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How IT leaders use agentic AI for business workflows

CIO

An AI briefer could inform a sales pipeline review process, for instance, or an AI trainer could simulate customer interactions as part of an onboarding program, he adds. Similarly, software provider Akamai is prioritizing agentic AI where processes are already highly matured and supported by high-quality data and security controls.

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DocRaptor Review – HTML to PDF API

The Crazy Programmer

Here, in this article, we’ll review the DocRaptor tool, an HTML to PDF API converter. The DocRaptor review will briefly discuss how it works with Python, some code examples, features, benefits, and perhaps pros and cons. DocRaptor is an HTML to PDF and Excel format transforming document API. Infinite Throughput.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, consider a text summarization AI assistant intended for academic research and literature review. Such a virtual assistant should support users across various business functions, such as finance, legal, human resources, and operations. Such queries could be effectively handled by a simple, lower-cost model.

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How PwC and SAP are doing right by helping clients unlock ESG value

CIO

When presented by the new Supply Chain Due Diligence Act ( SCDDA) in Germany, PwC realized their clients would need tools and processes to automate evaluation of suppliers. In addition, the app provides options for defining and tracking measures for high-risk suppliers, as well as documentation and reporting.

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10 most in-demand generative AI skills

CIO

Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer. AI image processing enables organizations to analyze and extract data from documents such as invoices, purchase orders, packing lists, receipts, and more.

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Beyond Negation Detection: Comprehensive Assertion Detection Models for Clinical NLP

John Snow Labs

When we fit() on the pipeline with a Spark data frame, its text column is fed into the DocumentAssembler() transformer and a new column document is created as an initial entry point to Spark NLP for any Spark data frame. Then, its document column is fed into the SentenceDetector(), Tokenizer() and WordEmbeddings().

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Legal NLP Releases Law Stack Exchange Classifier, Subpoena NER and more

John Snow Labs

internet”) due to limited examples. setInputCols(["document", "token"]).setOutputCol("class") I have been helping a nonprofit by developing a piece of software that they needed. The software is more-or-less built to their specs in a ‘functional’ way, but I wrote 100% of the code: they are not programmers.