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Blog
NLP Innovations with Small Datasets
A basic foundation of Deep Learning (DL) neural networks is large corpuses of data that have been curated and labeled to train the models on.
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Meet FILBERT. Google’s BERT trained on Finance, Insurance and Legal
Solving context-specific sentiment classification, along with a litany of additional NLP use cases, is the purpose of the Knowledge Process Automation (KPA) Platform we produce at DeepSee.
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Incorporating Knowledge into your Process Automation
The DeepSee Knowledge Process Automation (KPA) flows start with desired and scalable business outcomes instead of collections of minute capabilities that the user needs to learn to connect.
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Moving Beyond the Hype: Implementing AI to Solve Real-World Business Problems.
Many of us are all too familiar with the infamous “Gartner Hype Cycle.” The model is a branded version of other models to represent the maturity, adoption, and social application of specific technologies.
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D3O: Insights Storage from Unstructured Text
As part of the DeepSee platform and, more particularly, its ingestion of unstructured data, an array of data preparation functions and machine learning models are employed that give various insights and/or different views to the original source text.
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A Personal Perspective on DeepSee and Platforms
In the late 1980’s and early 1990’s I was an engineer with a software firm in Utah, Novell. I was with Novell for 8+ years and left in late 1994.
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Introduction to the DeepSee Platform
With each passing year the Internet and its many services, data sources and general capabilities, improves and expands. And in improving, it changes with offerings of different interfaces, access methods and functionalities.
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