❓ How to do more with the simulations and data you already have? The obvious answer is Ansys TwinAI! 👇 1️⃣ Bring your physics or data into TwinAI through Reduced Order Models 2️⃣ Incorporate sensor data to improve the model through AI 3️⃣ Scaled deployment on the Cloud or on the Edge #digitaltwin #digitaltwins #AI #hybridanalytics
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CMATER student, Department of Computer Science and Engineering, Jadavpur University, Kolkata | Undergraduate Computer Science and Engineering, RCCIIT, Kolkata | Machine Learning | scikit-learn, Python | AI | Tableau | C
Excited to embark on a journey into the future of digital creativity with Google Cloud Skill Boost! 🚀 Just completed the Image Generation course and feeling inspired by the possibilities of AI. #GoogleCloud #AI #ImageGeneration #SkillBoost #TechInnovation #LifelongLearning 🌟
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UBITECH introduces a scalable and fully generalizable AI Theoretical Framework. The framework is an AI-verified software solution and benchmarking tool that enables the measurement, storage, and visualization of energy consumption and hardware resource utilization during AI models' preparation and training phase at edge and cloud contexts. The framework leverages containerization to encapsulate AI model training. It deploys it within a Kubernetes cluster and benchmarks several widely used AI algorithms across different data modalities, including tabular, image, and time-series data.
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🌫️ Fog Computing is revolutionizing how we approach Machine Learning at the edge! In the realm of machine learning, Fog Computing acts as a critical intermediary layer between cloud data centers and hardware devices. It enables faster processing and analysis of data by bringing computational resources closer to where data is generated, thus reducing latency and bandwidth use. This decentralized approach not only enhances real-time analytics and decision-making in AI applications but also addresses privacy concerns by processing sensitive data locally. With Fog Computing, machine learning models can be trained and updated more efficiently, leading to smarter and more responsive AI systems. Consider checking out MLNOW.ai if you're learning this stuff, and follow me for more! #machinelearning #ai #datascience
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Read part 2️⃣ of Zilliz CEO, Charles Xie's blog series where he jumps into the evolution of AI technologies, discussing the critical role vector databases play in the age of Foundation Models. Key highlights ⬇️ : ▪️ Zilliz's pioneering #Milvus vector database paved the way for efficient unstructured data management pre-LLM era. ▪️ Transitioning to democratize AI through accessible solutions like Zilliz Cloud. ▪️ Vector databases are crucial knowledge reservoirs for LLMs, boosting retrieval-augmented generation (RAG) accuracy. ▪️ Milvus 3.0's hybrid search to achieve 80% RAG retrieval accuracy. ▪️ The future vision of Affordable General Intelligence (AGI) through efficient data management. https://bit.ly/43XrwE3
The Evolution and Future of AI and Its Influence on Vector Databases: Insights from Charles, CEO of Zilliz - Zilliz blog
zilliz.com
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Level Up! Just earned my badge for "Introduction to Image Generation" on Google Cloud Skills Boost Lab Excited to dive deeper into the world of AI-powered image creation! This badge course provided a fantastic intro to the potential of image generation models and the creative possibilities they unlock. #GoogleCloud #AI #MachineLearning #ImageGeneration
Introduction to Image Generation
cloudskillsboost.google
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AI is growing at a frenetic pace - just look at how things changed over the course of 2023! So, what AI developments should we expect in 2024? In this online video session, IBM Master Inventor Martin Keen discusses this very topic and offers nine trends to watch out for in 2024 ... and possibly a 10th? 9 Topics & Trends : - Reality Check - Multimodal AI - Smaller Models - GPU + Cloud Costs - Model Optimization - Custom Local Models - Virtual Agents - Regulation - Shadow AI Note : Upon registration, a userid and password will be provided for login access to watch the online video session. https://lnkd.in/gu62qXwb
Top AI Trends of 2024
eventbrite.sg
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🌟 Exciting Update! 🌟 Excited to share that Apoorva Uppalapu, PM at Microsoft, will be joining us at the upcoming Generative AI Day in Guntur! 🚀 Apoorva will enlighten us about Azure and Copilot, showcasing the latest innovations and possibilities in AI-driven development. This event just got even more exciting with Apoorva's insights and expertise added to the agenda. 📅 Save the date: Generative AI Day Location: Guntur Date: 29th April 2024 Let's dive into the world of AI with Azure and Copilot! See you there! 🌍🔗 #GenerativeAI #Azure #Copilot #AIInnovation #TechLeadership #Guntur
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How to Get GPU Recommendations with Cloudwatch and Nvidia Agents Discover how to easily obtain GPU recommendations with the Cloudwatch agent. In this insightful clip, our experts delve into the necessities for leveraging this powerful tool efficiently. For the full episode, visit: -Youtube: https://lnkd.in/g6kSWp5d -LinkedIn: https://lnkd.in/gKYJDKPR Check out the CloudFix announcement on GPU Finder/Fixers: https://lnkd.in/gHqhwZUb #aws #finops #costoptimization #awsmadeeasy #cloudfix #AI #optimization
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Python Programmer, Data Analyst, Aspiring Business Analyst, Aspiring Project Manager, Engineering student
This course taught me; How to explore diverse applications of AI across various industries. Understanding concepts like Machine Learning, Deep Leaning, training and inference. Trace the evolution of AI Technologies. From its inception to the revolutionary advances brought by Generative AI, and the role of GPUs. How to become familiar with deep learning frameworks and AI software stack. To learn about considerations when deploying AI workloads on a data center on prem, in the cloud, on a hybrid model, or on a multi-cloud environment. #Nvidia
Completion Certificate for AI Infrastructure and Operations Fundamentals
coursera.org
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Utilizing our e-AI translator tool on our RA6M5 cloud kit bridges the gap between the cloud and the edge, seamlessly unlocking AI inference on resource-constrained MCUs and MPUs. This specialized tool translates trained models from PyTorch, Keras, TensorFlow, and TensorFlow Lite into programs tailored for embedded systems. By prioritizing code efficiency and minimal footprint, this tool empowers even the most compact devices with intelligent capabilities – from voice recognition and anomaly detection to predictive maintenance and intelligent sensor processing. Swipe through to see the process and visit the link in the comments to learn more! #AI #semiconductors
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