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 […]
The era of ChatGPT is upon us. It is the end times… Well, many would have you believe so. Let’s talk about what’s reality and what’s hype.
GPT-4, the model used in ChatGPT, and other such models (including Bard, LlaMa, etc.) are a type of AI called Large Language Models (LLMs). They are so good […]
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 […]
Ethics is not a new phenomenon to the human race. Philsophers have struggled for centuries to try and form a framework where “good” and “bad” are defined ideas, fixed and abstracted from the personal opinions of the reader and the mores of the society. […]
As automation ramps up and aggregators grow, consumers are looking for quick insurance covers. Automated risk selection is required, but traditional computer programming is not up to the task.
For years the insurance industry has tried to describe what a good risk looks like. We make our best attempt at it and […]
The assessment of risks by insurers is not new. For […]
Automotive News Europe has a good piece on the general application of AI in the General Insurance value chain. One word of warning from MLPrograms though, there are serious questions over the accuracy of damage […]
Machine learning has been around for a while and is widely used from YouTube hobbyists to the Silicon Valley tech giants. However, the adoption of applied AI in the insurance community is still very much in its infancy. In this article, MLP’s head of product James Parry looks at how the industry can make use of machine learning tools and, more importantly, how to pick the right tools for the job.
Machine Learning Programs’ CEO, Tom Murphy, discusses the benefits of machine learning and how it is revolutionising the insurance industry with actionable insights to help its customers work smarter.
