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Sentient AS
Spangereid, Norway
A
1-10 Employees
2018
Key takeaway
Sentient is a company with specialized expertise in artificial intelligence and big data, focusing on the enterprise market. They emphasize their ability to solve significant challenges through deep learning.
Reference
Core business
Sentient – Deep learning
Trollhetta AS
Trondheim, Norway
A
1-10 Employees
2001
Key takeaway
Trollhetta offers advanced development tools and solutions that incorporate Deep Learning applications, specifically through new modules added to their DynamicImager product. Their expertise in artificial intelligence and image analysis positions them to address significant industry challenges effectively.
Reference
Core business
Trollhetta AS » New Deep Learning modules added to DynamicImager.
Epigram AI
Oslo, Norway
A
1-10 Employees
2017
Key takeaway
The company offers a platform that enables scientists and domain experts to perform fast and precise image analysis, allowing them to build and operate advanced machine learning models without needing extensive expertise.
Reference
Core business
HOME | Epigram
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Data Respons
Høvik verk, Norway
A
11-50 Employees
1994
Key takeaway
Data Respons specializes in AI, analytics, and data science, utilizing these technologies to collect, analyze, and interpret data, which enables clients to make better real-time decisions. Their expertise in software development and advanced embedded systems positions them as a key partner in digital transitions across various industries.
Reference
Service
AI, Analytics & Data Science | Data Respons
By using AI and data science to collect, analyse and interpret we can help you turn data into better decisions in real-time.
Datalounges AS
Aurskog-Høland, Norway
A
1-10 Employees
2017
Key takeaway
Datalounges is a cloud-native platform company that provides holistic container services, enabling organizations to securely and compliantly manage their applications. With a focus on agility and infrastructure maintenance, Datalounges helps businesses adapt to the digital landscape effectively.
Reference
Core business
Datalounges - The container operations company, an infrastructure expert
Datalounges, an infrastructure expert with best practices to consume considering automation, continuity, reliable operations and visibility.
StellAi
Oslo, Norway
A
1-10 Employees
2022
Key takeaway
The company, Stellai, emphasizes its expertise in AI and tech innovation, highlighting a multidisciplinary team that develops efficient and sustainable solutions. Their commitment to continuous improvement and advanced models suggests a strong foundation in technologies like deep learning.
Reference
Product
Products – stell.ai
CAIR Centre for Artificial Intelligence Research
Grimstad, Norway
A
11-50 Employees
2017
Key takeaway
The company is actively advancing the integration of AI and deep learning techniques, particularly in the realm of remote sensing and data analysis. Their research group focuses on innovative approaches like the Tsetlin Machine, which enhances interpretability and reduces computational demands in AI applications, aligning with the transformative potential of deep learning in understanding and reasoning with data.
Reference
Core business
CAIR - Center for Artificial Intelligence Research
Cloud Explorers
Oslo, Norway
A
1-10 Employees
2011
Key takeaway
Cloud Explorers has developed an advanced Cloud-based Mobile and Big Data platform, indicating their capability to implement cutting-edge technology solutions across various industries. Their focus on harnessing significant technical and social shifts aligns with the evolving landscape of deep learning and data analytics.
Reference
Product
Cloud Explorers | Touching is believing
Home Project.Tech
Oslo, Norway
A
51-100 Employees
-
Key takeaway
HomeProject specializes in making Nordic languages accessible for AI training and applications, providing data collection and annotation services that are crucial for deep learning development. Their expertise in linguistics and commitment to quality ensures that they deliver both off-the-shelf and customized datasets for progressive companies in the AI space.
Reference
Service
Human & AI Transcription, Data Annotation, Speech Services| HomeProject
HomeProject offers localization and language services for. We provide expert human and AI transcription, segmentation, data collection, data annotation, synthetic data, search & content relevance, speech services, image & location recognition and more.
Deep Insight
Oslo, Norway
A
11-50 Employees
2017
Key takeaway
Deepinsight is focused on utilizing vast amounts of underused health data to derive valuable insights, addressing significant challenges in the healthcare sector. They collaborate closely with clients and partners to develop mathematical and programming solutions that extract value from this data.
Reference
Core business
Deepinsight - Making an Impact with Data | Deepinsight
DeepInsight enjoy working on hard problems that are important to you, and important to society.
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A selection of suitable use cases for products or services provided by verified companies according to your search.
Use case
EU-AI Act
All industries, Pharma, Finance, E-Mobility, Healthcare
er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.
Use case
EU-AI Act
All industries, Pharma, Finance, E-Mobility, Healthcare
er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.
When exploring the Deep Learning industry in Norway, several key considerations are essential. The country boasts a robust technological infrastructure and a strong emphasis on research and development, particularly in artificial intelligence and machine learning. Norway's commitment to sustainability and environmental concerns influences the application of deep learning technologies, promoting eco-friendly solutions in various sectors. Regulations surrounding data protection, such as the General Data Protection Regulation (GDPR), are critical to consider, as they impact how companies manage and utilize data for training deep learning models. Challenges in the industry include a relatively small talent pool and competition for skilled professionals, leading to a need for companies to invest in training and development. Opportunities abound in industries like healthcare, energy, and maritime, where deep learning can optimize processes and enhance decision-making. The competitive landscape features both established firms and startups, creating a dynamic environment for innovation. Additionally, Norway's strategic position in the European market provides companies with access to a broader audience. Overall, understanding these factors is crucial for anyone interested in entering or collaborating within the deep learning sector in Norway.
Some interesting numbers and facts about your company results for Deep Learning
| Country with most fitting companies | Norway |
| Amount of fitting manufacturers | 38 |
| Amount of suitable service providers | 26 |
| Average amount of employees | 1-10 |
| Oldest suiting company | 1994 |
| Youngest suiting company | 2022 |
Some interesting questions that has been asked about the results you have just received for Deep Learning
What are related technologies to Deep Learning?
Based on our calculations related technologies to Deep Learning are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Who are Start-Ups in the field of Deep Learning?
Start-Ups who are working in Deep Learning are StellAi
Which industries are mostly working on Deep Learning?
The most represented industries which are working in Deep Learning are IT, Software and Services, Other, Education, Automation, Consulting
How does ensun find these Deep Learning Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.