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.

Data Scientist 253

Data Scientist Metadata Responsible AI Explainability 253

IBM Journey to AI blog

FEBRUARY 8, 2023

Adherence to responsible artificial intelligence (AI) standards follows similar tenants. Gartner predicts that the market for artificial intelligence (AI) software will reach almost $134.8 billion by 2025. Documented, explainable model facts are necessary when defending analytic decisions.

Responsible AI 130

Responsible AI Explainability Explainable AI Automation 130

Unite.AI

SEPTEMBER 13, 2023

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

Explainability 278

Explainability Generative AI AI Tools AI 278

Dlabs.ai

JULY 19, 2023

The International Data Corporation predicts that the global datasphere will swell from 33 zettabytes in 2018 to a staggering 175 zettabytes by 2025. Possible solution: Explainable AI Fortunately, a promising solution exists in the form of Explainable AI.

Explainable AI 97

Explainable AI Explainability Auto-complete Algorithm 97