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Read about the latest use cases and real-world applications of Causal AI

Causal AI: from predicting to shaping the future

Causal AI allows organizations to easily run virtual experiments, facilitating risk-free learning and optimal decisions.

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Towards Artificial Imagination

This paper introduces how, via artificial imagination, Causal AI supercharges business' insight-generation and diagnostic capabilities

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Why machine learning “succeeds” in development but fails in deployment

At a glance… The pandemic has exposed weaknesses in conventional machine learning (ML) algorithms, which have been unable to adapt […]

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Incoming EU AI regulations on Enterprise AI: why you need to prioritize the adoption of Causal AI

Incoming EU regulations on Enterprise AI call for more explainable AI. Here's why it's time to prioritise the adoption of Causal AI.

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5 Steps to Prepare for AI Regulations

AI regulations are arriving, and rapidly. Abstract frameworks and guidelines are crystallizing into binding regulations with big penalties for noncompliance.

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Truly Explainable AI: Putting the “Cause” in “Because”

Truly explainable AI (XAI), can be achieved through Causal AI. Causal AI models are both highly accurate and inherently explainable

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AI that SME lenders can bank on

SME lenders must be able to evaluate loan default risk rapidly and accurately, amid volatility and crises. CausalAI delivers 5x better performance than conventional machine learning systems during crises, and 13% more PnL under normal conditions.

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Empower Experts with Causal AI

Causal AI empowers experts by utilising causal inference to make decisions based on cause and effect. Harness causality in your enterprise AI.

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Why Correlation-Based Machine Learning Leads to Bad Predictions

Machine learning models often fail in production due to spurious correlations. Causal AI can fix this problem.

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