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Decoding Emotions: AI Model Predicts People's Feelings - Neuroscience News

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Researchers developed a computational model capable of predicting human emotions, encapsulating social intelligence attributes typically associated with the human 'theory of mind'

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Can Empathetic AI become the Foundation of Customer Interactions?

Unite.AI

As AI adoption jumped over 70% in 2024, global interest in technology is soaring, paving the way for new artificial intelligence concepts. What role is empathetic AI going to play in the future? Some assumptions suggest that emotional AI will never happen due to the complexity and nuance behind human empathy.

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SK Telecom outlines its plans with AI partners

AI News

Furthermore, SKT aims to collaborate with Scatter Lab, a renowned AI startup known for its Lee Lu-da chatbot. The company plans to integrate an emotional AI agent into its AI service, ‘A.’ By joining forces, the companies aim to establish a leading position in the global AI market.

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Josh Feast, CEO and Co-Founder of Cogito – Interview Series

Unite.AI

Cogito received funding from the Defense Advanced Research Projects Agency (DARPA) to research and develop an artificial intelligence platform and behavioral models to automatically detect human psychological states. In turn, this improves both the customer experience, and the agent experience.

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AI Emotion Recognition and Sentiment Analysis (2025)

Viso.ai

Enterprise computer vision pipeline with Viso Suite We provide an overview of Emotion AI technology, trends, examples, and applications: What is Emotion AI? How does visual AI Emotion Recognition work? Facial Emotion Recognition Datasets What Emotions Can AI Detect? What is Emotion AI?

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This AI newsletter is all you need #59

Towards AI

NASA and IBM Openly Release Geospatial AI Foundation Model for NASA Earth Observation Data NASA and IBM Research have collaborated to release the HLS Geospatial FM, an open-source geospatial AI model for Earth observation data.

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How to Detect AI-Generated Content

Viso.ai

Lexical diversity is low in AI-generated content because AI models learn from large datasets of text, which might contain common words and phrases used repeatedly. While human writers readily employ sentences of varying lengths and structures, AI models often struggle with constructing longer, more intricate sentences.