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Developing this data for AI usage is often overlooked — but it is one of the most powerful ways to build an AI moat. If you are interested in accelerating the data backbone of your AIstrategy with Snorkel’s Foundation Model DataPlatform, please connect with our team here.
Developing this data for AI usage is often overlooked — but it is one of the most powerful ways to build an AI moat. If you are interested in accelerating the data backbone of your AIstrategy with Snorkel’s Foundation Model DataPlatform, please connect with our team here.
While traditional PIM systems are effective for centralizing and managing product information, many solutions struggle to support complex omnichannel strategies, dynamic data, and integrations with other eCommerce or dataplatforms, meaning that the PIM just becomes another data silo.
Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.
These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.
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