Data is a critical component of artificial intelligence (AI). Many experts would probably even argue that data is in fact the most critical component of our most advanced form of technology to date. A fair analogy could even look something like, gravity is to Earth as data is to AI. Does that mean any kind of data works when it comes to AI software? Depends on who you ask. Much of the industry would likely argue that in order for artificial intelligence products and solutions to actually work, the data being gathered to train that AI must be good and/or clean data. Beyond Limits likes to take that notion and turn it on its head a bit.
“Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.” (SAS Institute Inc.)
“There are a lot of different methods for dealing with missing data that range from very simplistic statistical and interpolation approaches to advanced machine learning neural network techniques. With machine learning, you can utilize neural networks or autoencoders to essentially learn behavior from a group and infill those missing data sets as much as possible. You can also make use of the other analog data to which you do have access in order to try and predict what might make up the missing parts.” (Beyond Limits Manager AI Solutions, Michael Krause)
“We’ve moved beyond deep learning techniques to embed human knowledge and experiences into the AI algorithms, allowing for more complex decision-making to solve never-seen-before problems — those problems without historical data or references. Machine learning techniques equipped with encoded human knowledge allow for AI that lets users edit their knowledge base even after it’s been deployed. As it learns by interacting with more problems, data, and domain experts, the systems will become significantly more flexible and intelligent.” (Beyond Limits CEO, AJ Abdallat, CMSWire)