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Embeddable AI saves time building powerful AI applications

IBM Big Data Hub

Just a few weeks ago, IBM announced an expansion to their embeddable AI software portfolio with the release of three containerized Watson libraries. The new libraries include: IBM Watson Natural Language Processing Library for Embed. IBM Watson Speech-to-Text Library for Embed. Partner solutions using embeddable AI.

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Five open-source AI tools to know

IBM Big Data Hub

Open-source AI projects and libraries, freely available on platforms like GitHub, fuel digital innovation in industries like healthcare, finance and education. Leveraging existing libraries and tools, small teams of developers can build valuable applications for diverse platforms like Microsoft Windows, Linux, iOS and Android.

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Technology sets the pace of change in content delivery and management

CILIP

Now we are in a place where Big Data and Artificial Intelligence (AI) are the ideas that are set to launch the next big thing. New conference, ConTech, which takes place in December and is in its second year aims to capitalise on the buzz about data and AI for anyone working with content ?

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Jisc Futurist Q&A ? and 25 per cent off ILI Conference 2018

CILIP

My parents were very poor, but our town had an excellent public library that I practically moved into. s Near Future Library Symposium. Can you give us your Top 5 things on the horizon that library and information professionals need to know about, and why? Do our libraries need to recruit data scientists?

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Application modernization overview

IBM Big Data Hub

While the above is for application decomposition/design, event-storming needs process maps and this is where Generative AI assists in contextualizing and mapping extracts from process mining tools. It also requires some focused effort to improve the data quality of data needed for tuning the models.

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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

ARMA International

For example, organizations can re-package video libraries, songs, research, and course material for different audiences – customers, researchers, academics, students, and so on; and they can monetize the content via CaaS. Data Analytics. Acting generates new data, causing the cycle to repeat, as shown in Figure 4. Press, Gil.