Remove AI Development Remove Data Quality Remove Generative AI
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Step-by-step guide: Generative AI for your business

IBM Journey to AI blog

It provides practical insights accessible to all levels of technical expertise, while also outlining the roles of key stakeholders throughout the AI adoption process. Establish generative AI goals for your business Establishing clear objectives is crucial for the success of your gen AI initiative.

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Navigating the Misinformation Era: The Case for Data-Centric Generative AI

Unite.AI

In the digital era, misinformation has emerged as a formidable challenge, especially in the field of Artificial Intelligence (AI). As generative AI models become increasingly integral to content creation and decision-making, they often rely on open-source databases like Wikipedia for foundational knowledge.

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The High Cost of Dirty Data in AI Development

Unite.AI

It’s no secret that there is a modern-day gold rush going on in AI development. According to the 2024 Work Trend Index by Microsoft and Linkedin, over 40% of business leaders anticipate completely redesigning their business processes from the ground up using artificial intelligence (AI) within the next few years.

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Chuck Ros, SoftServe: Delivering transformative AI solutions responsibly

AI News

He also cautioned against rushing to deploy generative AI solutions without properly assessing feasibility and business viability, stating, “We need to pay at least as much attention to whether it should be built as we do to whether it can be built.”

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The importance of data ingestion and integration for enterprise AI

IBM Journey to AI blog

The emergence of generative AI prompted several prominent companies to restrict its use because of the mishandling of sensitive internal data. According to CNN, some companies imposed internal bans on generative AI tools while they seek to better understand the technology and many have also blocked the use of internal ChatGPT.

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The risks and limitations of AI in insurance

IBM Journey to AI blog

Artificial intelligence (AI) is polarizing. In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. It excites the futurist and engenders trepidation in the conservative.

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How Quality Data Fuels Superior Model Performance

Unite.AI

Its not a choice between better data or better models. The future of AI demands both, but it starts with the data. Why Data Quality Matters More Than Ever According to one survey, 48% of businesses use big data , but a much lower number manage to use it successfully. Why is this the case?