OpenAI CEO Sam Altman questioned the need for large amounts of RAM in personal computers. He said memory stays unused most of the time. However, the AI industry’s massive demand for computing power has pushed up memory prices, making many smartphones and PCs more expensive for regular people today.
Synopsis
OpenAI CEO Sam Altman has questioned the need for large amounts of RAM in personal computers, arguing that much of the memory remains unused and could be utilised more efficiently through centralised cloud infrastructure. However, his remarks come at a time when the AI industry's growing demand for computing power is contributing to rising memory prices, making smartphones, PCs and other consumer devices more expensive.
OpenAI CEO Sam Altman has sparked a debate after suggesting that keeping large amounts of DRAM in personal computers is an inefficient use of the world’s limited memory supply.
Speaking on the Cheeky Pint podcast, Altman argued that memory inside personal computers is utilised only around 5% of the time and that centralised cloud infrastructure could make better use of these resources.
His argument about resource utilisation has merit. However, the timing is questionable, particularly when the AI industry’s growing appetite for memory is contributing to rising prices across consumer electronics.
Over the past several months, we at Economic Times Digital have extensively reported on how rising memory and storage costs are affecting smartphones and other consumer devices.
In our conversations with executives from Samsung, Google and realme, the growing demands of AI, memory costs and on-device computing have been recurring industry discussions.
Samsung executive JB Park acknowledged that elevated memory prices could persist for another year or two. Similarly, realme executives described the current memory cost increases as among the most serious the industry has witnessed in decades. Our discussions with Google have also explored the growing importance of on-device AI.
And consumers are already feeling the impact.
As highlighted in Economic Times reporting, smartphone manufacturers including Samsung, realme, Vivo, Oppo and OnePlus have increased prices across select devices amid rising component costs.
Even the second-hand market is feeling the pressure. As we highlighted in our Economic Times Digital Instagram video, pre-owned smartphones are becoming more expensive, affecting consumers who traditionally relied on refurbished devices as affordable alternatives.
AI’s enormous computing appetite
Importantly, this is not about OpenAI alone. The entire AI industry is making extraordinary investments in computing infrastructure.
OpenAI’s Stargate project outlined plans for up to $500 billion in AI infrastructure investment. The company has also expanded its computing partnership with Amazon Web Services, with announced agreements totalling $138 billion.
Meanwhile, Anthropic has announced commitments exceeding $100 billion for AWS technologies and expanded its computing partnerships with Google and Broadcom. Amazon, Microsoft, Google and Meta are also investing heavily in AI data centres.
These are multi-year investments and commitments, not necessarily amounts already spent. But they demonstrate the scale of computing resources the industry requires.
And that demand extends beyond processors to high-bandwidth memory, server DRAM and storage. While data-centre memory and PC RAM are not always interchangeable, they compete for manufacturing resources and investment across the semiconductor supply chain.
Why Altman’s argument is being scrutinised ?
Personal computers are not simply underutilised hardware. They power professional workflows, creativity, gaming and increasingly, on-device AI. Local computing also gives consumers greater control over privacy and their dependence on cloud services.
There is an irony in technology companies encouraging consumers to embrace AI-powered personal devices while questioning the efficiency of memory inside those same computers.
This is not to suggest AI companies should stop expanding their infrastructure. AI computing demand is real, and the technology has significant applications. But consumers should not be expected to compromise on their hardware while the industry collectively commits hundreds of billions of dollars to computing capacity.
The bigger question is not whether personal computers are wasting DRAM. It is whether AI’s rapid expansion is making everyday technology increasingly expensive for the very consumers the industry wants to serve.
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