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Datasaur Launches LLM LAB Through Which Enterprises can Create their Own Generative AI Application

This approach alleviates concerns related to business and data privacy risks commonly associated with third-party services while affording teams more project autonomy.

Datasaur, an AI startup specializing in text and audio labeling for AI projects, unveiled the launch of the LLM lab. This all-encompassing platform serves as a one-stop solution to assist teams in constructing and training personalized large language model applications similar to ChatGPT. 

Accessible for deployment in both cloud and on-premise environments, LLM Lab offers enterprises an initial foundation for developing their own in-house generative AI applications. 

This approach alleviates concerns related to business and data privacy risks commonly associated with third-party services while affording teams more project autonomy. 

Read More: Andrew Ng introduces ‘Generative AI with LLMs’ with AWS

LLM LAB offers a diverse set of features to enable users to experiment with various base models, link to their internal documents, streamline server expenses, and access various other functionalities.

Collaborating with industry leaders such as Google and Blackbird, Datasaur has significantly accelerated the data labeling process, achieving a 5.9-fold increase in speed compared to manual labeling. Over the last few years, the company has dedicated its efforts to crafting a robust NLP solution encompassing various functionalities, including entity recognition, text classification, speaker diarization, and more.

Datasaur’s platform is expanding its support to accommodate data scientists in NLP and LLM methodologies, enabling them to combine these approaches and utilize LLMs to automate data labeling in conventional models.

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Boudhayan Ghosh
Boudhayan Ghosh
I am a Journalism and Communication graduate, currently working with Analytics Drift as an Associate Technology Journalist. My other hobbies include consuming art and watching football.

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