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News articleIEEE Spectrum

AI Models Fail Miserably at This One Easy Task: Telling Time

View original at spectrum.ieee.org
AI Models Fail Miserably at This One Easy Task: Telling Time <img src="https://spectrum.ieee.org/media-library/a-digitally-structured-tree-with-a-melting-clock-hanging-off-one-of-its-branches-the-concept-resembles-salvador-dali-s-persist.jpg?id=62053134&width=1200&height=800&coordinates=0%2C133%2C0%2C134" /><br /><br /…
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  • If a MLLM struggles with one facet of image analysis, this can cause a cascading effect that impacts other aspects of its image analysis

    80% confidence
  • We cannot take model performance for granted and extensive training and testing with varied inputs is necessary to ensure models remain robust against diverse real-world scenarios

    80% confidence
  • If the MLLMs made an error in recognizing the clock hands, this in turn resulted in greater spatial errors

    80% confidence
  • Reading the time is not as simple a task as it may seem, since the model must identify the clock hands, determine their orientations, and combine these observations to infer the correct time

    80% confidence
  • While such variations pose little difficulty for humans, models often fail at this task

    80% confidence

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AI Funding Surge: Capital Floods Fintech, Foundation Models, and Autonomous Systems
A concentrated burst of AI-linked funding on 2026-08-28 pushed well over $1.5B into companies spanning fraud/identity fintech (Socure, which also acquired Fravity), foundation models (Stability AI), AI agents and enterprise tooling (Instinct, Generalist AI, Emerald AI, Owner), and AI-adjacent autonomous/aerospace ventures (Gatik, Regent Craft). The breadth and simultaneity of these rounds signal that investor appetite for AI is not concentrated in a single vertical but is broadening into applied and infrastructure-adjacent domains, with consolidation (Socure-Fravity) beginning alongside fresh capital formation.
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Morgan Stanley & Co. LLC
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