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AI & Machine Learning
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Harnessing AI To Build Lightning-Fast Customer Insights in Natural Language
If you're like most businesses, you've collected much more data in the past than you need, relying on analysts and dashboards to turn your mountain of data points into actionable insights. In this article, our AI and Data Science team will show you some key ideas on how you can make super-fast natural language insights work for you by leveraging LLMs.
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The Road to Trustworthy LLMs: How to Leverage Retrieval-Augmented Generation
People say generative AI is prone to hallucinations, but using specific techniques we can greatly enhance both precision and transparency. Join us as we take you on a survey of how Retrieval Augmented Generation, a.k.a. RAG, can show you what's behind the AI curtain.
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Overcoming LLM Hallucinations with Trustworthiness Scores
In today's AI-driven world, businesses increasingly rely on large language models (LLMs) to scale operations. However, the risk of AI generating inaccurate or misleading information can also scale, posing significant challenges. This article delves into trustworthiness scoring, exploring its key dimensions and techniques. Through real-world examples, we show how trustworthiness scores can help mitigate LLM hallucinations, making your AI solutions more reliable and accurate. Discover how to enhance the trustworthiness of your AI implementations in our comprehensive guide, with a nod to the work done by MIT's CleanLabs.
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How the Best Companies Actually Build Intelligence: The Secrets Behind High-Volume Knowledge Graphs
What makes a Knowledge Graph scalable? This guide unpacks how top companies design and maintain high-volume graphs—covering ontology tips, identifier strategies, and common pitfalls to avoid.
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Scraped by AI? The Signs You’re Being Harvested—and What to Do
Bots now train AI on your content. Learn the warning signs and a layer defense playbook, that you can use.
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