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Transcripts For BBCNEWS Talking 20240615

for more of this energy hungry infrastructure. also on the show, we re going to get the view from the us tech giant ibm. yeah, they ve seen their demand for al skyrocket. so what are they doing to cut down on their carbon emissions? wherever you rejoining me from around the world, once again, a big hello and a warm welcome to the show. artificial intelligence. yep, ai. it is everywhere nowadays. and the big tech companies like google, meta, microsoft, and now apple, they re muscling in to be at the head of the ai race, unveiling ever more sophisticated chat bots and other machine learning tools. but one aspect of the ai race that s perhaps not talked about as much is the impact on the environment. these language models, like chatgpt, are some of the most energy guzzling technologies. they need vast data centres to store the amount of data required to train the chat bots. so let me just show you some of the numbers. emissions from global cloud computing account for around 2.1%

Technology interventionsBusiness weeklyLet s goTake a lookAaron heslehurstArtificial intelligenceCarbon emissionsEnergy consumptionBig tech sDirty secretGreen energyMachine learning toolsData centreDavid pughBig bossTech giant

Transcripts For CSPAN Public Affairs 20130709

Competitors who are investing heavily in renewable and next Generation Energy technologies. I strongly urge that we defeat the previous question and i urge a no vote on the underlying bill. I yield back the balance of my time. The speaker pro tempore the gentleman from colorado yields back the balance of his time. The gentleman from texas is recognized. Mr. Burgess thank you mr. Speaker. I yield myself the balance of our time. The speaker pro tempore the gentleman is recognized. Mr. Burgess i cannot recall a place in the constitution where it says the house passes a bill, the senate cant pass it, so the house comes back and tries to find a better bill that maybe the senate will now take up. I wish that had happened on that health care stuff back in 2009 and 2010, we would have a lot better world today. The fact of the matter is the house has passed the student loan bill. The senate has the obligation to act. The deadline of july 1 was in fact provided to us by a funding clip the democr

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Accelerating Energy Transition for Greener ICT | Huawei Global Digital Power Forum Held Successfully

Accelerating Energy Transition for Greener ICT | Huawei Global Digital Power Forum Held Successfully
sydneysun.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from sydneysun.com Daily Mail and Mail on Sunday newspapers.

Comunidad autonoma de catalunaYang bifeiAnthony gacanjaMauro leuceSanjay kumar sainaniKyriakos exadaktylosHenry daunertLi shaolongCharles yangVodafone energy flexibilityEnergy transition for greenerEnergy performanceData center facility critical powerGlobal data center businessHead of network architecture specificationsVodafone group technology

Accelerating Energy Transition for Greener ICT | Huawei Global Digital Power Forum Held Successfully

Accelerating Energy Transition for Greener ICT | Huawei Global Digital Power Forum Held Successfully
tmcnet.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from tmcnet.com Daily Mail and Mail on Sunday newspapers.

Comunidad autonoma de catalunaAnthony gacanjaMauro leuceSanjay kumar sainaniLi shaolongYang bifeiHenry daunertKyriakos exadaktylosCharles yangPrnewswire huawei global digital power forumService transformationEnergy performanceVodafone energy flexibilitySafaricom networkData center facility critical powerEnergy transition for greener

Data-driven surrogate optimization for deploying heterogeneous multi-e by Haoshan Ren, Dian ce Gao et al

Energy storage such as battery and thermal energy storage is an effective approach to shift building peak load and alleviate grid stress at a building cluster level. However, due to the heterogeneous performance of different types of storage (e.g., response speed, charge/discharge efficiency and rate, storage capacity) and highly diversified energy use patterns of individual buildings, the multi-energy storage should be properly selected and optimally designed for individual buildings to achieve effective load shifting. The optimal deployment of multi-energy storage at a cluster level is a challenging optimization problem due to the nonlinear dynamic performance of the multi-energy storage and the high dimensionality as a result of a large number of buildings. To tackle the challenges, this study proposes a data-driven surrogate optimization method that optimally deploys multi-energy storage at a cluster level to minimize the building cluster energy bill under demand response programs.

Building clusterData driven optimizationDemand responseEnergy flexibilityEnergy storagePtimal deployment