🚀 Just listened to fantastic podcast episode from BG^2 where they spoke to Jensen Huang of NVDA — mind-blowing insights on AI and the future of computing! 🤯 If you’re into AI or NVIDIA’s advancements, this is a must. It’s a window into the next decade of tech. https://lnkd.in/ga4pih_W What do you think the impact of these AI developments will be in various sectors? #AI #NVIDIA #FutureOfCompute #AGI #TechTalks
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🚀 NVIDIA Just Released a Game-Changer! 🖥️ NVIDIA has casually dropped a 70B open-source model that outperforms the giants in the AI world, including OpenAI's GPT-4.0 and Anthropic's Claude 3.5! This marks a huge leap in the open-source community and AI development, offering cutting-edge innovation with accessibility for everyone. 🌍✨ 🔗 Why is this important? A new frontier for developers to push the limits of AI.Opens up competitive possibilities in AI research.Enhances AI capabilities for numerous industries. Exciting times ahead for the AI space! What are your thoughts on this breakthrough? 💭 #NVIDIA #AI #OpenSource #Innovation #TechNews
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Learn how to use nvidia rapids to accelerate computing - Path to AI
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🚀 Excited to share updates from #Day12 of my #100DaysOfALXSE journey! 🎉 Just wrapped up watching the replay of Nvidia GTC's conference "What's Next In Generative AI," and the insights were really interesting. 😁 Highlights included: 🔍 Gaining valuable insights into OpenAI’s vision for the future of the market. 🌐 Exploring practical applications and real-world examples of AI tools. 💡 Anticipating the emergence of revolutionary apps reshaping industries. 🌱 Addressing societal implications and key issues surrounding AI adoption. 💼 Learning about OpenAI's strategies for scaling AI tools effectively. Huge thanks to Brad Lightcap, COO at OpenAI, and Manuvir Das, VP of Enterprise Computing at NVIDIA, for their enlightening talk! 🙌 Stay tuned for more updates on my #100DaysOfALXSE journey! 🚀 #ALX #ALX_SE #DoHardThings #GenerativeAI #NvidiaGTC
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🚀 Big News in AI! 🚀 I'm so excited about Nvidia's latest release: the NVLM 1.0 family of massive multimodal language models, featuring the game-changing NVLM-D-72B! With 72 billion parameters, this model is an absolute powerhouse, pushing the boundaries of vision-language tasks while enhancing text-only capabilities—a feat that most similar models struggle with. What really sets this apart is Nvidia's decision to open-source the model weights and promise the release of the training code. This move breaks from the industry's tendency to keep cutting-edge AI models proprietary, giving researchers and developers unprecedented access to advanced technology. Imagine the possibilities: interpreting memes, analyzing complex images, solving intricate math problems step-by-step, and more—all with impressive precision! It's going to revolutionize not just how we approach AI research but how AI integrates into real-world applications. I can't wait to dive deeper into this model and explore the innovative opportunities it opens up for the future. 🌟 #AI #Nvidia #NVLM #MachineLearning #GPT4 #OpenSourceAI #Innovation #AIResearch
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With so many players in the generative AI space, it's getting harder to keep track! What are your favorite tools and platforms? Let's dive into the generative AI ecosystem! This visual breaks down key players in different categories: Application: Microsoft Copilot, Jasper, Adept, Synthesia, Vic.ai Deployment: LangChain, LlamaIndex, Metal Evaluation: PromptLayer, Vellum, HoneyHive, Gentrace, baserun.AI Security: Arthur, Credal.ai, CalypsoAI, WhyLabs, Kobalt.io Data: Pinecone, Databricks, mawticios, gretel, Scale AI Models: OpenAI, Anthropic, Hugging Face, Stability AI Compute: NVIDIA, arm, CoreWeave, WMODAL, BANANA Share your thoughts below! #GenerativeAI #AI #MachineLearning
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Learn more about #FlashStack for AI and the build/operate/update roadmap of delivering private AI solutions in your enterprise. @purestorage @ciscodc #AI
GenAI, RAG, Say What? Going beyond the AI Buzzwords to Business Value
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🔥 Nvidia Nemotron is here, and it's setting new benchmarks! Outperforming both GPT-4o and Claude Sonnet 3.5, this model takes AI capabilities to the next level. If you're excited about the future of AI, you’ll want to keep an eye on Nemotron’s performance. 🔍 Check out the model: https://lnkd.in/dgpwAEmC You can download weights from Huggingface 🤗 : https://lnkd.in/dfsq2_Ti With impressive advancements, Nvidia Nemotron pushes the limits of machine learning, offering new possibilities for understanding and generating human-like responses. 💡 What are your thoughts on this new contender in AI? #AI #Nvidia #MachineLearning #HuggingFace #Innovation
llama-3_1-nemotron-70b-instructand model by nvidia | NVIDIA NIM
build.nvidia.com
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Unleash the power of innovation with this all-in-one GPU platform, designed to fuel your groundbreaking endeavors - whether you're unlocking the secrets of the universe through scientific research or accelerating AI apps. Witness dramatic speedups and revolutionize your work now: https://lnkd.in/gDd4c-zA #innovation #scientificdiscovery #aiapplications
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The NVIDIA Video Search and Summarization Blueprint has been unveiled, offering a cutting-edge solution for analyzing both live and stored videos to derive valuable insights. The blueprint focuses on two key functionalities: 1) Summarization - Condensing lengthy video content into concise summaries. 2) Interactive Q&A - Enhancing engagement by facilitating interactive question and answer sessions. Experience the power of this technology firsthand by accessing it online at build.nvidia.com. Learn more: https://lnkd.in/gN2ybYth #VLM #nvidiavia #nvidiametropolis #nvidia #visualinsights #visionai #videosummarization #ai #videoanalytics #computervision
nvidia model by video-search-and-summarization | NVIDIA NIM
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I'm happy 🎉 to share that I've achieved the "Generative AI with Diffusion Models" certification from NVIDIA Big thanks to Kaleb Smith, Ph.D. Smith for his insightful instruction and to Yang Hong for her invaluable support throughout this learning experience. Key takeaways include: - Building 𝗨-𝗡𝗲𝘁𝘀 for image generation from noise. - 𝗘𝗻𝗵𝗮𝗻𝗰𝗶𝗻𝗴 𝗶𝗺𝗮𝗴𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 using the denoising diffusion process. - Exploring various 𝗱𝗶𝗳𝗳𝘂𝘀𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹s like DDPMs and DDIMs. - Utilizing 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀 to manipulate image outputs. - 𝗧𝗲𝘅𝘁-𝘁𝗼-𝗶𝗺𝗮𝗴𝗲 generation using CLIP (Contrastive Language - Image Pretraining) Link: https://lnkd.in/eChFyMjf Excited to harness these skills in creating transformative AI-driven projects! Let's connect to explore the future of AI! 🚀 #generativeai #diffusionmodels #nvidia #aiinnovation #machinelearning #deeplearning #cuda #artificialintelligence #texttoimage
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