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Jensen Huang, CEO of Nvidia, has highlighted a critical juncture in AI chip development: advancements surpass Moore's Law, the long-standing predictor of computing power growth. This signifies a paradigm shift beyond simply building faster chips. We are witnessing the rise of intelligent systems that learn and evolve, pushing the boundaries of hardware innovation. This acceleration is not merely a technological trend; it's a fundamental shift that will redefine the limits of what's possible in computing. Read more 👉https://lnkd.in/gZZcUBnT #AI #Nvidia #MooresLaw #AIChips #TechTransformation #LLMs #Technology #TechSolutions #SafeUse #DataAnalysis #Australia #Innovation with SHAVIK Visit www.SHAVIK.ai

Nvidia CEO Jensen Huang argues that his company's AI chips are progressing at a rate faster than Moore's Law, traditionally used to gauge computing advancement. Nvidia's latest data center superchip, the GB200 NVL72, is 30 to 40x faster for AI inference than its predecessors. This improvement is due to innovations across the architecture, chip, system, libraries, and algorithms. Huang emphasizes that improving performance will lower AI inference costs, making advanced AI models more accessible. #AiChips #MooresLaw #Nvidia https://lnkd.in/gET4_fb6

Moore's Law predicted that the number of transistors on computer chips would roughly double every year, essentially doubling the performance of those chips, but Nvidia's latest data centre superchip is more than 30 times faster 💪 for running AI inference workloads than its previous generation. #AI #Nvidia #chips #Mooreslaw

Nvidia CEO Jensen Huang claims the company’s AI chips are advancing faster than Moore’s Law, which historically predicted that chip performance would double every year through increased transistor density. Speaking at CES 2025, Huang emphasized the accelerated progress in Nvidia’s AI hardware, citing the company’s latest data center superchip as being over 30x faster for AI inference workloads than its predecessor. While Moore’s Law has slowed in recent years, Huang’s comments suggest that Nvidia’s AI-focused designs are charting a new trajectory for computing performance in the age of artificial intelligence. #Nvidia #MooresLaw #AIChips #CES2025 #TechInnovation https://lnkd.in/gp6EUgwe

NVIDIA has recently secured a patent for its innovative Blackwell chip, designed to enhance AI processing capabilities. This advancement is expected to significantly improve performance in various applications, including machine learning and data analytics. With the growing demand for efficient AI solutions, NVIDIA continues to solidify its position as a leader in the semiconductor industry. The new chip could pave the way for even more breakthroughs in AI technology. https://lnkd.in/gx4rqCcw #NVIDIA #BlackwellChip #AI #Semiconductors #Innovation #MachineLearning #DataAnalytics #TechTrends #Patents #FutureOfTechnology #UnderstandingEnterpriseTech #EnterpriseTechnologyNow #EnterpriseTechnologyToday

Nvidia CEO Jensen Huang claims the performance of his company's AI chips is advancing faster than the historical rates set by Moore's Law. Huang says Nvidia can "innovate across the entire stack" to move faster than Moore's Law, which previously predicted a doubling of transistors on computer chips every two years. https://lnkd.in/gAwFsNSj

Very interesting article regarding Nvidia this morning. Jensen Huang’s recent announcement about Nvidia’s AI chips outpacing Moore’s Law is a game-changer if true, especially for industries like finance, law, and technology. As a pragmatic business management and product subject matter expert, I believe that the true power of AI lies in its ability to enhance workflows rather than operate independently in highly regulated environments. The potential for error in agentic AI is still significant, particularly in sectors where precision and compliance are paramount. From a business perspective, the key is to harness AI for data contextualization. By extracting and interpreting data, we can use railed triggers and functions to execute actions seamlessly and accurately. This approach not only minimizes risk but also maximizes efficiency and effectiveness. Nvidia’s advancements present an incredible opportunity for firms to leverage AI in a controlled and impactful manner, driving innovation and maintaining competitive edge. https://lnkd.in/gw2sDapT

In a bold move to democratize AI technology, a coalition led by Qualcomm, Google, and Intel Corporation spearheads the initiative to challenge NVIDIA's stronghold on #AIChip #architecture with its #GPUs. Leveraging the #UXLFoundation, they're developing an open-source software suite capable of operating across diverse AI accelerators. Additionally, Groq (https://lnkd.in/dqb3458i) is making waves with its innovative Tensor Streaming Processor (#TSP) architecture for its Language Process Units (#LPU), offering a deterministic performance model that simplifies and accelerates AI computations. This paradigm shift could significantly reduce dependencies on specific hardware vendors, potentially lowering costs and accelerating AI innovation across industries. Companies could benefit from more flexible and cost-effective AI implementations, enabling broader adoption and business transformation. As these technologies evolve, they could pave the way for a new era of AI development, where choice, interoperability, and performance predictability reign supreme. This marks a crucial step towards a more open, competitive market, promising exciting advancements in AI technologies. #GenerativeAI #AIChips #AIArchitecture More info here: https://lnkd.in/dB7sBKEX

Is Moore's law at the Next level? What an incredible earnings call. NVIDIA, Jensen Huang named everyone hosts to Blackwell and trusted partners, I was holding my breath, turned red in the face, then he said Supermicro, my breathing returned as I realized that I was listening to a man advertising his partners, hosts, minions to sell their technologies, creating platforms to traverse the data gap, to mine and bridge blackwell servers to different inference models, structured and unstructured. Machine teaching machine. We are witnessing a game changer in action. Product lifecycles, innovation, new architecture, complimentary and collabarative makes existing multibillion USD products like Hopper redundant by introducing new systems that translate into faster revenue growth. His roadmap to world collaboration is through microchips learning from microchips, all that data that google has stock piled since 1999 will be processed in a day. An army, as infinite as the eye can see, will parse through it strategically located in all corners of our Earth in data centers. Learning continuously through deduction, reasoning, inference adjustments to the models and then making decisions. All this in miliseconds using the blackwell server racks systems and super clusters for a starter.  An example of one from, as Jensen said, “everyone in the whole world is a customer // host // platform”.  " Supermicro integrates advanced liquid cooling technology, including coolant distribution manifolds and cold plates, which enhance efficiency and reduce operational costs. These systems feature advanced 8-GPU configurations designed for liquid or air cooling. They integrate NVIDIA Blackwell GPUs with optimized thermal and power management, enabling efficient scaling in AI data centers. Supermicro supports these superchips, which combine Blackwell GPUs with Grace CPUs. The systems deliver high throughput for AI and HPC, connected via NVIDIA NVLink to maximize bandwidth and efficiency. Supermicro builds rack-scale Super Clusters using Blackwell GPUs, offering unprecedented compute density and performance. These clusters support large-scale AI applications, such as generative AI and language model training." The data center model has changed- no longer big and huge but compact & more efficient. The best part is that this journey started a long time ago created by Intel Corporation, Gordon Moore who was living in chip architecture" doubling the number of transistors every two years on a micro chip creates exponential compute power and reduction in cost per transistor. Some say his law is dead, at 3nm the chip is almost atomic, the heat generated cannot be effectively dissipated this restricts putting more transistors on these almost atomic chips.  That may be the case - Moores law is dead at chip architecture level. Think about it, Moores law is alive at the multi-chip architecture level. Drees & Sommer We also design Data Centers.

Nvidia CEO Jensen Huang claims that the performance of Nvidia's AI chips is advancing at a rate faster than the historical benchmark set by Moore’s Law, which guided computing progress for decades. Coined in 1965 by Intel co-founder Gordon Moore, Moore’s Law predicted that the number of transistors on computer chips would double roughly every two years, effectively doubling chip performance. This prediction fueled decades of rapid technological advancements and cost reductions. This isn't Huang’s first statement on surpassing Moore’s Law. In a November podcast, he described the AI industry as being on track for “hyper Moore’s Law,” suggesting even faster growth in AI chip performance.