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Why Data Quality Matters in the Age of Generative AI

Dataiku

Generative AI is rapidly transforming the data science landscape. Its ability to create synthetic data promises exciting possibilities for data augmentation and improved model performance.

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Don’t Let Poor Data Quality Derail Your AI Dreams

Perficient

AI is reliant upon data to acquire knowledge and drive decision-making processes. Therefore, the data quality utilized for training AI models is vital in influencing their accuracy and dependability. Data Preprocessing AI collects the relevant data from various sources.

Data 52
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Don’t Let Poor Data Quality Derail Your AI Dreams

Perficient

AI is reliant upon data to acquire knowledge and drive decision-making processes. Therefore, the data quality utilized for training AI models is vital in influencing their accuracy and dependability. Data Preprocessing AI collects the relevant data from various sources.

Data 52
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Data Quality in the Age of AI: A User Story

Dataiku

Today, more than 90% of AI practitioners experience significant cascading data errors , and poor data quality is estimated to cost companies 20% of revenue. The bottom line: bad data is ubiquitous and costly, and it also reduces organizations’ overall AI productivity.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Accelerating Industry 4.0 at warp speed: The role of GenAI at the factory edge

CIO

While warp speed is a fictional concept, it’s an apt way to describe what generative AI (GenAI) and large language models (LLMs) are doing to exponentially accelerate Industry 4.0. I am fascinated and passionate about helping manufacturers leverage Gen AI-fueled edge deployments that break through legacy Industry 4.0

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Avoid generative AI malaise to innovate and build business value

CIO

Despite the promise generative AI holds for boosting corporate productivity, closing the gap between its potential and business value remains one of CIOs’ chief challenges. Sixty-six percent of C-level executives are ambivalent or dissatisfied with the progress of their AI or GenAI efforts, according to Boston Consulting Group 1.