Large Language Models (LLMs) are transforming how businesses interpret data, offering unprecedented contextual insights. For CIOs and CTOs, understanding the role of LLM tagging is crucial. New POV: https://lnkd.in/e6rTnsVA Key Takeaways: — Streamlined tagging: Automated tools like Tracer can handle the challenging and costly task of LLM tagging, freeing up engineers for higher impact tasks. — Contextual insights: Precise tagging enhances data quality, allowing for deeper contextual understanding and faster, more actionable business insights. — No-code solutions: Platforms like Tracer allow for easy data updates, maintaining high accuracy without advanced technical skills. Discover how to harness the power of LLMs for your organization. Read the full blog post. https://lnkd.in/e6rTnsVA
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Documents are the lifeblood of enterprises in financial services, government, and other industries that manage information at their core. Since the advent of large language models (LLMs), organizations have speculated about how they will transform document-heavy processes. This research goes beyond speculation by synthesizing insights from a survey about organizations’ progress and ambitions in using LLMs for document automation use cases. Via Craig Le Clair https://lnkd.in/eVmc8VPb
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bidirectional data leakage is a massive problem for llms models revealing sensitive info and users offering sensitive data to models via usage it's easy to get info from llms with just a little prompting, so secure data management practices are going to be essential and it can be necessary to offer key info for certain llm use cases data from academic papers: https://lnkd.in/dh3cgwy2 (https://lnkd.in/dzvnFfDb) convince llm to reveal a secret: https://gandalf.lakera.ai/ (also https://passwordgpt.io/)
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Besides supporting your coding as an assistant, function calling using LLMs is an incredibly powerful and fun tool to use in your software projects. My first mini-project to try this out was to create a 'textual calculator'. All it did was convert textual equations into a JSON format that contains the detected operands and operators. This allowed my software to call a math function based on the JSON data. This was run locally with a last generation GPU on a relatively tiny model. Although LLMs can do easy math without function calling, this is not advisable for anything reliable. Can't wait to take the course below!
Function calling is a powerful way to extend the capabilities of LLMs and AI agents by letting them use external tools. Our new short course Function calling and Data Extraction with LLMs, created with Nexusflow and taught by Jiantao Jiao and Venkat Srinivasan, demonstrates how to prompt LLMs to form calls to external functions. You'll work with NexusRavenV2-13B, a 13B parameter open-source model that excels in function calling tasks while still being small enough to host locally. Learn to use function calling to extract structured data from unstructured text and access web APIs, and build an end-to-end application that processes customer service transcripts. You'll learn how to build LLM-powered applications that can analyze feedback, automate data entry, and enhance search. Please get started here: https://lnkd.in/g9FpiCuH
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Try out the tutorial built by Nexusflow and DeepLearning.AI .
Function calling is a powerful way to extend the capabilities of LLMs and AI agents by letting them use external tools. Our new short course Function calling and Data Extraction with LLMs, created with Nexusflow and taught by Jiantao Jiao and Venkat Srinivasan, demonstrates how to prompt LLMs to form calls to external functions. You'll work with NexusRavenV2-13B, a 13B parameter open-source model that excels in function calling tasks while still being small enough to host locally. Learn to use function calling to extract structured data from unstructured text and access web APIs, and build an end-to-end application that processes customer service transcripts. You'll learn how to build LLM-powered applications that can analyze feedback, automate data entry, and enhance search. Please get started here: https://lnkd.in/g9FpiCuH
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Can AI technology help the industry prevent more outages? What tools and techniques available now can be used to improve the operational resilience of financial infrastructures? Find out from this month’s The World Federation of Exchanges Focus issue as Daria Degtiarenko, Exactpro’s Senior Communications Manager looks at outages as a “data” problem, to which AI-Driven Synthetic Data Engineering is the solution. Read the full piece at https://lnkd.in/e-mzddwW #exchanges #CCPs #AITesting #operationalresilience
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Meet VectorLink: A Vector Database that is Part of TerminusCMS, Providing Semantic Data and Content Management Tools Using Vector Embeddings The complexity of interconnected data is often difficult for developers. There are challenges like making sense of relationships in data or dealing with intricate queries. These struggles sparked the development of VectorLink, a powerful solution de... https://lnkd.in/eP3WHeYW #AI #ML #Automation
Meet VectorLink: A Vector Database that is Part of TerminusCMS, Providing Semantic Data and Content Management Tools Using Vector Embeddings
openexo.com
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Data Science Leader | 25,000 followers | Transforming businesses with AI / Data Science / Machine Learning
Function calling is a powerful way to extend the capabilities of LLMs and AI agents by letting them use external tools. This short course Function calling and Data Extraction with LLMs, created with Nexusflow and taught by Jiantao Jiao and Venkat Srinivasan, demonstrates how to prompt LLMs to form calls to external functions.
Function calling is a powerful way to extend the capabilities of LLMs and AI agents by letting them use external tools. Our new short course Function calling and Data Extraction with LLMs, created with Nexusflow and taught by Jiantao Jiao and Venkat Srinivasan, demonstrates how to prompt LLMs to form calls to external functions. You'll work with NexusRavenV2-13B, a 13B parameter open-source model that excels in function calling tasks while still being small enough to host locally. Learn to use function calling to extract structured data from unstructured text and access web APIs, and build an end-to-end application that processes customer service transcripts. You'll learn how to build LLM-powered applications that can analyze feedback, automate data entry, and enhance search. Please get started here: https://lnkd.in/g9FpiCuH
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Be sure to check out the "Function Calling and Data Extraction with LLMs" short course from DeepLearning.AI! It only takes about an hour or so to complete and is really great for learning a about practical techniques for interacting with external tools, processing structured data, and improving user interactions. These skills are crucial for enhancing interactions with external tools and processing structured data. As a product manager, understanding how to leverage large language models for function calling and data extraction can help improve product features, streamline data processing, and enhance user interactions & experience. It also helps to be able to communicate effectively when working with data scientists and engineers. Happy Learning! #AI #MachineLearning #DataScience #DeepLearning #LLMs #ProfessionalDevelopment
Function calling is a powerful way to extend the capabilities of LLMs and AI agents by letting them use external tools. Our new short course Function calling and Data Extraction with LLMs, created with Nexusflow and taught by Jiantao Jiao and Venkat Srinivasan, demonstrates how to prompt LLMs to form calls to external functions. You'll work with NexusRavenV2-13B, a 13B parameter open-source model that excels in function calling tasks while still being small enough to host locally. Learn to use function calling to extract structured data from unstructured text and access web APIs, and build an end-to-end application that processes customer service transcripts. You'll learn how to build LLM-powered applications that can analyze feedback, automate data entry, and enhance search. Please get started here: https://lnkd.in/g9FpiCuH
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Introducing Parsee.ai by SimFin - A Leap Forward in Data Structuring! We at SimFin are proud to announce the launch of Parsee, our latest open-source framework for data structuring. Parsee is here to transform the way you handle unstructured data, from PDFs to images and beyond. Key Features: - User-friendly interface with or without coding expertise - Customizable for various data types - Enhanced accuracy with LLMs and custom models Join us in embracing the next level of data management efficiency. Learn more about how Parsee can benefit your business. https://parsee.ai #SimFin #Parsee #DataManagement #LLMData
Open Source Framework for Data Extraction and Structuring
parsee.ai
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