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In today’s data-driven business landscape, the ability to efficiently extract and process information from a wide range of documents is crucial for informed decision-making and maintaining a competitive edge. However, traditional document processing workflows often involve complex and time-consuming manual tasks, hindering productivity and scalability. In this post, we discussContinue Reading

In large language model (LLM) training, effective orchestration and compute resource management poses a significant challenge. Automation of resource provisioning, scaling, and workflow management is vital for optimizing resource usage and streamlining complex workflows, thereby achieving efficient deep learning training processes. Simplified orchestration enables researchers and practitioners to focus moreContinue Reading

This post is co-written with Shamik Ray, Srivyshnav K S, Jagmohan Dhiman and Soumya Kundu from Twilio. Today’s leading companies trust Twilio’s Customer Engagement Platform (CEP) to build direct, personalized relationships with their customers everywhere in the world. Twilio enables companies to use communications and data to add intelligence andContinue Reading

Many companies across all industries still rely on laborious, error-prone, manual procedures to handle documents, especially those that are sent to them by email. Despite the availability of technology that can digitize and automate document workflows through intelligent automation, businesses still mostly rely on labor-intensive manual document processing. This representsContinue Reading

In the rapidly evolving digital landscape, travel companies are exploring innovative approaches to enhance customer experiences. One promising solution is the integration of generative artificial intelligence (AI) to create virtual travel agents. These AI-powered assistants use large language models (LLMs) to engage in natural language conversations, providing personalized recommendations, answeringContinue Reading

Name entity recognition (NER) is the process of extracting information of interest, called entities, from structured or unstructured text. Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. Some examples include extracting players and positions in an NFL game summary, products mentioned inContinue Reading