Salim Fedel

Philipp Kampshoff from McKinsey & Company is hosting Interesting discussion on supply chain for automotive industry at GSA US executive forum Maher S Matta from Infineon Technologies : "just on time" in automotive does not sync well with semiconductor, that is the hard lesson we learned from pandemic. Karn Budhiraj from Tesla : the problem was not with major semi supplier But those black boxes from tier1, tier 2 that had less direct information when supply shortage hit. Mohit Singh from QuantumScape : battery components are mainly from China, but lithuim is not the issues, refining process is. China is efficient in enabling manufacture supply chain One big thing coming from Tesla : RoboTaxi!!

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Arm's taken over the NASDAQ building in New York City to share why the world's biggest technology companies are innovating on the Arm compute platform for the age of AI. By building on the industry's most power-efficient and highest-performing compute platform, Arm's empowering the technology ecosystem to unlock all that AI promises. See how: https://okt.to/wW3Q9X

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Civilization runs on #semiconductors, but there is an exponentially growing gap between our appetite for advanced semiconductors and our ability to produce them. The good news is that we have proven technologies that can greatly advance state of the art: xLight Inc. is building a #EUV light source of unprecedented power & purity that can dramatically improve the economics and capabilities of our most advanced semiconductors. Coupled with thoughtful industrial policy and leadership as described by Gina Raimondo, the US is well positioned to lead this new space race. #CHIPS #AI #Lithography #ASML

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Generative AI and Large Language Models (LLMs) are changing the game, but the industry is shifting towards more specialized compute architectures to run these models efficiently. GPUs are a great example of such specialized architectures. However, the lack of competition has allowed a single company to dominate the market. But, with the increasing demand for specialized compute, new companies have the opportunity to enter the market. Traditional Silicon companies will need to relearn and adapt to these new designs. Learn more about the future of the semiconductor industry with Generative AI: The next S-curve for the semiconductor industry. #AI #SemiconductorIndustry #GenerativeAI Source: McKinsey & Company.

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Breaking New Ground in Battery Technology! 🌟🔬 Microsoft and the US Department of Energy’s Pacific Northwest National Laboratory (PNNL) are rewriting the rules of scientific discovery with their groundbreaking collaboration. Harnessing the power of artificial intelligence (AI) and high-performance computing, they've achieved the unthinkable: uncovering a revolutionary new material for resource-efficient batteries in less than 9 months! Want to know how they did it? Read more here👉 https://lnkd.in/gyBCRimY #BatteryTechnology #BatteryInnovation #AIandScience #FutureTechLeaders

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According to McKinsey, quantum computers could significantly contribute to climate change mitigation by potentially reducing global carbon emissions by 7 gigatons by 2035 and 150 gigatons over the next three decades, while simultaneously boosting key transition industries with an added value of up to $1.3 trillion; this potential stems from their ability to revolutionize technologies like electric vehicle batteries, optimize carbon-intensive industrial processes, develop cleaner agricultural practices, and innovate new fuel sources. I appreciate all my Microsoft and IBM friends working to make Quantum Computing scalable and more mainstream. #QuantumComputing #Climate #CarbonEmissions

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Deploy AI Everywhere. 🌏 Enterprise adoption of AI is increasing, and many adopters are successful in getting ROI and seeing tangible business value. Add to your reading list the latest solution brief to learn how VMware Private AI with Intel Business on Lenovo Infrastructure Solutions Group ThinkAgile VX V3 and ThinkSystem V3 can unlock #AIforAll: http://spr.ly/6048UzXgm #WeAreLenovo

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Room for more than Nvidia: Jim Keller rejects costly HBM, pushes for affordable AI chip designs Chip guru Jim Keller has expressed confidence that more companies will emerge to fill gaps in the AI market, as even Nvidia cannot meet all the demand. Keller, CEO of the Canada-based AI chip design firm Tenstorrent, has observed that due to the high cost of High Bandwidth Memory (HBM), many companies, including his own, are seeking alternative solutions. According to Nikkei Asia, Keller highlighted that as AI applications expand into smartphones, electric vehicles, and cloud services, more firms are looking for more affordable solutions. He believes the market leaves ample room for new competitors even with Nvidia supplying a big chunk of the market. https://lnkd.in/gfUemdfG

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"Google’s greenhouse gas emissions have soared 48% since 2019," mostly due to growth in data center energy demand. AI is poised to drive that demand even higher. For example, a "Google search query requires 0.3 watt-hours of electricity on average, while a ChatGPT request typically consumes about 2.9 watt-hours." Amazingly, in one scenario "Google’s AI systems could eventually consume as much electricity as the country of Ireland each year." That is only Google's AI. Unless the energy intensity of computing is cut massively (e.g. by quantum computing), the amount of electricity needed in the next 5-10 years is likely materially underestimated by current forecasts. This is driven by a confluence of surging demand from electrification of mobility and the increased energy intensity of information. https://lnkd.in/g47Y-2TQ

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✨ What are the top #AI use cases, challenges, and benefits for #energy companies in the upstream industry? Explore real-world case studies and examples from AAPG, NVIDIA, and ROGII in a webinar on October 8 at 12pm CDT. Register today.

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Exciting times in the world of AI! 🌟 Discover how Dell PowerScale, Dell PowerEdge, and NVIDIA are joining forces to supercharge Gen AI workloads! 🔹#PowerScale offers scalable storage solutions that ensure seamless data management and accessibility. 🔹 #PowerEdge servers deliver the robust performance needed to handle complex AI computations. 🔹 With #NVIDIA's cutting-edge GPUs, we're unlocking unmatched processing power for AI innovation. Dive into our latest blog to learn more: https://dell.to/41oJfos #AI #iwork4dell

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Accelerate your GenAI journey with NVIDIA NIM, our set of easy-to-use NVIDIA inference microservices for accelerating the deployment of foundation models. NIM combines advanced AI with domain expertise to deliver faster, more accurate results. Whether for research or next-gen applications, NIM streamlines workflows and empowers innovation. Learn how NIM can transform your GenAI initiatives today!

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AI, Machine Learning, and other demanding data-driven workloads mandate amazing computational capabilities from servers and networks. How are yours holding up? Share this to start a conversation. Download this infographic about HPE M-series Ethernet switches, the solution that ensures your M-series fabrics allow for significant speed and architecture upgrades over time.

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🚀 AI is transforming industries, but it’s the powerhouse storage architecture behind the scenes that makes it all possible. Learn how storage architecture fuels AI success and why it’s the key 🔑 to unlocking innovation: https://dell.to/3YMgJfh #AI #Storage #PowerScale #iwork4dell

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Groq, known for their high-performance AI hardware and software, released two new open-source models specifically designed for tool use: Llama-3-Groq-70B-Tool-Use and Llama-3-Groq-8B-Tool-Use, built with Meta Llama-3. Tools are utilized by AI assistants to respond to user prompts. Typically, a tool is an API call to an external system, like Google search. The results from the tool are then analyzed by the LLM and incorporated into the response. Thus, the LLM's performance in using tools is paramount. These models promise significant advancements in processing speed and efficiency. Llama-3-Groq-70B-Tool-Use boasts 70 billion parameters, while Llama-3-Groq-8B-Tool-Use features 8 billion parameters, both optimized for rapid deployment in various applications. By leveraging Groq’s advanced hardware, these models aim to set a new standard in AI tool use, focusing on enhancing both performance and accessibility.

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According to International Business Strategies, Inc. (IBS), global #semiconductor revenue is expected to top $1 trillion by the end of the decade. Currently, U.S. companies are leaders in many areas of #chip design, for example, while those in Taiwan, South Korea and mainland China dominate the later production and assembly stages. Does this domestic specialization make the #supplychain vulnerable to disruption? Learn more about this story in The Wall Street Journal: https://lnkd.in/eGn-PVZ4

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Apple is set to revolutionize its server infrastructure with the development of its own AI chip, Project ACDC, aiming to enhance the running of AI models within its data centers. This strategic move, leveraging Apple's renowned chip design expertise, underscores its commitment to advancing generative AI technology amidst increasing competition. 🔧 With a focus on inference operations rather than training, Apple's new server chip positions itself distinctively in a market where Nvidia currently leads in AI model training. The initiative reflects Apple's broader ambitions to integrate more AI-driven features across its product line, including upcoming iPad models that may benefit from accelerated AI tasks. Read more from Reuters here => https://neoswap.info/3zv #AppleAI #TechNews #Innovation #DataCenterAI

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