Technology Trends

Deep learning uses artificial neural networks to process massive data sets through binary logic, improving accuracy as systems process more data and remember patterns. Already powering Netflix content recommendations, Facebook image classification (inspect your profile picture to see detected tags), and Google Translate improvements. Medical applications in development promise to improve diagnosis accuracy beyond current 10-20 percent error rates and create gene-tailored medicine for individual genetic makeups.

38% of employees check email at dinner tables, but Batched Inbox restricts email delivery to specific hours. Rapportive reveals workplace and social profiles from email addresses while Clearbit Connect finds anyone's email from company names. Bananatag tracks exactly when recipients open messages with location and time stamps. Streak transforms Gmail into full CRM with pipeline management and customizable mass emails.

Enterprise applications integrate various business functions including accounting, customer relationship management, supply chain management, and enterprise resource planning into centralized systems that optimize efficiency and workflow. These comprehensive software platforms eliminate time-consuming repetitive tasks, automate record-keeping, improve interdepartmental collaboration, and create unified management structures that enable businesses to scale operations effectively.

Discover the Kanban system for just-in-time inventory control. Learn how Toyota pioneered this lean manufacturing approach, how it evolved from physical cards to electronic systems, and how it reduces costs while maintaining optimal stock levels.

Cisco predicts almost 50 billion smart devices by 2020. IoT generates massive data from fitness trackers, smart meters, and connected devices, but only companies with automated measurement and analysis workflows turn this into product improvements. Amazon Echo orders and smart fridge purchases mean customers expect instant service and same-day delivery, requiring inventory tracking and fulfillment processes most mid-size companies don't have.

Human in the loop describes machine learning systems that require human intervention when automated confidence falls below acceptable thresholds, combining computer efficiency with human judgment for optimal business process automation.