Axelera AI Platform Accelerates Edge Application Deployment
By Maurizio Di Paolo Emilio, EETimes (November 21, 2023)
Conventional AI applications frequently require local devices to transmit data to a centralized cloud server for analysis and processing. Although this methodology exhibits efficacy across various scenarios, it’s not without its constraints, encompassing latency, bandwidth consumption, and privacy and security considerations. Relocating AI processing near the location where the data is generated—otherwise known as the “bringing AI to the edge” approach—resolves these concerns through the execution of computations locally on the device or in close proximity to the data source.
In an interview with EE Times, Axelera AI co-founder and CEO Fabrizio Del Maffeo noted recent industry milestones the company achieved, as well as the appointment of a former Arm executive to Axelera’s board of directors.
To read the full article, click here
Related Semiconductor IP
- nQrux® Root of Trust IP
- AXI to UCIe Bridge IP
- UCIe 2.x Controller IP
- SWI3S (SoundWire I3S Interface) Peripheral Controller Core IP
- OpenTitan-based RISC-V Secure Element
Related News
- Axelera AI and Andes Technology Partner to Power Next-Generation “Europa” AI Platform with High-Performance RISC-V AX65 Cores
- Ainekko’s Edge AI Silicon Platform is Now an OpenHW Foundation Open Source Project
- Dolphin Semiconductor and INTERA Group Announce Reference Platform Combining Analog Voice Sensing and Neuromorphic AI for Ultra-Low-Power Edge Intelligence
- BrainChip Partners with Celus to Bring Its Neuromorphic Edge AI Processor to the CELUS Design Platform
Latest News
- Year-to-Date Global Semiconductor Sales Top $1 Trillion Through August
- Xiphera launches nQrux® Root of Trust with Post-Quantum Cryptography
- Skyechip Joins Rapidus Core Ecosystem, Bringing Advanced Silicon IP For AI and HPC to Japan's 2nm Platform
- GUC Monthly Sales Report – September 2026
- Rapidus Unveils “Rapidus CORE”, New Global Ecosystem Framework Supporting the Development and Mass Production of Cutting-Edge Semiconductors