EnCharge AI’s Post

Exciting advancements in AI and quantum computing are on the horizon, but are we ready for the energy surge they'll bring? The National Grid predicts a six-fold increase in data centre energy consumption over the next decade to power these innovations. CEO John Pettigrew emphasizes the need for proactive grid upgrades to sustainably meet this demand. As we aim for net zero emissions by 2050, it's crucial to address the environmental impact of technology growth. Read more here: https://lnkd.in/e_he_GWN #AI #QuantumComputing #Sustainability #Innovation

Data centres - The environmental cost of both embodied and operational carbon are killers.. Can anyone share the carbon footprint of a data centre - we are currently drawing up ways of reducing the carbon impact .. but need a base line. Is Data as bad as oil n gas?

Could energy supply be the downfall of AI? The recent improvement in energy consumption of the NVIDIA Blackwell generation of AI semiconductors obviously focused on power usage for one good reason - there isn’t enough energy to allow AI to expand quickly enough! This is where good old Moore’s law really needs to be held to account by helping reduce power in each generation of AI datacentre solutions. Yes originally it was based around doubling of compute power every year or so but a byproduct of the law was to ensure the doubling of compute capability could be achieved without heat and power loss! It’s clear that to achieve AI gains moving forward power consumption is a key factor and that is going to be the challenge. Perhaps we will see micro or nano datacentres appear near renewable sources with backup power systems as that would speed up construction and reduce the need for grid power transmission lines across the country ie; build power hungry users near the sources? Either way when you ask #chatGPT a question in the future will you need to switch off your kettle first in order to get an answer? #ai #power #sustainability #datacentre #energy https://lnkd.in/exV7Fgsd

If the rest of the developed world is not yet ready to handle the demands of increased electricity use - even before AI - then how on earth is NZ going to cope? "As one researcher notes, adding AI to Google “search” boosts the energy use per search tenfold. And that’s only the first, perhaps the least, significant of the many possible applications for AI." "Today’s global cloud, which has yet to absorb fully the power demands of AI, has grown from nonexistent, several decades ago, to using twice as much electricity as Japan. And that estimate is based on the state of hardware and traffic of several years ago. Some analysts claim that, as digital traffic has soared in recent years, efficiency gains were muting or even flattening growth in datacenter energy use. But such claims face countervailing factual trends. Since 2016, there’s been a dramatic acceleration in datacenter spending on hardware and buildings, along with a huge jump in the power density of that hardware—and again, all of this before the AI boom. To guess what the future holds for the energy appetite of the cloud, one must know two things: first, the rate at which efficiency improves for digital hardware in general, especially for AI chips; second, the rate of growth in demand for data itself." Add in electric vehicles, ever-increased use of electronic devices and communication and entertainment, demands for more electric heating and cooling and dehumidifying, then how we produce and use electricity is set to become the central eco-infrastrutural-political question of the next decade. Can NZ do it without increased use of natural gas or coal power?

🤣 Is 'The end of AI is photovoltaics and energy storage' media hype or did Jensen Huang indeed make a clear statement? Recently, during a latest conversation with Omar Sultan AlOlama, Minister of State for Artificial Intelligence, at the 'World Government Summit,' Jensen Huang, the founder of #nvidia, mentioned the immense energy requirements for AI and computational power in the future. However, there was no explicit statement made regarding 'The end of AI lies in photovoltaics and energy storage.' Nevertheless, it is undeniable that with the advancement in computing power, there is a growing need for more energy to drive this efficiently operating world. And the energy model of #photovoltaics + #energystorage is one of the most mature and promising technologies to date. Jensen Huang's exact words were as follows: "But it's clear that computer architecture is constantly improving. One of the greatest contributions we've made over the past decade is improving computing and artificial intelligence by a millionfold. So, whatever you think is driving the world's demand, you have to consider that it's going to grow by a factor of a million, faster and more efficiently." "When something improves by a millionfold and its costs, space, or energy consumption doesn't increase by a millionfold. In fact, you've already made this technology mainstream." In the conversation, Jensen Huang was praising himself for improving computing power by a millionfold, which translates to saving more energy. #Junnoenergy #artificialintelligence #solarenergy #news #rumors #technology

Energy for data centres serving AI requirements. Another very important consideration which makes simplistic policies look even more shallow. Read the excellent article in the link. An extract follows— ‘There’s a full-on race in the tech industry, and in tech-centric investment communities, to spend billions of dollars on new AI-infused infrastructures. The furious pace of expanding manufacturing to produce AI-capable silicon chips and simultaneously building massive, AI-infused datacenters is shattering the illusion that a digital economy enables a decoupling of economic growth from rising energy use.’

The rapid growth of artificial intelligence (AI) is driving an unprecedented surge in demand for power across the U.S., sparking a race among tech companies to secure energy resources. However, utilities are raising concerns about the strain on the already overburdened power grid, highlighting the immense costs and challenges of accommodating this exponential growth. As AI continues to advance, tech giants are vying for access to electricity, but many are finding themselves on long waiting lists due to the nation’s high-voltage electric grids reaching capacity. This pressure has been exacerbated by the expansion of electric vehicle (EV) infrastructure and the rise of new manufacturing plants, fueled in part by tax incentives from the Inflation Reduction Act. In places like Virginia, California, and Ohio, utilities are already rationing power, and some markets have stopped taking new requests altogether. The competition for power has grown so fierce that some regions, like Salt Lake City and Santa Clara, have instituted moratoriums on large power requests, effectively halting new data center developments. In Ohio, American Electric Power (AEP) is imposing higher electricity rates for data centers and cryptocurrency miners, a move met with resistance from tech companies, who balk at decade-long commitments without the assurance of future demand. AI’s energy consumption is staggering, with each AI query using significantly more energy than traditional search engines. By 2030, data centers are projected to account for up to 9% of U.S. electricity usage, amplifying the need for grid upgrades and new transmission lines. The challenge of building infrastructure quickly enough to meet demand is immense, with utilities warning that delays could stretch into the next decade. This rapid shift is not without controversy. Utilities are looking to shield homeowners and smaller businesses from absorbing the costs of these upgrades, proposing solutions such as “take-or-pay” contracts, which would require data centers to commit to paying for a minimum amount of power, regardless of actual usage. The situation has sparked debates about fairness, with consumer advocates pushing back against proposals that could see residential customers subsidizing the tech industry. As AI continues to reshape industries and drive economic growth, it’s clear that addressing the power infrastructure challenges will be crucial. The tech industry’s thirst for power is testing the limits of the grid and raising difficult questions about how to balance rapid innovation with long-term sustainability. #ArtificialIntelligence #DataCenters #PowerGrid #Utilities #ElectricityDemand #TechGrowth #AIInfrastructure #EnergyConsumption #Sustainability #RealEstate #ElectricVehicles #InflationReductionAct #GridUpgrades https://lnkd.in/eQV-iD3m

According to the CEO of National Grid, the demand for electricity from UK data centers will skyrocket in the next 10 years due to the rapid growth of artificial intelligence (AI) technology. A sixfold increase is expected, driving the need for more computing power and putting pressure on the country's electricity network. This significant surge in energy consumption is a crucial factor that needs to be addressed as the electrification of home heating, transportation, and industries is already straining the grid. As AI and quantum computing continue to evolve, it becomes even more critical to invest in energy-intensive computing infrastructure. Similar challenges are being faced by many countries worldwide. Investing in expanding capacity is essential to support the demand, and the UK's National Grid is studying the implementation of an ultra-high-voltage network. This innovative approach would pave the way for bulk power transfers between energy sources and demand centers, streamlining the process and ensuring a sustainable and resilient energy future. We are excited about the potential of AI to revolutionize various industries, but we also recognize the need for a robust and adaptable energy infrastructure to support this growth. By addressing these challenges head-on, we can ensure a greener and more efficient energy system for the future. Read more about this fascinating development here: https://lnkd.in/g_uiVXnY #AI #energytransition #sustainablefuture #energyinfrastructure

#Datacenters could use as much as 9% of U.S. electricity by 2030, per the Electric Power Research Institute. Big Tech is all-in pursuing an “all of the above” exploration for clean power to meet the demand of #AI. Kore can help data centers and companies solve their expanding #cleanenergy needs.

According to the CEO of National Grid, the demand for electricity from UK data centers will skyrocket in the next 10 years due to the rapid growth of artificial intelligence (AI) technology. A sixfold increase is expected, driving the need for more computing power and putting pressure on the country's electricity network. This significant surge in energy consumption is a crucial factor that needs to be addressed as the electrification of home heating, transportation, and industries is already straining the grid. As AI and quantum computing continue to evolve, it becomes even more critical to invest in energy-intensive computing infrastructure. Similar challenges are being faced by many countries worldwide. Investing in expanding capacity is essential to support the demand, and the UK's National Grid is studying the implementation of an ultra-high-voltage network. This innovative approach would pave the way for bulk power transfers between energy sources and demand centers, streamlining the process and ensuring a sustainable and resilient energy future. We are excited about the potential of AI to revolutionize various industries, but we also recognize the need for a robust and adaptable energy infrastructure to support this growth. By addressing these challenges head-on, we can ensure a greener and more efficient energy system for the future. Read more about this fascinating development here: https://lnkd.in/g_uiVXnY #AI #energytransition #sustainablefuture #energyinfrastructure