Analytical Software
This week we are looking at the four core building blocks of the Connected Intelligence Revolution.
Yesterday we talked about the rapidly expanding networked computing infrastructure to move and process data, and on Monday we talked about the massive amounts of data available from the Internet of Internets, but what can you do with that data in the cloud?
Well for starters, you can see it. Rapid advances are being made in the area of data visualization to make it easier to spot trends and patterns that matter to our business, as well as to spot potential correlations between different metrics to further test and analyze.
We also can analyze the data. Data mining tools and technologies continue to advance to handle larger amounts and varieties of data in discovering previously unseen patterns and relationships. The advances that are happening with artificial intelligence, especially machine learning and deep learning, can take that a step further to use self-learning algorithms to continuously improve the ability to reveal insights and to take action, even applying human-like reasoning to handle unexpected situations. These advances are at the heart of the Connected Intelligence revolution.
Image classification is a good measure of advances in machine learning. The ImageNet Large Scale Visual Recognition Challenge has been an annual competition where competing algorithms are applied against over a million images trying to place each one in the correct image category. There are over 1000 categories so, for example, instead of a “dog” category, there are categories for each of 90 dog breeds and the software must not only identify an image as being of a dog, but of the correct breed. In 2011, a good classification error rate was 25%. In 2017, 29 of the 38 competing teams achieved greater than 95% accuracy, requiring the challenge to be redesigned to be more difficult — involving 3D objects rather than just 2D images.
Unfortunately, as mentioned before, the loss of privacy is one aspect of the Connected Intelligence revolution that makes many people uncomfortable. On a personal level, the more information that is available about me, and the easier it is for that information to be discovered or shared, the greater the risk that I will be exposed to financial, emotional, or even physical danger. If these concerns aren’t addressed, then public backlash will appropriately constrain any benefits that could be realized in the Connected Intelligence revolution, so technologies to protect privacy are also critical enablers for the revolution.
Blockchain is a technology most closely associated with cryptocurrencies such as Bitcoin, but as an underlying technology, it can be used for many more use cases that involve secure and verified transactions. One of the use cases that Don Tapscott, co-author of The Blockchain Revolution describes is using the technology to take back control of your data and your identity and he names specific organizations working today to make it a reality. Advances in cryptography/encryption, authentication, and data security are also key to the Connected Intelligence revolution.
Tomorrow we will look at how this software moves into the real world!
