AI News

OCTOBER 17, 2024

Data integrity and security emerged as the biggest deterrents to implementing new AI solutions. Executives also reported encountering various AI performance issues, including: Data quality issues (e.g., Only 5% of executives reported that their organisation has implemented any AI governance framework.

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Big Data AI AI Data Quality 249

IBM Journey to AI blog

JULY 3, 2024

By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses. Data is exploding, both in volume and in variety.

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Metadata Data Quality AI AI 113

Unite.AI

MAY 23, 2024

When integrated successfully, AI technology can have massive ROI, leading to better sales, more satisfied customers, and streamlined operations that save thousands of dollars each year. With all of this in mind, it’s no surprise that investment in AI is projected to top $200 billion by 2025.

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IBM Journey to AI blog

OCTOBER 12, 2023

The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly. Here’s what’s involved in making that happen.

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IBM Journey to AI blog

MAY 15, 2024

However, businesses scaling AI face entry barriers. Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges.

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Marktechpost

AUGUST 10, 2024

High-Risk AI: These include critical applications like medical AI tools or recruitment software. They must meet strict standards for accuracy, security, and data quality, with ongoing human oversight. These entities will work together to ensure regulatory uniformity and solve new difficulties in AI governance.

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Artificial Intelligence Artificial Intelligence AI AI 131

ODSC - Open Data Science

OCTOBER 16, 2024

Increasingly powerful open-source LLMs are a trend that will continue to shape the AI landscape into 2025. A Focus on Explainability and Responsible AI: The session “ Causal Graphs: Applying PyWhy to Go Beyond Explainability ” underscores the growing importance of understanding the “why” behind LLM predictions.

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