Any financial services firm using AI must revisit its approach to model risk management. The reason is that AI models are evolving faster than the rules-based models that were standard previously. If AI models perform inadequately, major operational losses can grow quickly. Watson OpenScale helps
To enable companies to get the most out of their machine learning, Cloud Pak for Data, IBM’s leading data and AI platform, partners with Datameer to build an end-to-end pipeline that collects, organizes, and analyzes data and helps infuse AI throughout the business.
Business intelligence (BI) tools are undergoing massive disruption. The powerful integration of artificial intelligence (AI) frameworks like natural language processing and automated predictive insights are transforming what BI can do for businesses.
Thankfully, making sense of this new world of AI
Let’s be honest: no one wakes up in the morning excited to go through a procurement process. This reaction can be particularly true where data management is concerned. When quick responses to market changes are necessary, it’s essential to be able to adjust your architecture rapidly without
How to build a modern data management platform ready for the AI future
Every data architect knows the value of keeping their data management platform up-to-date and ready for the next phase. Yet how to put this into practice is not always clear. With many businesses embarking on their journey to AI
With the amount of choices surrounding big data analytics, data lakes and AI, it can sometimes be difficult to tell fact from fiction. With more than 40% of organizations expecting AI to be a “game changer,” it’s important to have a complete picture of the capabilities and opportunities available.
The expectation to achieve faster results continues to rise. Businesses everywhere are looking for ways to improve their operational efficiency and effectiveness to enable the best decision-making. The need to optimize typically comes to a head with the reality that there are many silos within any