Random Forests is a Machine Learning algorithm that tackles one of the biggest problems with Decision Trees: variance. Even though Decision Trees is simple and flexible, it is greedy algorithm. It focuses on optimizing for the node split at hand, rather than taking into account how that split impacts the entire tree. A greedy approach makes Decision Trees run faster, but makes it prone overfitting. An overfit tree is highly optimized to predicting the values in the training dataset, resulting in a learning model with high-variance.

Gradient Boosting algorithms tackle one of the biggest problems in Machine Learning: bias. Decision Trees is a simple and flexible algorithm. An underfit Decision Tree has low depth, meaning it splits the dataset only a few of times in an attempt to separate the data. Because it doesn't separate the dataset into more and more distinct observations, it can't capture the true patterns in it. When it comes to tree-based algorithms Random Forests was revolutionary, because it used Bagging to reduce the overall variance of the model with an ensemble of random trees.

For nearly a year now, the coronavirus pandemic rendered most summer vacations and holiday getaways impossible, rerouting itineraries to our living rooms. But there is a silver lining for those seeking a change of scenery amid our extended staycations. Already these past 12 months we've seen a rise in those spending their idle hours in video games, and certain titles can actually help scratch that itch to travel. Some games fit that need to hit the skies literally, such as "Microsoft Flight Simulator 2020," which lets players fly a plane across a hyper-realistic Earth crafted from satellite imagery. Still, this doesn't replicate exploring a foreign country's culture or taking in the sights and sounds of a bustling city far from home.

Apple's personal assistant Siri is more of a glorified voice recognition feature of your iPhone than a deep conversation partner. A personal assistant that could truly understand human conversations and written texts might actually represent an artificial intelligence capable of matching or exceeding human intelligence. The Canadian startup Maluuba hopes to help the tech industry achieve such a breakthrough by training AI to become better at understanding languages. The key, according Maluuba's leaders, is building a better way to train AIs. Like humans, AI can only get better at understanding languages by practicing.