Intel Labs’ Post

Marius-Constantin Dinu and Claudiu Leoveanu-Condrei share with us the latest features of SymbolicAI, a LangChain alternative which uses Large Language Models (LLM) to power functions and various interfaces like OCR, Whispr to power multi-modal inputs. We talk about how we can do automatic Retrieval Augmented Generation from a text file/pdf file using DocumentRetriever(). At the backend, the document is split into chunks and OpenAI Embeddings are done for you, and when queried, the cosine similarity to retrieve top k chunks are all done automatically. We also go through multi-modal input processing using the OCR and Whispr interfaces. This converts various other domains into text, which can be processed easily by an LLM. Lastly, we also share how we can customize your own functions/expressions and use the command prompt to run them without using Jupyter Notebook. For more details, do watch the tutorial at: https://lnkd.in/gVjzZZut Notebook can be downloaded at: https://lnkd.in/gEaViYBe

Hello Everyone, Are you looking to understand how to leverage Llama 2 for topic modeling? This fantastic video has got you covered! 🌟 In this tutorial, you'll see how Llama 2, an open-source large language model, clusters thousands of documents into a few easily interpretable topics. Using the BERTopic framework, keywords are extracted from each topic, and Llama 2 helps to interpret them more clearly and intuitively. The video also covers using Google Colab and the importance of a GPU to run large models like Llama 2 efficiently. With over 100,000 abstracts from academic papers, this tutorial shows how effectively these techniques provide meaningful topic labels. I highly recommend this video for anyone interested in topic modeling or looking to enhance their understanding of using large language models in text analysis. Check out the video here: https://lnkd.in/gDcjdS3e Happy watching, and enjoy the insights! 🚀

Elevate Your Object Detection and Tracking: Explore AS-One Library in this Computer Vision Tutorial! Join us for an exciting tutorial on Object Detection and Tracking with AS-One Library, your gateway to advanced computer vision applications! Discover the capabilities of AS-One as we guide you through the process of implementing object detection and tracking for enhanced visual analysis. https://lnkd.in/dT9diuGt 5 In this comprehensive guide, we'll delve into the features of AS-One, showcasing its effectiveness in object detection and tracking. Whether you're a computer vision enthusiast, a developer, or just eager to enhance your tracking skills, this tutorial is designed for you! Ready to level up your tracking game? Watch now and immerse yourself in the world of Object Detection and Tracking with AS-One Library! Don't forget to hit subscribe for more captivating tech tutorials! #ASOneLibrary #ObjectDetection #Tracking #ComputerVision #TechTutorial #VisualAnalysis #AI #PythonProgramming #AdvancedCV

Exciting News for Tech Enthusiasts! Unleash the power of Computer Vision with our latest tutorial: "Object Detection and Tracking with AS-One Library - A Step-by-Step Guide" What's Inside: Introduction to AS-One Library and its capabilities. Step-by-step guide on object detection and tracking. Real-world applications and use cases. Watch Now: https://lnkd.in/dNy-8Y_2... Why AS-One Library? AS-One Library takes your computer vision projects to new heights! Learn how to detect and track objects seamlessly in your applications. Who Should Watch: Whether you're a developer, hobbyist, or anyone curious about computer vision, this tutorial is tailored just for you. Engage with Us: Have questions or want to share your insights? Drop a comment below the video and let's spark a conversation! Ready to Elevate Your Computer Vision Skills? Dive into the tutorial now and unlock the world of Object Detection and Tracking with AS-One Library! #ComputerVision #ASOneLibrary #ObjectDetection #Tracking #TechTutorial #LearnCoding #AI #DeveloperCommunity

Image Embeddings for Enhanced Image Search: An In-depth Explainer #ImageEmbeddings are the core of modern #computervision algorithms. Understand their implementation and use cases and explore different image embedding models. ➡️ Understanding Image Embeddings ➡️ Traditional #Embedding Methods ➡️ Breakthroughs with #DeepLearning ➡️ The Rise of Transformers in #ImageProcessing ➡️ Multi-Modal Approaches with CLIP ➡️ Advanced Embedding Techniques ➡️ The Integration of Embedding Models with Vector Databases ➡️ Building a Robust Image Search System ➡️ Testing and Optimizing your Image Search System: ➡️ Use Cases and Real-world Link in the first comment.

🌟 Dive into the fascinating world of image similarity estimation with my latest project: "Fuzzy Pattern Recognition System using Image Similarity"! 📸 In this project, I've harnessed the power of fuzzy logic to precisely gauge the likeness between grayscale images, overcoming the challenges posed by uncertainties and imprecise data. 💡 Key Highlights: 🔹 Leveraging NumPy, scikit-fuzzy, Pillow, and Matplotlib libraries for robust implementation. 🔹 Crafting a sophisticated fuzzy system with inputs like image disparity and edge coherence, culminating in a comprehensive similarity metric. 🔹 Unveiling the intricacies of image processing, from grayscale conversion to edge detection and feature alignment. 🔹 Employing the Mamdani method for fuzzy inference, ensuring precise computation of image similarity. Experience the project in action as it seamlessly computes and visualizes the similarity between two images, unlocking a myriad of applications in image processing, pattern recognition, and beyond. 🚀 #FuzzyLogic #PatternRecognition #ComputerVision

Retrieval Augmented Generation (#RAG) is one of the most trending topics in search. But how does this innovative approach redefine information interaction? Discover everything about RAG in this 4-hour intensive session, and learn: - RAG optimization techniques with additional focus on prompt engineering - RAG implementation with snippets of code - RAG best practices, applications, and challenges 🌐 Live on Zoom 🗓 13th March 2024 🎟 1 ticket: 120 GBP - 3 tickets: 290 GBP Discover more and book your seat: https://lnkd.in/dkjZmeTv #retrievalaugmentedgeneration

Dijkstra's Algorithm was invented in 1959.. People Before 1959: #DijkstrasAlgorithm #GraphTheory #ComputerScienceHistory #Algorithms #Pathfinding #ShortestPath #TechInnovation #ProgrammingHistory #ComputerScience #TechMilestones

Title: Generating Stunning Images from Text Prompts with Stable Diffusion 3 Medium Excited to share my latest project on text-to-image generation using the powerful Stable Diffusion 3 Medium model! 🖼️ In this comprehensive step-by-step guide, I walk through how to set up the project environment, implement a Gradio app for generating images from text prompts, and leverage the advanced capabilities of the Stable Diffusion 3 Medium model. Key Highlights: - Learn about the core features and capabilities of the Stable Diffusion 3 Medium model - Follow along as I create a project environment, install required libraries, and generate Hugging Face access tokens - Dive into the implementation details of the image generation function using the `StableDiffusion3Pipeline` - Discover best practices for optimizing your setup and ensuring smooth execution of the model - See the stunning results of generating images from sample prompts like "Indian cricket team winning world cup" Check out the full tutorial on my YouTube channel: https://lnkd.in/gcNbFHHT Links: Hugging Face App URL: https://lnkd.in/gubkVZKt GitHub Repository: https://lnkd.in/g6jGk9YV LinkedIn Profile: https://lnkd.in/g4qAzxDN Medium Blog: https://lnkd.in/ghhPepFh I'm excited to share this knowledge and empower the community to explore the creative possibilities of Stable Diffusion 3 Medium. Let me know if you have any questions or feedback! #StableDiffusion #AI #MachineLearning #DeepLearning #TextToImage #ImageGeneration #ArtificialIntelligence #DataScience #HuggingFace #Python #Gradio #Tutorial #TechGuide #AIArt #AIResearch #ML #DL #gradio #huggingFace #python #openSource #appDevelopment #AIEnthusiast #ITAIEnthusiast #GenerativeAI #aiEnthusiast #itaienthusiast #generativeai

Unlock Object Detection and Tracking Mastery with AS-One Library! Attention Computer Vision Enthusiasts and AI Developers! Explore our latest tutorial: "Object Detection and Tracking with AS-One Library - Computer Vision Tutorial! " https://lnkd.in/dNy-8Y_2... Ready to take your object detection and tracking skills to the next level? In this comprehensive tutorial, we'll introduce you to the AS-One Library, a powerful tool for seamless object detection and tracking in computer vision applications. Say hello to precise and efficient object tracking with this essential guide! What's Inside: Introduction to AS-One Library and its Features Step-by-Step Object Detection and Tracking Implementation Hands-on Examples and Use Cases for AS-One Library Ready to revolutionize your approach to object detection and tracking tasks? Dive into our tutorial now and learn how to leverage the AS-One Library for accurate and robust object tracking! Don't forget to share with fellow developers and tap the bookmark button for future reference. Share this post with your developer community, AI enthusiasts, and anyone eager to master object detection and tracking with the AS-One Library! Let's innovate together and push the boundaries of computer vision technology. #ObjectDetection #Tracking #ComputerVision #ASOneLibrary #TechInnovation