AP's NLG Revolution: 14x Earnings Reports Surge
Associated Press harnessed Natural Language Generation (NLG) via Wordsmith to explode quarterly earnings coverage from 300 to 4,200 stories, freeing journalists for in-depth reporting and transforming news production.
Read case study →DHL's AI Predictive Maintenance: IoT & ML Slash Downtime
DHL combats vehicle breakdowns and delays using IoT sensors and ML models for predictive fleet maintenance. Achieved 15% less downtime, 10% cost savings, boosting delivery reliability across global operations.
Read case study →Khanmigo: Khan Academy's GPT-4 AI Tutor Scaling Education
Khan Academy's Khanmigo, powered by GPT-4, transforms learning with personalized tutoring for students and tools for teachers, growing from 68K pilot users to 700K+ in 2024-25, enhancing engagement amid scalability challenges.[1]
Read case study →Maersk's ML Predictive Maintenance Revolutionizes Fleet Ops
Maersk deploys machine learning to predict ship engine failures and optimize routes, slashing downtime, cutting fuel use by 5-10%, and boosting efficiency in global maritime logistics amid rising costs and emissions pressures.
Read case study →UPS ORION: AI Routes Save 100M Miles & $400M Yearly
UPS's ORION system leverages operations research and machine learning to optimize delivery routes, slashing 100 million miles driven annually, saving $300-400M in costs, 10M gallons of fuel, and cutting CO2 emissions. A logistics game-changer deployed across 55K vehicles.
Read case study →NVIDIA's RL Masters Chip Floorplanning in Hours
NVIDIA harnesses deep reinforcement learning to automate microchip floorplanning, slashing design time from months to 3 hours for a massive 2.7M-cell chip, revolutionizing semiconductor efficiency.
Read case study →Zalando's AI Virtual Try-On: Slashing Returns in Fashion
Zalando harnesses generative computer vision for virtual try-on, empowering customers to visualize fits online and in outlets, reducing high return rates from sizing woes while boosting satisfaction across 27M users.
Read case study →Rolls-Royce: AI Digital Twins Slash Jet Engine Downtime
Rolls-Royce leverages digital twins and predictive ML to forecast jet engine failures, boosting time on wing by 48% and cutting airline costs. Real-time sensor data powers IntelligentEngine for optimized maintenance.
Read case study →H&M's AI: Conquering Trends & Inventory Chaos
H&M harnesses AI predictive analytics to forecast fashion trends and optimize inventory, slashing waste by 25%, boosting profits 30%, and minimizing stockouts in fast fashion's volatile market. A data-driven turnaround powered by ML insights.
Read case study →Amazon Rufus: AI Assistant Ignites $10B Sales Surge
Amazon's Rufus, a GenAI shopping companion, tackles e-commerce discovery challenges, boosting purchases by 60% and projecting $10B in extra sales. Scaled on AWS chips, it serves 250M+ users with 210% YoY interaction growth.
Read case study →PepsiCo Frito-Lay: ML Predictive Maintenance Unlocks 4,000 Hours
PepsiCo's Frito-Lay tackled unplanned downtime with machine learning predictive analytics, analyzing sensor data to forecast failures. Result: 4,000 extra production hours, slashed costs, and boosted efficiency in snack manufacturing.[1]
Read case study →Ford's AI Cobots: Sanding Cars in 35 Seconds
Ford deploys AI-powered cobots with machine vision to automate sanding in vehicle assembly, slashing times from hours to 35 seconds per body while boosting safety and productivity in legacy plants.
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