• Using multiple labels improves neural network learning

    Axel Berg
    Axel Berg
    A single label is not enough. Label diversity can be introduced by creating several labels for each training example in a way that the ordinal structure allows.
    • February 22, 2021
  • Building a mobile AR filter app in Unity

    Pavel Rudko
    Pavel Rudko
    This blog describes the process for building an augmented reality (AR) filter mobile app in Unity.
    • February 11, 2021
  • Making the most of Arm NN for GPU inference: FP16 and FastMath

    Roberto Lopez Mendez
    Roberto Lopez Mendez
    This blog demonstrates how to significantly reduce memory usage and achieve a substantial inference speed-up through enabling new Arm NN features.
    • January 26, 2021
  • Profiling Arm NN Machine Learning applications running on Linux with Streamline

    Florent Lebeau
    Florent Lebeau
    This blog article introduces how to profile and optimize machine learning applications running with the Arm NN inference engine.
    • January 20, 2021
  • Kickstart your ML development with free Ethos-U55 platform

    Pareena Verma
    Pareena Verma
    In this blog, learn how to start your development with a free Ethos-U55 platform.
    • January 6, 2021
  • Why standard benchmarks matter to AI innovation?

    Dylan Zika
    Dylan Zika
    Arm and MLCommons, a global engineering consortium are working together to push industry benchmarks and best practices for AI.
    • December 4, 2020
  • TVM 2020

    Karl Fezer
    Karl Fezer
    What is TVM? A quick guide on why developers focused on ML Deployment should be aware.
    • December 2, 2020
  • Accelerating Edge Computing with Arm Ethos-N78 and Artisan Physical IP on GLOBALFOUNDRIES’ 12LP+ Specialty Solution

    Lakshmi Jain
    Lakshmi Jain
    In this blog, read about how to accelerate Edge Computing with Arm Ethos-N78 and Artisan.
    • November 4, 2020
  • Arm Ethos-U65: Powering innovation in a new world of AI devices

    Tanuj Arora
    Tanuj Arora
    Read about Arm Ethos-U65 and the expansion of Artificial Intelligence (AI).
    • October 19, 2020
  • New Arm ML Guide: Add a new operator to Arm NN

    Kevin May
    Kevin May
    Read the announcement of the new Machine Learning how-to guide - Add a new operator to Arm NN.
    • October 19, 2020
  • Research for a sustainable future

    René de Jong
    René de Jong
    To help companies find the breakthrough innovations needed to support the Global Goals, the UNGC set up the Young SDG Innovator Program, which our colleagues in Arm joined.
    • October 19, 2020
  • Making the most of Arm NN for GPU inference: OpenCL Tuner

    Roberto Lopez Mendez
    Roberto Lopez Mendez
    This blog explores how to make the most of Arm NN for GPU inference through the new OpenCL Tuner.
    • October 15, 2020
  • Smart Pruning: Improve Machine Learning Performance on Mobile

    Joshua Sowerby
    Joshua Sowerby
    This blog describes what smart pruning is and how it improves machine learning performance on mobile.
    • October 12, 2020
  • What is Digital Immersion?

    Jack Melling
    Jack Melling
    This blog explains exactly what Arm means when it talks about 'digital immersion' experiences, how they benefit the end-user and how digital immersion will evolve in the future.
    • September 28, 2020
  • Efficient Bug Discovery with Machine Learning for Hardware Verification

    Hongsup Shin
    Hongsup Shin
    For present-day microprocessors, it is even more challenging to identify bugs. Using (ML) to efficiently identify bugs, we've seen a 25% increase in efficiency than the default verification workflow. …
    • September 22, 2020
  • How to build scalable Next Best Action solution in pure SQL with Hivemall

    dkovachev
    dkovachev
    In this blog, read about Hivemall with Next Best Action (NBA) and how to build scalable solutions.
    • September 10, 2020
  • Computational Storage is bringing processing closer to the data

    Neil Werdmuller
    Neil Werdmuller
    We are generating, storing, and processing more and more data. Find out in this blog how computational storage generates insights and value from that data.
    • September 3, 2020
  • Reducing the Cost of Neural Network Inference with Residue Number Systems

    Matthew Mattina
    Matthew Mattina
    The size and computational complexity of neural network models continues to grow exponentially. However, the increase in computational requirements presents a major challenge to their adoption. Could Residue…
    • August 21, 2020
>