SubsidieMeestersA novel hardware & software platform to revolutionise artificial intelligence at the edge
Developing a scalable hardware and software platform for efficient edge AI inference, targeting computer vision and NLP, to drive adoption with reduced costs and power consumption.
Projectdetails
Introduction
Our solution is a hardware (HW) and software (SW) platform optimized for inference at the edge, which, as a market, is projected to grow exponentially, and to reach €15.52 B in 2025.
Solution Overview
Our solution will accelerate the latest generation of neural network models for:
- Computer vision
- Natural language processing
- Generative AI
This will revolutionize the way we use AI, at a fraction of the costs and power consumption of available solutions.
Hardware Features
The HW will be available in various form factors for rapid adoption and is highly scalable:
- From a single device running in an embedded system
- To multiple instances on cards in an edge datacenter
Software Tools
Our SW tools provide a consistent, powerful, and easy-to-use development environment for all of these instances, while driving the adoption of AI through our no-code web composer.
Team Expertise
We have a strong team led by the CEO who was the Head of Artificial Intelligence at Bitfury and has 20+ years of managerial experience in tech corporations such as Asus and Advantech.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 2.499.999 |
| Totale projectbegroting | € 3.580.000 |
Tijdlijn
| Startdatum | 1-3-2024 |
| Einddatum | 28-2-2026 |
| Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- AXELERA AI BVpenvoerder
Land(en)
Vergelijkbare projecten binnen EIC Accelerator
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End to end Real-time Interactive Edge AI analytics platform for Industry and Automotive
Developing an end-to-end edge AI platform for Industry and Automotive, enabling non-coders to create real-time AI models efficiently for faster market deployment.
AI-centric Server on Chip for increasing complexity and scale of AI inference applications, enabling the scale of real-life AI applications.
NeuReality aims to finalize and validate its NR1 Server-on-a-Chip solution to enable scalable AI deployment through optimized architecture and infrastructure for commercial use.
Scalable Unified Processor Enhancing Revolutionary Computing, Harnessing Integrated Performance for Edge AI, Autonomous Driving, Generative AI, and Decentralized AIoT Applications
Developing the Tyr chip to enable real-time, efficient processing for Level 4/5 autonomous driving, addressing current data and processing limitations in the industry.
Europe’s first unified and versatile processing platform architecture in 5nm technology with proven scalability from edge to central high-performance solutions with unmatched cost and power efficiency
videantis aims to develop a scalable 5nm processor architecture for automotive and AI applications, enhancing European chip sovereignty and reducing costs for OEMs by up to 90%.
Quantum-enhanced Machine Learning
Equal1 aims to finalize a scalable, sustainable quantum processor chip for AI applications, enhancing machine learning capabilities while reducing carbon footprint.
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SpiNNaker on the Edge
SpiNNcloud Systems aims to develop real-time, energy-efficient AI applications by transitioning cutting-edge neuromorphic computing technology from cloud to edge, enhancing performance and commercialization.
n-ary spintronics-based edge computing co-processor for artificial intelligence
MultiSpin.AI aims to revolutionize edge computing by developing a neuromorphic AI co-processor that enhances energy efficiency and processing speed, enabling transformative applications while reducing CO2 emissions.
Hybrid electronic-photonic architectures for brain-inspired computing
HYBRAIN aims to develop a brain-inspired hybrid architecture combining integrated photonics and unconventional electronics for ultrafast, energy-efficient edge AI inference.
Industrial Edge AI - Mobile 3D Imaging (Instant NGP-based)
Het project ontwikkelt een innovatieve Edge AI-techniek voor het mobiel genereren van hoogwaardige 3D-beelden, gericht op de automotive sector, door samenwerking tussen CV en PM.
Outplaying the hardware lottery for embedded AI
The BINGO project aims to revolutionize embedded AI by enabling rapid customization of heterogeneous compute platforms using prefabricated chiplets, achieving 100x efficiency gains in days.