Richard Norris’ Post

Nvidia's valuation is bigger than most tech companies combined (pictured) Excellent reporting by John Loeffler on the future of this terrifying monster: "The current-gen Hopper data center chips draw up to 1,000W, so Nvidia Blackwell is nearly doubling the power consumption of these chips. Data center energy usage is already out of control, but Blackwell is going to pour jet fuel on what is already an uncontained wildfire. Worse still, Huang said that in the future, he expects to see millions of these kinds of AI processors in use at data centers around the world. One million Blackwell GPUs would suck down an astonishing 1.875 gigawatts of power. For context, a typical nuclear power plant only produces 1 gigawatt of power. Fossil fuel-burning plants, whether that's natural gas, coal, or oil, produce even less. There's no way to ramp up nuclear capacity in the time it will take to supply these millions of chips, so much, if not all, of that extra power demand is going to come from carbon-emitting sources. I always feared that the AI data center boom was likely going to make the looming climate catastrophe inevitable, but there was something about seeing it all presented on a platter with a smile and an excited presentation that struck me as more than just tone-deaf. It was damn near revolting." https://lnkd.in/desHhcA6

America may run out of power with AI's growing energy appetite 🔌🏭 The bottleneck for AI progress will shift from NVIDIA/TSMC's chip production to energy companies' capacity to power AI data centers. For example: ⚡️ Amazon's 1GW data center next to a nuclear plant https://lnkd.in/g4zqTwhG ⚡️ Microsoft & OpenAI planning $100B, multi-gigawatt "Stargate" AI supercluster https://lnkd.in/gWvnhZms To feed the AI beast, we'll need 💰💰💰 of investments in new power plants, massive data centers, and chip fabs that can churn millions of GPUs/year. Leopold Aschenbrenner's back-of-the-envelope analysis highlights the staggering power needs (https://lnkd.in/gfBc5xhb) 💡 Rumored $100B cluster = 10GW = small US State's power draw The intersection of AI and energy markets is 🔥🔥🔥 Think beyond chips and models. What's the NVIDIA or TSMC of the energy space? Nuclear? Solar? Exotic energy source? #ai #ml #llm #largelanguagemodels #gpu #cloud #datacenter #aicompute #energy #datacenterenergy #nuclear #greenenergy #startups #venturecapital

Sam Altman eyes nuclear fusion for AI energy needs, balancing innovation with sustainability. Major tech firms collaborate to counter Nvidia's AI dominance. Nvidia and Hippocratic AI's AI nurses excel in medical tasks, offering precise assessments at a fraction of the cost. Apple may use Baidu's AI for iPhone 16, Mac OS, and iOS 18 - Read the full article below and subscribe to AI Pitstop to stay up to date on all AI advancements!

⚡ 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐨𝐧𝐬𝐭𝐫𝐚𝐢𝐧𝐭𝐬 𝐀𝐫𝐞 𝐇𝐨𝐥𝐝𝐢𝐧𝐠 𝐁𝐚𝐜𝐤 𝐀𝐈… 𝐒𝐨, 𝐖𝐡𝐚𝐭’𝐬 𝐍𝐞𝐱𝐭? 𝐍𝐮𝐜𝐥𝐞𝐚𝐫 𝐏𝐨𝐰𝐞𝐫?! ⚡ To keep scaling LLMs, you need three main things: data, compute (GPUs), and electricity. If you’re missing one, well… maybe it’s time to consider a different business model. 😅 As LLMs scale, so does electricity consumption, and many companies are hitting a wall due to government restrictions on power usage. Even Mark Zuckerberg recently said: “We would probably build out bigger clusters than we currently can if we could get the energy to do it.” Now, despite efforts to go green, CNBC reports that Microsoft is reportedly signing deals with nuclear plants to power their next-gen foundation models. 💥 What do you think? Is it worth it—regardless of the price the planet might have to pay for it? 🔗 Link to the article: https://lnkd.in/ddXtRBfX ♻️ Repost if you liked this and follow me for a pragmatic (and occasionally funny) take on Artificial Intelligence and Generative AI! #AI #GenerativeAI #Energy #LLM #NuclearPower #Business #Innovation

Discover how #DataCentres can meet the power demands of #AI as Chris Sharp from Digital Realty talks about alternative power sources, innovative cooling tech, and more. Compared to the servers that run traditional workloads, such as virtual machines, containers, storage, and databases, hardware-accelerated AI is a different animal. A single rack of GPU servers today can easily consume 40 kW or more. Next-gen rack-scale systems from NVIDIA and others will require at least 100 kW. According to Sharp, accommodating these demanding systems at scale isn't easy and requires a different way of thinking about datacentre power and cooling, which you can learn more about in this interview with The Register below. It's possible datacentres could end up looking wildly different. Sharp suggests small nuclear reactors #SMRs and other primary onsite power generation may play a role. ® Embrace the future of AI with #TheDataMeetingPlace #WhereTomorrowComesTogether #PlatformDIGITAL. Learn more here:

It’s been a huge week for AI. I’ve summarised everything announced by Meta, Tesla, AMD, Perplexity, and Google. Number 5:  Google is buying nuclear reactors to power AI. The power demands for AI led Google to venture into nuclear energy procurement for the first time. By investing in nuclear energy, Google is following the likes of Microsoft and Amazon to power AI data centres with green power. Number 4: Perplexity entered into finance. Searching for a ticker on Google shows the stock price for that company, with a chart. Perplexity takes it further, powering research with company deep dives, comparisons and dynamic charts, with one command. Number 3:  AMD announced new chips for AI. The chip manufacturer introduced the Instinct MI325X, designed to compete with Nvidia’s H200 chip. It’s already showing some impressive performance with up to 40% better inference for models like Llama 3.1. Number 2: Tesla showcasing autonomy. Two new vehicles and a humanoid robot: Robotaxi, Robovan and Optimus. They’re a long way from production but each of these products have significant potential when they hit our roads, factories and workplaces. Number 1:  Meta unveiled Movie Gen. Their video platform claims to be the most advanced foundation model and the demos I’ve seen back that up. The quality of video that can be produced for next to no cost gives creatives new avenues to deliver the best videos we’ve ever seen. I rated these 1-5, which one do you think belongs at number 1? Let me know in the comments. *** If this resonates, repost to help your network with AI ♻️ and follow Josh Phillips for more in the future.

Insightful 💡 Ensuring electricity supply is key.

Accile AI Chronicles: Daily Industry News Amazon, Google and Microsoft Are Investing in Nuclear Power Tech giants like Amazon, Google, and Microsoft are investing heavily in nuclear power as a sustainable energy source for their operations, including artificial intelligence. This move is seen as a way to reduce emissions and ensure a reliable power supply for their energy-intensive businesses. However, concerns about the high costs, safety, and waste management of nuclear power remain. #Amazon #Google #Microsoft #nuclearenergy #AI #sustainability #emissions #energy #investments #techgiants #critique The full article is available here: https://lnkd.in/dh4cAdQM Accile Consulting - AI Automation Specialists Are you looking to enhance your customer experience and keep up with the latest AI advancements? Partner with Accile Consulting to tap into the full potential of AI Automation and revolutionize your business. #AccileConsulting #AIIntegration #Innovation #Partnership #AIAutomation.

Artificial Intelligence (#AI) is consuming far more energy than traditional applications. The International Energy Agency (IEA) predicts datacenters will DOUBLE their energy use by 2026 (!). 3x3 facts & 2 actions items: The article linked In the comments (in German) discusses:  🌍 Small modular reactors (SMRs) are being considered to help achieve Google's 2030 climate neutrality goal. 🌎 Google plans to power its data centers with nuclear energy to meet AI-driven power demands. 🌏 The topic focuses on using nuclear energy as a sustainable solution for the tech industry’s growing power needs. At QuantumBasel, we’ve raised this issue early:  ✅ Training and feeding AI models 'on the fly' require more computational power, leading to increased energy demand.  ✅ #Mooreslaw is flattening out as microprocessors hit physical shrinking limits (5nm, 4nm, 2nm, ?), so more datacenters are the only option.  ✅ #ChatGPT uses 10-20x more energy than a traditional Google search. Will #quantumcomputing be the answer to this global challenge?  🔹 It may help design new materials for more efficient energy storage and production, enhancing sustainable energy technologies. 🔹 Quantum computing could optimize energy systems, improving efficiency in areas like grid management and renewable energy use. 🔹 Quantum computers use much less energy: a supercomputer uses 10-20 MW, while quantum computers average just 25 kW. ➡️ Subscribe to our newsletter for more insights -> check out my profile ➡️ Get involved in our quantum & AI projects: info@quantumbasel.com uptownBasel #planetaryhealth #energy #QML Christoph Mettler IonQ D-Wave IBM Rima Alameddine Lorenzo Martinelli Josselin Milloz Hans-Jörg Fankhauser Thomas Staehelin Baschi Dürr Dr. Frederik Flöther Herman Gyr, Ph.D. Jan Mikolon Jan Kuenne Catrin Hinkel Sebastian di Paola Dr. Heike Riel https://lnkd.in/dr2CHc2C