Jinri Yixiu Releases Self-Developed Physiological Signal Large Model and ISHO Personal Agent
On October 29, Jinri Yixiu officially released its self-developed physiological signal large model and the ISHO Personal Agent. The latter features 255 data observation items and supports opening MCP to mainstream AI tools. Its energy index model evaluates users' physiological state from three dimensions: sleep performance, nighttime recovery, and previous day's exercise load. Wang Teng stated that the company plans to collect more than 1,000 cases of gold-standard clinical PSG data within one year, with the goal of building a globally leading AI sleep technology ecosystem within 5-10 years.
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Sina Tech News, October 29 evening news: Today, JINRIYIXIU officially released its self-developed physiological signal large model and the ISHO Personal Agent.
It is understood that the energy index model evaluates the user's physiological state from three dimensions: sleep performance, nighttime recovery, and yesterday's exercise load. The Personal Agent has as many as 255 data observation items, and integrates expert knowledge, personal data, and historical feedback to take over scheduling and provide analysis, planning, and effect tracking. ISHO Personal Agent supports opening MCP to mainstream AI tools.
At the same time, Wang Teng said at the launch event that JINRIYIXIU focuses on precise monitoring, scientific intervention, and energy recovery, and plans to collect more than 1,000 cases of gold-standard clinical PSG data within one year. The scientific research scope of sleep products is extending from nighttime sleep quality to post-waking scenarios such as daytime energy status.
Regarding strategic goals, Wang Teng said that relying on China's excellent engineer resources and top-tier industry chain capabilities, JINRIYIXIU aims to build a globally leading AI sleep technology ecosystem in 5-10 years. news_keyword_pub,stock, iframe below the main text iframe below the main text General statement General statement QR code at the end start QR code at the end start
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