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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. However, these systems lack genuine understanding and can’t adapt to situations outside their training. Regardless, these are examples of narrow AI.

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5 things to know: Driving innovation with AI and hybrid cloud in the year ahead

IBM Big Data Hub

For organizations of all types—and especially those in highly regulated industries such as financial services, government, healthcare and telco—considerations including the rise of generative AI, evolving regulations and data sovereignty laws and ongoing security challenges must be top of mind.

Cloud 70
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At IBM Think, partners are front and center

IBM Big Data Hub

It’s why we gave partners access to the same training and enablement as IBMers last year, launched a new partner program in January, and continue investing in and growing the IBM Ecosystem. Now I’d like to share a few examples of partner work doing just that.

Cloud 101
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The aftermath of an incident – business considerations surrounding record-keeping

Data Protection Report

Organizations should also be aware of sector-specific statutory obligations which may apply to them, for example in health or financial services industries. In this post we discuss the operational advantages of a good privacy breach record-keeping program. Risk management and mitigation.

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What can AI and generative AI do for governments?

IBM Big Data Hub

Such services can empower citizens and help restore trust in public entities by improving workforce efficiency and reducing operational costs in the public sector. Or they can stay on the sidelines and risk missing out on AI’s ability to help agencies more effectively meet their objectives.

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Conversational AI use cases for enterprises

IBM Big Data Hub

For example, natural language understanding (NLU) focuses on comprehension, enabling systems to grasp the context, sentiment and intent behind user messages. Enterprises can use NLU to offer personalized experiences for their users at scale and meet customer needs without human intervention.

Analytics 106
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Confidential Containers with Red Hat OpenShift Container Platform and IBM® Secure Execution for Linux

IBM Big Data Hub

Some example use cases to highlight: Confidential AI: leverage trustworthy AI and while ensuring the integrity of the models and confidentiality of data Organizations leveraging AI models often encounter challenges related to the privacy and security of the data used for training and the integrity of the AI models themselves.