Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Advanced AI System to Process Package Data 10x Faster with Higher Accuracy

NVIDIA announced that the United States Postal Service – the world’s largest postal service, with 485 million mail pieces processed and delivered daily – is adopting end-to-end AI technology from NVIDIA to improve its package data processing efficiency.

The new system starts with high-performance servers powered by NVIDIA V100 Tensor Core GPUs and deep learning software to train multiple AI algorithms. The trained models are then deployed to NVIDIA EGX edge computing systems at close to 200 Postal Service facilities throughout the US to enable more efficient package data processing. The NVIDIA-powered systems are being purchased by the Postal Service under contract with Hewlett Packard Enterprise.

Read More: Sun Genomics Launches Breakthrough Solution to Deliver Personalized Probiotics in Only Six Weeks

“AI is transforming multiple industries, enabling processes, accuracy and efficiency not possible before,” said Anthony Robbins, vice president of the Federal Sector Business at NVIDIA. “The US Postal Service’s adoption of AI demonstrates how this powerful technology can improve an excellent service that we rely on every day. Benjamin Franklin would be proud.”

The Postal Service operates the world’s highest volume logistics operation, processing and delivering some 146 billion pieces of mail annually, including more than 6 billion packages. The new AI system will process package data 10x faster and with higher accuracy.

Related Posts
1 of 40,812

Read More: Accenture Expands Innovation Hub in Chicago, Adds New Industry X.0 Studio to Accelerate Smart, Connected Products and Services Development for Clients

Engineering teams from the Postal Service and NVIDIA have been collaborating for several months to develop AI models, using NVIDIA software including TensorRT for high-throughput, low-latency inference optimization; automatic mixed precision in PyTorch to accelerate training while maintaining model accuracy; NGC containers, which are GPU-optimized for streamlining software deployment; and DeepOps tools for optimizing GPU clusters.

Delivery and testing of the system will start this year and it is expected to be fully operational by spring of 2020.

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.

Read More: NMPi Appointed by Draftkings to Lead Google Strategy and Media Buying

3 Comments
  1. j.mp says

    Right here is the right website for anyone who hopes to
    understand this topic. You know so much its almost hard to argue with you (not that I actually will need to…HaHa).
    You definitely put a fresh spin on a subject
    that has been written about for ages. Great stuff, just wonderful!

  2. Scrap copper inspection says

    International trade of Copper scrap Copper recovery services Metal reprocessing facility
    Reception of Copper cable scrap, Metal recycling plant, Copper scrap quality assurance

  3. Iron recovery center services says

    Forecasting in metal recycling industry Ferrous material recycling agreements Iron waste restoration

    Ferrous material retrieval, Iron scrap import regulations, Metal waste processing tools

Leave A Reply

Your email address will not be published.