Is AI killing technology?

"Major RAM makers Samsung, SK Hynix, and Micron have shifted their production to focus on High-Bandwidth Memory (HBM) needed for AI. This has led to shortages of standard DRAM and NAND chips used in smartphones, laptops, and medical devices. Driving hardware prices up. Due to the memory shortage, building non-AI electronics is becoming expensive. By early 2026, prices for standard computer memory and storage drives (SSDs) had surged"

"Delaying GPUs and the devices that use them. The demand for AI compute power, which usually relies on Graphics Processing Units (GPUs), has created a massive backlog for the processors and with it, the devices that use them for, you know, processing graphics. Creating COVID-like shortages. The diversion of chips to AI infrastructure is causing problems for non-AI hardware launches. Shortages of basic power and auto chips are affecting industries from automakers to home appliance makers. It's like COVID all over again."

"Diverting investment in startups. Non-AI startups are struggling to raise money. Investors are funneling cash almost exclusively into AI ventures, forcing non-AI founders to pivot or adopt "AI-first" aspects (called "AI washing"), even when unnecessary. Private AI companies are hiring away top academic researchers and engineers with massive salaries. This hollows out university departments and non-AI research labs, threatening the pipeline of future talent"

The AI industry is redirecting memory production toward High-Bandwidth Memory (HBM) for AI, creating shortages of standard DRAM and NAND used in consumer and medical devices. Memory scarcity has pushed up prices for non-AI electronics and SSDs, prompting some consumers to buy second-hand laptops. Intense demand for GPUs has produced a significant backlog, delaying devices that rely on them. Chip diversion to AI infrastructure is causing shortages across power, automotive, and appliance sectors. Investors concentrate capital into AI ventures, leaving non-AI startups underfunded and prompting superficial AI pivots. High salaries at private AI firms are luring top academic researchers, weakening university labs and future talent pipelines.

Read at Computerworld