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A user on X (formerly Twitter) discusses using the AI tool Apodex 1.1 to analyze the causes of rising global oil prices, predict future price trends, and highlight market uncertainties.
TRACES is a new AI benchmark by Apodex designed to measure discoverative AI by focusing on the problem-solving process rather than memorized answers, challenging traditional benchmarks.
Apodex has released an open-weight DeepResearch fine-tuned model, Apodex-1.0-mini, based on Qwen3.5-35B-A3B. It scores 71.5 on BrowseComp, approaching flagship model performance, and can run efficiently locally. The author packaged an out-of-the-box skill.
Discusses the challenge of verifying AI-generated hypotheses in scientific discovery where no ground truth exists, and presents Apodex's multi-agent approach with independent verifier agents as a solution.
This article uses the AI tool Apodex to thoroughly fact-check an investment blogger's narrative about CPO stock $SIVE, finding that four out of five core claims are problematic. It demonstrates how to leverage AI for fact-checking investment narratives.
Apodex releases Apodex-1.0, a deep-research model that uses a heavy-duty agent team with global verification, achieving state-of-the-art results on multiple benchmarks including BrowseComp, DeepSearchQA, and HLE.
The author tests the Apodex 4B-SFT and 35B mini models, finding the 4B-SFT surpasses other 4B models in multi-hop search tasks without hallucination, and notes the design philosophy of separating answer checking from generation.
AgentOS and Apodex 1.0 introduce a runtime and open-weight model family for long-horizon agent tasks, using independent verification to prevent agent drift. The platform includes skeptical sub-agents and achieves high scores on complex benchmarks.