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When we observe App notifications, there is a correlation between the number of notifications sent by the App and the probability that the user opens it.
If the number of notifications is high, there is a greater chance of the user opening the app, while at the same time, a greater risk of annoying the user. This analogy plays the same in the area of the feedback that we receive for our actions.
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The Gradient Descent, which is a machine learning technique used in a neural network, provides us with this insight:
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The way to overcome the problem of "Feedback Frequency" is to change your 'Step Size', which is inversely proportional to the feedback received. This is done by:
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“It ain’t what you know that gets you into trouble. It’s what you know for sure that just ain’t so.”
The most useful learning isn’t usually a strict addition of new knowledge, but first unlearning something false or unhelpful.
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... was modelled by Leonardo DiCaprio in the 2013
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...are common thinking errors that harm our rational decision-making.
We don't always see things as they are. We don't simply glean information through the senses and act on it; inste...
Is our tendency to overestimate the odds of our own success compared to other people's.
Overly optimistic predictions can be dangerous, leading us to waste time and resources pursuing unrealistic goals. In the real world of business, things don't always work out for the best, and it serves us well to know when conditions are not on our side.