Flexible bankThe ambitions of noble artificial intelligence are collided with the harsh reality of the prices.
The Japanese conglomerate plan to invest $ 100 billion in AI infrastructure in the United States has slowed down, Bloomberg reported Monday, May 12, because the risks linked to the Prices of the White House led to funding discussions.
Earlier this year, SoftBank and OPENAI undertakes it Stargate Project, an AI infrastructure effort that could cost $ 500 billion over time.
Months after this announcement, However, Softbank still doesn’t have find A project financing model or has held detailed discussions with banks, investor investors and asset managers, according to the report.
Although there have been preliminary conferences with lenders and managers of alternative assets, no transaction has followed because financiers rethink the data centers in a context of increasing economic volatility and cheaper IA services, according to the report.
The White House trade policies have escaped investors of more risky bets in the midst of concerns about a recession. In addition, the appearance of AI models Like China In depth has raised questions about long -term profitability of OPENAI projects, according to the report.
Softbank did not respond to the request for comments from Pymnts.
The news came while Openai is dealing with changes. This month, the company supported the plans to convert into a vitreous entity. The restructuring effort of the startup still requires the approval of Microsoftits greatest investor. This weekend Also has seen information that the two companies rework their income sharing agreement.
The Stargate project is one of the many AI data center efforts be developed by large technological companies.
“AI data centers are fundamentally different because they require specialized equipment and infrastructure to manage the massive parallel processing necessary for AI workloads”, ” Deborah Perry Piscioneco-founder of Work3 Institutesaid an AI and Web3 consulting firm, told Pymnts in January. “Traditional data centers focus on storage and basic calculation, while AI installations need GPU dense configurations and AI Accelerators, such as NVIDIA H100, designed specifically for complex matrix calculations that feed the AI models.”
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