The aftershock of the event could be felt all across the world because, as it turns out, 12% of the globe’s trading goes through the canal. On average, the blockage caused 400 million dollars in losses per hour. It was a rude awakening call for the world as we realized just how fragile our supply chains truly are.
When Machine Learning Fails
It was also a rude awakening for AI country wise email marketing list enthusiasts. The shipping industry has been adopting machine learning and automation to predict shipping routes, port schedules, and overall optimization. Unfortunately, it wasn’t enough to avoid the disaster.
Don’t get me wrong, machine learning is extremely powerful, but it has its flaws. A model is only as good as the data used to train it, so the more a situation deviates from the norm the less the model can accurately predict it.
The Suez blockage and the COVID-19 seo and content marketing work together in perfect symbiosis pandemic are the kinds of events that are anathema to machine learning and data scientists. However, if the situation becomes the new norm, then the models won’t be useful anymore, so it’s back to gathering data and training new models.
The lesson here is that machine learning can’t stand on its own as the sole solution to supply chains and worldwide distribution. We have to broaden our scopes and seek other strategies that will prepare us for the next disaster.
Digital Twins
Back when the COVID-19 pandemic spam data was still in its early stages, researchers were desperately searching for ways to predict infection patterns, and many turned to one of the least likely sources of inspiration: video games.In fact, Forbes touted it as one of the most transformative trends in the modern market. But what is a Digital Twin? Imagine a virtual replica of an object or a process that reacts and adapts to new situations in the same way the real thing would.
