Tech
Google Reveals Energy and Water Use of AI Prompts in New Study
Google has disclosed new details about the environmental footprint of its artificial intelligence chatbot Gemini, saying each text prompt consumes only a fraction of energy and water compared with earlier public estimates.
According to a technical paper and accompanying blog post released by the company, a single text query on Gemini uses about 0.24 watt-hours (Wh) of energy — roughly equivalent to watching nine seconds of television. That consumption, Google says, translates to about 0.03 grams of carbon dioxide emissions. In addition, each query requires around 0.26 millilitres of water, or approximately five drops, largely used in cooling data centre equipment.
The company stressed that its measurements accounted not only for the power consumed by the chips running Gemini but also the energy used by IT equipment in data centres, idle chip power, and water for cooling systems. By including these factors, Google argued, its estimates provide a more accurate picture of environmental impact than many existing studies.
“Per-prompt emissions are quite small,” the blog post noted, adding that the company’s figures show energy and water usage to be “substantially lower than many public estimates.”
The announcement comes as concerns grow about the rising energy demands of advanced computing. The International Energy Agency (IEA) recently projected that electricity demand from data centres, AI, and cryptocurrency could double by 2030, with AI alone expected to consume up to 945 terawatt-hours annually — nearly equivalent to Japan’s current power use.
Comparisons between Gemini and other platforms highlight stark differences. A study by the Electric Power Research Institute estimated that a prompt issued to OpenAI’s ChatGPT consumes 2.9 Wh of energy, nearly ten times Google’s figure. By contrast, a traditional internet search requires about 0.3 Wh.
Despite these relatively low per-query figures, Google’s overall emissions have surged in recent years. Its latest environmental report showed emissions up 51 percent since 2019, driven largely by the production and assembly of hardware needed to support AI technology. The company acknowledged that upstream supply chain activities are contributing significantly to its carbon footprint.
At the same time, Google said efficiency improvements are underway. The company claims that since August 2024, energy use and carbon emissions per Gemini prompt have fallen 33-fold and 44-fold respectively, reflecting advances in hardware and software optimization.
However, analysts note that the company’s data leaves key questions unanswered. While per-query emissions are modest, Google has not disclosed the total number of Gemini prompts processed daily. Without those figures, the full scale of the chatbot’s energy demand remains unclear.
As AI adoption accelerates worldwide, the debate over its environmental costs is intensifying. Google’s new disclosures suggest progress in efficiency but also underscore the challenge of balancing technological innovation with sustainability.
Tech
Study Finds AI Use May Weaken Basic Problem-Solving Skills
Tech
Meta Launches Muse Spark, Its First Major AI Model in Nine Months
Meta has unveiled its first major AI model in nine months, following a $14.3 billion (€12.24 billion) investment spree and executive hiring push to rival OpenAI and Google. The American tech company introduced the model, called Muse Spark, on Wednesday, claiming it is faster and smarter than its previous technologies.
The company, founded by Mark Zuckerberg, invested $14.3 billion in Scale AI in June 2025 and recruited its CEO and co-founder, Alexandr Wang, to oversee Meta Superintelligence Labs, which houses teams working on foundational AI models. Zuckerberg also embarked on a hiring campaign, bringing in executives from competitors including OpenAI, Anthropic, and Google.
In a blog post, Meta said, “Over the last nine months, Meta Superintelligence Labs rebuilt our AI stack from the ground up, moving faster than any development cycle we have run before. This initial model is small and fast by design, yet capable enough to reason through complex questions in science, math, and health. It is a powerful foundation, and the next generation is already in development.”
Muse Spark is positioned as a significant upgrade over Meta’s last major release, Llama 4, launched in April 2025. The company highlighted that the model excels in advanced reasoning, particularly in scientific, mathematical, and medical queries. To improve its health advice capabilities, Meta worked with over 1,000 physicians to curate training data, aiming for more accurate and comprehensive responses.
The AI model will power the company’s digital assistant in the Meta AI app and website, with planned integration across Facebook, Instagram, WhatsApp, Messenger, and the Ray-Ban Meta AI glasses. A “contemplating mode” will gradually roll out, allowing multiple AI agents to reason in parallel on complex tasks. Meta’s technical blog noted this feature is designed to compete with high-level reasoning in models such as Gemini Deep Think and GPT Pro.
Zuckerberg emphasized on social media that Meta aims to build AI products that “don’t just answer your questions but act as agents that do things for you.” Unlike conventional chatbots, these AI agents operate autonomously, gathering information based on user preferences to assist without direct human commands.
One notable shift for Meta is the move away from open-source AI models. Unlike earlier releases, Muse Spark is not available for public download, meaning access to the technology is currently restricted. The company said the model is initially available only in the United States.
Muse Spark underscores Meta’s aggressive push into the competitive AI market, combining extensive investment, executive recruitment, and technical innovation to challenge the dominance of established players like OpenAI and Google.
Tech
OpenAI Urges Governments to Rethink Economy as AI Growth Accelerates
OpenAI has called on governments to rethink the foundations of the economy, warning that artificial intelligence (AI) could soon surpass human intelligence and drastically change how people work, live, and pay taxes. The company outlined its initial policy ideas on Monday, aimed at mitigating the economic disruption caused by rapid AI adoption in the United States and worldwide.
One key proposal is the creation of a public wealth fund that would give citizens a direct stake in AI-driven economic growth. According to the policy document, the fund could invest in diversified, long-term assets, including AI companies and broader firms adopting AI technologies, with returns distributed to all citizens.
The company also suggested that governments encourage businesses to launch four-day workweek pilot programs without any reduction in pay. This approach aims to balance the productivity gains provided by AI with the well-being of workers. Lawmakers are also urged to modernize tax systems by increasing taxation on corporate income and capital gains instead of labor income, which could be affected by AI-related job losses. The report proposes additional measures, such as taxing companies that replace human labor with automation.
OpenAI recommends that social benefits, including retirement pensions and healthcare, be provided through portable accounts that follow individuals across different jobs, industries, and entrepreneurial ventures. This model would help ensure continuity of support in a labor market increasingly influenced by AI.
These recommendations echo broader discussions among AI leaders about the future of work. OpenAI CEO Sam Altman and xAI’s Elon Musk have previously highlighted universal basic income as a potential necessity as traditional employment declines. Other tech leaders, including Nvidia’s Jensen Huang and Zoom’s Eric Yuan, have advocated shorter workweeks to distribute productivity gains from AI more evenly.
Concerns about AI’s long-term impact extend beyond economics. In January, Anthropic CEO Dario Amodei warned that superintelligent AI, capable of outpacing human decision-making, poses “existential danger.” He suggested tighter controls on the export of key technologies, such as semiconductor chips used to train large language models, as one way to manage the risk. Amodei also called for transparency laws requiring AI companies to disclose how they guide their models’ behavior.
OpenAI’s policy document represents an early step in urging governments to address the structural changes AI may bring. The proposals highlight the need to rethink traditional concepts of work, taxation, and social support as the technology continues to advance rapidly.
As AI continues to reshape global economies, policymakers and industry leaders face increasing pressure to develop strategies that protect citizens while fostering innovation and sustainable growth.
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