Remove Deep Learning Remove Interactive Remove Risk Remove Unstructured Data
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Why Financial Services Firms are Championing Natural Language Processing

CIO Business Intelligence

Those numbers represent the projected growth of chatbot interactions among banking customers between 2019 to 2023 and the cost savings from 862 hours less of work by support personnel, according to research by Juniper Research. NLP solutions can be used to analyze the mountains of structured and unstructured data within companies.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time.

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Perplexing Impacts of AI on The Future Insurance Claims

Smart Data Collective

Key benefits of AI include recognizing speech, identifying objects in an image, and analyzing natural or unstructured data forms. Customers are becoming more accustomed to interacting with AI in their day to day lives, even if they don’t always realize it. What will be the main changes to insurance claims?

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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Big Data Hub

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Modeling 101: How It Works and Why It’s Important

Domino Data Lab

The model uses algorithms to identify patterns in the data that form a relationship with an output. Models can predict things before they happen more accurately than humans, such as catastrophic weather events or who is at risk of imminent death in a hospital. It’s used for developing deep learning models.

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The Superpowers of Ontotext’s Relation and Event Detector

Ontotext

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

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Ontotext’s Semantic Approach Towards LLM, Better Data and Content Management: An Interview with Doug Kimball and Atanas Kiryakov

Ontotext

Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. We use other deep learning techniques for such tasks. That’s something that LLMs cannot do.