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Large language models capable of writing poems, summaries, and computer code are driving the demand for “natural language processing (NLP) as a service.” As these models become more capable — and accessible, relatively speaking — appetite in the enterprise for them is growing. According to a 2021 survey from John Snow Labs and Gradient Flow, 60% of tech leaders indicated that their NLP budgets grew by at least 10% compared to 2020, while a third — 33% — said that their spending climbed by more than 30%.
Well-resourced providers like OpenAI, Cohere, and AI21 Labs are reaping the benefits. As of March, OpenAI said that GPT-3 was being used in more than 300 different apps by “tens of thousands” of developers and producing 4.5 billion words per day. Historically, training and deploying these models was beyond the reach of startups without substantial capital — not to mention compute resources. But the emergence of open source NLP models, datasets, and infrastructure is democratizing the technology in surprising ways.
Open source NLP
The hurdles to developing a state-of-the-art language model are significant. Those with the resources to develop and train them, like OpenAI, often choose not to open-source their systems in favor of commercializing them (or...
Read Full Story: https://venturebeat.com/2021/12/23/open-source-nlp-is-fueling-a-new-wave-of-startups/
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