article thumbnail

AI-powered underwater vehicle transforms offshore wind inspections

AI News

This deployment marks a crucial step in Beam’s roadmap for autonomous technology, with plans to extend this AI-driven solution across its fleet of DP2 vessels, ROVs, and autonomous underwater vehicles (AUVs) throughout 2025 and 2026.

Robotics 288
article thumbnail

Data observability: The missing piece in your data integration puzzle

IBM Journey to AI blog

Delivering projects on time and within budget often took precedence over long-term data health. Data engineers often missed subtle signs such as frequent, unexplained data spikes, gradual performance degradation or inconsistent data quality. Better data observability unveils the bigger picture.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

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. Effective data quality management is crucial to mitigating these risks.

Metadata 113
article thumbnail

AI Bias & Cultural Stereotypes: Effects, Limitations, & Mitigation

Unite.AI

How to Reduce Bias in AI Models Experts estimate that by 2026, 90% of the online content could be synthetically generated. Some of these are: Ensure Data Quality: Ingesting complete, accurate, and clean data into an AI model can help reduce bias and produce more accurate results.

AI 278
article thumbnail

Transforming AI Accuracy: How BM42 Elevates Retrieval-Augmented Generation (RAG)

Unite.AI

According to a report by Gartner , over 80% of businesses plan to implement some form of AI by 2026, highlighting the growing reliance on AI for accurate information retrieval. This combination allows AI to efficiently access and utilize vast amounts of data, providing users with accurate and contextually relevant responses.

Algorithm 255
article thumbnail

Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. This process involves extracting data from multiple sources, transforming it into a consistent format, and loading it into the data warehouse. ETL is vital for ensuring data quality and integrity. from 2021 to 2026.

article thumbnail

World’s First Major Artificial Intelligence AI Law Enters into Force in EU: Here’s What It Means for Tech Giants

Marktechpost

They must meet strict standards for accuracy, security, and data quality, with ongoing human oversight. This interim measure aims to ease the transition before most of the Act’s provisions take effect on August 2, 2026. Content like deep fakes should be labeled to show it’s artificially made.