Spatial econometric research typically relies on the assumption that the spatial dependence structure is known in advance and is represented by a deterministic spatial weights matrix. Contrary to classical approaches, we investigate the estimation of sparse spatial dependence structures for regular lattice data. In particular, an adaptive least absolute shrinkage and selection operator (lasso) is used to select and estimate the individual connections of the spatial weights matrix. To recover the spatial dependence structure, we propose cross-sectional resampling, assuming that the random process is exchangeable. The estimation procedure is based on a two-step approach to circumvent simultaneity issues that typically arise from endogenous spatial autoregressive dependencies. The two-step adaptive lasso approach with cross-sectional resampling is verified using Monte Carlo simulations. Eventually, we apply the procedure to model nitrogen dioxide ($\mathrm{NO_2}$) concentrations and show that estimating the spatial dependence structure contrary to using prespecified weights matrices improves the prediction accuracy considerably.

Apple has another tool to help make Siri smarter thanks to its recent purchase of Lattice Data. The company specializes in artificial intelligence and dark data, which ultimately could turn out to be as cool as it sounds. Apple's Lattice Data purchase means Siri is getting smarter Sources speaking with TechCrunch spilled the beans on the deal, which reportedly cost Apple around US$200 million. Apple offered up its usual noncommittal confirmation saying, "Apple buys smaller technology companies from time to time and we generally do not discuss our purpose or plans." The technology Lattice Data created aids with artificial intelligence by finding the structure in dark data, or data that otherwise doesn't seem connected.

Apple (AAPL) is looking to stay ahead of the artificial intelligence development curve with the purchase of Lattice Data, a company that uses AI technology to turn so-called "dark" data into more usable data sets The deal closed a couple of weeks ago at $200 million, according to a report from TechCrunch. On Sunday, Apple issued a generic statement on the deal that said it "buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans." Founded in 2015, Lattice Data claims that its work is "human-caliber quality at machine-caliber scale." As part of the deal, about 20 engineers from Lattice Data are now working at Apple. This is a common practice in the tech sphere.

Apple has recently acquired Lattice Data for around $200 million. The firm basically transforms the unstructured "dark data" like text and images and turns it into structured data. The latter can then be handled with conventional data analysis tools. The news comes from TechCrunch and essentially, the Cupertino giant has confirmed the acquisition by issuing a statement on the subject. So lets dive in to see some more details on the subject and how might Apple use the firm for its own set of purposes.

Apple bought Lattice Data, a company that uses an artificial intelligence (AI) based interface engine for transforming unstructured "dark" data into structured and more usable information. TechCrunch reported Saturday, citing sources, that the tech giant reportedly paid $200 million for the acquisition. On being asked about the deal, Apple neither confirmed nor denied it. "Apple buys smaller technology companies from time to time and we generally do not discuss our purpose or plans," an Apple spokesperson told the publication. There is a massive amount of data produced globally every year – 4.4 Zetabytes in 2013 by a conservative estimate.