Remove tag transportation
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Asset lifecycle management strategy: What’s the best approach for your business?

IBM Journey to AI blog

Procurement and installation: The next stage of the asset lifecycle concerns the purchase, transportation and installation of the asset. Many industries rely on CMMS as a component of EAM, including manufacturing, oil and gas production, power generation, construction and transportation.

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Asset lifecycle management best practices: Building a strategy for success

IBM Journey to AI blog

From a wastewater treatment plant that an entire city depends on to a smaller-sized transportation company expected to provide timely deliveries, businesses of all sizes rely on the assets and equipment they own to create value every day. Read this blog post to explore how digital twins can help you optimize your asset performance.

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10 everyday machine learning use cases

IBM Journey to AI blog

Machine learning and transportation ML informs a lot of our transportation these days. Machine learning and apps We see lots of ML use on social media platforms today: Social media, such as Facebook, automates friend-tagging suggestions by using ML face detection and image recognition to identify a face in its database.

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Best practices for building secure applications with Amazon Transcribe

AWS Machine Learning Blog

Both HTTP/2 and WebSockets streaming connections are established over Transport Layer Security (TLS), which is a widely accepted cryptographic protocol. Best Practice 5 – Use tag-based access control. You can use tags to control access within your AWS accounts. We recommend using TLS 1.2

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Real-Time Supply Chain Visibility: Leveraging IoT and Data Analytics for Real-Time Monitoring and Insights

Towards AI

Route Optimization: Real-time traffic data and tracking of locations allow companies to find the best routes, contributing to cutting loss of time and costs for transportation.

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The most valuable AI use cases for business

IBM Journey to AI blog

Clarify computer vision AI-powered computer vision enables image segmentation , which has a wide variety of use cases, including aiding diagnosis in medical imaging, automating locomotion for robotics and self-driving cars, identifying objects of interest in satellite images and photo tagging in social media.

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Multimodal Language Models Explained: Visual Instruction Tuning

Towards AI

Similarly, MM-ReAct [2] incorporates visual information in the forms of image captioning, dense captioning, image tagging, etc., inside the prompt to feed to the LLM.