There’s no shortage of AI article suggestions in my inbox these days. No doubt the number of distributions I sign up for factors into how these agencies sell my email address to others. Long live burner accounts! As a technology firm specializing in construction and engineering project history data, I found this article particularly insightful.
Two areas of specific interest are the Hype Cycle for Artificial Intelligence chart and Trend #4: Data for AI. The chart appears often when contextualizing new technology trends—specifically, the promise of BIM and now AI, big data, and the like. However, “small data” and “wide data” referenced in Trend #4 is especially relevant for our clients and how they use Eos Cortex Project History as a corporate asset.
AI-focused media and technology offerings address organizations with A LOT of data. Data lakes, deep neural networks, and high computing power support goals to maximize customer and consumer trends, improve marketing exposure, and of course benefit communities with the discovery of new drugs, traffic circulation improvements, and so forth. The analytics feast on billions of data points. It doesn’t make sense otherwise.
What if your organization has limited data? Perhaps only hundreds, thousands, or even tens of thousands of data points? At Eos, this is the problem we try to solve: making the best use of limited data. In the article, Laurence Goasduff points out that leaders are now turning to small data and wide data. If your organization’s lack of big data has been a reason to avoid a project history initiative, it might be a good time to reconsider.