Dr Darko Matovski, CEO and co-founder of causaLens, discusses why Causal AI is the only path to true AI and how it is helping businesses in finance and beyond.
The current state-of-the-art in machine learning can work for static environments and closed loop problems with fixed rules, but it often fails in other situations. The likelihood of failure is especially pronounced for highly dynamic, low signal-to-noise environments, which are so common for time-series data.
An understanding of the true causal drivers should enable causal AI to navigate and draw inferences and make forecasts for complex, dynamic and metamorphosing systems. Further, it should be capable of ‘imagining’ scenarios not encountered in the past so allowing it to simulate counterfactual worlds to learn from, instead of relying solely on ‘training’ data.