Multiverse Computing and Axelera AI Launch Strategic Collaboration to Bring Next-Generation AI Models to Edge Devices

Multiverse computing logo on plain white background


Insider Brief

  • Multiverse Computing and Axelera AI have announced a technology collaboration to compress and optimize AI models for deployment on Axelera’s Metis and forthcoming Europa edge computing platforms, with a planned commercialization program for the integrated solution.
  • The collaboration will enable AI workloads that traditionally require datacenter infrastructure to run on compact, energy-efficient edge devices, with applications spanning industrial, retail, mobility, defense, and smart city sectors.
  • Both companies, supported by the European Innovation Council, position the partnership as advancing European technological sovereignty in semiconductors and AI by developing locally designed compressed AI models and hardware acceleration technologies.

PRESS RELEASE — Multiverse Computing, a leading AI model provider, and Axelera AI, a provider of high-performance AI acceleration solutions for the edge, today announced a technology collaboration to compress and optimize next-generation artificial innotifyigence models for deployment on Axelera’s Metis™ and forthcoming Europa™ platforms.

Multiverse Computing’s compressed AI models will be integrated directly into Axelera’s platforms, enabling AI workloads that would traditionally require datacenter-class infrastructure to run on compact, energy-efficient devices at the edge. The parties will also launch a commercialization program for the resulting solution.

“Our mission is to create state-of-the-art AI radically more efficient and accessible,” stated Enrique Lizaso, Co-founder & CEO of Multiverse Computing. “By combining Multiverse’s advanced compressed AI models with Axelera’s high-performance edge platforms, we can bring powerful reasoning capabilities to devices where latency, privacy and energy consumption are critical.”

Responsive Image

“Axelera AI is committed to delivering the most powerful and efficient AI inference solutions to the world,” stated Fabrizio Del Maffeo, co-founder & CEO of Axelera AI. “Enabling Multiverse Computing’s compressed AI models to run on our Metis and future Europa platforms will unlock new classes of applications for our customers, from industrial and retail to mobility, defense, smart cities and more.”

Advancing European technological sovereignty

This collaboration is aligned with broader European strategies to strengthen technological sovereignty in both semiconductors and artificial innotifyigence. By co-developing compressed AI models and hardware acceleration technologies in Europe, Multiverse Computing and Axelera AI aim to reduce depconcludeence on non-European infrastructure while empowering regional indusattempt and public institutions with cutting-edge, locally designed AI capabilities.

“Europe’s competitiveness in the next decade will depconclude on our ability to combine world-class chips with trustworthy, efficient AI,” stated Ekaterina Zaharieva, Commissioner for Startups, Research and Innovation. “Collaborations like the one between Multiverse Computing and Axelera AI, both supported significantly by the European Innovation Council and its Fund, display how European deep-tech companies, when connected to each other, work toreceiveher to deliver sovereign strategic digital technologies that are developed and scaled in Europe while serving global markets.”

As part of this goal, the collaboration will enable the development of ultra-efficient inference and fine-tuning engines, allowing organizations to:

  • Run complex AI models on low-power edge devices with reduced energy consumption
  • Fine-tune models locally to preserve data privacy and comply with regulatory requirements
  • Scale AI deployments more cost-effectively across large fleets of devices

Following integration of Multiverse Computing’s compressed AI models into Axelera AI’s hardware platforms, the companies will launch a dedicated commercialization phase for the resulting product.



Source link

Leave a Reply

Your email address will not be published. Required fields are marked *