Quantum computing can be explained simply. See how Python helps to clean up the response. AI can be used to build applications that'll power a large language. Think of it as building with Lego blocks, where all the blocks fit together for a single purpose. #quantumcomputing #python #artificialintelligence #dougortiz

Is your AI experiencing memory loss? 🤯 Frustrated with disjointed conversations? This video is your ultimate guide to building conversational AI that remembers, understands context, and transforms your projects into intelligent dialogues! We're diving deep into #LangChain and #TinyLlama to give your AI the memory it deserves. 🧠 In this hands-on tutorial, you'll learn: - How to set up your #GoogleColab environment for AI development. - Installing essential libraries like #AutoTokenizer and #AutoModelForCausalLM. - Loading the powerful #TinyLlama model for efficient text generation. - The magic of #ConversationBufferMemory for giving your AI memory. - Crafting effective #PromptTemplates for seamless dialogue. - Practical examples of how your AI can remember names and hobbies! Say goodbye to forgetful AI and hello to fluid, engaging conversations. This isn't just a tutorial; it's a transformation for your #AIProjects. 🔥 Next up: We'll explore how to teach your AI to read and understand PDFs! Stay tuned for Part 3! Resources: - LangChain Memory Docs - Tiny Llama Don't forget to like, comment, and subscribe for more AI tutorials! Let me know what you build! 👇 #AIChatbots, #ChatbotTutorial, #HuggingFace, #ConversationalAI, #AIWithMemory, #BuildAIChatbot, #AIDevelopment, #PythonProgramming, #GoogleColab, #TinyLlama, #LangChain, #AutoTokenizer, #TextGeneration, #NLP, #MachineLearning, #DeepLearning, #AIProject, #StepByStepTutorial, #CodingTutorial, #AIChatbotWithMemory, #ContextualAI, #EasyAITutorial, #AIForBeginners, #PracticalAI, #AIAplications, #AITools, #HowToCreateAIChatbots, #AIChatbotDevelopment, #CreateYourOwnAIChatbot, #PythonForAI, #FreeAITutorial, #LLM, #LargeLanguageModel, #MemoryAugmentation, #ConversationBuffer, #PromptEngineering, #ModelSelection, #ModelTraining, #AIModelDeployment, #DougOrtiz #dougortiz ▬▬▬▬▬▬ 👋 Contact Me ▬▬▬▬▬▬ ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ ▬▬▬▬▬▬ ⏱ Timestamps ▬▬▬▬▬▬ 00:00 Introduction: Solving AI's Memory Problem 00:23 Setting Up the Environment 00:41 Installing and Importing Libraries 01:13 Configuring the Model and Tokenizer 01:46 Building the Conversational Pipeline 02:03 Implementing Memory in AI 02:24 Testing and Verifying AI Memory 04:17 Conclusion and Next Steps

Is your AI experiencing memory loss? 🤯 Frustrated with disjointed conversations? This video is your ultimate guide to building conversational AI that remembers, understands context, and transforms your projects into intelligent dialogues! We're diving deep into #LangChain and #TinyLlama to give your AI the memory it deserves. 🧠 In this hands-on tutorial, you'll learn: - How to set up your #GoogleColab environment for AI development. - Installing essential libraries like #AutoTokenizer and #AutoModelForCausalLM. - Loading the powerful #TinyLlama model for efficient text generation. - The magic of #ConversationBufferMemory for giving your AI memory. - Crafting effective #PromptTemplates for seamless dialogue. - Practical examples of how your AI can remember names and hobbies! Say goodbye to forgetful AI and hello to fluid, engaging conversations. This isn't just a tutorial; it's a transformation for your #AIProjects. 🔥 Next up: We'll explore how to teach your AI to read and understand PDFs! Stay tuned for Part 3! Resources: - LangChain Memory Docs - Tiny Llama Don't forget to like, comment, and subscribe for more AI tutorials! Let me know what you build! 👇 #AIChatbots, #ChatbotTutorial, #HuggingFace, #ConversationalAI, #AIWithMemory, #BuildAIChatbot, #AIDevelopment, #PythonProgramming, #GoogleColab, #TinyLlama, #LangChain, #AutoTokenizer, #TextGeneration, #NLP, #MachineLearning, #DeepLearning, #AIProject, #StepByStepTutorial, #CodingTutorial, #AIChatbotWithMemory, #ContextualAI, #EasyAITutorial, #AIForBeginners, #PracticalAI, #AIAplications, #AITools, #HowToCreateAIChatbots, #AIChatbotDevelopment, #CreateYourOwnAIChatbot, #PythonForAI, #FreeAITutorial, #LLM, #LargeLanguageModel, #MemoryAugmentation, #ConversationBuffer, #PromptEngineering, #ModelSelection, #ModelTraining, #AIModelDeployment, #DougOrtiz #dougortiz ▬▬▬▬▬▬ 👋 Contact Me ▬▬▬▬▬▬ ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ ▬▬▬▬▬▬ ⏱ Timestamps ▬▬▬▬▬▬ 00:00 Introduction: Solving AI's Memory Problem 00:23 Setting Up the Environment 00:41 Installing and Importing Libraries 01:13 Configuring the Model and Tokenizer 01:46 Building the Conversational Pipeline 02:03 Implementing Memory in AI 02:24 Testing and Verifying AI Memory 04:17 Conclusion and Next Steps

Build Your First AI in 15 Minutes! (Free LangChain and Google Colab Tutorial for Beginners) 🚀 Ready to build your first AI application but don't know where to start? You're in the right place! In this tutorial, we'll show you how to create a powerful AI in less than 15 minutes using Google Colab, LangChain, and Hugging Face. The best part? It's completely FREE, requires ZERO installs on your machine, and uses NO API keys. This means your project is 100% private and local to your environment. Perfect for beginners who want a hands-on AI project right now! You will learn how to set up your environment, install the necessary libraries, load a Large Language Model (LLM) like Tiny Llama, and execute your very first prompts to generate text, code, and more. Stop just watching and start building! 🔥 What You'll Accomplish in This Video: ✅ Set up a FREE GPU environment in Google Colab. ✅ Install essential AI libraries like LangChain and Hugging Face Transformers. ✅ Load and run a powerful, local Large Language Model (LLM). ✅ Build a complete text-generation pipeline from scratch. ✅ Run multiple AI prompts and get instant results. ✅ Understand the basics of LangChain as a framework for building AI apps. 👇 RESOURCES FROM THE VIDEO 🔗 Google Colab Notebook: https://github.com/illustris-admin/ai/tree/main/langchain-for-beginners 🔗 Tiny Llama Model on Hugging Face: https://www.google.com/url?q=https%3A%2F%2Fhuggingface.co%2FTinyLlama%2FTinyLlama-1.1B-Chat-v1.0 🔗 LangChain Documentation: https://www.google.com/url?q=https%3A%2F%2Fpython.langchain.com 🔗 Hugging Face Models: https://www.google.com/url?q=https%3A%2F%2Fhuggingface.co%2Fmodels 🔔 Don't forget to LIKE the video if you learned something new, COMMENT with what you're building, and SUBSCRIBE for more easy AI tutorials! #AITutorial #LangChain #HuggingFace #Python #AIforBeginners #GoogleColab #MachineLearning #LLM #AI #FreeAITutorial #AIProject #DougOrtiz ▬▬▬▬▬▬ 👋 Contact Me ▬▬▬▬▬▬ ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ ▬▬▬▬▬▬ ⏱ Timestamps ▬▬▬▬▬▬ 00:00 Introduction and Overview 00:35 Setting Up the Environment 01:11 Installing Required Libraries 01:50 Running the Model 02:49 Executing Prompts 03:44 Understanding LangChain 04:19 Summary and Next Steps 04:45 Conclusion and Resources 🔗 LET'S CONNECT: Website: https://www.illustris.org ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ // ABOUT THIS VIDEO This tutorial is a masterclass in prompt engineering for beginners and aspiring YouTubers. We cover how to write better ChatGPT prompts, the difference between vague and detailed AI instructions, and how to use AI for YouTube growth effectively. If you want to learn AI content creation and get ahead, this video is your starting point. YouTube Tags (Keywords): #ProductionAI #MachineLearning #MLOps #AIEngineering #TechReality #Doug Ortiz #DougOrtiz ProductionAI,MachineLearning,MLOps ,AIEngineering,TechReality,Doug Ortiz,DougOrtiz

The Rise of the Full-Stack ML Engineer 🤖 Is it the Future or a Burnout Trap? Are you a machine learning engineer feeling the pressure to do it all? You're not alone. In this video, we dive into the blurring lines between ML Engineering and MLOps and the emergence of the "full-stack" machine learning expert. From building models to deploying them with Docker, Kubernetes, and CI/CD pipelines, the expectations for ML engineers are higher than ever. We explore why companies are combining these roles, with some offering up to a 30% salary increase for this skill set. But what's the real cost? We discuss the risks of burnout, increased pressure, and the feeling of doing two jobs at once. Join the conversation and learn how to adapt to this evolving landscape without sacrificing your well-being. We share actionable tips on intentional learning, building a strong network, and taking on projects that bridge the gap between development and deployment. What do you think? Is the full-stack ML engineer the future of the industry, or are we setting ourselves up for an impossible standard? Let us know your thoughts in the comments below! 👇 full-stack machine learning engineer, machine learning engineer, MLOps engineer, machine learning, ML engineering, AI, artificial intelligence, data science, full-stack developer, software engineer, DevOps, Docker, Kubernetes, CI/CD, cloud infrastructure, fintech, tech startup, recruiting, job market, career advice, tech career, salary, high-paying jobs, work-life balance, time management, productivity, learning strategies, future of ML engineering, Reddit, tech trends, how to become a full-stack ML engineer, Doug Ortiz #fullstackmachinelearningengineer #machinelearningengineer #MLOps #machinelearning #MLengineering #AI #artificialintelligence #datascience #fullstackdeveloper #softwareengineer #DevOps #Docker #Kubernetes #CI_CD #cloudinfrastructure #fintech #techstartup #recruiting #jobmarket #careeradvice #techcareer #highpayingjobs #worklifebalance #burnout #timemanagement #productivity #learning #futureofML #Reddit #techtrends #MLjobs, #Doug Ortiz

Are you a Machine Learning Engineer feeling the pressure to do it all? Or maybe you're an MLOps specialist wondering where you fit in the future? The lines are blurring, and the era of the "full-stack" ML engineer is here. In this video, we dive deep into a major shift happening in the tech industry, especially within startups and agile teams. We'll explore why companies are ditching the traditional handoff between building and deploying models and instead, creating a single, powerful role. This video breaks down: 🚀 The "Why": Discover why CTOs and tech leads are combining ML and MLOps teams to eliminate bottlenecks. 🛠️ The Skill Set: Learn about the essential skills you need to thrive, from advanced modeling to Docker, Kubernetes, CI/CD, and cloud infrastructure. 💰 The Salary: Find out why companies are paying up to 30% more for this comprehensive skill set. 🥵 The Burnout Risk: We'll address the real-world pressures and the feeling of "doing two jobs at once." 🌱 Your Action Plan: Get actionable advice on how to adapt, learn intentionally, and protect your energy without burning out. Is this the future of machine learning careers, or are we creating an unrealistic ideal? Join the conversation in the comments below and let us know your thoughts! #MachineLearning, #MLOps, #MLEngineer, #DataScience, #AI, #TechCareers, #FullStackDeveloper, #Kubernetes, #Docker, #FutureOfWork machine learning, ml engineering, mlops, full stack machine learning engineer, full stack ml engineer, docker, kubernetes, cicd, cloud infrastructure, model deployment, machine learning jobs, tech jobs, high paying tech jobs, fintech, software engineering, data science, artificial intelligence, ai, youtube algorithm, video seo, content strategy, channel optimization, subscriber growth, watch time, youtube monetization, monetization tips for beginners, youtuber mistakes, youtube tips, growing on youtube, new youtuber advice, youtube growth, increase youtube subscribers, get more youtube views, youtube seo tips, future of machine learning, machine learning trends, tech career advice, career advice, programming, software development, developer skills, in demand skills, high demand jobs, tech industry, burnout, work life balance, time management, mentorship, reddit, community, tech community, learning resources, online learning, future of tech, tech future, technology trends, how to learn machine learning, machine learning tutorial, beginner machine learning, expert machine learning, machine learning tips, tech interview, job search, job hunting, salary negotiation, making money on youtube, youtube tutorial, youtube for beginners, new youtube channel, youtube channel growth, future of work, remote work, tech salaries, high paying jobs, how to get a job in tech, tech career path, machine learning career path, career development, professional development, skill development, upskilling, reskilling, coding, programming languages, python, r, java, cloud computing, aws, azure, gcp, devops, agile, scrum, software testing, data engineering, big data, Doug Ortiz

📝 UNLOCK THE SECRET OF REVERSE PROMPTING: Get EXACTLY What You Want from AI! 📝 Struggling with AI prompt writer's block? Say goodbye to vague AI responses! In this game-changing tutorial, I reveal the powerful technique of "reverse prompting" that will transform how you interact with ChatGPT, Claude, and other AI tools. ✅ WHAT YOU'LL LEARN: - How to turn AI into your personal interviewer - The 3-question framework that delivers precise results every time - Real before-and-after examples showing dramatic improvements - Time-saving techniques for better AI conversations This simple yet effective approach treats AI as a conversational partner that helps narrow down exactly what you need through strategic questioning. No more frustration, just tailored AI responses! #ReversePrompting #AIPractices #ChatGPT #AIPrompts #PromptEngineering #AIProductivity #Claude #AITips #AITools #PromptWriting #AIAssistant #AIEfficiency #AIforBeginners #AITutorial 🔔 Subscribe for more practical AI techniques to streamline your workflow! ▬▬▬▬▬▬ 👋 Contact Me ▬▬▬▬▬▬ ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ ▬▬▬▬▬▬ ⏱ Timestamps ▬▬▬▬▬▬ 00:00 Introduction: Facing the Prompt Writer's Block 00:27 Understanding the Importance of Specific Prompts 01:23 Introducing Reverse Prompting 01:51 Live Demonstration: Crafting a Tailored Prompt 03:15 Analyzing the Results 03:46 Final Tips and Takeaways 04:54 Conclusion and Community Engagement

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Extract Data from ANY Text with AI (ChatGPT JSON Prompt - NO CODE!) Transform Messy Text into Clean Data with AI (No Coding Required) Tired of manually copying data from emails, documents, and web content? This tutorial reveals the "JSON Extraction Prompt"—a powerful AI technique that instantly converts unstructured text into clean, structured data without any coding knowledge. In this video, I'll show you: ✅ How to extract specific data points from any text source ✅ A step-by-step implementation using ChatGPT or Claude ✅ Three critical tips to dramatically improve your results ✅ Real examples that reduced data processing time from 20+ hours to minutes This approach has helped automate their data extraction workflows, eliminate manual errors, and save countless hours of tedious work. Perfect for: ➡Business analysts ➡Customer service teams ➡Marketing professionals ➡Operations managers ➡Anyone who processes text data regularly 🔔 Subscribe for more practical AI techniques to streamline your workflow! #AITutorial #DataExtraction #BusinessAutomation #NoCode #ChatGPT #Claude #Productivity ▬▬▬▬▬▬ 👋 Contact Me ▬▬▬▬▬▬ ➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/ ✍️ Blog: https://dougortiz.blogspot.com/ ▬▬▬▬▬▬ ⏱ Timestamps ▬▬▬▬▬▬ 00:00 Introduction 01:06 The problem with unstructed data 01:47 The AI Extraction Solution 02:10 Implementation 03:15 Practical Tips 03:52 Conclusion

Unlock Better AI Results: The Prompting Secret You're Missing Still getting generic AI responses? 🤖 Your prompts might be the problem. This video reveals the simple secret to getting exactly what you want from AI tools like ChatGPT, Claude, and more. This video breaks down the difference between a weak, broad prompt and a powerful, specific one. Learn how to transform your requests by defining the target audience, the core focus (like machine learning), and the exact format you need. Stop wasting time with vague answers. Master the art of the prompt and start getting effective, targeted results today! 💡 If you found this tip helpful, hit LIKE and SUBSCRIBE for more tech insights! #AIPrompts #PromptEngineering #ArtificialIntelligence #TechTips #GenerativeAI #MachineLearning #ChatGPT #ProductivityHacks #FutureOfWork