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FinTech and Machine Learning

IdeaScale

When people talk about machine learning they are a referring to a type of artificial intelligence that has the ability to learn without explicit programming. These programs can grow and change on their own once they know how to learn and some financial companies are beginning to use machine learning for a variety of different reasons.

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Agility is the 2023 Success Factor

Leapfrogging

In a landmark study, for example, Google identified “psychological safety” as the top characteristic of its most successful teams. Evaluate progress: Based on what you achieved, what did you learn, and what’s the next logical set of short-term goals? Iteration drives learning and success. Learning by doing.

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4 Mindsets to Grow Through Innovation

Innovators Alliance

I hope you enjoy this excerpt from an article I wrote for BOSS Magazine that introduces the importance of measuring an organization’s mindset. For example, whether the organization has a competitive spirit that strives for profits, and/or an entrepreneurial spirit that strives for new ideas and growth.

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How to See Your Hidden Assumptions

Leapfrogging

This is a very simple example to illustrate how we all make assumptions. When it comes to developing your strategy or innovating, get clear on what you need to know and learn. Examples might include things like board games children like most , the healthiest yet best tasting desserts , or the most successful social media influencers.

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Why “Never Stop Learning” Is As True for Your Life As It Is for Your Business

The Human Factor

What you learned in a class just a couple of months ago might not be accurate or valid any longer. However, others involve having to go the extra mile to find out about what the competition or benchmark companies are doing. This education can come from magazines, articles, reviews, or even the news. Everything is learning!

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You can't burn data

Jeffrey Phillips

This comparison was strong enough to lead Wired magazine to define data as the new oil in a magazine article some years ago. Veracity or truthfulness or data quality is obviously key, especially when training a machine learning algorithm. After all, both are abundant commodities that can create value.

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DISRUPTIVE THINKING

Michael Michalko

One of the best examples I have heard of comes from a talk given by Luke Williams, which illustrates the potential of Disruptive Thinking. This example comes from the ultra-competitive drinks industry. Within the ‘real’ world, there are a number of really exciting examples of disruptive thinking in action.