Eric Malmi

As AI evolves, so does its ability to tackle complex scenarios. Graph RAG systems are at the forefront of this transformation, promising to enhance how we interconnect and utilize knowledge across industries. Read more from Brian Godsey, PhD now! #RAG

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Image compression is key in computer vision, making it possible to store and transmit images efficiently while preserving quality. Learn all about image compression with OpenCV in this latest article by Jeremy Morgan. 🔗 Read here: https://hshno.de/01euoNm

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🤷‍♂️Why is #syntheticdata so helpful for training #computervision, and how does it compare to real data📡?? To maximize efficiency and output💪and reduce training costs💰, there is a time and a place for each.💚Learn more in the latest Rendered.ai blog! Read our blog now📣: https://buff.ly/3VfN4b1 Real #sensor data is vital for training algorithms👍but comes with its own set of challenges👎: 🚨Acquiring and processing real data can be expensive and time-consuming 🚨Insufficient data for algorithm training and validation, such as for projects dealing with new sensor types for which real data does not currently exist 🚨Lack of ability to control bias easily or cost-effectively 🚨Inaccuracies in data labeling, compromising the effectiveness of training algorithms and complicating dataset integration. 🚨The risk of using real data with significant privacy and security concerns, limiting the ability to share and use data to train algorithms. Adding physics-based synthetic data🚀to #artificialintelligence and #machinelearning systems during development and reiterative training💥solves these real data problems with: ⭐Cost-Efficiency: Synthetic data generation typically costs a fraction of acquiring real sensor data. ⭐Customization: Datasets tailored to specific requirements reducing post-processing time. ⭐Controlled Bias: With synthetic data, users can control the distribution of objects and scenarios in their data to add controls for specific training needs. ⭐Innovation: Ability to facilitate experimentation with edge cases and scenarios where real data is scarce or completely unavailable. ⭐Risk Mitigation: Synthetic data eliminates the risks associated with using sensitive real-world data. But what exactly is "physics-based" synthetic data🤔? Dive further into this and explore🤓 tips from experts currently using synthetic data in computer vision today! https://buff.ly/3VfN4b1 ⌛It's a great time to try synthetic data generation for yourself through the Rendered.ai #PaaS.⚡Activate your free trial (https://buff.ly/45kzU0X) or request a demo with one of our synthetic data experts (https://buff.ly/3XcW0AG)! Space Capital Union Labs Ventures Marlinspike Congruent Ventures Tectonic Ventures In-Q-Tel (IQT) #NVIDIAInception AI Partnerships Corp.

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Do you know the secrets behind effective image shape detection with OpenCV? Read our latest blog to uncover the techniques for reading and detecting shapes in images, practical applications, and how OdiTek can enhance your projects with OpenCV. https://lnkd.in/gdw8SrpQ #OpenCV #ImageProcessing #ComputerVision #ShapeDetection #TechInnovation #ReadImage #Image #Shape #OdiTek

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At this #OCPSummit2024 session, learn how NVIDIA is accelerating #quantumcomputing research, including new methods of using #AI models to develop novel quantum algorithms. Register now and learn more at our session on October 16: https://nvda.ws/4f0YA2l

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In this work, the authors propose a #machine-#learning-based framework called #ReLy that intelligently embeds the time-critical messages in the preamble of outgoing frames at the transmitter. These messages are inferred from the channel state information variations at the receiver. As ReLy is implemented entirely at the #physical #layer, the transmitter is able to deliver information within 5 ms latency and ultra-high reliability of 99 percent. They experimentally demonstrate the feasibility of achieving #ultra-#reliable #low-#latency #communication (#URLLC) with moving robots in a busy workshop with a number of other peer robots, equipment, desks, and robotic arms, as expected in a typical factory setting. ---- Kunal Sankhe, Ph.D., Dheryta Jaisinghani, Kaushik Chowdhury More details can be found at this link: https://lnkd.in/dnhrv_ip

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Develop AI apps faster with NVIDIA AI Workbench, part of RTX AI Toolkit 🙌 Learn more in this week's #AIDecoded blog 👉 https://nvda.ws/3xmU1ix ✍️ Build custom AI projects | 👥 Seamless collaboration | ☁️ Local to cloud scaling | ⚙️ Easy model fine-tuning | 🚀 Deploy anywhere

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If you're curious about RAPIDS Libraries, José Carlos Gonzáles Tanaka delivers practical examples in this QuantInsti tutorial: https://lnkd.in/eYs6ce2N #MachineLearning #AlgorithmicTrading

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This paper estimates the #uplink #channel of an #extra #large-#scale #multiple-#input-#multiple-#output (#XL-#MIMO) system, with the #base #station (#BS) consisting of multiple antenna #sub-#arrays. The BS has a decentralized processing architecture, wherein each sub-array is connected to a #local #processing #unit (#LPU), which performs its signal processing tasks. The #non-#stationarity in XL-MIMO channel causes it to become sparse. The authors design a decentralized #channel #estimation algorithm to exploit this sparsity.----Jayanth N Pisharody, Anupama Rajoriya, Rohit Budhiraja More details can be found at this link: https://lnkd.in/gN9cT7Bg

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📖 Dive into the world of #AI -Driven language translation with our latest blog post. Learn how to easily customize models for enhanced translation accuracy. ⬇️ https://nvda.ws/4btaNvf

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The NVIDIA CUDA toolkit lets you write code that runs on both the CPU and GPU. This makes your code more performant for tasks like deep learning and computer vision. In this article, Abraham walks you through how to install CUDA on Ubuntu 22.04.

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We're thrilled to announce that Audino 2.0, our powerful audio annotation tool, is now open-source and available on GitHub! 🎧✨ Key Highlights: - Enhanced Performance: Leveraging CVAT's robust backend. - Supported by HUMAN Protocol: Advancing our mission to democratise AI development. - Versatile Tool: Ideal for Voice Activity Detection, Speaker Diarization, ASR, and more. - Audino empowers researchers, developers, and organisations to create high-quality labelled datasets for audio machine-learning tasks. Features Include: ✅ Multi-language support ✅ Emoji annotations ✅ Flexible label creation ✅ User-level project management ✅ Various export formats (Common Voice, Librispeech, and many more) We're excited to see how the community will use and contribute to Audino 2.0. Check out our GitHub repository to get started! https://lnkd.in/gjZbSw5X Thanks to CVAT.AI and HUMAN Protocol Foundation for helping us with this. #OpenSource #AudioAnnotation #MachineLearning #AI #ArtificialIntelligence #AudioProcessing #TechInnovation #DataScience #AIResearch #VoiceRecognition #DeepLearning #AudioML #TechForGood #OpenSourceCommunity #GitHub #Innovation #DataAnnotation #MLCommunity #AIForAll #StartupTech #AIDevelopment #FutureOfAI #AICommunity #AudioTech #AIProjects

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Boosting Freelance Rates 3X with Specialized Skills: A Success Story from OpenCV University! Meet Antonio de Jesús Luna Macías, a Computer Vision Engineer who transformed his career by mastering cutting-edge skills at OpenCV University. In a recent one-on-one with our CEO, Satya Mallick, Antonio shared how our focused and practical courses enabled him to not just stay relevant but excel in an increasingly competitive market. While general programming rates have dipped significantly due to automation tools like GPT, Antonio’s expertise in computer vision has allowed him to triple his freelancing rates, showcasing the substantial value of specialized skills in today’s tech landscape. Learn how targeted learning and a strong portfolio can significantly enhance your market value and freelance opportunities, just as it did for Antonio! Explore all courses at OpenCV University and start your journey today! Check out the full list of courses here: https://lnkd.in/gAD8wH-i CVDL Master Course: https://lnkd.in/g8kjRggC #aicareer #ai #machinelearning #aicareers #artificialintelligence #OpenCVUniversity #ComputerVision #CareerDevelopment #TechEducation #Freelancing

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Today is Digital Government Update Monday! 📱💼 From the perspective of Mukundan Govindaraj AI & Digital Twin at NVIDIA, we'll learn about the structure of Omniverse: 🔹 Immerse yourself in a journey where the boundaries of reality blur. 🌌 🔹 Explore how Omniverse empowers creators to bring metaverses and digital twins to life. 🎨 🔹 From enriched social experiences to physically accurate simulations, the metaverse is the next evolution of digital interaction. 💻 🔹 Imagine connected worlds, where humans and AI avatars interact in photorealistic environments. 🌐 🔹 Discover how the metaverse will transform how we work, play, and interact online. 🌟 🔹 From entertainment to engineering, the potential of the metaverse is limitless. 🔧 Every day we broadcast Daily Digital Updates - DDU on our social media platforms at 8:00 am in English and 8:00 pm in Spanish, Denver / CDMX Time. Monday - Digital Government Tuesday - AI & Disruptive Tech Wednesday - HR Technologies Thursday - E-commerce & Web 3.0 Friday - Smart Cities Join us and watch all the full recordings and replays of Global Digital Week 2023 and 2022: link #tech #latam #edtech #software #startups #companies #talent #gidcomp #technology #bigdata #digital #innovation #deeplearning

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Explore best practices around building, customizing, and deploying large language models (#LLMs) and get expert insights on generative AI from industry leaders. Browse #generativeAI sessions at NVIDIA's #AISummit India. https://nvda.ws/3XTzpZC

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🚀 Excited to share how you can deploy Depth Anything V2 on NVIDIA Robotics Jetson Orin NX in just one click! 👉 More info in GitHub: https://lnkd.in/g56Jp3Y2 Depth Anything provides a great method for monocular depth estimation training, which can extract various image features from a single 2D image and convert them into accurate #3D structures. The v2 delivers 10x faster than models built on Stable Diffusion. To improve depth prediction performance, it increases teacher model capacity and utilizes large-scale pseudo-labeled real images for training student models, offering models of various sizes from 25M to 1.3B parameters to fit in diverse application scenarios, including robot mapping, AR/VR, etc. 📖 Read the paper at: https://lnkd.in/gX5UrDAu Now it's easy to deploy Depth Anything v2 with WebUI into Jetson examples, maintaining the basic features of the first generation version. Let's get started!! 1️⃣ Select depth estimation models in the UI. 2️⃣ One-click TensorRT model conversion. 3️⃣ Support for video, image, and webcam inputs. #depthestimation #robotics #AR #VR #stablediffusion #nvidia #jetson

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