Difference between revisions of "Palantir"

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[https://www.bing.com/news/search?q=Palantir&qft=interval%3d%228%22 ...Bing News]
 
[https://www.bing.com/news/search?q=Palantir&qft=interval%3d%228%22 ...Bing News]
  
* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
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* [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database]] ... [[Graph]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
 
* [https://www.palantir.com/offerings/ai-ml/ Palantir]
 
* [https://www.palantir.com/offerings/ai-ml/ Palantir]
 
* [https://www.palantir.com/platforms/aip Palantir Artificial Intelligence Platform]
 
* [https://www.palantir.com/platforms/aip Palantir Artificial Intelligence Platform]

Revision as of 14:52, 17 June 2023

YouTube ... Quora ...Google search ...Google News ...Bing News


Palantir offers AI services, providing a Secure Data Foundation that allows organizations to build a solid foundation of sufficient, quality data, and then bring that data into daily operations.


Palantir’s ontology translates complex data interactions into human-readable concepts, allowing models to reflect how an organization views the world around a common semantic layer.



Palantir has pioneered an entirely new approach to enterprise modeling called Micro Models. Rather than building one all-encompassing model, Micro Models let you address discrete parts of a large problem — and then combine them to create an overall solution. Palantir offers a new way to manage models by attaching each model to a specific organizational objective. Objectives ensure that business logic is tied to specific business KPIs and deployed for a consistent purpose across use cases. Palantir revolutionizes how organizations build and deploy AI/ML by combining the enterprise data foundation with end-to-end AI/ML deployment infrastructure. Data scientists and engineers can customize, deploy, assess, and compare across homegrown, open-source, and third-party algorithms.