Skip to main content

How the USPS uses Nvidia GPUs and A.I. to track missing mail

United States Postal Service USPS
USPS

The United States Postal Service, or USPS, is relying on artificial intelligence-powered by Nvidia’s EGX systems to track more than 100 million pieces of mail a day that goes through its network. The world’s busiest postal service system is relying on GPU-accelerated A.I. systems to help solve the challenges of locating lost or missing packages and mail. Essentially, the USPS turned to A.I. to help it locate a “needle in a haystack.”

Recommended Videos

To solve that challenge, USPS engineers created an edge A.I. system of servers that can scan and locate mail. They created algorithms for the system that were trained on 13 Nvidia DGX systems located at USPS data centers. Nvidia’s DGX A100 systems, for reference, pack in five petaflops of compute power and cost just under $200,000. It is based on the same Ampere architecture found on Nvidia’s consumer GeForce RTX 3000 series GPUs.

The algorithms are then deployed and used on a network consisting of 195 distributed Apollo servers created by Hewlett Packard Enterprise, with each server equipped with four Nvidia V100 GPUs. The result is a system called the Edge Computing Infrastructure Program, or ECIP, which tracks items for the postal service.

Combined with optical character recognition, these systems can locate missing mail that goes through the USPS network. In the past, it would take days to track down packages, but A.I.-powered technologies is reducing the manhunt for lost packages down to just mere hours.

Image used with permission by copyright holder

“It used to take eight or 10 people several days to track down items, now it takes one or two people a couple hours,” said Todd Schimmel, the manager who oversees USPS systems in an Nvidia blog post.

The use of graphics-accelerated computing was perfect for this A.I. task, as it would have taken a network of 800 CPUs more than two weeks to complete to do the same thing that four Nvidia V100 Tensor Core GPUs could accomplish in a span of 20 minutes on the HPE Apollo 6500 server.

Each of the Apollo edge servers process 20 terabytes of images daily from more than 1,000 mail processing machines, Nvidia stated. The USPS contract was awarded in September 2019, Schimmel said, and the hardware installation was completed by August 2020.

“The app that checks for mail items alone requires coordinating the work of more than a half dozen deep-learning models, each checking for specific features,” Nvidia stated. “And operators expect to enhance the app with more models enabling more features in the future.”

In addition to mail tracking, the USPS is working on different use cases for A.I. at the edge, ranging from enterprise analytics to finance and marketing. There are currently 30 applications planned for ECIP, and the postal service hopes to implement a few of its ideas this year. One such idea would have A.I. analyze if a package has the correct postage for its size, weight, and destination, and another ECIP app could decipher a damaged barcode, for example.

Chuong Nguyen
Silicon Valley-based technology reporter and Giants baseball fan who splits his time between Northern California and Southern…
I saw Google’s Gemini AI erase copyright evidence. I am deeply worried
Gemini Advanced on the Google Pixel 9 Pro Fold.

Update: Google has responded to Digital Trends’ queries. The story has been updated with company’s statement below.
The rise of generative AI has been a fairly messy process, especially from fair usage ethics and copyright perspective. AI giants are inking deals with publishers to avoid legal hassles, while at the same time, they are embroiled in copyright tussles in courts in multiple countries.
As the ravenous appetite for training AI on user data grows, we might be in for another ethical conundrum. Multiple users on X and Reddit have shared demonstrations of how Google’s latest Gemini 2.0 series AI model can remove watermarks from copyright-protected images.
Going by the before/after samples of images, it seems Gemini is doing a fairly good job of removing the watermarks. Notably, it’s not only erasing those banner-style watermarks, but also fairly complex overlays with design and stylized text elements.
https://x.com/ajiteshleo/status/1901484196972945872?s=61
The model in question is the Gemini 2.0 Flash, which was released earlier this year and got a reasoning upgrade, as well. It is worth noting here that you can not remove the watermark if you are using the mobile or desktop version of the Gemini 2.0 Flash model. Trying to do so returns a message like this:
“Removing watermarks from images without the explicit permission of the copyright holder is illegal in most countries. It is important to respect the copyright laws and intellectual property rights. If you want to use an image with a watermark, you should contact the copyright holder and ask for permission.”
You can, however, try and remove the watermark from images in the Google AI Studio. Digital Trends successfully removed watermarks from a variety of images using the Gemini 2.0 Flash (Image Generation) Experimental model.
 
It is a violation of local copyright laws and any usage of AI-modified material without due consent could land you in legal trouble. Moreover, it is a deeply unethical act, which is also why artists and authors are fighting in court over companies using their work to train AI models without duly compensating them or seeking their explicit nod.

How are the results?
A notable aspect is that the images produced by the AI are fairly high quality. Not only is it removing the watermark artifacts, but also fills the gap with intelligent pixel-level reconstruction. In its current iteration, it works somewhat like the Magic Eraser feature available in the Google Photos app for smartphones.
Furthermore, if the input image is low quality, Gemini is not only wiping off the watermark details but also upscaling the overall picture. .
https://x.com/kaiju_ya/status/1901099096930496720?s=61
The output image, however, has its own Gemini watermark, although this itself can be removed with a simple crop. There are a few minor differences in the final image produced by Gemini after its watermark removal process, such as slightly different color temperatures and fuzzy surface details in photorealistic shots.

Read more
Apple Intelligence could solve my App Store pet peeve, but I’m skeptical
The app store open on a MacBook Pro.

It’s no secret that Apple’s App Store has its problems, but it generally works pretty well. Yet there’s one thing about it that just feels absolutely useless: the reviews section.

Apple highlights a few reviews on each app’s page, but infuriatingly, they’re often from many years ago. It’s not uncommon to see reviews complaining about issues that have long-since been fixed, yet they still get highlighted. When your initial impression is based on completely inappropriate information, it makes the review section borderline useless and is a terrible way to sum up information about an app.

Read more
Google AI Mode will reinvent Search. I’m worried — and you should be, too
Google AI Mode for Search.

Update: A Google spokesperson responded to our queries. The story has been updated with their answers in a dedicated section below. 

Google is pushing forward with more AI into how internet search works. Remember AI Overviews, which essentially summarizes the content pulled from websites, and presents it at the top of the Google Search page?

Read more