National Post (Canada)
중도 성향
IT/기술
The federal government is getting into AI data centres. It should expect controversies
An AI data centre is a facility designed to power artificial intelligence systems
IT/기술 · "CENTRES" · 총 24건
필터 보기현재 지수
50.3
0 = 부정 우세
50 = 중립
100 = 긍정 우세
최근 7일 기준 86,271건을 분석한 결과, 뉴스 심리지수는 50.2(균형)입니다. 긍정 4,345건(5.0%)·중립 79,797건(92.5%)·부정 2,129건(2.5%)이며, 중립 비중이 뚜렷하게 높습니다. 성향 지수는 종합 14.7(중도 균형)입니다.
An AI data centre is a facility designed to power artificial intelligence systems
States are competing for data centres, cloud infrastructure, AI compute capacity and digital ecosystems.
Blackstone-backed AirTrunk plans a massive Rs 3 lakh crore investment in India by 2030 to boost digital infrastructure, including data centres and AI capacity. Prime Minister Modi welcomed the move, highlighting its potential to strengthen India's global position in cloud computing and AI, create jobs, and drive innovation-led growth.
Ottawa's AI strategy includes plans to build out data centres, which many Canadians have pushed back against because of the environmental and community impacts.
TAIPEI, June 4 — Foxconn said today it will work with US chipmaker Intel to jointly develop and deploy next-...
Anwar Ibrahim says rising electricity demand from AI, semiconductors, and data centres is straining infrastructure, which could transfer the cost burden to consumers.
By 2023, the major hyperscalers (Amazon, Google, Microsoft and Meta) operated close to 992 data centres globally, with capacity having doubled in just four years
The race to build data centres in Australia could force household electricity prices up by as much as 26 per cent within a decade, a study has found.
[New Times] Microsoft and G42's planned digital investment in Kenya has become a case study in how large infrastructure deals can run into challenges tied to power availability, policy direction, and public interest.
Shares of Anant Raj surged as much as 4.6% to Rs 563.25 in Tuesday's trade after the company announced a landmark partnership with the Government of Haryana to accelerate the state's digital infrastructure buildout.The real estate and infrastructure developer has signed a Memorandum of Understanding (MoU) with the Haryana Enterprises Promotion Centre (HEPC), marking a significant step in its ambitions to expand its data centre and cloud services business.The agreement was formalized on June 1, 2026, during the launch of the "Make in Haryana Policy & Other Sectoral Policies" event, presided over by Haryana Chief Minister Nayab Singh Saini.Rs 25,000 crore investment planUnder the MoU, Anant Raj intends to invest around Rs 25,000 crore in building data centres and cloud infrastructure across Haryana. The move highlights the company's increasing emphasis on digital infrastructure as demand continues to grow for artificial intelligence (AI), cloud computing, and data storage solutions.The partnership framework involves several key government departments and agencies, including:Haryana Enterprises Promotion Centre (HEPC)Department of Information Technology, Electronics & CommunicationHaryana State Electronics Development CorporationCitizen Resources Information DepartmentDepartment of Industries & CommerceThe agreement is designed to support Anant Raj's expansion of its Digital Infrastructure Business, encompassing both data centre operations and cloud services. The Haryana government, through HEPC, has committed to providing facilitation support and ease-of-doing-business assistance to help fast-track the project.The company said the arrangement aims to foster long-term cooperation between the state government and Anant Raj, positioning Haryana as a major hub for next-generation digital infrastructure investments.Anant Raj clarified that the MoU does not involve any shareholding arrangement, special rights, equity issuance, or related-party transaction. The agreement is focused solely on enabling investment and operational expansion in the state.Share price performance and technical indicatorsOver the past three years, the stock has delivered strong returns, rallying nearly 254%. The company currently commands a market capitalization of approximately Rs 19,406 crore.From a technical perspective, the 14-day Relative Strength Index (RSI) stands at 61. An RSI reading below 30 typically indicates oversold conditions, while a reading above 70 suggests the stock may be overbought.The stock also exhibits strong bullish momentum, trading above all eight of its key Simple Moving Averages (SMAs), signaling a positive technical trend.(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)
Coalition of more than 100 organisations says move could lead to more children ending up in adult detention facilities A coalition of more than a hundred refugee children’s organisations has said controversial plans to use AI to assess the age of young asylum seekers could lead to more children wrongly ending up in adult prisons or detention centres. The warning follows a Home Office announcement on Friday of a contract to roll out AI facial age estimation technology on young asylum seekers whose age is disputed. Continue reading...
Artificial intelligence is getting expensive — and companies are starting to rethink their embrace of the disruptive technology. Playing by a well-worn Silicon Valley playbook, AI companies charged rock-bottom prices to hook customers after ChatGPT burst onto the scene. Kevin Simback of startup incubator Delphi Labs calls it the era of “subsidised intelligence” — meaning investors were basically footing the bill so companies could offer AI on the cheap. “But the tides are beginning to turn,” Simback warned and an era where the big AI companies actually need to make money has begun — with leaders OpenAI and Anthropic looking to go public and attract main street investors later this year. Prices are rising across the board, and one big reason is AI agents. Unlike a chatbot that just answers questions, agents actually do things — book appointments, write code, manage files. And they’re expensive to run, because one task can spin up dozens of agents all working at once, each racking up charges. Those charges are measured in tokens — the basic unit AI companies use to bill customers. A single agent-powered task can burn through dozens of times’ more tokens than a simple chat message. Meanwhile, the computer chips and data centres needed to power all this AI can’t keep up with demand, creating computing shortages and adding further uncertainty to the nascent industry. “Especially in developer circles, the cost to use AI for things like coding has grown exponentially,” said Mark Barton of tech consultancy Omniux. “All the costs are really starting to skyrocket.” Some companies have been so eager to use AI that they’ve gone overboard in a usage binge called “tokenmaxxing”. “In some cases, people are seeing the cost of tokens exceed the cost of the employee within a month or two of use, just because they’re using it too much,” says analyst Jack Gold of J.Gold Associates. Smarter spending Even Meta — which earlier this year encouraged employees to use as many tokens as possible as a measure of productivity — has had second thoughts. “Nobody should be using AI tools just for the sake of using them,” chief technology officer Andrew Bosworth wrote in a memo to staff, reported by the Wall Street Journal. Uber’s chief operating officer this week went a step further, raising eyebrows by saying all this AI spending was showing no noticeable increase in productivity. To cut costs, some companies are switching to free, open-source AI models that anyone can download — not as powerful as ChatGPT or Anthropic’s Claude, but good enough for many tasks. Others are moving to smaller, more specialised models built for specific industries like real estate or finance, rather than giant general-purpose ones. And some are simply breaking big AI tasks into smaller steps, handing each piece to the cheapest model that can handle it. The price difference can be dramatic. “The big large monolithic model, it’s $15 per million tokens, but you can get that down to like five cents if you use the smaller mini model,” says Adrian Balfour of consultancy Enverso. All of this points to AI becoming more like a commodity — where the specific model matters less than finding the right one at the right price. But don’t count out the big players and their state-of-the-art models just yet. “The most advanced users” will always be willing to pay for the best, says John Belton, a portfolio manager at Gabelli Funds. “It’s a growing pie.”
Artificial intelligence is getting expensive — and companies are starting to rethink their embrace of the disruptive technology. Playing by a well-worn Silicon Valley playbook, AI companies charged rock-bottom prices to hook customers after ChatGPT burst onto the scene. Kevin Simback of startup incubator Delphi Labs calls it the era of “subsidised intelligence” — meaning investors were basically footing the bill so companies could offer AI on the cheap. “But the tides are beginning to turn,” Simback warned and an era where the big AI companies actually need to make money has begun — with leaders OpenAI and Anthropic looking to go public and attract main street investors later this year. Prices are rising across the board, and one big reason is AI agents. Unlike a chatbot that just answers questions, agents actually do things — book appointments, write code, manage files. And they’re expensive to run, because one task can spin up dozens of agents all working at once, each racking up charges. Those charges are measured in tokens — the basic unit AI companies use to bill customers. A single agent-powered task can burn through dozens of times’ more tokens than a simple chat message. Meanwhile, the computer chips and data centres needed to power all this AI can’t keep up with demand, creating computing shortages and adding further uncertainty to the nascent industry. “Especially in developer circles, the cost to use AI for things like coding has grown exponentially,” said Mark Barton of tech consultancy Omniux. “All the costs are really starting to skyrocket.” Some companies have been so eager to use AI that they’ve gone overboard in a usage binge called “tokenmaxxing”. “In some cases, people are seeing the cost of tokens exceed the cost of the employee within a month or two of use, just because they’re using it too much,” says analyst Jack Gold of J.Gold Associates. Smarter spending Even Meta — which earlier this year encouraged employees to use as many tokens as possible as a measure of productivity — has had second thoughts. “Nobody should be using AI tools just for the sake of using them,” chief technology officer Andrew Bosworth wrote in a memo to staff, reported by the Wall Street Journal. Uber’s chief operating officer this week went a step further, raising eyebrows by saying all this AI spending was showing no noticeable increase in productivity. To cut costs, some companies are switching to free, open-source AI models that anyone can download — not as powerful as ChatGPT or Anthropic’s Claude, but good enough for many tasks. Others are moving to smaller, more specialised models built for specific industries like real estate or finance, rather than giant general-purpose ones. And some are simply breaking big AI tasks into smaller steps, handing each piece to the cheapest model that can handle it. The price difference can be dramatic. “The big large monolithic model, it’s $15 per million tokens, but you can get that down to like five cents if you use the smaller mini model,” says Adrian Balfour of consultancy Enverso. All of this points to AI becoming more like a commodity — where the specific model matters less than finding the right one at the right price. But don’t count out the big players and their state-of-the-art models just yet. “The most advanced users” will always be willing to pay for the best, says John Belton, a portfolio manager at Gabelli Funds. “It’s a growing pie.”
MONTREAL — About three months ago, a U.S. shipping broker saw nearly a dozen loads of copper and electronics bound for artificial intelligence data centres vanish in transit. The theft cost it nearly US$5 million, estimates Keith Lewis, who was working with the company. “The bad guys are good at marketing,” said Lewis, head of […]
Japanese tech investor SoftBank will spend €75 billion ($87.5 billion) on artificial intelligence infrastructure in France, its founder Masayoshi Son told a French newspaper in an interview published Saturday.
As artificial intelligence strains the physical limits of existing data centres, scientists and investors are turning to the ultimate speed limit of the universe for the next computing frontier: light. For Mi Lei, founder of CAS Star, a venture capital firm born out of the state-run Chinese Academy of Sciences (CAS), the sudden global fascination with photonics is less a surprise than a delayed validation. It is a thesis he has spent more than a decade trying to support with funding. “New...
The announcement is a major boost to president Emmanuel Macron's efforts to attract high-tech industries to France.
ENQUÊTE - Depuis le Covid, les demandes de diagnostic de neuroatypie chez les adultes ont explosé en France, saturant les centres spécialisés. Entre vraie révélation et fausse piste, ce que cherchent ces adultes est souvent plus complexe qu’ils ne l’imaginent.
China's abundant supply of cheap electricity is a key advantage in the rollout of data centres needed to run AI models.