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Introducing the technology behind watsonx.ai, IBM’s AI and data platform for enterprise

IBM Journey to AI blog

It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know. Traditional AI tools, while powerful, can be expensive, time-consuming, and difficult to use. Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models.

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10 Best AI Tools for Retail Management (December 2024)

Unite.AI

What makes these tools particularly useful is their ability to process millions of micro-decisions simultaneously, from optimal shelf placement to precise inventory timing, creating a level of retail orchestration that was previously impossible. The post 10 Best AI Tools for Retail Management (December 2024) appeared first on Unite.AI.

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Advancing AI trust with new responsible AI tools, capabilities, and resources

AWS Machine Learning Blog

Responsible AI builds trust, and trust accelerates adoption and innovation. As generative AI continues to grow and evolve, transparency on how technology is developed, tested, and used will be a vital component to earn the trust of organizations and their customers alike. We also updated the AWS Responsible Use of AI Guide.

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Data is essential: Building an effective generative AI marketing strategy

IBM Journey to AI blog

The generative AI tool can also incorporate external factors like weather, upcoming events or the shopper’s location. But what if the generative AI tool recommends the customer buy a bathing suit in the middle of winter or a snow parka in the summer? For decades, IBM has been at the forefront of AI for business.

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How Cities Are Deploying Leading Technologies Leveraging Unbiased AI Algorithms

Unite.AI

Unfortunately, many municipalities remain locked into contracts with hardware and device providers who claim to operate under “open architecture” yet are unwilling to work under an open data platform, and these cities severely restrict themselves from the true possibilities that a cloud-based platform can provide.

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Generative AI use cases for the enterprise

IBM Journey to AI blog

Existing content can be reimagined and edited using AI tools. Organizations can also create custom generative AI language generators trained on their brand’s tone and voice to match previous brand content more accurately. Jobs that have historically been automation-proof will be further affected by generative AI.

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Sarah Assous, Vice President of Product Marketing, Akeneo – Interview Series

Unite.AI

While traditional PIM systems are effective for centralizing and managing product information, many solutions struggle to support complex omnichannel strategies, dynamic data, and integrations with other eCommerce or data platforms, meaning that the PIM just becomes another data silo.