I am excited to bring you a comprehensive step-by-step guide on how to fine-tune the newly announced MPT-7B parameters model using just a single GPU. This remarkable model is not only open source but also commercializable, making it a valuable tool for a wide range of natural language processing (NLP) tasks. MPT token size beat GPT4 and also it outperformed many available language models like GPT-J, LLAMA and etc.

Don't forget to subscribe to our channel and hit the notification bell to stay updated with the latest tutorials and developments in the field of AI. Let's dive in and empower your AI projects with the limitless potential of MPT-7B!

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Notebook: https://github.com/antecessor/mpt_7b_fine_tuning

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In this Edureka video on “ Introduction to AI Engineering ”, You will gain a thorough understanding of the principles and core components of Artificial Intelligence . Following that, you will learn about the real-world applications of AI and develop a brief understanding of the distinct responsibilities played by AI engineers. Finally, we covered the AI concepts in more detail. Let us know what you think of this video by leaving a comment.
00:00 Introduction
01:40 Why you might want to become an AI engineer
01:58 What AI engineers do?
02:23 AI Engineer's Responsibilities
02:44 Salary prospects of an AI engineer
03:15 Top companies that are actively hiring AI engineers
04:05 The skills required to become an AI engineer
04:38 How you can become an AI engineer
05:20 AI projects
05:40 Thanks giving

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🔵 About Edureka Artificial Intelligence Certification Course

Edureka’s Artificial Intelligence Course is a well researched amalgamation of Natural Language Processing and Deep Learning, specifically designed for professionals and beginners to meet the industry standards. This course gives you an in-depth understanding of Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing using Python’s NLTK package, CNN, RCNN, RNN, LSTM, RBM, and their implementation using TensorFlow 2.0 package.

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There are many reasons why someone might want to take up an online artificial intelligence course. Here are a few:
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⭐️ Course Contents ⭐️
⌨️ (00:00:00) Introduction
⌨️ (00:00:55) What Is a Computer?
⌨️ (00:03:37) Buttons and Ports on a Computer
⌨️ (00:06:01) Basic Parts of a Computer
⌨️ (00:08:47) Inside a Computer
⌨️ (00:10:58) Getting to Know Laptop Computers
⌨️ (00:12:55) Understanding Operating Systems
⌨️ (00:14:21) Understanding Applications
⌨️ (00:15:53) Setting Up a Desktop Computer
⌨️ (00:18:47) Connecting to the Internet
⌨️ (00:22:41) What Is the Cloud?
⌨️ (00:25:06) Cleaning Your Computer
⌨️ (00:29:02) Protecting Your Computer
⌨️ (00:32:17) Creating a Safe Workspace
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⌨️ (00:47:40) Mac OS X Basics: Getting Started with the Desktop
⌨️ (00:52:26) Browser Basics


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Artificial general intelligence (AGI) promises to unlock unbelievable new capabilities, from AI that can reason across domains to the potential for runaway self-improvement. This video explores the rise of AGI, visions of the singularity, and the long-term implications of advanced AI systems that may one day far surpass human-level intelligence.
We define AGI and consider predictions about when it could emerge, from futurists like Ray Kurzweil who foresee the singularity as early as the 2030s. But perhaps more importantly, what ethical precautions should guide AGI development? How can we ensure advanced AI aligns with human values and avoids existential catastrophe?
This video delves into the possibilities and perils of merging biological and nonbiological intelligence, and whether we could ever fully align an AI's goals with our own complex values. We contemplate whether uncontrolled AGI could view humanity as atoms to be used for a different purpose. But with diligence and wisdom, perhaps we can harness AI's potential as a force for good, ending disease, hunger, and environmental destruction.

Video Title: Are We Ready for Artificial General Intelligence? The Coming Of AGI

#agisimplyexplained #whatisagi #understandingagi #artificialgeneralintelligenceexplained #agideinition #agiexplained #agiconcept #agifuture #agitechnology #agibenefits #agirisks

As we stand at the threshold of superintelligent machines, we must thoughtfully shape the institutions that will guide the next phase of our civilization. Join us for an expansive look at artificial general intelligence and technological singularity. How humanity navigates this transition may determine our destiny across the stars.

Disclaimer: We do not accept any liability for any loss or damage which is incurred by you acting or not acting as a result of watching any of my publications. You acknowledge that you use the information I provide at your own risk. Do your own research.

Copyright Notice:
Video clips used here under fair use for educational purposes.
Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.

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✅ Other Videos You Might Be Interested In Watching:

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https://www.youtube.com/watch?v=EKQ1MqfqJT8

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=============================

✅ About AI Tech Academy.

Welcome to AI Tech Academy!

We are your go-to source for all the latest news, trends and insights into the world of Artificial Intelligence and Technology. Our mission is to make AI and technology more accessible to everyone. We create content to educate, inform, and entertain viewers on the topics of AI and tech. Our videos cover everything from AI tutorials to tech product reviews. We also discuss the implications and potential of AI in the future.

Our goal is to make AI and technology more understandable and accessible to everyone. Through our videos, we hope to empower viewers to become more informed about the potential of AI and tech and to become active participants in shaping its future.

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В чём проблема научных сенсаций?

«Учёные открыли сверхпроводник комнатной температуры», «учёные создали червоточину на квантовом компьютере» и много других подобных новостей мы регулярно читаем в СМИ. И тут же попадаем в анекдот про нюанс, потому что научный результат есть, но он или преувеличен, или искажён. Так в чём всё-таки проблема? Может быть, в журналистах, которые гонятся за сенсациями? Или в том, как в принципе работает современная наука? В этом видео Дерек Маллер общается с учёными и пытается понять, как можно исправить ситуацию с новостями науки.

Перевод: Егор Афонин
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Озвучки Vert Dider выходят с вашей помощью:

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In this video on How To Make PPT Using ChatGPT, learn the art of crafting engaging PowerPoint presentations effortlessly with ChatGPT's assistance. Discover two dynamic methods to elevate your presentation game. Dive into the first approach, where ChatGPT generates content based on your input, ensuring coherence and relevance. Then, explore the second method, employing ChatGPT's vast knowledge to refine your ideas and enhance the overall quality of your slides. From brainstorming to polishing, master the power of AI in PowerPoint creation.

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This video is a crash course on understanding how finetuning on LLM models can be performed uing QLORA,LORA, Quantization using LLama2, Gradient and Google Gemma model. This crash course includes both theoretical intuition and practical intuition on making you understand how we can perform finetuning.

Timestamp:

00:00:00 Introduction
00:01:20 Quantization Intuition
00:33:44 Lora And QLORA Indepth Intuition
00:56:07 Finetuning With LLama2
01:20:16 1 bit LLM Indepth Intuition
01:37:14 Finetuning with Google Gemma Models
01:59:26 Building LLm Pipelines With No code
02:20:14 Fine tuning With Own Cutom Data

Code Github: https://github.com/krishnaik06/Finetuning-LLM
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►Learn In One Tutorials

Statistics in 6 hours: https://www.youtube.com/watch?v=LZzq1zSL1bs&t=9522s&pp=ygUVa3Jpc2ggbmFpayBzdGF0aXN0aWNz

End To End RAG LLM APP Using LlamaIndex And OpenAI- Indexing And Querying Multiple Pdf's

Machine Learning In 6 Hours: https://www.youtube.com/watch?v=JxgmHe2NyeY&t=4733s&pp=ygUba3Jpc2ggbmFpayBtYWNoaW5lIGxlYXJuaW5n

Deep Learning 5 hours : https://www.youtube.com/watch?v=d2kxUVwWWwU&t=1210s&pp=ygUYa3Jpc2ggbmFpayBkZWVwIGxlYXJuaW5n

►Learn In a Week Playlist

Statistics:https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay

Machine Learning : https://www.youtube.com/watch?v=z8sxaUw_f-M&list=PLZoTAELRMXVPjaAzURB77Kz0YXxj65tYz

Deep Learning:https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns

NLP : https://www.youtube.com/watch?v=w3coRFpyddQ&list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn
---------------------------------------------------------------------------------------------------
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Python Tutorial For Beginners | Edureka
**** Python Certification Training for Data Science: https://www.edureka.co/data-science-p... ****
This Edureka video on "Machine Learning Tutorial" will help you get started with all the Machine Learning concepts.

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⏩ NEW Top 10 Technologies To Learn In 2024 - https://www.youtube.com/watch?v=vaLXPv0ewHU

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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: +18338555775 (toll-free) for more information.

🔥Edureka Machine Learning Engineer Masters Program: https://www.edureka.co/masters....-program/machine-lea
This Edureka video on Machine Learning Python is a part of the Python Tutorial Series which will give you an introduction to Machine Learning. Python is a powerful language and is a widely used high-level language for general-purpose programming. With features like open-sourced, clear syntax, object-oriented, interpreted, and interactive programming language Python has become the number one choice when it comes to Machine learning. This Python Tutorial on Machine Learning Python also talks about how to implement machine learning algorithms in Python along with the topics like:
00:00 Introduction to Python Tutorial
00:54 Why Machine Learning with Python?
02:39 What is Machine Learning?
05:09 Types of Machine Learning
06:25 Supervised Learning
07:28 KNN algorithm
18:10 Unsupervised Learning
19:03 K-means Clustering Algorithm

Python Tutorial Playlist: https://goo.gl/Na1p9G
Python Tutorial Blog Series: https://goo.gl/wd28Zr

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#edureka #pythonEdureka #machinelearningPython #Python #PythonTutorial #PythonMachineLearning #PythonTraining #machinelearningTutorial #machinelearning
------------------------------------------------------------------------

About the ML Master's Program

Edureka’s Machine Learning Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

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

Why Learn Machine Learning?

Machine Learning is a concept that allows the machine to learn from examples and experience, and that too without being explicitly programmed. So instead of you writing the code, what you do is you feed data to the generic algorithm, and the algorithm/machine builds the logic based on the given data.
-------------------------------------

Edureka's Machine Learning Masters Program Curriculum

🟠 Live Courses 🟠
Python Programming Certification Course: https://www.edureka.co/python-....programming-certific
Machine Learning Certification Training using Python: https://www.edureka.co/machine....-learning-certificat
Graphical Models Certification Training: https://www.edureka.co/graphical-modelling-course
Reinforcement Learning: https://www.edureka.co/reinfor....cement-learning-cour
Natural Language Processing with Python Certification: https://www.edureka.co/python-....natural-language-pro
Deep Learning with TensorFlow 2.0 Certification Training: https://www.edureka.co/ai-deep....-learning-with-tenso
Python Spark Certification Training using PySpark: https://www.edureka.co/pyspark....-certification-train

🟠 Elective Course 🟠
Python Scripting Certification Training: https://www.edureka.co/python-scripting

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

Prerequisites

There are no prerequisites for enrollment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

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

Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information

🔥 Purdue Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=Live-11Sep2024GenAI&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥Professional Certificate Course In AI And Machine Learning by IIT Kanpur (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=Live-11Sep2024GenAI&utm_medium=DescriptionFF&utm_source=youtube
🔥AI & Machine Learning Bootcamp(US Only): https://www.simplilearn.com/ai-machine-learning-bootcamp?utm_campaign=Live-11Sep2024GenAI&utm_medium=DescriptionFirstFold&utm_source=youtube
About the Webinar
Unlock the transformative power of artificial intelligence with our Applied Generative AI Specialization in partnership with Purdue University.

Join us on April 18th, 09:00 PM, for an exclusive insight into our Applied Generative AI Specialization. Discover the cutting-edge curriculum, hands-on projects, and unique features of this program designed to prepare you for success in developing and deploying AI-driven solutions.

👉Know more about the upcoming Live and Interactive Webinars here: https://sites.google.com/simplilearn.net/webinars/home?utm_campaign=Live-11Sep2024GenAI&utm_medium=Description&utm_source=youtube

✅Subscribe to our Channel to learn more about the top Technologies: https://www.youtube.com/user/Simplilearn

⏩ Check out the Artificial Intelligence tutorial videos: https://www.youtube.com/watch?v=ad79nYk2keg&list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq

#ArtificialIntelligence #MachineLearning #AIAndMachineLearning #ArtificialIntelligenceFullCourse #MachineLearningFullCourse #MachineLearningTutorial #AITutorial #AIAndML #Simplilearn

Topics Covered:

In this enlightening session, we will explore key components of our Applied AI Course, including:

✅ Foundational AI Concepts
✅ Developing AI Applications
✅ AI in Practice
✅ AI Governance
✅ Interactive Q&A Session

About Applied Generative AI Specialization

Master Generative AI with this cutting-edge program delivered collaboratively by Purdue University Online and Simplilearn. Explore concepts like prompt engineering, large language models, attention mechanisms, and LLM fine-tuning. Learn in-demand tools and shape the future of intelligent systems.

Key Features
✅ Program completion certificate from Purdue University Online and Simplilearn
✅ Access to Purdue’s alumni association membership on program completion
✅ 50+ hours of core curriculum delivered in live online classes by industry experts
✅ Build Generative AI-enabled applications through hands-on projects
✅ Live online masterclasses delivered by Purdue faculty and staff
✅ Gain exposure to ChatGPT, OpenAI, Hugging Face, DALL-E 2 and other prominent tools
✅ Explore concepts like prompt engineering, attention mechanism, transformers, LLM application development, and LLM fine-tuning
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Earn official trophy and badges for ‘Microsoft Azure AI Fundamentals: Generative AI’ on the Microsoft Learn portal

Applied Gen AI Course Advantage
Gain a competitive edge with hands-on learning in the transformative arena of Generative AI. Master prompt engineering, LLMs, attention mechanisms, fine-tuning techniques, and LLM application development.

Applied Gen AI Course Details

Explore our Applied Generative AI program to deploy advanced techniques in real-world scenarios. Master GANs, VAEs, and prompt engineering, alongside tools like ChatGPT, DALL-E 2, OpenAI and Hugging Face. Develop LLM applications, fine-tuning skills, and explore governance principles.

Learning Path
✅ AGS: Program Induction
✅ AGS: Python Basics (Optional)
✅ AGS: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ AGS: Advanced Generative AI - Models and Architecture
✅ AGS: Advanced Generative AI - Building LLM Applications
✅ AGS: Advanced Generative AI - Image Generation Capabilities
✅ AGS: Generative AI Governance
Electives:
✅ AGS: Microsoft Azure AI Fundamentals - Generative AI
✅ AGS: Academic Masterclass

Skills Covered
✅ Python Programming
✅ Explainable AI
✅ Prompt Engineering
✅ Variational Autoencoders VAEs
✅ Generative Adversarial Networks GANs
✅ Transformers
✅ LLM Architecture
✅ Attention Mechanism
✅ Langchain for Workflow Design
✅ GenAI Application Development
✅ LLM Fine Tuning
✅ LLM Benchmarking
✅ Stable Diffusion
✅ Generative AI Governance

Tools Covered

✅ Python
✅ ChatGPT
✅ OpenAI
✅ Hugging Face
✅ Bard
✅ Dall-E-2
✅ LangChain
✅ Gradio
✅ Chroma
✅ StreamLit

Industry Projects
✅ Project 1
Craft an AI Powered HR Assistant

✅ Project 2
Build a Creative Logo Designer

✅ Project 3
Conversational Chatbot for Document Interaction

👉Learn more at: https://www.simplilearn.com/applied-ai-course?utm_campaign=Live-11Sep2024GenAI&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
** New 2024 Edition **

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline
0:00​ - Introduction
3:42​ - Sequence modeling
5:30​ - Neurons with recurrence
12:20 - Recurrent neural networks
14:08 - RNN intuition
17:14​ - Unfolding RNNs
19:54 - RNNs from scratch
22:41 - Design criteria for sequential modeling
24:24 - Word prediction example
31:50​ - Backpropagation through time
33:40 - Gradient issues
37:15​ - Long short term memory (LSTM)
40:00​ - RNN applications
44:00- Attention fundamentals
46:46 - Intuition of attention
49:13 - Attention and search relationship
51:22 - Learning attention with neural networks
57:45 - Scaling attention and applications
1:00:08 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

Anthropic’s Alex Albert (Claude Relations) sits down with Erik Schluntz (Multi-Agent Research and co-author of our blog post, Building Effective Agents) for a discussion on the evolution of agents over the past six months, including tips for building multi-agent systems, common multi-agent patterns, and best practices for using skills, MCP servers, and tools.

00:00 - Introductions
00:35 - Training Claude to tackle agentic tasks
1:30 - Making Claude more autonomous with code
3:20 - Using the Claude Agent SDK to build agents
5:00 - Tips for using Agent Skills
6:40 - The evolution of workflows and agents (workflows of agents)
8:30 - The value of simple agent architectures
9:30 - Building multi-agent systems: orchestrators, subagents, and tool calling
11:40 - Training Claude to use subagents
12:25 - Multi-agent use design patterns: parallelization, MapReduce, and test-time compute
13:20 - Coordinating problem solving with tools and subagents
14:15 - Common agent failure modes
15:00 - Best practices for getting started with building agents (context engineering, MCPs, and tools)
17:15 - The future of agents: coding, computer use, and beyond

Read the original blog post: https://www.anthropic.com/engi....neering/building-eff
Learn more about Agent Skills: https://www.anthropic.com/engi....neering/equipping-ag

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai

In this webinar, you will gain an introduction to the concept of agentic language models (LMs) and their usage. You will learn about common limitations of LMs and agentic LM usage patterns, such as reflection, planning, tool usage, and iterative LM usage.

This online session will cover:
Overview of LMs
LM Usage and limitations
Retrieval Augmented Generation (RAG)
Tool usage
Agentic LMs
Agentic design patterns

About the speaker: Insop Song

Insop is a Principal Machine Learning Researcher at GitHub Next. Previously he worked at Microsoft, where he focused on leveraging machine learning and large language models to boost engineering productivity. His projects included fine-tuning open-source large language models with internal code and text, developing document assistance tools, and applying AI to various engineering tasks. He is currently a course developer as well as a course facilitator for Stanford Online’s professional AI program.


Chapters:
00:00 - Introduction
00:10 - Overview of the Talk
01:50 - Training Language Models
02:30 - Modeling Objectives
04:00 - Examples of Training Data Formatting
05:40 - Applications of Language Models
06:50 - Using API for Language Models
09:00 - Best Practices for Prompt Preparation
11:10 - Importance of Clear Instructions
13:40 - Reflection and Improvement Techniques
16:30 - Tool Usage and Function Calling
20:30 - Definition of Agentic Language Models
21:50 - Reasoning and Action in Agentic Models
24:00 - Example of a Customer Support AI Agent
29:20 - Summary of Applications
36:00 - Key Design Patterns in Agentic Models
44:00 - Summary of Agentic Language Model Usage
47:40 - Audience Q&A
50:00 - Addressing Ethical Considerations
54:50 - Getting Started with Language Models
57:00 - Resources for Staying Updated
58:20 - Closing Remarks