Alphabet, Google’s parent company, is developing a new server chip to enhance the efficiency of its in-house Gemini models. The chip, internally known as 'Frozen v2,' is expected to be released in 2028, according to The Information, which cited anonymous sources. The report suggests the chip could be between six and 10 times more efficient than Google’s existing AI chips, measured by the number of tokens generated per unit of power. Google did not confirm or deny the report when contacted by TechCrunch, instead emphasizing its ongoing research into innovations for improved performance and efficiency. 'Our teams are constantly researching and experimenting with new innovations to deliver maximum performance and efficiency for our users and customers,' the company stated. 'While not every project moves into production, this rigorous exploration is central to our full stack approach.'

The move aligns with a broader industry trend of AI firms developing custom chips to optimize their models and reduce reliance on external hardware providers like Nvidia. Such efficiency has become a key selling point as concerns about AI spending have tempered market enthusiasm. Companies are also seeking to reduce their dependence on Nvidia, which has historically dominated the AI chip market. In June, OpenAI announced its first custom chip, an inference processor called Jalapeño. Earlier this month, it was reported that Anthropic was discussing a new chipmaking partnership with Samsung. Investors have previously expressed concerns about Alphabet’s massive planned expenditures for its AI strategy, which include a projected spending range of $180 billion to $190 billion. With significant investments at stake, the company needs to demonstrate the value of these initiatives.

The news of the more efficient Frozen v2 chip appears to have reassured investors, leading to a 3% rise in Google’s stock following the publication of The Information’s report. This boost comes ahead of Google’s earnings report later this week. The development highlights the growing importance of hardware innovation in the AI sector as companies strive for efficiency and independence from traditional chipmakers.

Source: techcrunch