California [US], July 8, (ANI): Apple has entered into a USD 30 billion partnership with Broadcom to build custom chips and cutting-edge wireless connectivity technologies for its products.
The agreement between the two US tech players aims to expand the domestic manufacturing of chips. Apple said that the multiyear commitment with Broadcom will lead to the production of 15 billion US-made chips, thereby supporting hundreds of American jobs.
“Apple and Broadcom have a long history together, and this new phase of our partnership further accelerates our commitment to American manufacturing and innovation,” Apple CEO Tim Cook said.
Cook said the company is deepening its investments in US-based suppliers, and thanked President Donald Trump and the US administration for supporting the efforts.
The agreement with Broadcom will be Apple’s largest commitment as part of its American Manufacturing Program (AMP) that was launched last year to bolster US manufacturing. Broadcom is part of Apple’s AMP initiative. The agreement will also see Broadcom expand and modernise its manufacturing facilities in Fort Collins, Colorado, with a $1.5 billion capital expenditure investment.
The US chipmaker will make advanced radio frequency components — including FBAR filters — and advanced wireless connectivity technologies at the Fort Collins facility.
“With Apple’s newest commitment, we’re pleased to expand our manufacturing footprint in Fort Collins, where we create groundbreaking technology that connects people around the world,” Broadcom President and CEO Hock Tan said.
In an SEC filing on July 6, Broadcom announced that it has entered into an agreement with Apple to expand its long-standing technology collaboration through 2031. It will develop and supply a range of custom ASIC silicon products for use in multiple generations of Apple products.
An ASIC is an application-specific integrated circuit that is used for specific tasks rather than being built for general-purpose computing. These chips offer superfast computing along with great efficiency and are used for performing AI tasks. (ANI)
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