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Real-time artificial intelligence and event processing  

IBM Big Data Hub

AI and event processing: a two-way street An event-driven architecture is essential for accelerating the speed of business. Non-symbolic AI can be useful for transforming unstructured data into organized, meaningful information. This helps to simplify data analysis and enable informed decision-making.

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Advancing AI: The emergence of a modern information lifecycle

CIO Business Intelligence

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact. What’s changed?

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Exploring real-time streaming for generative AI Applications

AWS Big Data

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

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Potentials & Advantages of Knowledge Graph Based Conversational AI in Manufacturing & Industry – Examples, Use Cases, Best Practises

Ontotext

What makes us attractive to our customers is that we centralize corporate knowledge in our Conversational AI platform, where everyone can access corporate data and information easily via natural language. With our technology we can cover most use cases in one go, our platform is data agnostic and can do text and speech in different languages.

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Do I Need a Data Catalog?

erwin

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. Three Types of Metadata in a Data Catalog.

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Commercial Lines Insurance- the End of the Line for All Data

Cloudera

I’ve had the pleasure to participate in a few Commercial Lines insurance industry events recently and as a prior Commercial Lines insurer myself, I am thrilled with the progress the industry is making using data and analytics. Commercial Lines truly is an “uber industry” with respect to data. A Long, Long Time Ago.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”. This is partly because integrating and moving data is not the only problem.

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