Alejandro Saucedo’s Post

AI Video generation continues to blow our minds - this last week we saw Runway's Gen-3 Alpha breaking through with high fidelity multimodal video generation. AI generated video only continues to get better and better - this model supports text prompts as well as image and video inputs to steer the generaiton of the scenes and transitions. It's interesting to see the required collaboration of scientists, engineers, and artists - although quite a competitive spce, it's certainly one to keep an eye on as we can be sure new (competing) models will continue to pop up across various different organisations and platforms. Announcement: https://lnkd.in/eKYQSWwj -- If you liked this article you can join 60,000+ practitioners for weekly tutorials, resources, OSS frameworks, and MLOps events across the machine learning ecosystem: https://lnkd.in/eRBQzVcA #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps #augmentedintelligence #deeplearning #privacy #kubernetes #datascience #python #bigdata

Working with a wide array of LLMs and multi-modal models has allowed me to explore new possibilities in AI. From OpenAI’s GPT series and Google’s Gemini to Meta’s LLaMA and Anthropic’s Claude, these models offer unique strengths. Additionally, multi-modal models like OpenAI’s GPT-4o are redefining how we process and interpret both text and images, expanding the scope of AI applications. However, harnessing the true power of these models requires the right tools. My current stack includes: 🔹 Milvus - A robust vector database for fast and scalable similarity search across vast datasets. 🔹 LangChain - Facilitating complex workflows between LLMs, vision models, and external data sources, enabling the development of cutting-edge AI solutions. 🔹 LlamaIndex - Streamlining the creation of custom knowledge graphs and real-time query pipelines. 🔹 Python - A core language for everything from prototyping AI solutions to deploying production-ready models. 🔹 Argo Workflows - Automating and scaling workflows efficiently, especially in machine learning pipelines. By combining top-tier language and vision models with these advanced tools, it’s possible to push the boundaries of AI innovation and create scalable, adaptive systems that solve complex challenges. #GenerativeAI #LLMs #MultiModal #VisionAI #LangChain #Milvus #Python #AIengineering #Innovation

🚀 Exciting News in the Agentic AI space! 🚀 I'm thrilled to announce that I've open-sourced Atomic Agents, an AI Agent framework to build agents atomically! This framework is designed to be modular, extensible, and easy to use, providing a set of tools and agents that can be combined to create powerful AI applications. 🔗 Check out the project here: https://lnkd.in/ePeB4K7J For a quick start, dive into our notebooks: - Quickstart Notebook: https://lnkd.in/e7_RZHBs - Orchestration Notebook: https://lnkd.in/ecU6pCWt Explore more examples in the examples directory: https://lnkd.in/e6S64SPc Core Values of Atomic Agents: - *Modularity*: Build complex systems from simple, interchangeable components. - *Extensibility*: Easily add new functionalities and tools. - *Ease of Use*: Intuitive design and comprehensive documentation to get you started quickly. - *Flexibility*: Compatible with various APIs and models, including OpenAI, Cohere, Anthropic, and more. - *Reliability*: Built on top of robust libraries like Instructor and Pydantic for data validation and serialization. I welcome contributions and feedback to make this project even better. Let's build something amazing together! More example notebooks and a video going more in-depth into the framework will be out soon. #OpenSource #AI #MachineLearning #Python #DataScience #DeveloperTools

Join AI founder & Author of O'Reilly Book "Designing ML Systems" Chip Huyen at this upcoming ACM fireside chat discussing practical advice on "AI Engineering" moderated by IEML Founder and Zalando Director Alejandro Saucedo. This session will explore the unique challenges of productionizing foundation models compared to traditional machine learning models. Despite sharing some core principles, foundation models introduce new complexities due to their open-ended nature, advanced capabilities, and computational demands. Key changes include shifting from closed-ended to open-ended evaluation, from feature engineering to context construction, and from structured data to unstructured data. This will be a great session so don't forget to RSVP! Announcement: https://lnkd.in/djur27aj -- If you liked this article you can join 60,000+ practitioners for weekly tutorials, resources, OSS frameworks, and MLOps events across the machine learning ecosystem: https://lnkd.in/eRBQzVcA #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps #augmentedintelligence #deeplearning #privacy #kubernetes #datascience #python #bigdata

Here, we explain the subtle differences between LLMs, Copilots, RAGs, and Agents. Also, watch how we created an AI agent from scratch in Python that can query databases, analyze data, and make autonomous decisions based on user inputs. Plus, we showcase real-world use cases where Agentic AI can be used for customer service, financial management, education, and more. Video Link: youtu.be/dsbjMbK_9Gw   Channel Link: youtube.com/@datatrek #datatrek #datascience #machinelearning #statistics #deeplearning #ai

🔍 **Tech Tip of the Day: Leveraging AI for Data Cleaning** Cleaning your data is crucial before feeding it into an AI model. Did you know that using AI for this task can save massive amounts of time? Tools like Python's pandas library combined with AI algorithms can help identify and correct inconsistencies. ✅ Here's a quick procedure: 1. Import your data with pandas. 2. Use an AI-based anomaly detection algorithm to spot outliers. 3. Apply corrections or impute missing values. 4. Validate the cleaned data before using it for model training. Embrace the power of AI for efficient data prep! 🚀 #ArtificialIntelligence #TechTip #DataScience #MachineLearning #AI #BigData #Innovation #DataCleaning

If you would like to learn the fundamentals of building Generative AI and #LLM applications , I encourage you to please refer this 18-lesson comprehensive #GenAI free course by Microsoft https://lnkd.in/gwGvb4-x This course will teach you the concepts of generative models, large language models (LLMs), prompt engineering, and more. You will also get to build your own generative AI applications using Python or TypeScript, and access the powerful OpenAI models through Azure OpenAI Service or OpenAI API. The course is hosted on GitHub, which means you can easily fork the entire repository to your own account and work on the lessons at your own pace. There are also few other courses! Check out: ML for Beginners: https://lnkd.in/gRZYAhTU Data Science for Beginners: https://lnkd.in/g2iSaNyp AI for Beginners : https://lnkd.in/gxWRe2ir #AI, #machinelearning, #datascience

Level Up Your #MachineLearning Game! Hey LinkedIn fam! Check out this Machine Learning Cheatsheet that’s a must-have for anyone in the field—whether you’re just starting out or scaling AI models in production. This cheatsheet breaks down everything from: Gradient Descent Basics (because optimization is life!) Linear vs. Nonlinear Models (know when to use which!) Bias-Variance Tradeoff (the eternal battle we all face) And even the nuances of Advanced Algorithms like Random Forests and SVMs What I love most is how accessible and compact it is—perfect for quick refreshers during those intense work sprints. It even dives into practical pros/cons and use cases for each algorithm. A true lifesaver for machine learning practitioners. This isn’t just a summary; it’s a toolkit for solving real-world problems efficiently and effectively. What’s YOUR go-to resource for staying sharp in ML? #MachineLearning #AI #ArtificialIntelligence #DataScience #DeepLearning #BigData #TechInnovation #AIResearch #TechCommunity #TechLeadership #GradientDescent #RandomForest #SVM #MLTips #MLAlgorithms #Python #DataEngineering #TechSkills #FutureTech #DataAnalytics #LearnAI #DataVisualization #AITrends #CodingLife #TechResources #LevelUpYourSkills

🚀 Excited to announce major updates to Grami AI - The Modern Async AI Agent Framework! introducing Grami AI 0.2.0, bringing powerful async-first AI capabilities to Python developers. 🔥 What's New: • Comprehensive documentation at https://lnkd.in/dkqk2ntV • Production-ready async tools system • Flexible memory management with Redis support • Multi-provider LLM integration (Gemini, GPT, Ollama) • Type-safe interfaces throughout 💡 Key Features: • Built async-first for high performance • Modular, plug-and-play architecture • Production-grade error handling • Extensive tool ecosystem • Comprehensive type hints 🛠️ Perfect for building: • AI-powered research assistants • Data analysis pipelines • Multi-tool workflows • Custom AI agents 🔗 Resources: • Docs: https://lnkd.in/dkqk2ntV • GitHub: https://lnkd.in/d_buWVxp • GitHub Pages: https://lnkd.in/dPY3hHZM Join us in building the future of AI agents! Star us on GitHub and share your feedback. #AI #Python #OpenSource #AsyncProgramming #ArtificialIntelligence #Development #Innovation

🚀 Day 11: Becoming an AI Engineer through Self-Learning! Today, I focused on NumPy projects and began my journey into Pandas. ✅ NumPy: - Built a project manipulating matrices   - Solved NumPy questions and quizzes 📊 ✅ Pandas:  - Started learning Pandas, creating series in different ways   - Explored series attributes, indexing & plotted graphs 📈 Loving the journey so far! 💡 #AI #NumPy #Pandas #DataScience #AIEngineer #SelfLearning