Khatuna Kurdovanidze’s Post

🚀 Just completed the "Large Multimodal Model Prompting with Gemini" course from DeepLearning.AI! 🎉 In this course, I delved into the Gemini model, exploring its capabilities in multimodal prompting and parameter control. I learned how to create use cases with images and video and integrate real-time data using function calling. The hands-on experience with these advanced techniques has been invaluable! The course provided a solid understanding of how Gemini can enhance model performance by leveraging multimodal inputs and dynamic data integration. I'm excited to apply these skills in upcoming projects to gain practical experience and further deepen my expertise. 🚀📈 #MachineLearning #AI #DeepLearning #Gemini #MultimodalAI

I’m thrilled to share that I have completed a certification in Large Multimodal Model Prompting with Gemini from DeepLearning.AI !!! 🚀 #AI #DeepLearning #Gemini #MultimodalModels #ArtificialIntelligence

This is a beginner-level course, and if you already have some experience, you might find it helpful to simply review the codes in the notebook. - Key Takeaways One of the most important things I learned is that the order of prompts significantly impacts the performance when using a Large Multimodal Model (LMM). - Feedback on Gemini LMM API One aspect I dislike about the Gemini LMM API is its approach to function calling. I would prefer using separate function calls to retrieve real-time data and then consolidating that data into the prompt before calling Gemini LMM API. #LMM #LargeMultimodalModel #AI #Gemini #DeepLearningAI

Just finished a course on Large Multimodal Models (LMMs)! 🤯 These AI beasts aren't just for text! 🎨🎥 I learned the following which is also applicable when working with Large Language Models (LLMs): * Give them context: Let them know what's going on. * Assign a role: Tell them who they're playing. * Be clear and specific: No beating around the bush. * Set expectations: Tell them what you want, and how you want it. And when working with images and videos, I learned to * Show & tell: Load the image or video first; provide some context. * Break it down: Simplify complex tasks for better results. Ask complex questions one at a time. #LMMs #GenAI #PromptEngineering

Great course for anyone hoping to learn the capabilities of multimodal AI!

Thanks to DeepLearning.AI for offering such a valuable learning experience!

Excited to announce I've completed the Large Multimodal Model Prompting with Gemini course from deepLearning.ai. Learned about multimodal models, prompt engineering, and integrating Gemini with external APIs and databases. Grateful to instructors Erwin Huizinga & Andrew Ng for their expertise. Highly recommend this course to anyone interested in learning more about multimodal models and prompt engineering. #large_multimodal_model #prompt_engineering #gemini #deep_learning #artificial_intelligence

🌍 Geospatial intelligence and AI in SAR Earth observation markets 🌍 In this episode, Claude Rousseau, speaks with Minda Suchan, Vice President of Geointelligence at MDA Space. They discuss the intersection of geospatial intelligence and AI in the synthetic aperture radar (SAR) Earth observation (EO) market. Minda shares her knowledge and perspectives on: Complexity in SAR Image Processing: How the complexity in SAR image processing is affecting adoption and insights, and how to remove these complexities with AI/ML in end-user downstream analytics markets. Generative AI (GenAI) Differentiation: The differentiation that GenAI can bring to customers’ applications in addition to enabling deep learning for insight generation. AI Use Cases: The use cases that AI enables, and which use cases will be slow to adopt the technology. AI/ML Advancements: How AI/ML is moving towards self-learning while also automating processes for geospatial intelligence. ChatGPT-like Platforms in EO: When we might see ChatGPT-like platforms being adopted in EO. Top Recommendations: The top three recommendations for anyone looking to implement AI/ML in the EO value chain. Tune in to gain valuable insights and learn how AI is reshaping the geospatial intelligence and SAR EO markets. Find out more about our Earth Observation programme: https://lnkd.in/eewHzNTn Analysys Mason https://lnkd.in/ePU8VyaK

Developing a model is cool, but building AI models that will run in space is cooler! 🛰️ Excited to announce the EO Onboard Edge AI Models #GrandChallenge in collaboration with Let's Talk Spatial and IEEE Geoscience and Remote Sensing Society (GRSS) GRSS. Calling all geospatial developers to join us on this thrilling journey of developing and testing models for edge computing in space.🌌 #SpaceAI #EdgeComputing #GeospatialTech"

Claude's Game-Changer: Discover the Power of Anthropic's Model Context Protocol (MCP) | DemoHub.dev #mcp #ai #genai #aiassistants #anthropic https://lnkd.in/gmdX3ycH