: What is AGI anyway?
0:47 Turing test
1:32 Other proposed tests
2:10 Does AI pass these tests today?
2:56 Applying tests to GPT-4
3:49 Part 2: What's left before AGI?
4:28 Scaling hypothesis
5:19 Exponential growth in intelligence
5:56 AGI continuum
6:14 Do we already have AGI?
6:55 Part 3: Has AGI already been created in secret?
7:19 Government agencies and contracts
8:55 Academic research
10:19 Industry labs
11:32 Summary: government, academia, industry
11:52 Nvidia GPU argument
12:57 Conclusion
13:34 Outro

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In this comprehensive data analysis full course, you will learn everything you need to know to become a data analyst, from the basics of data analysis to the most advanced techniques. This course is designed for beginners with no prior experience in data analysis.

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This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

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An engineer came up with a plan to drop tungsten telephone poles from space - the idea has been seriously considered on multiple occasions, so we tested it. Head to https://brilliant.org/Veritasium to start your free trial. The first 200 will get 20% off Brilliant's annual premium subscription.

Special thanks to our Patreon supporters! Join the community to help us keep our videos free, forever:
https://ve42.co/PatreonDEB

Massive thanks to Archisand for building such a beautiful sandcastle. https://www.youtube.com/@GregLeBon

Huge thanks to John and Angie Miller for helping us with securing the shooting location and going above and beyond to make this shoot happen – http://highdesertlocations.com/

Thanks to Inland Empire Film Services and the San Bernardino County Film Office for portions of the video shot in the County of San Bernardino.

Massive thanks to Dr David Wright for the interview and providing invaluable guidance during the research for this video.

Here’s a great video about space-based missile defense – https://www.ucsusa.org/resourc....es/space-based-missi

Massive thanks to Adam Savage for being part of this video.

Additional photos from NASA and ESA.

▀▀▀
References:
USAF. (2003). The US Air Force transformation flight plan.

Preston, R., Johnson, D. J., Edwards, S. J., Miller, M. D., & Shipbaugh, C. (2002). Space weapons earth wars. Rand Corporation.

Wright, D., Grego, L., & Gronlund, L. (2005). The physics of space security. A Reference Manual, Cambridge.

DeBlois, B. M., Garwin, R. L., Kemp, R. S., & Marwell, J. C. (2004). Space weapons: crossing the US Rubicon. International Security, 50-84.

Baucom, D. R. (2017). The Rise and Fall of Brilliant Pebbles 1. In United States Military History 1865 to the Present Day (pp. 329-376). Routledge.

Hitchens, T., & Samson, V. (2004). Space-based interceptors: still not a good idea. Georgetown journal of international affairs, 21-29.

National Research Council. (2012). Making sense of ballistic missile defense: An assessment of concepts and systems for US boost-phase missile defense in comparison to other alternatives. National Academies Press.

Borger, J. (2005). Bush likely to back weapons in space. The Guardian, 19.

▀▀▀
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▀▀▀
Written by Petr Lebedev, Derek Muller, and Emily Zhang
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Animation by Mike Radjabov, Fabio Albertelli, and Jonny Hyman
Edited by Trenton Oliver
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Intern: Katie Barnshaw
Additional video/photos supplied by Pond5 and Getty Images
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Thumbnail by Ignat Berbeci
Produced by Derek Muller, Petr Lebedev, and Emily Zhang

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👉Following topics are covered in this video:
00:00:00 - Introduction
00:04:45 - Introduction to Financial System
00:20:58 - Structure of Financial System
00:45:06 - Participants in Financial Markets
01:25:54 - Cash Equity and Fixed Income
01:33:48 - Various Ways of Raising capital
01:55:53 - Who is the Lead Manager?
02:01:09 - Types of Bonds on Collateral Basis
02:05:56 - Different Types of Bonds Based on Features
02:47:52 - Interest Rate and its Impact on Bonds
02:52:25 - Interest Rate vs Bond Prices vs Current Yield
02:57:29 - Yield to Maturity
03:14:10 - Current Yield
03:18:40 - Dirty Price vs Clean Price
03:29:53 - Introduction to Money Market
03:39:58 - Structure of the Indian Money Market
03:42:44 - Instruments of Money Markets
03:46:22 - Interbank Lending
03:56:37 - Advantages of Interbank Lending
04:04:43 - Disadvantages of Interbank Lending
04:14:20 - Treasury Bill
04:19:11 - Commercial Paper
04:21:48 - Certificate of Deposits
04:24:09 - Certificate of Deposits vs Term Deposit
04:26:36 - Capital Market vs Money Market
04:28:24 - Introduction to Foreign Exchange
04:52:53 - Features of Foreign Exchange
04:57:31 - Types of FX Quotations
05:02:13 - Non-Deliverable Forwards
05:09:22 - Interview Questions

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What exactly is Agentic AI? In this video, we will go through an extremely simple explanation of Agentic AI. We will compare Agentic AI systems with Workflows that use LLMs but are not agentic in nature.

00:00 Introduction
00:13 RAG Based AI System
01:06 Tool Augmented AI System
02:08 Agentic AI System
08:02 Agentic AI Apps with Code
09:31 Low Code Agentic AI
11:16 AI Agent vs Agentic AI
11:42 Gen AI vs Agentic AI

Anthropic agent guide: https://www.anthropic.com/engi....neering/building-eff
RAG and tool ammended AI system project 1: https://youtu.be/CO4E_9V6li0?si=4BhXW9c6HnPC2uww
RAG and tool ammended AI system project 2: https://youtu.be/jLM6n4mdRuA?si=oKer2d5eyixiTgF5
Agno reasoning agent: https://docs.agno.com/reasonin....g/reasoning-agents#r

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We're launching Claude Code, our agentic coding tool, in a limited research preview. Claude Code lets developers delegate substantial engineering tasks to Claude directly from their terminal.

Claude Code has already become indispensable for our team. In early testing, Claude completed tasks in one pass that would normally take 45+ minutes of manual work.

With Claude Code, our goal is to better understand how developers use Claude to help improve our models for all.

In this demo, Claude Code completes complex coding tasks that would ordinarily take a significant amount of manual work. It explains an unfamiliar Next.js project, adds new functionality, creates tests, fixes build errors, and explains its changes.

Read more and join the preview: http://www.anthropic.com/news/claude-3-7-sonnet

MIT 14.02 Principles of Macroeconomics, Spring 2023
Instructor: Ricardo J. Caballero

View the complete course: https://ocw.mit.edu/courses/14....-02-principles-of-ma
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This lecture covers an introduction to the topic of macroeconomics, which is the study of the behavior of an economy as a whole. The instructor also talks about the objectives of the course.

License: Creative Commons BY-NC-SA
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More courses at https://ocw.mit.edu
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For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

October 17, 2025
This lecture covers:
• Pretraining
• Quantization
• Hardware optimization
• Supervised finetuning (SFT)
• Parameter-efficient finetuning (LoRA)

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

Chapters:
00:00:00 Introduction
00:07:19 Pretraining
00:13:26 FLOPs, FLOPS
00:16:34 Scaling laws, Chinchilla law
00:24:49 Training optimizations overview
00:31:09 Data parallelism with ZeRO
00:35:51 Model parallelism
00:38:26 Flash Attention
00:52:37 Quantization
00:56:00 Mixed precision training
01:02:31 Supervised finetuning
01:09:21 Instruction tuning
01:37:53 Parameter-efficient finetuning with LoRA
01:45:16 QLoRA

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