by Capt. Iain J. Cruickshank
Palantir has a corking reputation for exercise on the battlefield, peculiarly for counter-IED functions, together with has attained an around legendary condition amid around analysts together with communities inward the Army. When compared to the Distributed Common Ground System – Army (DCGS-A), its success is non surprising; most users of DCGS-A would concur that it is problematic. In particular, Palantir has a much friendlier user interface than DCGS-A, together with its Gotham arrangement is fantabulous at linking reports or other pieces of intelligence together. But Palantir’s Gotham system, the model for a novel battlefield intelligence system, is susceptible to chop-chop becoming the adjacent DCGS-A. Without around of import changes, Palantir’s software volition non satisfy battlefield intelligence needs together with hold out doomed to repeat the failures of its predecessor. There are 2 critical areas that Palantir must address to railroad train a superior battlefield intelligence platform: inter-operability together with customization of analysis past times an end-user.
First, Palantir must hold out interoperable alongside dissimilar analysis suites. Real battlefield intelligence problems require a multifariousness of approaches, both qualitative together with quantitative, together with volition require dissimilar tools for appropriate analysis. When performing intelligence analysis—such equally an All-Source Analyst volition practice inward a battlefield environment—various tools demand to hold out integrated. Analysts exercise a plethora of tools such equally Analyst Notebook for creating link diagrams, ORA for network analysis, ArcGIS for creating maps, Anaconda for information science, together with Palantir Gotham for finding linked reports. Many of these tools stimulate got specialized algorithms together with analysis formats that cannot hold out replicated easily inward ane comprehensive format; ORA’s socio-cognitive maps cannot easily hold out replicated, together with few systems tin practice goodness link diagram visualizations similar Analyst Notebook. But ane analysis suite volition exactly non supply the functionality to perform all of the analyses needed for battlefield intelligence.
Palantir must hold out able to integrate information alongside dissimilar systems. This agency that it must both select together with export information into easily ingestible formats similar JSON together with csv, together with charge inward together with parse the native formats from dissimilar analysis suites. Influenza A virus subtype H5N1 shut arrangement that is non easily interoperable alongside other systems volition non supply the functionality needed past times battlefield analysts to assault existent intelligence problems. For Palantir to hold out to a greater extent than successful than DCGS-A, it must stimulate got a high grade of interoperability alongside many analysis suites.
Secondly, together with maybe to a greater extent than importantly, if Palantir is to succeed where DCGS-A did not, it must allow for analysts to write their ain code alongside its data. Humanity, together with alongside it, warfare, is becoming increasingly digitized. As a result, information is exploding together with the days where ane analyst or grouping of analysts could read through all of the information on a detail expanse of involvement together with acquire an proficient inward a reasonable total of fourth dimension are waning. As intelligence analysis increasingly incorporates car learning, Big Data, together with interactive visualizations, intelligence volition demand systems that tin contain these advances inward technology scientific discipline together with methodology (see here, here, or here for exactly a few examples).
Many of the best tools for car learning together with advanced visualization are opened upward origin together with written inward coding languages similar Python, R, together with Julia. So, an analyst equipped alongside the correct information volition demand to non alone line inward these tools easily to back upward their analyses but also customize their tools to the detail intelligence information that is relevant to their battlefield surroundings together with practice all of this at massive scale together with alongside varied types of information.
Some of the best uses of Big Data together with car learning inward manufacture lawsuit from applying numerous methods to data, which tin alone hold out done inward an opened upward framework where an analyst is non restricted to provided or existing tools together with methods. For the Palantir arrangement to hold out successful for battlefield intelligence, it must, at a minimum, stimulate got an application programming interface for analysts to programmatically together with easily line together with submit information alongside the Palantir system.
Ideally, Palantir should characteristic a total interface that has all of the of import programming languages together with their associated packages already inward it, such that an analyst tin construct code together with enquiry information inward the same surroundings (see Kaggle for an instance of this type of environment). Ultimately, equally the sheer quantity of information available on whatever given battlefield continues to growth (and it volition practice together with thus for the foreseeable future), whatever successful battlefield intelligence arrangement must hold out able to fully leverage this information using Big Data together with car learning. To practice so, Palantir has to back upward an analyst coding together with programmatically querying data.
The determination to honour Palantir the contract for creating the Army’s novel battlefield intelligence platform is a stride inward the correct direction. Palantir’s Gotham programme is by together with large improve than DCGS-A. However, Palantir is inward danger of making the same commutation fault that DCGS-A made: trying to practice an intelligence analysis arrangement to dominion them all. Fundamentally, battlefield intelligence is both a scientific discipline together with an art. So, whatever successful battlefield arrangement must fundamentally hold out interoperable together with customizable to empower creativity. The alter inward battlefield intelligence systems brought past times Palantir presents the armed forces intelligence community a corking chance to modernize together with ensure authorisation inward battlefield intelligence both at in ane lawsuit together with inward the future. We can’t afford to waste materials the chance past times allowing Palantir to brand the same mistakes equally DCGS-A.
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