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How to enable trustworthy AI with the right data fabric solution

IBM Big Data Hub

Trustworthy AI has become a requirement for the successful adoption of AI in the industry. Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

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

ARMA International

Peter Drucker (1999) compared the Industrial and Information Revolutions and their impacts on societies, industries, and jobs. So, the concept of DT is not new and was predicted as the foundation for the Fourth Industrial Revolution. [1] Figure 1: Illustration of Bush’s Memex. Information and Content Explosion.

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How to choose the best AI platform

IBM Big Data Hub

.” When observing its potential impact within industry, McKinsey Global Institute estimates that in just the manufacturing sector, emerging technologies that use AI will by 2025 add as much as USD 3.7 AI technology is quickly proving to be a critical component of business intelligence within organizations across industries.

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5 Major Cybersecurity Trends to Know for 2024

eSecurity Planet

After receiving input from industry experts and doing my own analysis of the year’s driving forces, I identified five major cybersecurity trends. Industry experts see that AI will require governance action, cause learning pains, and will be used to both improve and attack cybersecurity.

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

Our Watson suite is deployed to more than 100 million users across 20 industries, while the dedicated teams in IBM Research continue to push at the frontiers of the technology. The early use cases that we have identified range from digital labor, IT automation, application modernization, and security to sustainability.

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What’s your data democratization strategy? How to successfully democratize data

Collibra

This is, hands down, the most frequently cited barrier to data democratization—especially among organizations lagging behind the industry leaders. As with any organization-wide change, there will be hurdles to overcome as you train your team on new data-related tools and processes. Security risks. Secure buy-in.