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The Strengths and Limitations of Large Language Models

Eric D. Brown

LLMs are proving their worth in various applications, from customer service chatbots to content creation tools. They can sift through social media posts, customer reviews, and reports to identify trends and sentiment. Invest in training and development to ensure your team has the skills needed to work with advanced AI technologies.

Training 130
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Voice Cloning Conundrum: Navigating Deepfakes in Synthetic Media

SecureWorld News

We explored various applications of AI, tackled the strategic and ethical considerations, and emphasized the vital interplay between human expertise and automated systems. Given these developments, organizations and individuals relying on voice authentication must reconsider their security frameworks.

Media 92
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What is the responsibility of developers using generative AI

Dataconomy

“What is the responsibility of developers using generative AI?”—a This is why AI must be developed responsibly, in ways that address identifiable concerns like fairness, privacy and safety, with collaboration across the AI ecosystem. What is the responsibility of developers using generative AI in ensuring ethical practices?

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What IT leaders need to know about the EU AI Act

CIO Business Intelligence

The European Parliament voted in mid-March to approve the EU AI Act , the world’s first major piece of legislation that would regulate the use and deployment of artificial intelligence applications. The requirements to monitor AI development and use will add governance obligations for companies using both high-risk and general-purpose AIs.

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What LinkedIn learned leveraging LLMs for its billion users

CIO Business Intelligence

For the business- and employment-focused social media platform, connecting qualified candidates with potential employers to help fill job openings is core business. So the social media giant launched a generative AI journey and is now reporting the results of its experience leveraging Microsoft’s Azure OpenAI Service.

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Ethical AI: Tackling bias and ensuring fairness in machine learning algorithms

Dataconomy

One of the most recognizable trends of the early years of the 21st century has been the spread and application of AI (Artificial Intelligence) within many professional areas. Ethical concerns about data privacy, consent and security are critical particularly in AI-based applications that require lots of training data.

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Ethical AI: Tackling bias and ensuring fairness in machine learning algorithms

Dataconomy

One of the most recognizable trends of the early years of the 21st century has been the spread and application of AI (Artificial Intelligence) within many professional areas. Embedding ethical AI principles in development processes 1. These AI framework is little bit very complex task to understanding.