Cloud Study Network’s Post

AI Power Consumption: Rapidly Becoming Mission-Critical https://lnkd.in/gwXpEkPw #AI

We need to address the energy consumption associated with training AI models. ⚡ One of the key takeaways from #CollisonConf 2024 was the importance of considering AI's energy consumption. Training machine learning models, in particular, is extremely energy intensive. While many panels discussed AI's impact on society and productivity at a high-level, the focus on sustainability truly resonated with me and it NEVER crossed my mind just how much energy it consumes. I had the opportunity to attend a thought-provoking panel on clean tech at Collision, during which I was introduced to Clean AI Initiative. This experience sparked further reflection on the sustainability aspect of AI and how we can ensure its long-term viability. It's crucial to think about the environmental impact, especially now that creating images with AI is becoming more accessible. Sharing two interesting articles below. ✨ Forbes https://lnkd.in/eJT3SH9C https://lnkd.in/eXQr4aAs #AI #EnergyConsumption #LanguageModels #MachineLearning

Our friends at Tech Radar have highlighted the groundbreaking technology developed by Liqid. Interested in learning more about this game-changing product release? Check out the details here: [Link to the article] #TechInnovation #Liqid #TechnologyAdvancement #Nvdia #DellTechnolgies #AI #ML #HPC

AMD's Future in AI: MI400 AI GPU Anticipated for 2025, Refresh of MI300 in the Works

AI PCs are here: should they be on your radar?

Ever think you're spending too much on AI? Our latest piece reveals essential, yet often overlooked, hardware for LLM fine-tuning. These unsung heroes could be your ticket to cost-effective AI projects. 🔗 Dive in: https://lnkd.in/eySe5bfe How about you? Share your strategies for achieving high-performance AI without breaking the bank!

Packaging opens up new possibilities and is one way of solving the many challenges that comes with increased density. https://lnkd.in/emhFgN2a #5g #quantum #ai #semiconductor

Multiplying development of AI x10

#ai #hardwareprocessors NPU (Neural Processing Unit): The NPU is a specialized processor designed to accelerate machine learning algorithms, specifically neural networks. NPUs are optimized for the parallel processing required in AI and deep learning tasks, enabling faster and more efficient computations for tasks like image recognition, natural language processing, and autonomous driving. *TOPS > Tera (T): Represents a trillion, and Operations Per Second: Refers to the number of operations a processor can perform in one second.

As the #artificialintelligence market surges with a projected compound annual growth rate of 37%, #Nvidia emerges as a key player driving this extraordinary expansion. Learn how their innovative processors are fueling the #AI industry's growth.