Unite.AI

NOVEMBER 1, 2024

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.

AI Development 162

AI Development AI Developer Data Quality Data Science 162

Unite.AI

DECEMBER 27, 2024

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?

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

IBM Journey to AI blog

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Data Ingestion 222

Data Ingestion Data Integration Data Quality LLM 222

Unite.AI

DECEMBER 20, 2024

Being selective improves the datas reliability and builds trust across the AI and research communities. AI developers need to take responsibility for the data they use. AI tools themselves can also be designed to identify suspicious data and reduce the risks of questionable research spreading further.

Generative AI 130

Generative AI AI Modeling AI AI 130

Unite.AI

JULY 19, 2024

It integrates smoothly with other products for a more comprehensive AI development environment. This helps developers to understand and fix the root cause. Key features of Cleanlab include: Cleanlab's AI algorithms can automatically identify label errors, outliers, and near-duplicates. Enhances data quality.

LLM 279

LLM AI AI Data Quality 279

Unite.AI

JUNE 12, 2024

While cinematic portrayals of AI often evoke fears of uncontrollable, malevolent machines, the reality in IT is more nuanced. Professionals are evaluating AI's impact on security , data integrity, and decision-making processes to determine if AI will be a friend or foe in achieving their organizational goals.

Data Quality 147

Data Quality Automation AI AI 147

Towards AI

FEBRUARY 11, 2025

Author(s): Richie Bachala Originally published on Towards AI. Beyond Scale: Data Quality for AI Infrastructure The trajectory of AI over the past decade has been driven largely by the scale of data available for training and the ability to process it with increasingly powerful compute & experimental models.

Data Quality 54

Data Quality Neural Network ETL Computer Vision 54