Remove Deep Learning Remove Emotion AI Remove NLP
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Josh Feast, CEO and Co-Founder of Cogito – Interview Series

Unite.AI

The Emotion AI technology that is used at Cogito was first validated by assisting healthcare providers to detect early signs of PTSD and other mental health disorders in soldiers returning from combat. We are consistently working on and evolving our NLPs with new data to mitigate bias.

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Understanding the different types and kinds of Artificial Intelligence

IBM Journey to AI blog

Unlike basic machine learning models, deep learning models allow AI applications to learn how to perform new tasks that need human intelligence, engage in new behaviors and make decisions without human intervention. Emotion AI is a theory of mind AI currently in development.

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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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How to Detect AI-Generated Content

Viso.ai

Large Language Models (LLMs): These models are recent breakthroughs in the space of natural language processing (NLP), empowering machines to understand and generate human-like language. LLMs are built using deep learning techniques and trained on vast amounts of data. A few examples of GANs are CycleGAN, StyleGAN2, and GauGAN.

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How to Identify AI-Generated Content

Viso.ai

Large Language Models (LLMs): These models are the breakthrough in the space of natural language processing (NLP), empowering machines to understand and generate human-like language. LLMs are built using deep learning techniques and trained on vast amounts of data. A few examples of GANs are CycleGAN, StyleGAN2, and GauGAN.

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AI For The Blind: A Guide to Building Assistive Solutions

Viso.ai

Let’s explore the steps of building an AI for the blind one by one and go through some examples. Data Collection and Annotation Deep learning models are highly dependent on data quality and volume. Data collection and cleaning are critical steps in developing effective deep-learning models.

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Blockchain and AI Integration : Can These Technologies Work Together?

Pickl AI

Machine Learning AI systems often employ machine learning algorithms to learn from data and improve their performance over time. Natural Language Processing (NLP) NLP enables AI systems to understand, interpret, and generate human language.