EIZIE AI’s Post

Mastering LLM performance? 🤖 Use NVIDIA GenAI-Perf to benchmark between inference engines through KServe and OpenAI compatible APIs. Achieve the perfect balance for optimal inference results. #Triton #generativeAI #AI

Talking about the term vs actually understanding it are two different things. - Understanding in this case refers to the actual/potential business/functional users of AI. If they understand the impact of AI and how it will benefit them to do current work efficiently and do things better and differently in the future. - The complexity of the #AI solution stack is beyond stockpiling pallets and pallets of NVIDIA boxes. (The HPC Infra, on-premise, or at DCs )

Llama 3.1 is out! This massive 405b parameter LLM was trained on 16k H100’s and has been optimized for blazing fast inferencing using Nvidia TensorRT LLM.

If you still think of NVIDIA as a hardware company, have a good read of this - full stack is the way forwards for success with GenAI and this article provide a nice glimpse into what that means....

Explore how to leverage the power of Intel's integrated GPU for running OpenVINO models. This capability allows you to efficiently perform deep learning tasks right on your device. Find out more about optimizing your AI workflows with Intel's OpenVINO toolkit. Read the full article here: https://lnkd.in/gmmfHZeW #AI #MachineLearning #IntelGPU #OpenVINO #TechInnovation #ArtificialIntelligence #gpu #openvinotoolkit

Game changer ? NVIDIA’s - NVLM 1.0 just released frontier language model demonstrates great performance on vision, language and text tasks, rivalling the leading proprietary foundational models (e.g., GPT-4o) and open-access models. Exposes many disruptive threads that could change the direction of current closed foundational models mostly built on back of NVIDIA chipsets including opening access to much smaller organisations to contribute to the advancement of AI and domain specific AI !! NVIDIA's paper here - https://lnkd.in/eJRxWKW7 #ai #openai #airisk

Is your organization preparing to depend on AI solutions in the coming years? It may be time to consider a fleet tailored for AI applications. Watch this video to discover the #Microsoft Copilot+ PCs, powered by a unique neural processing unit capable of 40 trillion operations per second to meet all your AI needs effortlessly.

With Nvidia’s NVLM 1.0 hitting the market, AI is not just expanding—it’s driving complexity across every layer of the tech stack. As AI is integrated at all levels, the challenges of securing data within AI pipelines become more urgent. Each layer of technology now demands a rethink, especially around the sensitive data being processed. Is your organization ready for this evolution? Learn how to safeguard your data while staying compliant in an increasingly AI-driven world: https://lnkd.in/gcjiHRmP #DSPM #DSPMforAI #DataSecurityPostureManagement #AICompliance #Nvidia #DataSecurity

A practical list of high-risk AI applications has been identified by European Parliament's AI Act. Yes, AI can do many things, but NOT everything; at least, what we are doing indataanalytics. Also, AI is expensive 💰 🤑💸, as on electricity bills. Let's try this go/no-go test to see if AI works. Is there any today's AI data solution you know, that can interpret and answer the following Chinese-English multilingual questions? With our intellectual property (IP), a copyrighted multilingual metadata, we can provide real time answers, by census geographical locations, as evidence for decision/policy making. "Who, in the Ontario province of Canada, has new US patents granted on the nearest Tuesday, when the USPTO releases the newly granted US patents on a weekly basis?" "Who, in the "江蘇‘’ province of China, has new US patents granted on the nearest Tuesday, when the USPTO releases the newly granted US patents on a weekly basis?" Metadata is an enabler. Without metadata, NO data can be found/retrieved, even by the most advanced technologies, like AI, NVIDIA chips, supercomputers, etc. https://lnkd.in/g-aJFnX

🚀 Insights from Dreamforce: NVIDIA CEO Jensen Huang on the Future of AI TLDR: AI is ushering in a new era of computing, with exponential growth in capabilities driven by unsupervised learning. Safety, democratization, and hands-on experience are key focus areas. Key takeaways from Jensen Huang's chat with Marc Benioff : 1️⃣ New Era of Computing: We're entering the AI era, where computers write software based on human prompts. 2️⃣ Large Language Models: These models understand nuanced human requests, use tools, reason, and collaborate to solve complex problems. 3️⃣ Unsupervised Learning Breakthrough: AI can now learn from massive amounts of unlabeled data, leading to exponential growth in capabilities. 4️⃣ AI Safety: Fine-tuning, guardrails, and Chain of Thought reasoning are crucial for ensuring safe AI development. 5️⃣ Democratizing AI: Making AI accessible to everyone is a priority. Jensen encourages hands-on coding experience in building AI agents. 6️⃣ Future Outlook: The rapid advancement of AI promises exciting developments in the coming years. 🤔 What are your thoughts on the future of AI? Are you ready to dive into building your own AI agents? #AI #ML #Salesforce #TechInnovation #FutureOfComputing #NVIDIA https://lnkd.in/dD3STs9e