Unite.AI

JANUARY 1, 2025

But, while this abundance of data is driving innovation, the dominance of uniform datasetsoften referred to as data monoculturesposes significant risks to diversity and creativity in AI development. In AI, relying on uniform datasets creates rigid, biased, and often unreliable models.

AI 182

AI AI Algorithm Large Language Models 182

Unite.AI

DECEMBER 17, 2024

Humans can validate automated decisions by, for example, interpreting the reasoning behind a flagged transaction, making it explainable and defensible to regulators. Financial institutions are also under increasing pressure to use Explainable AI (XAI) tools to make AI-driven decisions understandable to regulators and auditors.

Automation 246

Automation AI Explainability AI 246

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

Towards AI

APRIL 2, 2024

However, the AI community has also been making a lot of progress in developing capable, smaller, and cheaper models. This can come from algorithmic improvements and more focus on pretraining data quality, such as the new open-source DBRX model from Databricks. Why should you care?

LLM 103

LLM OpenAI Explainable AI AI 103

AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

Responsible AI 111

Responsible AI Prompt Engineer Prompt Engineering AI 111

Marktechpost

DECEMBER 11, 2024

Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 models adhered to LG AI Research s Responsible AI Development Framework, prioritizing data governance, ethical considerations, and risk management.

AI Research 87

AI Research AI Researcher Generative AI AI 87

Pickl AI

DECEMBER 10, 2024

Businesses face fines and reputational damage when AI decisions are deemed unethical or discriminatory. Socially, biased AI systems amplify inequalities, while data breaches erode trust in technology and institutions. Broader Ethical Implications Ethical AI development transcends individual failures.

Explainability 52

Explainability AI AI Artificial Intelligence 52