Future Computer Systems and Networking Research in the Netherlands: A
Manifesto
- URL: http://arxiv.org/abs/2206.03259v1
- Date: Thu, 26 May 2022 11:02:29 GMT
- Title: Future Computer Systems and Networking Research in the Netherlands: A
Manifesto
- Authors: Alexandru Iosup (VU University Amsterdam), Fernando Kuipers (Delft
University of Technology), Ana Lucia Varbanescu (University of Twente), Paola
Grosso (University of Amsterdam), Animesh Trivedi (VU University Amsterdam),
Jan Rellermeyer (Delft University of Technology), Lin Wang (VU University
Amsterdam), Alexandru Uta (University of Leiden), Francesco Regazzoni
(University of Amsterdam)
- Abstract summary: We draw attention to CompSys as a vital part of ICT.
Each of the Top Sectors of the Dutch Economy, each route in the National Research Agenda, and each of the UN Sustainable Development Goals pose challenges that cannot be addressed without CompSys advances.
- Score: 137.47124933818066
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Our modern society and competitive economy depend on a strong digital
foundation and, in turn, on sustained research and innovation in computer
systems and networks (CompSys). With this manifesto, we draw attention to
CompSys as a vital part of ICT. Among ICT technologies, CompSys covers all the
hardware and all the operational software layers that enable applications; only
application-specific details, and often only application-specific algorithms,
are not part of CompSys. Each of the Top Sectors of the Dutch Economy, each
route in the National Research Agenda, and each of the UN Sustainable
Development Goals pose challenges that cannot be addressed without
groundbreaking CompSys advances. Looking at the 2030-2035 horizon, important
new applications will emerge only when enabled by CompSys developments.
Triggered by the COVID-19 pandemic, millions moved abruptly online, raising
infrastructure scalability and data sovereignty issues; but governments
processing social data and responsible social networks still require a paradigm
shift in data sovereignty and sharing. AI already requires massive computer
systems which can cost millions per training task, but the current technology
leaves an unsustainable energy footprint including large carbon emissions.
Computational sciences such as bioinformatics, and "Humanities for all" and
"citizen data science", cannot become affordable and efficient until computer
systems take a generational leap. Similarly, the emerging quantum internet
depends on (traditional) CompSys to bootstrap operation for the foreseeable
future. Large commercial sectors, including finance and manufacturing, require
specialized computing and networking or risk becoming uncompetitive. And, at
the core of Dutch innovation, promising technology hubs, deltas, ports, and
smart cities, could see their promise stagger due to critical dependency on
non-European technology.
Related papers
- Reducing the Barriers to Entry for Foundation Model Training [0.28756346738878485]
The world has recently witnessed an unprecedented acceleration in demands for Machine Learning and Artificial Intelligence applications.
This spike in demand has imposed tremendous strain on the underlying technology stack in supply chain.
We propose a fundamental change in the AI training infrastructure throughout the technology ecosystem.
arXiv Detail & Related papers (2024-04-12T20:58:25Z) - Social Intelligence Data Infrastructure: Structuring the Present and Navigating the Future [59.78608958395464]
We build a Social AI Data Infrastructure, which consists of a comprehensive social AI taxonomy and a data library of 480 NLP datasets.
Our infrastructure allows us to analyze existing dataset efforts, and also evaluate language models' performance in different social intelligence aspects.
We show there is a need for multifaceted datasets, increased diversity in language and culture, more long-tailed social situations, and more interactive data in future social intelligence data efforts.
arXiv Detail & Related papers (2024-02-28T00:22:42Z) - Multi-Tier Computing-Enabled Digital Twin in 6G Networks [50.236861239246835]
In Industry 4.0, industries such as manufacturing, automotive, and healthcare are rapidly adopting DT-based development.
The main challenges to date have been the high demands on communication and computing resources, as well as privacy and security concerns.
To achieve low latency and high security services in the emerging DT, multi-tier computing has been proposed by combining edge/fog computing and cloud computing.
arXiv Detail & Related papers (2023-12-28T13:02:53Z) - On the Opportunities of Green Computing: A Survey [80.21955522431168]
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades.
The needs for high computing power brings higher carbon emission and undermines research fairness.
To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
arXiv Detail & Related papers (2023-11-01T11:16:41Z) - Are machine learning technologies ready to be used for humanitarian work
and development? [2.156882891331917]
Digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development.
We argue that new technologies risk at best falling short of promised goals, at worst they can increase inequality, amplify discrimination, and infringe upon human rights.
arXiv Detail & Related papers (2023-07-04T19:32:35Z) - Naeural AI OS -- Decentralized ubiquitous computing MLOps execution engine [0.0]
We present an innovative approach for low-code development and deployment of end-to-end AI cooperative application pipelines.
We address infrastructure allocation, costs, and secure job distribution in a fully decentralized global cooperative community based on tokenized economics.
arXiv Detail & Related papers (2023-06-14T19:20:43Z) - Coordinated Science Laboratory 70th Anniversary Symposium: The Future of
Computing [80.72844751804166]
In 2021, the Coordinated Science Laboratory CSL hosted the Future of Computing Symposium to celebrate its 70th anniversary.
We summarize the major technological points, insights, and directions that speakers brought forward during the symposium.
Participants discussed topics related to new computing paradigms, technologies, algorithms, behaviors, and research challenges to be expected in the future.
arXiv Detail & Related papers (2022-10-04T17:32:27Z) - Physical Computing for Materials Acceleration Platforms [81.09376948478891]
We argue that the same simulation and AI tools that will accelerate the search for new materials, as part of the MAPs research program, also make possible the design of fundamentally new computing mediums.
We outline a simulation-based MAP program to design computers that use physics itself to solve optimization problems.
We expect to introduce a new era of innovative collaboration between materials researchers and computer scientists.
arXiv Detail & Related papers (2022-08-17T23:03:54Z) - Artificial Intelligence at the Edge [25.451110446336276]
5G mobile communication networks increase communication capacity, reduce transmission latency and error, and save energy.
The envisioned future 6G technology will integrate many more technologies, including for example visible light communication.
Many applications require computations and analytics close to application end-points: that is, at the edge of the network, rather than in a centralized cloud.
arXiv Detail & Related papers (2020-12-10T02:08:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.