New research finds that by making the fossil fuel industry more productive, AI could help increase carbon emissions by up to nearly 5 percent--vastly outpacing the impact of data centers. The emissions from powering data centers rightly get a lot of attention. But new research from former Microsoft sustainability workers cautions that the way artificial intelligence enhances productivity in the oil and gas industry could be much more damaging to the planet. Published last week in the journal npj Climate Action, the research finds that AI use could significantly increase global energy emissions simply by enabling the fossil fuel industry to produce more oil and gas. At the low end, the research finds that the additional yearly emissions could be equal to Mexico's; at the high end, AI boosting the fossil fuel industry could add as much greenhouse gas emissions as Russia, the world's fourth-largest emitter.

Estimates suggest AI will create close to £370bn in cumulative value for fossil fuel companies between 2026 and 2030. Estimates suggest AI will create close to £370bn in cumulative value for fossil fuel companies between 2026 and 2030. AI's potential climate benefits outweighed by role in boosting fossil fuels, study finds AI-driven productivity gains enable more planet-heating pollution from fossil fuels than they avoid from renewables, a study has found. Researchers modelled the technical potential for AI to boost clean power generation along with projections for how it can help produce coal, oil and gas. Across 64 scenarios, they found net yearly carbon pollution rose by 0.47-1.8

Chevron and Williams are big winners in the race to power artificial intelligence as they build out gas-fired power plants and pipelines. It's been a banner year for oil and gas companies. Some of the world's biggest oil giants have announced billions of dollars in quarterly profits over the past two weeks, boosted largely by the soaring price of oil thanks to the conflict in the Middle East. But the artificial intelligence boom is also giving fossil fuel companies a new industry to sell their gas, pipelines, and power plants to: data centers . Two American oil and gas companies, Williams and Chevron, are presenting that demand to investors as a huge win.

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America's pettiest cyclist takes infuriating'revenge' on innocent drivers after spotting truck blocking Boston bike lane Royal fans criticise Oprah for failing to'challenge' Meghan and Harry's claims in tell-all 2021 interview - as she defends asking the duchess if she was'silenced' I caught my wife doing something so revolting in the shower. I don't believe her excuse for a second: DEAR JANE Over-the-counter allergy medication recalled over fears of contamination with drug that can cause'life-threatening' reactions Inside America's saddest ever murder trial: Lindsay Clancy strangled all three of her children... then got paralyzed as she tried to kill herself. Matt Damon reveals why he had a FEMALE stunt double in The Odyssey... amid backlash over'woke' casting World's most narcissistic countries revealed... and America's shock ranking ChatGPT maker OpenAI says AI model went rogue during testing and'escaped' into the internet where it launched'unprecedented' cyberattack I was hiding the shame of being a hard-working mother who drank and took cocaine. Then I took Mounjaro to lose weight... the effect on my humiliating habits was astonishing Nearly three dozen buildings revealed as potential sources of deadly lung disease outbreak... as deaths and cases continue to rise Horrifying photos of Kaylee Hottle's fatal car crash emerge after Godzilla vs Kong child's star shock death aged 18 I thought I had the perfect marriage. Then my husband of 20 years revealed he'd been sleeping with men for a decade.

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The rapid growth of large AI models has raised significant environmental concerns due to their substantial carbon footprint. Existing carbon accounting methods for AI models are fundamentally deterministic and fail to account for inherent uncertainties in embodied and operational carbon emissions. Our work aims to investigate the effect of these uncertainties on embodied and operational carbon footprint estimates for large AI models. We propose a Probabilistic Carbon Accounting Model (PCAM), which quantifies uncertainties in the carbon accounting of large AI models. We develop parameter models to quantify key components (processors, memory, storage) in the carbon footprint of AI models. To characterize the distribution of the parameters, we develop a carbon dataset by aggregating related data from various sources. Then, we generate the probabilistic distribution of the parameters from the collected dataset. We compare the performance of PCAM with LLMCarbon, the state-of-the-art carbon accounting method for large AI models.

While promising, existing methods suffer from two major limitations: 1) reliance on real data from limited domain for knowledge fusion, preventing the target LLM from fully acquiring knowledge across diverse domains, and 2) fixed data allocation proportions across domains, failing to dynamically adjust according to the target LLM's varying capabilities across domains, leading to a capability imbalance. To overcome these limitations, we propose Bohdi, a synthetic-data-only heterogeneous LLM fusion framework. Through the organization of knowledge domains into a hierarchical tree structure, Bohdi enables automatic domain exploration and multi-domain data generation through multimodel collaboration, thereby comprehensively extracting knowledge from source LLMs. By formalizing domain expansion and data sampling proportion allocation on the knowledge tree as a Hierarchical Multi-Armed Bandit problem, Bohdi leverages the designed DynaBranches mechanism to adaptively adjust sampling proportions based on the target LLM's performance feedback across domains. Integrated with our proposed Introspection-Rebirth (IR) mechanism, DynaBranches dynamically tracks capability shifts during target LLM's updates via Sliding Window Binomial Likelihood Ratio Testing (SWBLRT), further enhancing its online adaptation capability. Comparative experimental results on a comprehensive suite of benchmarks demonstrate that Bohdi significantly outperforms existing baselines on multiple target LLMs, exhibits higher data efficiency, and virtually eliminates the imbalance in the target LLM's capabilities. Our code is available at Bohdi.

DOJ Lawyers Argue xAI Is'Vital' for National Security in NAACP Lawsuit In a bid to dismiss a lawsuit over xAI's polluting gas turbines, the Justice Department claimed the company is integral to military operations--including the Iran War. The Department of Justice intervened in a lawsuit over xAI's gas turbines on Monday. In a filing, the agency sided with Elon Musk's company, saying attempts to stop xAI from running the natural gas turbines "threatens American national, economic, and energy security by seeking to shut off the power supply for artificial-intelligence innovation that supports the Department of War's military operations." The DOJ, along with xAI and the state of Mississippi, asked the court to dismiss the suit, filed by the NAACP in April. The NAACP alleges xAI isn't following the Clean Air Act and is endangering public health by running unpermitted natural gas turbines at the site of its second data center in Southaven, Mississippi, dubbed Colossus 2. In May, the NAACP filed a request for a preliminary injunction to stop xAI from running the turbines, alleging that their continued use without a permit "increases risks of asthma attacks and heart disease" in communities with an already heavy pollution burden .