Claire Tse on LinkedIn: Kiwi Pi RK3588 SBC (2024)

AMD x 🤗: Large Language Models Out-of-the-Box Acceleration with AMD GPU. In this blog post, we provide an update on our progress towards providing great out-of-the-box support for AMD GPUs, and improving the interoperability for the latest server-grade AMD Instinct GPUs. Amazing? Hugging Face is a leading company in the field of natural language processing (NLP) and offers a wide range of tools and models for developers. One of their popular offerings is the Limber model, which is an LLM (Language Model) that can generate realistic text based on a input prompt. The Hugging Face LLM can be used for various applications, such as text classification, language translation, and text generation.New Hugging Face blog: https://lnkd.in/eRv73Ske #AMD #HuggingFace #AI #LLM #artificialintelligence AMD

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Check out the latest minipc from Asrock. I'm curious to see what the reviewers have to say about it's AI capabilities.https://lnkd.in/d5fAfeXp#ai #amd #mini

There has been an explosion of interest in AI over the past year as businesses and the general public have seen what new apps and services can do. The truth is our AI-powered future is just getting started. The launch of Ryzen AI is a first for x86 processors and an investment in the future of computing, but why integrate an AI engine in the first place? Read my new blog post to put things in perspective of processor evolution and using the right tool for the right task. https://lnkd.in/g8t4d8t5#AMD #TogetherWeAdvance #AI #innovation #semiconductors

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Ever wondered why the AI and related technologies boomed after 2022!Well AI is not new technology but it was in development from 50's. But there were multiple new upgradation in infrastructure , processing and data analysis that helped its explosive growth.While completing OCI AI certification i narrowed down to 2 very large impactful changes in infrastructure and processing side which led to this growth i.e GPU's and Transformer.GPUs - They have become the backbone of AI, propelling us into the generative AI1. Parallel Processing Prowess: With thousands of cores, GPUs slice through AI model calculations, offering unparalleled computing power.2. Scaling to New Heights: As AI models grow complex, GPUs scale up effortlessly, thanks to NVLink interconnects and Quantum InfiniBand networks.3. Expansive Software Stack: NVIDIA’s GPU software stack, including CUDA and cuDNN-X, empowers developers to innovate in AI.Transformers -They are a cutting-edge deep learning architecture, have transformed the field of Natural Language Processing (NLP). 1. Attention Mechanism: Transformers use a multi-head attention mechanism to contextualize each token within a context window. This allows them to capture long-range dependencies and understand complex relationships in text.2. No Recurrent Units: Unlike traditional recurrent neural networks (RNNs), transformers don’t rely on recurrent connections. This absence of recurrence speeds up training and enables efficient parallel processing.3. State-of-the-Art NLP Models: Transformers are the backbone of state-of-the-art NLP models like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformers). These models excel at tasks like language understanding, sentiment analysis, and machine translation.4. Beyond NLP: Transformers aren’t limited to NLP. They’re also making waves in computer vision, audio processing, and multi-modal applications.1. https://lnkd.in/d5cpwCWG2. https://lnkd.in/dbiUAFm7#AI #GPUs #NLP #DeepLearning #Transformers #Oracle #OracleCloud #IBMFor More details here is the good article on GPU and research paper on Transformers.

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AI-powered solutions are becoming increasingly popular, especially generative AI 📈 But which GPUs are best for businesses tackling heavy AI workloads? Panchaea Founder Pete Overell delves into the best options 👇 https://lnkd.in/eWZr8yBd#AI #GPUs #Visualisation

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In-Depth Analysis: Consumer GPUs for Stable Diffusion LoRA TrainingOur latest study provides valuable insights into the use of consumer-grade GPUs for AI training:🖥️ Performance Across Resolutions: Discover how consumer GPUs perform at different resolutions in LoRA training.🧠 VRAM's Role in AI Training: Gain insights into the crucial role of VRAM in handling high-resolution AI models.📈 Efficiency with Gradient Checkpointing: Explore how gradient checkpointing can optimize training on GPUs with limited VRAM.🌐 Resource for AI Professionals: An essential read for AI professionals and enthusiasts exploring cost-effective training solutions.Dive into the full article:https://hubs.ly/Q02dvrCY0

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In our most recent blog, we take a deep dive into the world of GPU clusters, explore what they are, why they matter, and how Redapt can help you harness their full potential.Read our blog now: https://hubs.li/Q025052r0. #GPU #AI #Blog

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“Sharing is Caring”Hi #AI Community!!!#sharingiscaring“Send me an Invite and get your skills endorsed on evaluation straightaway as pleasantries !”“#Knowledge Booster”📚 Expand your knowledge base with this helpful article..Keep #Learning !! 👍NOTE : This is NOT a paid Advertisem*nt#Robotics#artificialintelligence#dataanalytics #datascience #machinelearning #deeplearning#python#R#probability#permutations#statistics#calculus#linkedinfamily #knowledgesharing #machinelearningalgorithms #neuralnetworks #deeplearning #deeplearningai #computervisionJoin me on my way into an exciting world of Data/Analytics/AISend me an Invite and get your skills endorsed on evaluation straightaway as pleasantries 😊🍁Let’s Connect Now

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While You Were Sleeping? : #5While this story is a few weeks old, I think it is an interesting representation of a few things. First, there seems to be no end to new attack vectors. If it has a chipset someone will find an angle. Second, and this is just an opinion, I think this is a precursor to unforeseen issues with AI as both Large Language Models and the Hardware it uses start to come of age.. Enjoy the short read.Knowledge is PowerDave https://lnkd.in/ef7xpsS4

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Easy to read article that explains how #pcie and #cxl combine to enable applications like #ai and #ml that require faster data rates and low latency. https://lnkd.in/e2U2fa_jInterested? Contact Rik Boelee to discuss this further.

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