UK to acquire $130M in AI chips amid computing power rush
August 21, 2023 5:28 AM
According to a recent survey, 20% of organizations do not have adequate computing capacity for AI, so the chips could be utilized to establish an AI resource.
In the midst of a worldwide scarcity and battle for computing capacity, British Prime Minister Rishi Sunak has announced plans to spend 100 million pounds ($130 million) on purchasing thousands of computer chips to enable artificial intelligence.
As part of Sunak's strategy to make the UK an AI tech center, the country plans to construct an "AI Research Resource" by the middle of 2024, as reported→ by The Telegraph on August 20.
The government is purportedly purchasing processors from NVIDIA, Intel, and AMD; the organization leading the initiative, UK Research and Innovation, is supposedly in the final stages of placing an order for 5,000 NVIDIA GPUs.
While $130 million has been set aside for the project, it is being stated that this amount falls short of what Sunak envisions for his AI hub. As a result, government officials may push for additional money during a summit on AI safety in November.
It comes after a report found that many businesses are having trouble deploying AI due to a lack of funding and expertise in the field.
According to a March report→ on the state of artificial intelligence computing in the country, funding for this field is "seriously lagging" behind that of the United States and the European Union.
At the time, there were just over 1,000 NVIDIA chips available for academics to develop AI models on; a panel advised that the UK make at least 3,000 high-quality chips available to address immediate needs.
In its worldwide AI trend study released on August 16th, S&P Worldwide discovered that many companies claimed they are not ready to embrace AI owing to a lack of processing capacity, difficulties managing data, and security issues.
It may be early in the history of artificial intelligence, but according to S&P senior research analyst Nick Patience, the ability to sustain AI workloads will be a significant element in determining market dominance.