Defined.ai blog
AUGUST 10, 2023
Explainable AI (XAI) As AI models become more complex, understanding how they arrive at decisions becomes crucial, especially in a heavily regulated sector like finance. Explainable AI aims to make AI decision-making processes transparent and understandable. Implementing robust data security measures.
IBM Journey to AI blog
OCTOBER 16, 2023
Foundation models are widely used for ML tasks like classification and entity extraction, as well as generative AI tasks such as translation, summarization and creating realistic content. The development and use of these models explain the enormous amount of recent AI breakthroughs. ” Are foundation models trustworthy? .
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Marktechpost
MAY 12, 2024
SEON SEON is an artificial intelligence fraud protection platform that uses real-time digital, social, phone, email, IP, and device data to improve risk judgments. It is based on adjustable and explainable AI technology. They automate insights using business intelligence (BI), analytics, and low-code and pro-code applications.
ODSC - Open Data Science
JUNE 1, 2023
Take a deep dive into the theory underpinning and applications of Generative AI at our first-ever Generative AI Summit on July 20th. Augmented Analytics — Where Do You Fit in at the Intersection of Analytics and Business Intelligence? Register for free!
Mlearning.ai
SEPTEMBER 5, 2023
Modern organizations rely heavily on business intelligence (BI) tools to consolidate and analyze data. Manual analysis simply cannot keep pace with the speed of business. The Need for AI-Powered Business Intelligence To gain a competitive edge, organizations need to move beyond consolidated data and manual analysis.
DataRobot Blog
JUNE 23, 2022
For human decision-makers, decision models can be used to ensure that the business intelligence or environment presents data and predictions in ways that mesh with the defined decision-makers. AI models, especially transparent and explainable AI models, are potentially transformative. Take Action.
IBM Journey to AI blog
OCTOBER 12, 2023
Explainable AI — Explainable AI is achieved when an organization can confidently and clearly state what data an AI model used to perform its tasks. Key to explainable AI is the ability to automatically compile information on a model to better explain its analytics decision-making.
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