
What happened
A programmer who attended Ceatec 2026 wrote on Zenn that almost every booth was AI-related, that he was surprised to find a staffing agency there, and that his local LLM (an AI model run on a company's own machines) plan for internal AI had been branded "AI knowledge".
Why it matters
He argues the industry now prioritizes the buyer's image over technical specifications, and that "AI says wrong things" is disclosed largely because a company could face huge damages if something happened and it were not disclosed.
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The Zenn post is framed around a visit to Ceatec 2026, where the author found almost every booth AI-related and was surprised to see a staffing agency among them. He contrasts this with past shows where visitors came specifically to touch products like the Mac, and says today's exhibits are mostly parts of larger systems, prompting image-based pitches rather than technical specifics.
The author ties this to a broader concern that both buyers and sellers let image take priority over understanding what is real. In that context, he notes that current AI cannot explain the mathematics of Transformer Self-Sttension's KQV, and that it is used because validation studies found its answers accurate. That, he writes, is the real reason AI is labeled as sometimes wrong: without such disclosure, a lawsuit could cost an AI company massive damages.
He also describes his own experience using AI as a programming aid past retirement age, saying his form system ACR took a year to build with AI and required what would likely have been over 1,000 programmers and testers, and hundreds of millions in yen, 30 years ago. He closes by reflecting on a TV story of an 85-year-old woman with three months to live who talks with AI daily, and on the hope that machines, originally meant to help people, are never used to harm or deceive.
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