SANTA CRUZ, Calif. - eTradeWire -- Two major architectures for Natural Language Processing (NLP) tasks are vying to dominate the market but GPT has an edge according to developers working with NLPs. In Evans Data's semi-annual Artificial Intelligence and Machine Learning Development survey conducted last month, developers were asked whether an autoregressive model or a bidirectional one is best suited for their NLP projects. Autoregressive (GPT) was selected by 43% while bidirectional was cited by 40%.

Auto-regressive and bidirectional models are two different approaches used in NLP tasks. Auto-regressive models, such as GPT generate text by predicting the next word in a sequence given the previous words. In contrast, bidirectional models like BERT capture information from both preceding and succeeding words, enabling a deeper understanding of language.

When we got more specific, developers were more likely to cite using GPT4 than any other specific language model, although more versions of BERT were cited.

There are a host of uses for NLPs, and developers working on them cited search engines as the top technology that would benefit, followed by customer service apps, grammar correction software and legal research and contracts as the top implementations for NLPs today.

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The AI/ML Development Survey is conducted twice a year in the spring and fall and delivers over 180 fresh data points about what developers are doing on up to the minute subjects such as neural networks and transformers, generative AI, deep learning methods, computer vision and image recognition, NLPs, machine learning frameworks and much more detailed comprehensive information.

For an in-depth view of the topics addressed, view the full table of contents and more at https://evansdata.com/aiml.

Press and bloggers contact aakau@evansdata.com for more information and statistics.

About Evans Data Corporation

Evans Data Corporation (http://www.evansdata.com/) provides regularly updated IT industry market intelligence based on in-depth surveys of the global developer population. Evans' syndicated research includes surveys focused on developers in a wide variety of subjects.

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