Machine learning is an exciting field that has been gaining popularity recently due to some recent advancements that enhance our ability to compute solutions to problems that previously were not in reach.
Advances in computer hardware enable algorithms to run faster. This is not in the algorithmic abstract sense: an algorithm that takes O(n) runtime will still take O(n), regardless of hardware implementation. This is, rather, in the physical time. If an O(n) algorithm runs in 60 seconds on a computer, then Apple develops a computer that is twice as fast as the previous one, we get the algorithm running in 30 seconds. Computers in our pockets can do much more than desktops could 10 years ago, so this opens up the possibility of new methods of data collection and data analysis.
Theoretical advances are also cruical in the advancement of machine learning. Neural Networks are the hot new buzzword now, and everybody is scrambling to get their hands on experts that know how to implement these for their data. Although the concept was invented many years ago, it has seen a recent boom in popularity due to advances in the runtime of the training algorithm, as well as previously mentioned advances in hardware such as GPU accelleration that enable parallel training or the like.
The Bay Area
The San Francisco bay area is home to silicon valley, one of the technology advancement hubs in the world. Companies like Apple, Google, and Facebook are employing machine learning techniques to build artificial intelligence software, and to accelerate data analytics within their companies. The location of the bay area is often overlooked as a central driver of change, but its California location is without a doubt a factor. The lovely weather allows us to make better machine learning advances.
Machine learning is the literacy of the future. The bay area is where it will happen.