OpenAI confirmed to lawmakers that it would support a bipartisan effort in Congress to curb China's access to AI chips and chipmaking tools, Bloomberg reported1.
The company is backing the congressional push to block China's access to artificial intelligence chips. Details of the specific legislation, its sponsors, and the scope of the proposed restrictions were not disclosed in the available reporting.
The effort targets not only finished AI chips but also the equipment used to manufacture them. Applied Materials, a major chipmaking-equipment supplier, separately guided fiscal first-quarter revenue to approximately $11.10 billion, above analysts' $10.89 billion estimate, citing AI chip demand as the key driver2. The company's Semiconductor Systems unit recorded $8 billion in quarterly revenue, roughly 64% higher than a year earlier, and adjusted earnings of $4.16 per share topped the $4.05 analysts tracked by LSEG had expected.
Applied Materials CEO Gary Dickerson said customers want tools "sooner, not later" and that he expects wafer fab equipment demand to rise more than 30%, with 2027 shaping up as another record year. TECHnalysis Research, an analyst firm, said chipmakers and foundries are "buying as much equipment as they possibly can".
ANALYSIS OpenAI's public alignment with chip-export restrictions marks a notable positioning choice for a company that consumes large volumes of advanced AI accelerators and depends on continued access to cutting-edge silicon.
The congressional activity follows a period of heightened scrutiny of AI-related ties to China. Former Nvidia Corp. CEO Jensen Huang agreed to testify before Congress by Thanksgiving on his relationship with a woman suspected of spying for China, House Foreign Affairs Committee Chairman Brian Mast said on November 12[2].
ANALYSIS OpenAI's endorsement of tighter export controls, paired with the booming demand Applied Materials reports for chipmaking tools, frames a tension between restricting adversary access and sustaining the capital-equipment spending cycle that underpins AI infrastructure expansion.