NVIDIA AI Technology Center (NVAITC)
NVIDIA AI Technology Center (NVAITC) is a joint research center of the Finnish Center for Artificial Intelligence FCAI, NVIDIA, and the Finnish IT Centre for Science CSC. NVAITC Finland accelerates research, education and adoption of artificial intelligence in Finland. Thanks to the new collaboration, researchers are better equipped to develop computationally demanding artificial intelligence applications for research and industry use.
NVAITC enables artificial intelligence researchers to benefit from NVIDIA’s expertise in utilizing graphics processing units (GPUs) and AI software in AI applications. NVIDIA can also actively contribute to research carried out at FCAI. CSC contributes to the collaboration by supplying a considerable amount of computing power for AI researchers at its data centre located in Kajaani, central Finland.
NVAITC projects enable academics at all levels to do their research more efficiently. NVIDIA’s GPUs are used especially for AI model training and inference. NVAITC is able to support research projects that require exceptional amounts of computing power, such as AI solutions for healthcare or smart cities.
Project submission and selection
The selection process for new NVAITC projects is simple and interactive:
PI submits a proposal by email to NVAITC Finland Lead Niki Loppi (nvaitc-project-emea at nvidia.com) using this template. Niki is available for input, suggestion, advise before submitting.
PI is typically contacted for clarification and SoW settlement after submission.
The review of the proposal takes a couple of weeks. Niki reviews proposal with help of fellow NVAITC engineers on a first-come first-serve basis. Evaluation is based on
NVAITC criteria (target publication, technology stack and computing scale),
rules of engagement (compact timeline, no compute, no funding, etc.), and
shared & realistic expectations (an agreed-upon SoW).
This call for proposals remains open as long as there is capacity to handle projects.
When acknowledging the support from NVAITC Finland in publications, please use the full name as in the examples below:
We thank the NVIDIA AI Technology Center (NVAITC) Finland for their contribution of (…)
We wish to thank the NVIDIA AI Technology Center (NVAITC) Finland for their assistance with (…)
This research was supported by the NVIDIA AI Technology Center (NVAITC) Finland. We thank [first last name] who provided (…)
News about the center
August 24, 2022
GPU TECHNOLOGY CONFERENCE 2022
There’s one month until the next GPU Technology Conference (GTC), held Sept 19–22. GTC is fully online, with a large selection of live sessions during European-friendly hours. The conference is free but requires online registration, please use this link sponsored by the NVIDIA AI Technology Center (NVAITC) Europe.
The session catalog is also now online, here are a few curated lists per theme :
Top GTC Sessions
Top Sessions for Developers
Top Sessions for 3D Creators and Developers
Top Sessions for Startups
Top Higher-Ed & Research for Educators/Researchers & Students
EMEA-specific times:
Applied AI - Developers (EMEA)
Autonomous Machines (EMEA)
Data Science (EMEA)
Deep Learning (EMEA)
Omniverse (EMEA)
June 30, 2022
Call for ECCV 2022 workshop papers
NVAITC is involved with two workshops at ECCV this year! There’s still time submit your papers on computational aspects of deep learning (deadline: July 11) and uncertainty quantification for computer vision (deadline: July 10). Please follow the links below for more info.
Computational Aspects of Deep Learning
The ECCV workshop on Computational Aspects of Deep Learning fosters the submission of novel research works that focus on the development of deep neural network architectures, libraries, frameworks, strategies, HW solutions to address challenging experiments while optimizing the use of computational resources. This includes computationally efficient training and inference strategies, the design of novel architectures for increasing the efficacy or the efficiency in feature extraction and classification, the optimization of hyperparameters to enhance model’s performance, solutions for training in multi-node systems such as HPC (High Performance Computing) clusters, and the reduction of model complexity through numerical optimization, e.g. quantization.
Uncertainty Quantification for Computer Vision
In the last decade, substantial progress has been made w.r.t. the performance of computer vision systems, a significant part of it thanks to deep learning. These advancements prompted sharp community growth and a rise in industrial investment. However, most current models lack the ability to reason about the confidence of their predictions; integrating uncertainty quantification into vision systems will help recognize failure scenarios and enable robust applications. In addition to advances in Bayesian deep learning, providing practical approaches for vision problems, the workshop will provide a forum for discussing promising research directions, which have received less attention, as well as advancing current practices to drive future research. Examples include: the development of new metrics that reflect the real-world need for uncertainty when using vision systems with down-stream tasks; and moving beyond point-estimates to address the multi-modal ambiguities inherent in many vision tasks. This workshop on Uncertainty Quantification for Computer Vision aims to raise the vision community's awareness about uncertainties surrounding the model, data, and predictions. Moreover, bringing together experts from ML and vision will create a new generation of well-calibrated and effective methods that know when they do not know.
October 22, 2021
Reminder to register for GTC’21 Nov 8-11
NVIDIA AI Technology Center (NVAITC) Finland, in collaboration with FCAI and CSC invites you to attend GTC (GPU Technology Conference) Fall 2021. The conference will run continuously, across all time zones and NVIDIA CEO Jensen Huang’s keynote is 9 November at 10am Finland time. GTC is free to attend online but you must register. There will be 500+ sessions, including talks from leaders in AI, Graphics, and HPC. In addition, NVIDIA is offering hands-on technical training on both introductory and advanced topics in AI and accelerated computing, through its Deep Learning Institute. You can learn more here.
The full session catalog is now online. Here are some examples of talks that you may find interesting:
Ambient Intelligence: Illuminating the Dark Spaces of Healthcare [A31487], Fei-Fei Li, Professor, Stanford University
Can Neural Networks Learn to Reason? Insights, Plus a Look at Long-term Research in Machine Learning [A31620], Samy Bengio, Senior Director of Machine Learning Research, Apple
Computer Vision Research at NVIDIA [A31691], Jan Kautz, VP Learning and Perception Research, NVIDIA
Convergence of AI and Scientific Computing [A31509], Anima Anandkumar, Director of ML Research, NVIDIA
Deep Learning: What the Future Might Hold [A31496], Ilya Sutskever, Co-founder and Chief Scientist, OpenAI
Accelerated Computing for the Era of Exascale AI [A31560], Ian Buck, Vice President and General Manager of Accelerated Computing, NVIDIA
Thanks for registering using this NVAITC-sponsored link.
April 21, 2021 (last updated on September 29, 2021)
NVAITC Webinar Series on AI Applications in Computational Sciences – Presentation Archive
All presentation materials related to the webinar series are posted under this news entry after the live sessions. Upcoming sessions can be found on https://fcai.fi/aix-forum.
Session 1: AI in Atmospheric Sciences - Dr. David Hall (NVIDIA): materials, video
Session 2: AI in Computational Fluid Dynamics - Prof. Ricardo Vinuesa (KTH): video
Session 3: AI in Materials Science - Dr. Milica Todorovic (Aalto University): materials, video
Session 4: AI to Drive a Low-carbon Energy Transition - Dr. Farah Hariri (NVIDIA): video
Session 5: AI Meets Nuclear Fusion - Prof. Diogo R. Ferreira (University of Lisbon): video
Session 6: AI in Astrophysics - Prof. Brant Robertson (University of California, Santa Cruz): video
March 4, 2021
GPU Technology Conference 2021
NVAITC Finland (NVIDIA AI Technology Center), in collaboration with CSC and FCAI, invites you to attend GTC’21 (GPU Technology Conference), starting April 12 with NVIDIA CEO’s keynote at 18:30 Finland time. GTC is free to attend online and you can register here. There will be 1000+ interactive sessions and recorded presentations, ranging from very technical developer and researcher-focused talks to business and implementation-focused talks, on a variety of accelerated-computing topics: Artificial Intelligence, Data Science, GPU Programing, Graphics, High-Performance Computing, etc. In addition to the sessions, NVIDIA is offering hands-on technical training in both introductory as well as advanced AI and accelerated computing, through its Deep Learning Institute.
February 5, 2021
NVAITC Webinar series on AI Applications in Computational Sciences
NVIDIA AI Technology Center Finland in collaboration with FCAI and CSC are pleased to announce a webinar series focusing on AI applications in computational sciences, with a goal of bringing together AI researchers and researchers in other fields. Each webinar will highlight a different scientific field and they are given by domain-specific experts who are using AI as part of their numerical simulation workflows. The webinars will be running from the beginning of March approximately every three weeks as part of the AI Across Fields Forum. Confirmed topics include AI in Atmospheric Science, AI in Computational Fluid Dynamics and AI in Material Science. There is no registration and Zoom details will be included in separate session announcements.
Session 1: AI in Atmospheric Science →
Session 2: AI in Computational Fluid Dynamics →
Session 3: AI in Materials Science →
Session 4: AI to Drive a Low-carbon Energy Transition →
Session 5: AI Meets Nuclear Fusion →
Session 6: AI in Astrophysics →
December 1, 2020
Materials of the AI webinar series available
Higher-quality recordings of the AI Webinar Series given in September 2020 are now available on YouTube (NVIDIA Developer) and its associated codebase on Github (NVIDIA).
September 28, 2020
Optimising differentially private learning for GPUs
Niki Loppi (NVAITC) and Lukas Prediger (Aalto/FCAI) presented their work on optimising differentially private learning for GPUs at FCAI’s Machine Learning Coffee Seminar series. The presentation showcased the first collaborative project that was conducted under the NVAITC Finland. Differential privacy provides a strong theoretical foundation for machine learning algorithms that guarantee that the result cannot be used to violate the privacy of the data subjects. FCAI researchers have successfully applied differential privacy to a range of tasks, including data anonymisation using generative models. The algorithmic basis for this research is the differentially private version of stochastic gradient optimisation. An initial implementation of this algorithm was found to suffer from unexpectedly poor performance relative to standard learning. By correctly harnessing GPU-acceleration and introducing a new GPU-optimised random permutation generator, we were able to deliver significant performance improvements to the original implementation.
September 17, 2020
Webinar Series on Deep Learning
NVAITC is starting a weekly webinar series to explore the fundamentals of deep learning by building and training neural networks, optimizing data loading and performance through mixed precision arithmetic and parallelization across several GPUs.
May 25, 2020
Safe at the Finnish Line: Privacy Project Kicks Off Collaboration
GPUs accelerate privacy algorithm 100x in first project with researchers in Finland.
May 25, 2020
Finnish Center for Artificial Intelligence and NVIDIA to establish a joint NVIDIA AI Technology Center
FCAI and NVIDIA’s joint NVIDIA AI Technology Center (NVAITC) will accelerate AI research, education and adoption in Finland. Thanks to the new collaboration, researchers will be better equipped to develop computationally demanding artificial intelligence applications for research and industry use.
Contact information
NVAITC Technical Committee
Heikki Ailisto, FCAI/VTT
Keijo Heljanko, FCAI/University of Helsinki
Niki Loppi, NVIDIA
Frédéric Parienté, NVIDIA
Simon See, NVIDIA
Arno Solin, FCAI/Aalto University
Aleksi Kallio, CSC
If you have questions about NVAITC, please contact the respective contact person of your institution.