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Google’s recent development in the AI chip sector has sparked notable shifts in the stock market, particularly impacting Nvidia and AMD. The news centers around Google’s potential deal with Meta to supply billions of dollars worth of its custom AI chips.

Google’s Strategic Move into AI Chips

According to a report from The Information, Meta is in talks with Google to purchase AI chips for its data centers starting in 2027. This collaboration includes plans for Meta to rent access to Google’s chips from the cloud business next year.

Market Implications

This potential partnership may allow Google to capture a significant share of the chip market, possibly equating to 10% of Nvidia’s annual revenue. Historically, Google provided chip access primarily through its cloud business, without direct sales to third parties.

Performance of Google’s AI Chips

• Google’s AI chips, known as tensor processing units (TPUs), have gained attention for their cost-effectiveness compared to Nvidia’s offerings.
• These chips were instrumental in training Google’s latest generative AI model, Gemini 3, which received positive reviews.
• As a result, Google’s stock has reached record highs, overtaking Microsoft in market capitalization.

Meta’s Interest in TPUs

Meta is reportedly considering utilizing TPUs for training complex tasks rather than just for inference. This showcases the growing demand for efficient AI processing solutions.

Stock Market Reactions

The announcement had immediate effects on the stock market. Shares of Nvidia and AMD dropped approximately 2% in after-hours trading, while Google’s stock rose by about 2%.

Nvidia’s Response

Nvidia’s CEO, Jensen Huang, recently commented on the competitive landscape during a conference call. He suggested that the complexity of inference tasks presents a challenge, implying that traditional GPUs may still hold an edge over custom chips.

Adapting Software for AI Development

As part of its strategy, Google has been enhancing its JAX software, making TPUs more accessible to developers. Updates include compatibility with open-source frameworks like PyTorch, which was developed by Meta, and improvements in error reporting and custom coding capabilities.

This shift highlights Google’s intent to strengthen its position in the competitive field of AI technology, indicating a significant evolution in the landscape of processor design and development.