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AI tool uses face photos to estimate biological age and predict...

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OpenAI’s agentic age begins: ChatGPT Tasks provides job scheduling, reminders, and...

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ChatGPT now handles reminders and to-dos.

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Samsung teases Bixby AI makeover

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Google tests simpler Circle to Search

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Google Photos removing the ‘Memories tab’ on Android

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Meta accused of using pirated torrents to train its AI

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Meta AI’s Llama Language Model modded to run in old Xbox...

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OpenAI presents a new blueprint for AI regulation that is its...

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Sa2VA: A Unified AI Framework for Dense Grounded Video and Image...

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This AI Paper Introduces Toto: Autoregressive Video Models for Unified Image...

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Is Automated Hallucination Detection in LLMs Feasible? A Theoretical and Empirical...

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This AI Paper Introduce WebThinker: A Deep Research Agent that Empowers...

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A Step-by-Step Guide to Implement Intelligent Request Routing with Claude

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Researchers from Fudan University Introduce Lorsa: A Sparse Attention Mechanism That...

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Is Automated Hallucination Detection in LLMs Feasible? A Theoretical and Empirical...

Recent advancements in LLMs have significantly improved natural language understanding, reasoning, and generation. These models now excel at diverse tasks like mathematical problem-solving and generating contextually appropriate text. However, a persistent challenge remains: LLMs often generate hallucinations—fluent but factually incorrect responses. These hallucinations undermine the reliability of LLMs, especially...