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Shield Your RAG System from these 4 Unstructured Data Risks

While large language models excel in mimicking human-like content generation, they also pose risks of producing confusing or erroneous responses, often stemming from poor data quality.  Poor data quality is the primary hurdle for companies embarking on generative AI projects, according to...

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Contemplative AI, (In)Stability AI, AI Antibodies, and More

Augmented Shelf | Issue 3 | March 26, 2024 Welcome to Augmented Shelf, a wrap-up of the week’s AI news, trends and research that are forging the future of work. Enterprises Quintuple-Down on GenAI in 2024 New research from a16z punctuates the enterprise sector’s growing bet on...

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Pick the Best Conversational AI Platform: A Straightforward Guide

Whether it’s through text-based chatbots on a website or voice-activated assistants in our homes and smartphones, conversational AI is becoming an integral part of our daily lives. By simulating human-like conversations, these advanced AI systems are breaking down the barriers between...

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Can AI Governance Frameworks Protect You from GenAI’s Risks?

Artificial intelligence is changing technology in groundbreaking ways, affecting everything from business to daily life. However, this rapid advancement brings up significant ethical, legal, and societal concerns, highlighting the urgent need for effective AI governance frameworks. To ensure AI...

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The Panoramic Guide to Diffusion Models in Machine Learning

Diffusion models for machine learning are cutting-edge technologies that are reshaping how we leverage artificial intelligence. They excel at generating and transforming data in ways we once thought were exclusive to human creativity. Imagine an artist starting with a blank canvas, gradually...

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The Rise of Generative Question Answering with LLMs

Businesses face an overwhelming amount of data rich with insights to unlock. Traditional keyword-based searches have long been the go-to method for wading through this informational deluge, but as the complexity and volume of data expand, the inefficiencies of such systems become more apparent....

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How Data Hydration Can Unlock the Potential of Your Data

Data hydration, the process of enhancing and enriching existing data, has become increasingly vital in the era of big data and artificial intelligence. In this article, we explore the concept of data hydration, the challenges organizations face in managing structured and unstructured data, and the...

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GANs Explained: How Generative Adversarial Networks Work

As artificial intelligence continues to push boundaries and redefine industries, Generative Adversarial Networks (GAN) have emerged as a game-changer. GANs are transforming the way we generate creative content, from artwork to music, and are revolutionizing fields such as healthcare, art,...

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Natural Language Processing – A Deep Dive for IT Leaders and Data Scientists

Natural Language Processing (NLP) is an interdisciplinary field blending computer science, artificial intelligence, and linguistics, aimed at enabling computers to understand, interpret, and engage with human language in both written and spoken forms. NLP combines computational linguistics with...

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10 Tried and Tested Generative AI Prompts for Customer Service Agents

This article presents 10 Generative AI prompts tested and refined to improve customer service effectiveness excerpted from our eBook, 51 Tried and Tested Generative AI Prompts for Customer Service Agents. With Generative AI, agents can rapidly generate personalized, context-aware responses across...

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Opening the Black Box: How to Create AI Transparency and Explainability to Build Trust

Can we really trust Artificial Intelligence? Let’s face it. AI has trust issues. AI is rapidly permeating our lives. But perhaps even more rapidly permeating, are fears about AI. Fears that are largely due to a lack of transparency as to how AI works. These concerns are evident in questions people...

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AI Bias, What It Is and How to Fix It

What Is Bias in AI? In the realm of artificial intelligence (AI), bias is an anomaly that skews outcomes, often reflecting societal inequities. AI bias can originate from various sources, including the data used to train AI models, the design of algorithms themselves, and the way results are...

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