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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution.

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Re-evaluating data management in the generative AI age

IBM Journey to AI blog

A good place to start is refreshing the way organizations govern data, particularly as it pertains to its usage in generative AI solutions. For example: Validating and creating data protection capabilities : Data platforms must be prepped for higher levels of protection and monitoring.

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How a solid generative AI strategy can improve telecom network operations

IBM Journey to AI blog

Chain-of-thought (CoT) loops : Network use cases often involve multistep reasoning across multiple data sources. Without proper control, AI agents can enter endless loops, leading to inefficiencies due to incomplete or misunderstood data.

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How two software companies are using IBM watsonx for their enterprise generative AI solutions

IBM Journey to AI blog

In the year since we unveiled IBM’s enterprise generative AI (gen AI) and data platform, we’ve collaborated with numerous software companies to embed IBM watsonx™ into their apps, offerings and solutions.

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What can AI and generative AI do for governments?

IBM Journey to AI blog

When implemented in a responsible way—where the technology is fully governed, privacy is protected and decision making is transparent and explainable—AI has the power to usher in a new era of government services. appeared first on IBM Blog. IBM stands ready to empower governmental organizations in the age of AI.

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Shooting to score with Scout Advisor’s NLP

IBM Journey to AI blog

As Victor Orta, Sevilla FC Sporting Director, explained at his conference during the World Football Summit in 2023: “We are never going to sign a player with data alone, but we will never do it without resorting to data either. In fact, paperwork is a much more significant part of the job than one might imagine.

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Open source large language models: Benefits, risks and types

IBM Journey to AI blog

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. Proprietary LLMs are owned by a company and can only be used by customers that purchase a license.