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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分47

@millionwaysai 发布 Thorsten-4,用于分析对话中的行为特征

AI 导读

Thorsten-4 可分析会议、访谈、邮件和客服通话等对话,为每个人评估 50 项行为与心理特征。它可通过 millionways Platform、API、MCP 或自行托管接入现有 AI 产品。发布材料称,在已完成的企业试点中,结合 Thorsten-4 的 GPT 比单独使用 GPT 更擅长判断客户意图,但未给出试点规模或具体成绩。

原帖引用 · 原文

@rohanpaul_ai

🧵3/n 10+ companies already use Thorsten-4 across executive search, customer experience, financial services and AI agent platforms, and a multi-strategy hedge fund began trading a dedicated $50M portfolio on its reads of earnings calls.

Multiple top-10 executive search firms also confirmed its read on leadership interviews against their own assessments.

回复Rohan Paul@rohanpaul_ai
🧵2/n. Official Site - https://t.co/71q9knXri3 AI is now learning psychology the way psychologists do, by watching the same people for years. Thorsten-4 plugs into the models, agents and AI products companies already run, through the millionways Platform, an API, MCP (Model Context Protocol, a standard way to hook AI agents up to outside tools) or a self-hosted setup, so nothing gets replaced. In completed enterprise pilots, GPT paired with Thorsten-4 beat GPT alone at reading customer intent.
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相关上下文Rohan Paul@rohanpaul_ai
Brilliant release and this is such a different kind of AI. @millionwaysai launched Thorsten-4 today, AI that reads people’s motives Every AI company trains on the same internet, and the internet doesn’t record why people do what they do. So the AI agents now running sales calls, job interviews and customer service keep misreading people, and each misread costs a dea. > Thorsten-4 is built on 15+ years of psychology research that started long before ChatGPT, > 50+ trained psychologists interviewed 7,000+ people repeatedly over 4 years (from an 8-year-old to billionaires), > hand-tagged 35M+ words from those conversations, and checked the model’s predictions against what people actually did. It’s a Large Psychology Model that lets AI read the person behind the words, predicting their motives, decision style and likely reactions with 90% validated accuracy. AI agents now run sales calls, job interviews, and negotiations, but they miss the hesitation and pushback that decide how those conversations end, like the doubt behind a prospect’s “sounds great”. LLMs were built to read words, not people, and 10 leading AI models fall about 45% short of humans at tracking how a person’s thoughts and feelings change over time. They also cave easily, since leading AI models flip a correct answer 46% of the time when a user pushes back. Thorsten-4 reads the conversations companies already have (meetings, interviews, emails, chats and support calls) and scores each person on 50 behavioral and psychological traits, showing what drives them, how they decide and how they react under stress. Its training data can’t be scraped off the internet, because 50+ trained psychologists interviewed 7,000+ people again and again over 4 years and hand-tagged 35M+ words from those conversations. The team then checked the model’s predictions against established psychology tests and against what those people actually did over several years. Every read is explainable and traces back to the evidence behind it, and Thorsten-4 holds its read when a user pushes back. Companies plug it into the AI tools they already use, so their agents know when to push, when to pause and how to adapt. 🧵1/n https://t.co/pobxIhjhtP
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来源:Rohan Paul · x.com

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