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This week, why skill levels necessary for Digital Transformation have increased.


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

Our team of experts has scoured the internet for the most exciting and informative articles so that you can stay up-to-date on Digital, Data, Blockchain, AI & Analytics, and Digital Transformation.

Understanding the Role of Data Scientists in Risk Modeling

Innovation in risk modelling requires understanding the role data scientists play in the process. As risk models become increasingly important to the modern insurance carrier

Risk models are an increasingly critical component of the modern insurance carrier. They are relied upon for all phases of insurance, from marketing and sales to pricing, claims, and operations.

After more than two decades of working with insurance carriers on their risk models, it has become apparent to me that there are some common mistakes insurers make in the management of their analytics programs. It is clear that to get the most value out of their risk models, carriers need to more actively manage their data scientists and do so in a manner that suits the core capabilities of these professionals.


Google engineer put on leave after saying AI chatbot has become sentient

Blake Lemoine says system has perception of, and ability to express thoughts and feelings equivalent to a human child

The suspension of a Google engineer who claimed a computer chatbot he was working on had become sentient and was thinking and reasoning like a human being has put new scrutiny on the capacity of, and secrecy surrounding, the world of artificial intelligence (AI).

The technology giant placed Blake Lemoine on leave last week after he published transcripts of conversations between himself, a Google “collaborator”, and the company’s LaMDA (language model for dialogue applications) chatbot development system.

Lemoine, an engineer for Google’s responsible AI organization, described the system he has been working on since last fall as sentient, with a perception of, and ability to express thoughts and feelings that was equivalent to a human child.

What Is Data Leakage, and How Can It Be Avoided in Machine Learning?

While the metrics that are used in machine learning can show impressive results on the test set, they can sometimes be misleading unless understood thoroughly.

After performing all the tasks and the workflow of machine learning, such as the data collection, data visualization, data processing, data manipulation and training, you are yet to perform one of the interesting tasks which is to analyze your models and evaluate their performance.

In order to do this, you divide the overall data into 2 parts where the first part, which often includes the majority of samples, is used to train the machine learning models while the remaining samples are used to test how well they are performing on the test data or the data that the models have not seen before.

After performing the training and waiting for the ML models to generate good results on various metrics such as accuracy, precision, recall, and F1 score in the case of classification and mean squared error, mean absolute error and root mean squared error along with R-squared errors in the case of regression, you decide to deploy the machine learning model that performs the best in the test set.

    Synthetic Data Is About To Transform Artificial Intelligence

    These people do not exist. These faces were artificially generated using a form of deep learning known as generative adversarial networks (GANs). Synthetic data like this is becoming increasingly indistinguishable from real-world data.

    Imagine if it were possible to produce infinite amounts of the world’s most valuable resource, cheaply and quickly. What dramatic economic transformations and opportunities would result?

    This is a reality today. It is called synthetic data.

    Synthetic data is not a new idea, but it is now approaching a critical inflection point in terms of real-world impact. It is poised to upend the entire value chain and technology stack for artificial intelligence, with immense economic implications.


    Bill Gates says crypto and NFTs are ‘100% based on greater fool theory’

    The tech billionaire said he’s “not involved” in crypto, “I’m not long or short any of those things.”

    Bill Gates is not a fan of cryptocurrencies or non-fungible tokens.

    Speaking at a TechCrunch talk on climate change Tuesday, the billionaire Microsoft co-founder described the phenomenon as something that’s “100% based on greater fool theory,” referring to the idea that overvalued assets will go up in price when there are enough investors willing to pay more for them.

    Gates joked that “expensive digital images of monkeys” would “improve the world immensely,” referring to the much-hyped Bored Ape Yacht Club NFT collection.



    Featured Article


    Why Skill Levels Necessary For Digital Transformation Has Increased.

    Siemens leverages its learning and development platform to deliver the right training to the right employee at the right time.

    The Digital Eye is your weekly tech roundup. This week's feature - Why Skill Levels Necessary For Digital Transformation Has Increased.

    Article by @MIT

    The skills and capabilities needed to undergo digital transformation are in high demand as every company jockeys to gain a competitive advantage. To address the skills gap, some companies are prioritizing upskilling and reskilling. But to be effective, learning and development itself must undergo a transformation.


    According to Daniela Proust, global vice president and head of global people enablement and growth at Siemens, learning and development is at the core of digital transformation. “In light of a major transformation that businesses are facing, either by new business models arising or new innovation and technologies driving a certain business area forward, you see that you need to accompany that structural change, that structural workforce transformation in order to drive business transformation,” she says.



    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.