The promise of what AI can do for organizations has been at a fever pitch over the past few years. Yet, as the predictive potential of AI-powered models grows exponentially with new machine learning algorithms, so does their complexity-making them challenging to interpret by the business. But for AI systems to become trusted advisors to human decision-makers they need to be able to explain the “why.”
With ‘trust’ being the core factor driving adoption of AI insights, Explainable AI (XAI) has the capabilities to overcome these business concerns, while providing reassurance that decisions are made in an appropriate and non-biased way
Take a deep dive into the world of explainable AI for business and learn,
Humans have been hardwired to pay attention to stories since the beginning of humanity. When presented with meaningful stories, audiences are compelled to pay attention. This applies to data storytelling and analysis as well. Lumin by Fosfor is a Decision Intelligence product that already has storytelling features. Diagnostics answer the “why,” while simulation, forecast, and shared workspaces create intriguing data stories.
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Technical debt refers to the cost of any shortcuts or sub-optimal solutions taken in the development process that can result in difficulties and increased costs in future maintenance and software upgrades. The term "technical debt" was coined by Ward Cunningham in 1992.
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As the amount of data generated by industries increases daily, the importance of reevaluating the data stack has never been greater. Studies predict that by 2025, the world will create approximately 463 exabytes of data each day. Given this vast amount of data and its value, a modern data infrastructure is needed to store, transform, and extract meaningful insights.
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