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Disney-backed Inworld raises new cash for its AI-powered virtual characters

TechCrunch

The video game industry is no exception to this, and that hardly comes as a surprise. The brainchild of Ilya Gelfenbeyn, Michael Ermolenko and Kylan Gibbs, the startup’s AI-powered service generates virtual characters primarily for games, but also in broader entertainment and marketing campaigns.

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Innovation without disruption: virtual agents for hyper-personalized customer experience (CX)

CIO

Virtual Agent, or VA, is the next natural step for significantly better customer and business outcomes. VAs make use of automation and a host of AI technologies like machine learning (ML), natural language processing (NLP), sentiment analysis, language translation, speech-to-text, intent recognition, and robotic process automation (RPA).

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CommonGround raises $25M for immersive video avatar technology that doesn’t rely on VR gear

TechCrunch

Like “TrueSelf Scan,” the name of the initial application that’s used to scan a person’s image, the meeting software also will not require a VR headset to use and engage with — users will be “seated” in a room that will be shown on a video screen.

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List of Top 10 Machine Learning Examples in Real Life

Openxcell

But with technological progress, machines also evolved their competency to learn from experiences. This buzz about Artificial Intelligence and Machine Learning must have amused an average person. But knowingly or unknowingly, directly or indirectly, we are using Machine Learning in our real lives.

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Machine Learning In Internet Of Things (IoT) – The next big IT revolution in the making

Openxcell

From human genome mapping to Big Data Analytics, Artificial Intelligence (AI),Machine Learning, Blockchain, Mobile digital Platforms (Digital Streets, towns and villages),Social Networks and Business, Virtual reality and so much more. What is Machine Learning? Machine Learning delivers on this need.

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Generative AI is pushing unstructured data to center stage

CIO

The evolution of AI and the use of structured and unstructured data When discriminative AI rose to prominence in sectors such as banking, healthcare, retail, and manufacturing, it was primarily trained on and used to analyze, classify, or make predictions about unstructured data. have encouraged the creation of unstructured data.

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How we created amazing music with video using Artificial Intelligence

Xebia

We’ve also utilized AI to produce our very own music videos, creating a rich visual narrative that harmonizes perfectly with our music. Every frame of these videos is a testament to the power of AI in generating compelling visual art. These models are powerful tools that use machine learning to generate human-like text.