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The key to operational AI: Modern data architecture

CIO Business Intelligence

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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FPGA vs. GPU: Which is better for deep learning?

IBM Big Data Hub

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.

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New Deep Learning Systems Profoundly Disrupt Fleet Management Operations

Smart Data Collective

Deep learning tech is influencing and enhancing many industries, promising to provide insights into key business operations which were not previously possible to unearth. One of the biggest applications of this technology lies with using deep learning to streamline fleet management. Route adjustments made in real time.

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Deep Learning is Critical for Modern Small Business Accounting

Smart Data Collective

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. There is usually a steep learning curve in terms of “doing AI right”, which is invaluable. The resulting cost savings can fuel the capital investment required to address growth objectives.

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An AI Data Platform for All Seasons

Rocket-Powered Data Science

In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g., document, image, video, audio clip) is reduced (transformed) to a condensed vector representation using deep neural networks. Note: When you see “full-stack,” read “Pure Storage + NVIDIA working together seamlessly.”