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Apple Acquires 'Dark Data' Machine Learning Company Lattice Data

Apple recently paid around $200 million to acquire Lattice Data, a firm that aims to turn unstructured "dark data" such as text and images into structured data that can then be handled with traditional data analysis tools. News of the acquisition comes from TechCrunch, and Apple has essentially confirmed the acquisition by issuing its standard statement on the topic.

lattice data
Lattice uses machine learning techniques to take mass amounts of initially unusable data and turn it into properly labeled and categorized data that can be used for AI, medical research, and more.

It’s unclear who Lattice has been working with, or how Apple would intend to use the technology. Our guess is that there is an AI play here: Our source said that Lattice had been “talking to other tech companies about enhancing their AI assistants,” including Amazon’s Alexa and Samsung’s Bixby, and had recently spent time in South Korea.

TechCrunch says the deal closed "a couple of weeks ago," with roughly 20 Lattice engineers having joined Apple.

Top Rated Comments

116 months ago
The valley is running out of ridiculous synonyms to attract VC money. "Dark data?" Next will be "deep space dense data matter".
Score: 19 Votes (Like | Disagree)
Andres Cantu Avatar
116 months ago
Anything to improve Siri.
Score: 10 Votes (Like | Disagree)
nvmls Avatar
116 months ago
While at it, dark mode too..?
Score: 10 Votes (Like | Disagree)
busyscott Avatar
116 months ago
PhaseNeutral Anti-Matter Data


PAMD
Dynamic Unilateral Machine Planning

DUMP
Score: 8 Votes (Like | Disagree)
nuckinfutz Avatar
116 months ago
Dynamic Unilateral Machine Planning

DUMP
LOL. Just added that to my LinkedIn skills
Score: 7 Votes (Like | Disagree)
116 months ago
I feel like I just watched an advertisement for "snake oil"....

If the conveyance of something's usefulness cannot be explained in such a way that is easily understood, then 1) it is either BS, or 2) the only people who DO understand it, were not involved in the attempt to explain it.
Score: 7 Votes (Like | Disagree)

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