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Training LLMs to Predict World Events (Guest Post with Mantic) - Thinking Machines Lab

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Mantic have been using Tinker since it launched. This guest post is a technical deep dive on what they have built so far. The top AI forecasting systems are approaching superforecaster-level accuracy on geopolitics and current affairs.It’s over (Polymarket, 2026) This is exciting because scalable, automated forecasting could significantly improve the quality of decision-making across the economy and in government. To date, the most successful recipe in forecasting tournaments has been to combine an off-the-shelf LLM (like Gemini 3 or GPT-5) with forecasting-specific context-gathering. These models, to our knowledge, have not been explicitly trained for forecasting. Can we improve the recipe by replacing them with models fine-tuned specifically for forecasting?

Mantic have been using Tinker since it launched. This guest post is a technical deep dive on what they have built so far. The top AI forecasting systems are approaching superforecaster-level accuracy on geopolitics and current affairs. It’s over (Polymarket, 2026) This is exciting because scalable, automated forecasting could significantly improve the quality of decision-making across the economy and in government. To date, the most successful recipe in forecasting tournaments has been to combine an off-the-shelf LLM (like Gemini 3 or GPT-5) with forecasting-specific context-gathering. These m

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