With the rise in machine learning and artificial intelligence approaches to big data, systems that can integrate into the complex ecosystem typically found within large enterprises are increasingly important.
Hadoop systems can hold billions of data objects but suffer from the common problem that such objects can be hard or organise due to a lack of descriptive meta-data. SciBite can improve the discoverability of this vast resource by unlocking the knowledge held in unstructured text to power next-generation analytics and insight.
Here we describe how the combination of Hadoop and SciBite brings significant value to large-scale processing projects.
To learn more, download the full use case.
Large language models (LLMs) have limitations when applied to search due to their inability to distinguish between fact and fiction, potential privacy concerns, and provenance issues. LLMs can, however, support search when used in conjunction with FAIR data and could even support the democratisation of data, if used correctly…Read
GPT3 is a large language model that is capable of generating text with very high fidelity. Unlike previous models, it doesn't stumble over its grammar or write like an inebriated caveman. In many circumstances it can easily be taken for a human author, and GPT-generated text is increasingly prolific across the internet for this reason.Read
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