Vishal Anand’s Post

🌐 [Post 2/3] In this second part of our series, I'm thrilled to invite you to explore our model on Hugging Face Spaces! 🚀 This user-friendly platform lets you test our innovative lipreading model firsthand. Dive in and experience its capabilities for yourself. 🧑💻 Don't forget to share your thoughts and feedback with us! Your insights are invaluable as they help us enhance our project. 💡 Let us know how it goes, and stay tuned for the exciting conclusion of our series where we'll reveal our findings and the valuable lessons we learned along the way. 🌟 #AI #MachineLearning #Lipreading #TechInnovation #UserExperience #HuggingFaceSpaces

Join me in celebrating the successful deployment of the Mistral 8x 7B model on Hugging Face Space! This state-of-the-art model, known for its exceptional capabilities in natural language processing, is now easily accessible for educational and fun use. The Mistral 8x 7B model, when used with Hugging Face's powerful platform, offers a unique opportunity for developers, researchers, and enthusiasts to explore, learn, and innovate. This deployment aims to lower the barriers to entry in the AI field, fostering a community that shares knowledge, ideas, and resources. Whether you're looking to dive into the world of AI, enhance your skills, or simply have some fun, this deployment is for you. Explore the Mistral 8x 7B model on Hugging Face Space today and let your AI journey begin! #HuggingFace #MistralModel #AIEducation #FunWithAI #GenAI https://lnkd.in/g4A5hCVS

🤖🚀#Cohere For #AI Launches #Aya23 : 8 and 35 Billion Parameter Open Weights Release! Cohere unveiled Aya 23, a groundbreaking family of #multilingual generative large language research models (#Aya Initiative - A global initiative led by Cohere For AI involving over 3,000 independent researchers across 119 countries) covering 23 different languages. This release includes both the 8-billion and 35-billion parameter models as open weights, showcasing commitment to advancing multilingual research. 🔍💡 Key Highlights of Aya 23: 🌐 Multilingual Excellence: Aya 23, built on the extensive Aya dataset collection, supports 23 languages, enhancing state-of-the-art language modeling capabilities for nearly half of the world's population. 📈 Superior Performance: The 35B parameter Aya 23 achieves the highest results across all benchmarks, excelling in tasks like natural language understanding, summarization, and translation. The 8B model offers best-in-class performance with reduced computational requirements, making advanced AI more accessible. 🔄 Efficient and Accessible: The 8B version of Aya 23 is designed for everyday developers, offering high efficiency and democratized access to cutting-edge technology, aligned with Cohere's mission to close the global AI research gap. 🔗 Experience Aya 23: https://lnkd.in/g3BJrfwZ 🔗 Learn More About Aya 23 and the Aya Initiative: https://lnkd.in/gGh_BG3W 📢 Join the Conversation! What are your thoughts on this exciting development in multilingual AI from the Aya Initiative? 🤝 Connect with us at ShellKode and explore the future of AI. hashtag #AIResearch #MultilingualAI #LanguageModeling #AICommunity #TechInnovation #CohereForAI #Aya23

NuExtract is a large language model developed by NuMind for structured information extraction from unstructured texts. Interestingly, this family of compact models often outperform larger models like GPT-3.5 and Llama3, setting new standards in the realm of data extraction. 🔧 How to Use NuExtract? * Define Your Schema: Create a JSON template that outlines the information you need. * Input Your Text: Provide the text from which you want to extract data. * Get Structured Output: NuExtract processes the text and outputs a structured JSON adhering to your schema. Try out NuExtract on HuggingFace - https://lnkd.in/gbsx-JTq Blog - https://lnkd.in/ghnaWB7j #DataScience #MachineLearning #AI #DataExtraction #NER #Innovation #NuExtract #TechTransformation

Exciting News🚀: I've Built Own Generative Al App with GUVI!!! I'm thrilled to share that I've developed a new Generative Al app using GUVI's RAG Al model. This app is designed to explain Al technology and techniques, offering insights into the world of artificial intelligence. 🤖What can the app do? - Provides detailed explanations of Al concepts. Helps users explore techniques in Al, from basics to advanced levels. Answers questions related to Al technologies and their real-world applications.("Fit Friend") 🔗Try it out yourself!!! https://lnkd.in/gFApqJ9U #guvi #genAi #womenempowerment #Tech #RAG #AI #app #ML #DP

A lot of noise about Luma AI's new Dream Machine video-generating AI software. And well-deserved, it’s pretty incredible (link to the intro video below). But let’s not forget about Luma’s app/API/process for developing NeRFs - it’s pretty mind-blowing too! All of which begs the question; Luma AI - is there a future in which NeRFs can be used as a stage to create Dream Machine AI videos with, within, or around? That would be spectacular! #lumadreammachine #lumaai #aivideo #wecandream

🤖 Latest #AI News Roundup: 1️⃣ Qwen QwQ-32B  2️⃣ ComfyUI BETA Desktop App 3️⃣ Claude - Create Custom Style 4️⃣ Runway Expand [but NO Frames] 6️⃣ Anthropic Model Context Protocol 7️⃣ Open AI Last Chance Reasoning Model o1  8️⃣ Luma Dream Machine Photon image AI model #AINews #TechNews #MachineLearning

𝐓𝐡𝐞 𝐜𝐨𝐮𝐧𝐭𝐝𝐨𝐰𝐧 𝐡𝐚𝐬 𝐛𝐞𝐠𝐮𝐧....16 𝐡𝐨𝐮𝐫𝐬 𝐛𝐞𝐟𝐨𝐫𝐞 𝐰𝐞 𝐠𝐨 𝐥𝐢𝐯𝐞 𝐰𝐢𝐭𝐡 𝐨𝐮𝐫 #PH 𝐥𝐚𝐮𝐧𝐜𝐡. A lot of hard work has gone in to build this new exciting product and we believe it could be a game changer for many of you. Adding a completely new dimension to debugging on mobile…..Oops 🤫 #productlaunch #producthunt #mobile #AI

Introducing the Face Beauty Rating Model! I’m thrilled to share my latest project—a Face Beauty Rating Model that combines deep learning and facial symmetry analysis to predict beauty scores based on key facial features! What is it? This model uses a pre-trained ResNet50 deep learning architecture, fine-tuned on the SCUT-FBP5500 dataset, to evaluate and score facial beauty. To enhance the analysis, I've integrated facial landmark detection using Dlib, which evaluates the symmetry and proportions of key facial features like the eyes and nose. The result? A combined beauty score based on both machine learning and facial feature symmetry. 💡 How does it work? Deep Learning Score: A model trained on facial beauty data provides a score based on learned patterns of attractiveness. Facial Feature Scores: The model also computes separate scores for eyes and nose symmetry and combines them for a final score. 🏆 Why is it exciting? Innovation: This project leverages both classical and modern techniques to provide a well-rounded analysis of facial beauty. It’s a practical example of how AI can evaluate aesthetic concepts using data-driven approaches. Entertainment: The model is designed for fun and entertainment purposes only. It’s not meant to define anyone’s beauty, but it’s a fascinating experiment in applying AI to subjective measures. 👨💻 Try it out! You can try out the model and see your own results by uploading an image. It’s live on Hugging Face Spaces—check it out below: Note: Please upload a clear, front-facing photo where the face is fully visible and not obstructed. Ensure good lighting and that the face is not too angled or cropped. The model requires the face to be properly aligned to detect landmarks such as the eyes and nose accurately visible. you can share your experience by liking or disliking🤪, by comments. Thanks 🙏 or reach out me by: kumargirish.rama@gmail.com 🔗 https://lnkd.in/giT44P8q #AI #MachineLearning #DeepLearning #FacialRecognition #BeautyAI #Innovation #HuggingFace #Dlib #ComputerVision #ArtificialIntelligence