📈 #35 Minimum Google Cut

How Google has significantly reduced the complexity of a problem with a 70-year history.

The other day, I read on the Google Research blog that they had made significant advances in solving a typical optimization problem.

And then I realized that everything I have been thinking and have told you about on occasion (like in the previous post) is truly materializing.

Operations Research is gradually making its way into our lives to the point that it will be inevitable to have systems that, by default, have at least a little bit of this area of knowledge.

What would happen if the mobile phone network went down? Or if a very important Internet node stopped providing service? What if autonomous cars took a long time to understand the objects in an image?

It would be a disaster, honestly. So today on Feasible, I tell you:

• The importance of the minimum cut problem in real life.

• Why Google really nailed it with this.

• The 3 steps they follow to solve the problem.

Come on, one more Sunday… Let’s get to it!

✂️ The Importance of the Minimum Cut Problem in Real Life

The minimum cut problem is a classic problem in network design, graph theory, and combinatorial optimization.

The ultimate goal is to find the smallest subset of edges - or nodes - that, if removed from the graph, would disconnect it.

And you might ask what the point is of solving this problem. In general, it can be used to find critical points of failure or bottlenecks in a network of nodes, but let me tell you about more specific cases: