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News Réglementées
29/07/2026 09:00

Giotto.ai and University of Applied Sciences and Arts Northwestern Switzerland (FHNW) Join Forces to Advance the Computational Efficiency of AI Models

Dynamics Group AG / Key word(s): Miscellaneous
Giotto.ai and University of Applied Sciences and Arts Northwestern Switzerland (FHNW) Join Forces to Advance the Computational Efficiency of AI Models

29.07.2026 / 09:00 CET/CEST


PRESS RELEASE


Giotto.ai and University of Applied Sciences and Arts Northwestern Switzerland (FHNW) Join Forces to Advance the Computational Efficiency of AI Models


The collaboration will explore new methods and tools to optimise the deployment of Giotto’s models across different hardware architectures, improving performance while reducing computational requirements.

Lausanne and Windisch, 29 July 2026 — Giotto.ai, the Swiss artificial intelligence laboratory specialising in advanced reasoning systems, and the University of Applied Sciences and Arts Northwestern Switzerland  (FHNW) have initiated a scientific and industrial collaboration focused on improving the computational performance and deployment efficiency of artificial intelligence models.

The initiative will bring together FHNW’s applied research capabilities, coordinated by Prof. Dr. Tomasz Kacprzak and the FHNW High-Performance Computing Lab, with Giotto.ai’s expertise in frontier AI.

The research programme will investigate the optimisation of serving engines, deployment profiles and accelerator configurations.

“Computational efficiency is becoming as critical as model capability,” said Wallyson Lemes, Chief AI of Giotto.ai. “The more consequential frontier is our ability to transform computation into intelligence with the greatest possible efficiency. This collaboration with FHNW reinforces one of Giotto’s founding convictions: advanced AI should be portable, predictable and capable of running on infrastructure chosen and controlled by its users.”

“The recent remarkable progress in artificial intelligence reasoning was enabled by orders-of-magnitude improvements in computing power, said Prof. Dr. Tomasz Kacprzak, Professor for High Performance Computing at FHNW Institute for Data Science. But this is just the beginning: computing capacities will grow, new computing paradigms will emerge, and AI architectures will evolve fast. In order to keep up and maintain a competitive edge, is critical to continuously optimize and adapt the performance of AI inference serving. As reasoning AI models are particularly challenging for resource utilization, the collaboration with Giotto.ai provides an excellent opportunity for FHNW students and researchers to engage with the most impactful problems in computing today.”

The collaboration reflects a shared ambition to move beyond the prevailing assumption that greater intelligence must necessarily require ever-larger models and ever-greater computational resources. For Giotto.ai, computational efficiency is not merely a technical consideration: it is a condition for making advanced AI more portable, affordable, sustainable and strategically controllable.


About Giotto.ai
Giotto.ai is a Swiss artificial intelligence company developing compact and advanced reasoning systems designed to operate on infrastructure selected and controlled by their users. Its mission is to make powerful AI more efficient, portable, secure and accessible to enterprises, institutions and public organisations.

About University of Applied Sciences and Arts Northwestern Switzerland (FHNW)
Based on 4 locations comprising 10 schools in Basel, Aargau, and Solothurn regions, the University of Applied Sciences and Arts Northwestern Switzerland — Fachhochschule Nordwestschweiz (FHNW) — is one of Switzerland’s leading universities of applied sciences. Through its research and educational activities, FHNW works closely with industry and public institutions to translate scientific expertise into practical innovation.

Media contacts: Thierry Meyer, Senior Partner, Dynamics Group – tme@dynamicsgroup.ch – +41 79 785 35 81


Additional features:

File: Press release (PDF)


End of Media Release
View original content: EQS News


2372652  29.07.2026 CET/CEST

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