AI is transforming every industry—from finance and healthcare to energy and retail. But there’s one thing powering all of it: data.
To build useful AI tools, companies need huge amounts of data. That data has to be pulled in, cleaned up, and processed quickly. If that doesn’t happen, the AI slows down—or fails altogether.
Old computing systems using only CPUs can’t keep up. They’re slower, cost more to run, and don’t scale well. That’s why companies are now using accelerated computing with GPUs and smarter software. It speeds up AI work by up to 150x and can cut energy use by over 40%.
Here’s how fast data processing is driving AI forward across different industries.
Finance: Catching Fraud in Real Time
Financial companies deal with billions of transactions. Spotting fraud means scanning all that data fast. Traditional tools can’t keep up.
American Express uses GPUs to power LSTM models (a type of AI good at spotting patterns). These models run fast—detecting fraud in just two milliseconds. That’s 50x faster than using CPUs.
PayPal uses accelerated tools for heavy data workloads and reports up to 70% savings in cloud costs for AI and big data jobs.
Faster data = safer accounts and better fraud protection.
Telecom: Smarter Dispatch and Better Service
Telecoms like AT&T generate massive amounts of data—from calls, billing, and network activity.
Managing large dispatch teams and networks takes fast computing. AT&T uses NVIDIA cuOpt and RAPIDS to handle routing and AI tasks. They cut cloud costs by 90% and sped up route planning to just 10 seconds.
With GPU-powered AI, AT&T improves customer service, keeps its network stable, and lowers its environmental footprint.
Healthcare: Faster Drug Discovery
Medical researchers deal with millions of genes and papers. It’s too much to sort through by hand.
AstraZeneca created a knowledge graph that helps find links between genes and diseases. Using GPUs and RAPIDS, they trimmed a gene list from 3,000 to 40 in seconds—a job that used to take months.
Faster processing means quicker breakthroughs—and potentially life-saving treatments.
Energy: Building a Smarter Grid
Renewable energy is growing, but it makes the power grid harder to manage. Smart grids need fast data to balance energy flows from wind, solar, and batteries.
Utilidata built an edge AI platform called Karman using NVIDIA tech. It processes data from power meters in real time—helping utility companies predict usage, prevent outages, and respond faster.
This kind of real-time grid intelligence supports cleaner energy without expensive infrastructure upgrades.
Automotive: Safer Self-Driving Cars
Self-driving cars rely on sensors like cameras and lidar. These feed live data into AI models that help vehicles drive safely.
NIO, an electric car company, uses NVIDIA Triton Inference Server to manage this. With GPUs, they reduced latency by 6x and boosted throughput by 5x.
This also makes it easier to update models across cars, helping the company move faster without needing new hardware.
Retail: Better Forecasts, Less Waste
Big retailers need accurate forecasts to keep shelves stocked and avoid waste.
Walmart used GPUs to improve demand forecasting for 500 million product-location combos. Their new models use 350 data features and run 100x faster—finishing in hours instead of weeks.
Forecast accuracy improved from 94% to 97%, saving $100 million in food waste alone.
Government: Faster Emergency Response
Governments use drone and satellite images for everything from search-and-rescue to climate tracking. But missing location data makes some of this imagery hard to use.
One U.S. agency worked with NVIDIA and Booz Allen to fix this. They used GPU-accelerated tools to locate images without metadata—cutting processing time from 24 hours to 67 microseconds.
Faster data helps agencies respond quicker to disasters and make better decisions.
The Bottom Line
Faster data processing is unlocking the full potential of AI. It helps companies:
- Analyze more data
- Train better models
- Deliver results in real time
- Cut costs and energy use
Whether it’s fraud detection, smart cars, or saving lives—accelerated computing is the engine behind it all.
