The AI data problem nobody talks about: Why more information isn't making better decisions
Commerce in the information age has thus far been one long quest to gather as much information as possible. Customer data, sales data, inventory data, system data, operational data, technical data, every facet of business can and has been tracked and quantified, guided by the idea that knowing more means decisions can be made faster and more conclusively.
Business Development Manager at PropertyShark.
While sound in theory, that process has clearly hit a snag, as more and more companies abandon their AI projects after finding that the exponential explosion of data creation isn’t generating comparable value.
Has AI peaked in its utility? Or is the issue one of interoperability? Why exactly has this monumental trend hit such a stumbling block?
Expecting scale to produce clarity
It’s entirely understandable to assume that feeding more information into an AI increases the accuracy and quality of the output. Models need to...
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