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SambaNova Systems, a company that builds advanced software, hardware, and services to run AI applications, announced the addition of the Generative Pre-trained Transformer (GPT) language model to its Dataflow-as-a-Service™ offering. This will enable greater enterprise adoption of AI, allowing organizations to launch their customized language model in much less time — less than one month, compared to nine months or a year.

“Customers face many challenges with implementing large language models, including the complexity and cost,” said R “Ray” Wang, founder and principal analyst of Constellation Research. “Leading companies seek to make AI more accessible by bringing unique large language model capabilities and automating out the need for expertise in ML models and infrastructure.”

Natural language processing

The addition of GPT to SambaNova’s Dataflow-as-a-Service increases its Natural Language Processing (NLP) capabilities for the production and deployment of language models. This model uses deep learning to produce human-like text for leveraging large amounts of data. The extensible AI services platform is powered by DataScale®, an integrated software, and hardware system using Reconfigurable Dataflow Architecture™, as well as open standards and user interfaces.

OpenAI’s GPT-3 language model also uses deep learning to produce human-like text, much like a more advanced autocomplete program. However, its long waitlist limits the availability of this technology to a few organizations. SambaNova’s model is the first enterprise-grade AI language model designed for use in most business and text- and document-based use cases. Enterprises can use its low-code API interface to quickly, easily, and cost-effectively deploy NLP solutions at scale.

“Enterprises are insistent about exploring AI usage for text and language purposes, but up until now it hasn’t been accessible or easy to deploy at scale,” said Rodrigo Liang, CEO, and cofounder of SambaNova. “By offering GPT models as a subscription service, we are simplifying the process and broadening accessibility to the industry’s most advanced language models in a fraction of the time. We are arming businesses to compete with the early adopters of AI.”

GPT use cases

There are several business use cases for Dataflow-as-a-Service equipped with GPT, including sentiment analysis, such as customer support and feedback, brand monitoring, and reputation management. This technology can also be used for document classification, such as sorting articles or texts and routing them to relevant teams, named entity recognition and relation extraction in invoice automation, identification of patient information and prescriptions, and extraction of information from financial documents.

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