Mind Foundry

How Do Machines Learn? title image

5 min read

How Do Machines Learn? Meta-learning as an Approach

In the previous two blogs in the series, we addressed what makes machine learning models trustworthy and how machine learning models fail. This blog is focused on how machines learn and one particular approach called meta-learning, which enables...

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3 min read

5 Ways to Manage AI Responsibly in Insurance

The integration of Artificial Intelligence (AI) and machine learning has already brought transformative opportunities across the rapidly evolving landscape of the insurance industry. As data generation has surged and competition intensified,...

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5 min read

Explaining the Origins of AI

AI is everywhere. It has rapidly become an integral part of how we organise our lives, go about our jobs, and get from place to place. And yet, in our discussions with customers, we often encounter a wide range of misconceptions about what AI...

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Academia to Industry Blog Title

9 min read

Academia to Industry: Going from Theory to Practice

Taking the leap from the world of academia to pursue a career within industry can be a daunting proposition. After years spent studying and gaining skills in a very focused area, going out into the world and applying that knowledge to a broad range...

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Insurance Data Blog Title Image

6 min read

Insurance Data: The Challenge of Successful AI Adoption

It’s hardly a secret that data is the lifeblood of the insurance sector. Some experts predict there will be over 30 billion connected devices worldwide by 2025, and the resulting explosion of data, coupled with huge leaps forward in the capabilities...

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How Machine Learning Models Fail Title Image

4 min read

How Machine Learning Models Fail

In our first blog in this four-part series, we discussed how Machine Learning (ML) models might be considered ‘trustworthy’, and we emphasised challenges in bias and fairness, the need for explainability & interpretability, and types of data drift....

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6 min read

Insurance and Generative AI: Seeing Past the Headlines

Generative AI (GAI) has been firmly at the centre of discussion ever since it was popularised by the launch of ChatGPT in November 2022. Although the insurance sector, with its focus on cost, has generally reacted with interest and excitement to the...

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What makes a Machine Learning model ‘trustworthy’?

7 min read

What Makes a Machine Learning Model 'Trustworthy’?

Last year, Mind Foundry worked closely with Professor Brent Mittelstadt (of the Oxford Internet Institute) to get a deeper understanding of the law, policy, and standards in development surrounding machine learning. The output of this work was an...

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International Day of Women and Girls in Science

5 min read

International Day of Women and Girls in Science

The International Day of Women and Girls in Science, supported by the UN, is a fantastic opportunity to acknowledge the inspirational contributions of women across the globe in science and technology who continue to break down stereotypes and...

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6 min read

How Mind Foundry’s Goals Framework Led to Outstanding Achievements

Change is hard. We're creatures of habit by nature, and despite our best efforts, we often struggle to avoid repeating entrenched behaviours that take up much of our time and energy. It’s altogether too easy to find yourself coasting along the same...

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Explainable AI

3 min read

Making AI Explainable in the UK Public Sector

Mind Foundry hosted 'Defining Ambitions: The Future of AI in Public Sector', an invaluable virtual learning exchange for the public sector. Delivered in partnership with GovNewsDirect, the session's objective was to explore the possibilities for AI...

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2 min read

Mind Foundry Named in ‘Ethical AI Startup Landscape’ by EAIGG

Mind Foundry are thrilled to have been included in the ‘Ethical AI startup landscape’ research, mapped by researchers at the EAIGG (Ethical AI Governance Group), who have vetted nearly 150 companies working in Ethical AI across the globe. This...

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News, announcements, and blogs about AI in high-stakes applications.