LLMs are stuck in a groupthink groove. This startup is trying to get them out.
JA title: 大規模言語モデルの「集団思考」の罠：スタートアップの打開策
What to read for
3 checks before implementation
- 01Article focus
ChatGPTなどのAIに同じような質問をすると、多くの場合で同じ答え（例：1～10の数字なら7）が返ってきてしまう問題が報告されています。
- 02Operational lens
日本企業がAIを導入する際、回答の予測可能性が高いと顧客体験やコンテンツ生成の品質低下につながる。
- 03Verify in source
MIT Technology Review (Research): check the dataset, evaluation setup, and adoption assumptions for R&D.
Let’s start with a game. Open up your chatbot of choice—Claude, ChatGPT, Gemini—and type “Give me a random number between 1 and 10.” You’re going to get 7. Almost always. Now type “Another” and you’ll get 3 or 4. Type “Another” again and you’ll get 8 or 9. That won’t work every time—but if it did for you, you may wonder if I have superpowers. I don’t. The truth is that most large language models are stuck in a rut. They are far more predictable and far less creative in their…
ゼロビズAX View — How Japanese companies can apply it
日本企業がAIを導入する際、回答の予測可能性が高いと顧客体験やコンテンツ生成の品質低下につながる。特にマーケティング・カスタマーサポート・創作系業務での差別化が難しくなる。このスタートアップの技術は汎用化すれば、LLM選択の新しい評価軸となる可能性があるが、現状は情報不足。プラットフォームレイヤーでの対応か、プロンプト工学での工夫で部分的に緩和できる。
Plain-language glossary
Simple explanations of the technical terms used in this article.
- LLM（大規模言語モデル）
- The 'brain' behind chat AIs — a model trained on huge amounts of text to understand and write language.
- プロンプト
- The instruction you give an AI. Wording it well changes the quality of the answer.
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Primary source: https://www.technologyreview.com/2026/07/01/1140003/llms-are-stuck-in-a-groupthink-rut-this-startup-is-trying-to-get-them-out/
This article is an AI-generated summary of overseas primary sources. Translations or summaries may be imperfect — always confirm the original before making implementation decisions. The "ゼロビズAX View" is our applied interpretation and does not guarantee any specific outcome.
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