APIs Banking Chatbots Construction 
AWS Machine Learning
SEPTEMBER 1, 2023
Main use cases are around human-like chatbots, summarization, or other content creation such as programming code. In this scenario, the generative AI application, designed by the consumer, must interact with the fine-tuner backend via APIs to deliver this functionality to the end-users. 15K available FM reference Step 1.
AWS Machine Learning
MAY 7, 2024
Tasks such as routing support tickets, recognizing customers intents from a chatbot conversation session, extracting key entities from contracts, invoices, and other type of documents, as well as analyzing customer feedback are examples of long-standing needs. You reuse this function throughout the examples. max_tokens=512, top_p=0.9,
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SmartKarrot
SEPTEMBER 25, 2020
While Shopify delivers a digital platform to be used by businesses, it relies on a SaaS model to construct this relationship with the customers. With ‘ API-led connectivity ’, MuleSoft aims at unleashing the true potential of AI in data governance. Could any better implementation of AI in SaaS exist? Salesforce.
SmartKarrot
SEPTEMBER 25, 2020
While Shopify delivers a digital platform to be used by businesses, it relies on a SaaS model to construct this relationship with the customers. With ‘ API-led connectivity ’, MuleSoft aims at unleashing the true potential of AI in data governance. Could any better implementation of AI in SaaS exist? Salesforce.
AWS Machine Learning
MARCH 19, 2024
To enhance code generation accuracy, we propose dynamically constructing multi-shot prompts for NLQs. The dynamically constructed multi-shot prompt provides the most relevant context to the FM, and boosts the FM’s capability in advanced math calculation, time series data processing, and data acronym understanding.
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