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Reuters, October 7 – Applied Digital (APLD.O) reported a more than fourfold increase in first-quarter revenue, but its net loss widened compared to the same period last year, as the company ramped up investments to meet the growing demand for data center services. The Dallas, Texas-based company primarily develops and operates data centers to support artificial intelligence and other high-performance computing tasks. In volatile after-hours trading on Wednesday, its stock price rose nearly 2%. Details are as follows: According to data compiled by the London Stock Exchange Group (LSEG), the company’s first-quarter revenue surged from $80.9 million a year earlier to $341.9 million, surpassing the average analyst estimate of $133.8 million. Net loss attributable to common shareholders was $221 million, or $0.76 per share, compared to $18.5 million, or $0.07 per share, in the prior year period. As of August 31, Applied Digital held $3.7 billion in cash, cash equivalents and restricted cash, while carrying $6.4 billion in debt. Total costs and expenses this quarter jumped from $90.7 million a year earlier to $404.3 million. Applied Digital stated that the increase in costs resulted from higher spending to prepare customers’ data centers, increased stock-based compensation, and higher interest expenses as the company expanded its AI infrastructure. “We are focused on long-term development, with a clear commitment to building large-scale, sustainable AI factory campuses, and signing durable, high-quality long-term contracts with leading, proven, investment-grade hyperscale enterprises in the AI industry,” CEO Wes Cummins said in a statement. (For the convenience of non-native English speakers, Reuters provides automated translations of its reports into several other languages. Since automated translations may contain errors or lack necessary context, Reuters does not guarantee the accuracy of the automated translations and provides them solely for reader convenience. Reuters is not liable for any damages or losses caused by the use of automated translation features.)