Category: GenAI

  • Why you should learn prompt engineering now, even if it will not be needed in the future …

    Why you should learn prompt engineering now, even if it will not be needed in the future …

    Forrester predicted, a whopping 60% of employees will be trained in prompt engineering by 2024! (Forrester) But what exactly is prompt engineering, and why is it the skill everyone will soon be scrambling to master? Prompt engineering is the craft of designing queries that steer Generative AI models like ChatGPT and Claude to deliver highly…

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  • The Rising Value of Vector Indexes for Generative AI

    The Rising Value of Vector Indexes for Generative AI

    As Gen AI solutions begin to become a common component of data ecosystems, one approach that’s quickly becoming a foundational feature is Retrieval-Augmented Generation (RAG), which combines the power of large language models with external knowledge retrieval. RAG systems work by first retrieving relevant information from a knowledge base (e.g., Wikipedia, corporate documents) and then…

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  • Data Clean Rooms for Generative AI

    Data Clean Rooms for Generative AI

    Could Data Clean Rooms open new collaborative opportunities with GenAI? This security-centric technology could potentially unlock new use cases. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮 𝗗𝗮𝘁𝗮 𝗖𝗹𝗲𝗮𝗻 𝗥𝗼𝗼𝗺? A data clean room is a secure environment where different organizations can share and analyze data sets while maintaining strict controls around data privacy and security. The data clean room…

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  • Digital Twins … Use of Gen AI for Synthetic Data Creation

    Digital Twins … Use of Gen AI for Synthetic Data Creation

    Generative AI has been making waves in the tech world, and one of the most promising applications is in the realm of synthetic data creation. But what exactly is synthetic data, and how can generative AI be used to create it? Synthetic data refers to artificial data that is computer-generated to mimic real-world data. This…

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  • Fine-tuning Large Language Models

    Fine-tuning Large Language Models

    Fine-tuning Large Language Models is like hiring a specialist with exact experience for the best outcomes. Like an arm wrestler, intensely training to be extremely proficient at performing a specific task. That’s essentially what fine-tuning is for large language models (LLMs) – a way to customize a powerful, general-purpose model to specialize in your organization’s…

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  • The Rejuvenation of Modern Data Lakes to Support Generative AI

    The Rejuvenation of Modern Data Lakes to Support Generative AI

    The era of generative AI has ushered in a new wave of innovation and disruption across industries. As these models become more sophisticated and widely adopted, the demand for high-quality, diverse, and well-structured data has skyrocketed. This may have potentially reignited interest in modern data lake architectures, which offer a compelling solution for managing the…

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  • Explaining: Explainable AI (XAI)

    Explaining: Explainable AI (XAI)

    In the ever-evolving world of technology, Artificial Intelligence (AI) continues to make leaps and bounds, enhancing how we work, make decisions, and interact with the world around us. A pivotal aspect of this transformation is Explainable AI (XAI), which is steering the conversation from mere outcomes to understanding the ‘how’ and ‘why’ behind AI decisions.…

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  • Challenges of GenAI-Integrated Coding Today

    Challenges of GenAI-Integrated Coding Today

    From the start, generative AI has had a strong focus in the world of coding.  Although it brings great value and possibilities, in its current state, there are still complexities which create situations to be considerate of when leveraging GenAI for the coding world. Here’s a deep dive into some of these challenges: 🔍 Understanding…

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  • The Power and Limits of Retrieval-Augmented Generation (RAG)

    The Power and Limits of Retrieval-Augmented Generation (RAG)

    Empowering GenAI with relevant details about a business to truly enable it to provide value for an organization can be done through supplementing its knowledge. A key player in this space is Retrieval-Augmented Generation (RAG), a cutting-edge technology blending traditional AI with advanced information retrieval techniques. 🔍 What is RAG?Imagine you’re preparing a crucial market…

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  • LLM Mesh: Enabling Organizations to Get True Value from GenAI

    LLM Mesh: Enabling Organizations to Get True Value from GenAI

    🕸 What is LLM Mesh? LLM Mesh is framework designed to integrate and manage Large Language Models (LLMs) within the enterprise environment. It’s a common backbone for generative AI applications, addressing key challenges in scalability, cost, and security. Think of it as a central hub that connects various AI models and services, streamlining their application…

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