2709, 2023

MLP announces changes to executive leadership team

Categories: Uncategorized|

19 September 2023 – MLP (Machine Learning Programs), part of the Open GI Group since 2019, has today confirmed changes to the executive leadership team in a move to position the company for the next stage in their growth trajectory. Chief Executive Officer, Damian Baxter, will continue to lead the company, which offers Machine Learning and Artificial Intelligence services [...]

809, 2023

Why is explainability important in AI?

Categories: Blog|

In the ever-evolving landscape of artificial intelligence, there's a term you're likely to encounter more frequently - 'explainability.' If you haven't crossed paths with it yet, don't worry; you're about to embark on a journey to unravel its significance. Today, we embark on a quest to unravel the essence of AI explainability – what it encompasses, and why [...]

1907, 2023

MLP Launches Groundbreaking Propensity to Claim Enrichment Service

Categories: News, Press Release|

MLP (Machine Learning Programs), part of the Open GI Group, has launched MLP Score, a cutting-edge enrichment service which predicts the likelihood that a driver is to make a claim on their motor insurance policy within 12 months. MLP Score is the evolution of MLP’s Propensity to Claim model. Available at point of quote, it uses artificial intelligence (AI) [...]

103, 2023

Bias in Machine Learning – Part 2

Categories: Blog|Tags: , , , , , |

Following on from part one of my last blog – ‘what is bias and how do we avoid it?’ – there is also societal bias, and this can be a doozy! Recently there has been a big movement in art being created by AI from text. Some of it is exceptionally good and the power of these systems is [...]

2102, 2023

Bias in Machine Learning – Part 1

Categories: Blog|Tags: , , |

What is Bias and how do we avoid it? Part 1 Bias, in simple data science terms, can be thought of as a tendance for a model to stray from the “ground truth”. That’s a broad definition and some biases are simply irritations, but others are potentially highly illegal. All data scientists [...]