dan fiehn
dan fiehn

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This week, two Insurtechs work together to deliver groundbreaking AI solutions for insurers and brokers.


Welcome to The Digital Eye, your weekly roundup of the latest technology news. 

Our team of experts have scoured the internet for the most exciting and informative articles so that you can stay up-to-date on all things digital, data, blockchain, AI & analytics.

How IoT Uses Machine Learning To Change The World

Machine Learning Makes IoT Adaptable.

IoT and Machine Learning are the most advanced and evolving technologies that continue to rise in today’s modern world, simplifying human efforts and making lives easier. These technologies have proved to streamline operations and workflows for various industries and provide more robust and scalable applications that allow users to make things done seamlessly. 

In recent years, the popularity of the Internet of Things (IoT) and Machine Learning (ML) has greatly increased, especially in finding new ways to uncover business opportunities. The way people used to live before has revolutionized with the power of ML and IoT, making their lives simpler and easier. 

Taking reinforcement learning algorithms to real-world robotics

Background, needs, challenges, and outlook

Proving its success in gaming, commercial ML, and robotics, RL has morphed into the Swiss army knife of AI. This article is an exploration of what can RL currently do, why we need RL for robotics, what challenges and future work would look like.


Reinforcement Learning (RL) refers to a paradigm of algorithms where learning happens by trial and error. The RL agent learns in a reward-based system. The agent takes action and gets rewarded for success or punished for failure. Thus the agent successfully learns to perform a task by maximizing the reward. This is similar to how learning works for humans and animals (does Pavlo’s dog ring any bells?).

Does Information Weigh Something After All? What if It Does?

At the rate we create information today, one physicist computes that in 350 years, the energy will outweigh the atoms of Earth

In the 1960s, IBM researcher Rolf Landauer (1927–1999) observed that if the logical information in a computational system decreased, then the physical entropy in the system must increase (Landauer’s Principle). This conclusion follows from the principle that the entropy in a closed system can never decrease.

A decrease in the logical information corresponds to a decrease in entropy. And factoring in the principle that the entropy cannot actually decrease, the physical system itself must increase in entropy when the information decreases. This increase in entropy will result in the emission of heat, and a reduction of energy in the system.

    Our Next Enlightenment will be AI-Driven

    A realistic and symbiotic future between humans and AI

    The Enlightenment Ride to the Top

    The Age of Enlightenment took place during the 17th and 18th centuries and is seen as a global phenomenon where we collectively “turned on the light bulbs” in our heads. This movement was an intellectual and philosophical force that saw the rise of some of the most prominent thinkers ever like Kant, Voltaire, and Adam Smith.

    The Enlightenment was largely fueled by philosophers and mathematicians like Descartes and Newton. This is because the world before this point ascribed knowledge and power to higher powers — deities, stars, etc. These religious and spiritual beings were seen as primary authorities, consequently creating the society that humans live in.

    A deep-learning algorithm could detect earthquakes by filtering out city noise

    The model could uncover quakes that would previously have been dismissed as human-generated vibrations.

    Cities are loud places. Traffic, trains, and machinery generate a lot of noise. While it’s a mere inconvenience much of the time, it can become a deadly problem when it comes to detecting earthquakes. That’s because it’s difficult to discern an approaching earthquake amid all the usual vibrations in bustling cities.

    Researchers from Stanford have found a way to get a clearer signal. They’ve created an algorithm, described in a paper in Science Advances today, that they claim improves the detection capacity of earthquake monitoring networks in cities and other built-up areas. By filtering out background seismic noise, it can boost the overall signal quality and recover signals that may have previously been too weak to register. 


    Featured Article


    Two Insurtechs work together to deliver groundbreaking AI solutions for insurers and brokers

    Insurtech Deals: Percayso Inform Teams Up With Incited

    Does the best AI think like a Human?

    Article by @InsEdgeOnline

    Insurance data intelligence provider, Percayso Inform, today announces a new partner integration with Data Science Insurtech, Incited.

    Incited provides a range of solutions for insurers and brokers, delivering advanced analytics tools for real-time modelling and prediction, uncovering patterns in data, detecting fraud, improving customer retention and generating dynamic pricing solutions.

    Dan Fiehn, Chief Operating Officer at Incited, comments: “Our uniquely integrated data science, analytics and artificial intelligence proposition is helping insurance providers to unlock the value of their data, transforming it into insight and action that can make a measurable difference to their business performance. Partnering with like-minded businesses that can offer further routes into the insurance market is a key component of our strategy as we look to scale up our proposition, and we’re delighted to integrate our platform with Percayso.”




    How to Maximise Knowledge Transfer Between Business and Engineering Teams

    In this week’s feature article, discover how to maximise knowledge transfer between business experts and technical engineers to ensure the success of your digital transformation. Learn about creating structured knowledge transfer plans, fostering a learning environment, employing diverse transfer methods, and building trust and collaboration. These strategies will help you bridge knowledge gaps, boost innovation, and enhance operational efficiency. Dive into our expert insights to master the art of seamless collaboration and drive your organisation’s digital transformation forward.

    Strategic Planning Approaches: Top-Down vs. Bottom-Up

    Unravel the complexities of strategic planning with our latest exploration into Strategic Planning Approaches. Whether you’re leaning towards a top-down, bottom-up, or sideways strategy, our insight will guide you through the pros and cons of each method, helping you make informed decisions that align with your business objectives. Perfect for strategists and business leaders aiming to optimize their planning process and drive effective outcomes.

    Digital Sustainability Practices: A Guide to Greener Habits

    Explore the transformative power of digital sustainability practices. This guide unveils how adopting eco-friendly digital habits can significantly reduce your carbon footprint and pave the way for a greener future. Dive into practical tips and strategies for making a positive environmental impact through digital activities.