Automated Legal Discovery is an artificial intelligence technology designed to automate the process of finding relevant documents for legal cases by scanning large volumes of text.
The technology addresses the inefficiency and potential human error associated with manual document review in legal settings by automating the process, thereby saving time and resources.
These systems use advanced natural language processing (NLP) and machine learning algorithms, particularly large language models (LLMs), to analyze vast amounts of textual data. They can identify key phrases, patterns, and anomalies that are relevant to specific legal queries or precedents.
Manufacturing involves developing and training machine learning models on large datasets of legal documents. This requires significant computational resources and expertise in NLP and data science.
The build process includes data collection, model training, validation, and deployment. It often relies on cloud-based services for scalable computing power.
Field units draw low hundreds of watts; fabrication is energy-intensive due to vacuum baking and computational requirements.
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