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Thorsten-4 see through executives’ false confidence on earnings calls and beat sentiment tools at predicting actual stock outcomes, and a hedge fund now trades a $50M portfolio on it.
Language models predict the next word, while Thorsten-4 predicts a person’s next move.
It reads how someone writes or speaks (word choice, sentence structure, how those patterns shift over time) and maps those signals onto an established psychology framework to predict what drives them and how they’ll decide.
The big deal is the training data: 50+ psychologists interviewed 7,000+ people and went back over 4 years to compare what each person said with what they actually did, so the model learned the link between words and real behavior, which internet text never records.
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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AI can write code, pass the bar exam and sound human.
It still can’t tell when you’re unsure, holding back or about to walk away.
Today we’re introducing Thorsten-4, a Large Psychology Model that predicts what people will do next. https://t.co/0nlMOH9mA4
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