Expert Guide to Implementing Advanced AI in ABBYY Software: Fusing Machine Learning and Natural Language Processing Techniques for Superior Results
Expert Guide to Implementing Advanced AI in ABBYY Software: Fusing Machine Learning and Natural Language Processing Techniques for Superior Results
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The Developer’s Guide to ABBYY AI
by PJ, Chief Product & Technology Officer
Digital transformation will continue to evolve with more advanced, comprehensive, and personalization capabilities for business users and end users. But before we go there, it’s important to understand how developers are leveraging purpose-built AI to deliver business value today.
Algorithm- and heuristic-based artificial intelligence (AI) has been the basis of innovation for decades for businesses. Technologies such as machine learning, computer vision, and natural language processing have enabled human-like recognition, extraction, and classification of data from documents to automatically fuel enterprise systems and make more intelligent decisions faster. Now, the emergence of transformer-based generative AI has ushered in a new generation of artificial intelligence. The promises and opportunities are unchartered, and its impact to business is optimistic, yet also debatable.
What’s clear, though, is that digital transformation will continue to evolve with more advanced, comprehensive, and personalization capabilities for business users and end users. But before we go there, it’s important to understand how developers are leveraging purpose-built AI to deliver business value today.
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ABBYY Spotlight: Mihajlo Mulic, Senior Software Developer, Serbia
In this edition of The Intelligent Enterprise , we focus on the developer, who will hear from ABBYY experts on how to successfully integrate computer vision and large language models with IDP, and give you a look under the hood of ABBYY IDP to see how we use NLP, LLMs, DeepML, and FastML. We’ll also discuss industry-specific use cases such as how logistics providers can leverage AI for international shipping, where only one percent of documents are fully digitalized, and in insurance, where the claims process is made simpler for insurers using AI that focuses on the ability of machines to interpret and understand visual content and can be trained to recognize a wide variety of objects, patterns, and features in images. It can be added to the automation process by consuming services such as Microsoft Cognitive Services, AWS Amazon Rekognition, and Google Cloud Vision, among others, or even through specialized open libraries such as OpenCV and Python programming language.
We’ll also share with you the frequently asked questions we receive about AI when we speak at industry conferences and tell you why we loved hosting a hackathon this past September and what you can learn from it. You can also catch the latest episode of The AI Pulse podcast , where host Maxime Vermeir continues his conversation with ABBYY’s AI Ethics Evangelist Andrew Pery about the latest EU AI regulations and their impact on development.
Stay tuned here as we continue to bring you the latest developments of ABBYY’s purpose-built AI and how we’re uniquely combining traditional and new AI to put your information to work.
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- Title: Expert Guide to Implementing Advanced AI in ABBYY Software: Fusing Machine Learning and Natural Language Processing Techniques for Superior Results
- Author: John
- Created at : 2024-10-09 19:25:22
- Updated at : 2024-10-14 18:17:27
- Link: https://solve-hot.techidaily.com/expert-guide-to-implementing-advanced-ai-in-abbyy-software-fusing-machine-learning-and-natural-language-processing-techniques-for-superior-results/
- License: This work is licensed under CC BY-NC-SA 4.0.