AI (artificial intelligence) systems are programmed with data provided by its creator. Some developers of these systems are constantly having to rewrite code for continuous improvement while other times, the code is not updated as frequently because they consider the system as having been completed and the end goal achieved. The problem here, is not the frequency of the updates but, the type of data that is being programmed into these systems.
AI systems are made so that they can think and function on their own, in an intelligent manner similar to human-decision thought processes. However, if data is not placed in the right context or even properly conditioned to allow for informed decisions, then the reason for the AI system becomes irrelevant. Data is just data but what you do with the data, transforms it into information. Information is needed for informed decision making and unstructured data can impact on the functionality and effectiveness of the AI system.
The first step of programming AI is how it would retrieve the data. The second step is the algorithms used to help it to process and interpret the data. Data volume as we know is exploding every day and relevant metadata needs to be parsed before the data can be termed intelligent. According to CEO Pavel Bains, blockchain technology is a universal data store that allows data management teams to provide the most accurate context for AI systems as it accommodates both structured and unstructured data. In other words, distributed, peer-to-peer storage nodes are used to transfer data quickly, efficiently and accurately, maintaining high levels of integrity and making sure that the critical data does not remain in control of just any particular cloud storage system.
Smart applications today consume large quantities of both data and metadata through its algorithms, but the focus should be on the data we feed it and whether it is “good” data management. Remember, AI systems cannot differentiate between bad and good, wrong and right or even fact and fiction. It can easily misinterpret the data that it consumes and produce false outcomes, skewered results, and bad information. The truth is, AI is not intelligent at all. This is the reason why good data management systems need to be put in place.
Good data management systems do not involve AI, it involves the human brain. Only through human intelligence can data be collected and prepared to ensure that the AI delivers the output, operations, and services, that it is required to execute. Data management systems should be able to collate and transfer data which must be streamlined with AI systems. Recently, NetApp and Nvidia teamed up to create a solution that would effectively provide the “edge to core to cloud” data control. The end goal is direct access to data no matter the format or where it is stored so that analytical engines remain as accurate as possible. AI must be trained on high-quality data because it is only as smart as the data it is being trained on.