Decoding Transformers on Edge Devices

This blog introduces the transformer encoder and decoder architecture and discusses the challenges in inferring them on an edge device: high computational cost, high peak memory requirements, low arithmetic intensity.

Cheap Computing and the Balancing Act of Population Decline

Imagine a world where computing power reaches a historic practical equivalent of two human brains. In this blog article by our Director of Systems Software, Cristian Olar explores how our revolutionary Metis AIPU achieves a remarkable 200 TOPS result at a fraction of today’s costs.

How Will Generative AI Revolutionize Our Work?

On Labor Day, a day dedicated to celebrating the achievements and perseverance of the workforce, we find ourselves on the cusp of a new era where artificial intelligence (AI) is poised to transform the labor market.

The Metis AI Platform in detail

The Metis AI Platform is a one-of-a-kind holistic hardware and software solution establishing best-in-class performance, efficiency, and ease of use for AI inferencing of computer vision workloads at the Edge.

Interview with Jonathan Ballon, Chairman of Axelera AI

Interview with Jonathan Ballon, Chairman of Axelera AI. Coming from leadership roles in some of the world’s most recognizable companies, such as Cisco Systems, General Electric and Intel, Jonathan brings deep entrepreneurial and operational expertise to the company.

Introducing Axelera AI’s New Advisor, Andreas Hansson

Andreas Hansson joined Axelera AI as an advisor. Andreas is an angel investor in several start-ups and serves on the board of several public companies. He advise us on technology, market trends, and computing and artificial intelligence investment opportunities.

Insights and Trends in Machine Learning for Computer Vision

We are delighted to share the presentation “Insights and Trends of Machine Learning for Computer Vision” recently given, at different conferences, by our head of machine learning Bram-Ernst Verhoef and our Algorithm and Quantisation researcher Martino Dazzi.