Apple turns to the “dark side” of data

By Tian DuBelko

Apple is turning to the dark side of data with its latest AI startup acquisition.

According to Fortune, the tech giant recently spent around $200 million to acquire Lattice Data Inc, a company specializing in artificial intelligence. Specifically, the company uses machine learning to process “dark data” and turn it into more structured information.

When asked about the acquisition, Apple released a boilerplate statement,” Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans.”

Dark Data?

“Dark Data” refers to the amount of raw, unstructured data and information online th]at is difficult to analyze. Approximately 70 to 80 percent of all the data in existence today is unstructured. This unstructured data, or “dark data,” is mostly unusable when it comes to processing and analytics.

Lattice uses machines learning to arrange that useless information in a structured format so it’s more usable. Specifically, “Lattice turns dark data into structured data with human-caliber quality at machine-caliber scale,” according to Lattice.io.

Here’s a way to visualize dark data.  Think of jumbled number sets and information without labels or categorization. With the technology behind Lattice, this unstructured information could be organized and contextualized through AI and machine learning.

Smart Roots

In 2015, Lattice was co-founded by Chris Re and Michael Cafarella, computer science professors at Stanford and the University of Michigan, respectively. The company was originally a Stanford research project called DeepDive, a framework for statistical inference that used AI and machine learning to organize dark data.

However, the firm distances itself from typical machine learning, stating on its website “Unlike traditional machine learning, we do not require laborious manual annotations. Rather, we take advantage of domain knowledge and existing structured data to bootstrap learning via distant supervision.

Potential Applications

There are lots of potential future application of this type of AI and machine learning system. For one, this technology can be used in large-scale crime solving, such as in human trafficking. Another application includes medical as well as paleontological research. The system’s focus on big data can also be helpful in training more data-organizing AI systems.

Lattice could also be of value in analyzing map data and self-driving vehicles. It remains to be seen what Apple’s end game will be in acquiring this dark data specialist. However, one thing is clear: Apple certainly has a vested interest in furthering its AI and machine learning efforts.

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