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Building AI for business: IBM’s Granite foundation models

IBM Big Data Hub

The Granite family of models is no different, and so we trained them on a variety of datasets — totaling 7 TB before pre-processing, 2.4 TB after pre-processing — to produce 1 trillion tokens, the collection of characters that has semantic meaning for a model. Besides this, we apply a wide range of other quality measures.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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Capgemini and IBM Ecosystem strengthen partnership for Drone-as-a-Service

IBM Big Data Hub

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The global commercial drone market is projected to grow from USD 8.15

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Chart your path in AI: How OpenText Magellan is unlocking the power of information

OpenText Information Management

One of the big challenges for organizations today is how to realize the business value currently locked in the huge amounts of unstructured data being generated. Some experts claim as much as 80 percent of data collected by organizations is unstructured – information such as emails, social media feeds and documents.

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The most valuable AI use cases for business

IBM Big Data Hub

But right now, pure AI can be programmed for many tasks that require thought and intelligence , as long as that intelligence can be gathered digitally and used to train an AI system. Generative AI can produce high-quality text, images and other content based on the data used for training.

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Success of AI in academic libraries depends on underlying data

CILIP

Stephan will make a presentation as part of breakout on breakout on data behaviour with Julian Schwarzenbach and Caroline Carruthers at the forthcoming CILIP Conference 2019 in Manchester, in which he will be focusing on the use of unstructured data in libraries. What will be the benefit from analysing unstructured data with AI?

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.