Frequently asked questions and resources
Please click on the questions to see the corresponding answers
Am I proprietary of my data and results in Constellab?
Yes, according to our terms of use, as stated in the Gencovery website (https://gencovery.com), all Constellab users retain exclusive ownership of their pipelines and results.
Where are my data located in the cloud?
By default, the data within Constellab is stored in Europe. However, users have complete control over the geographic location of their data. Additionally, users can choose their preferred cloud infrastructure provider, such as OVHcloud or Azure, for storing their data.
Are my data secured enough in the cloud?
Yes, data within Constellab is hosted on highly secure cloud infrastructures, ensuring the utmost protection and privacy. Furthermore, as an added measure of data safety, daily replication is performed to ensure high recovery and resiliency in case of any unforeseen incidents.
Are my workspaces isolated from the others?
At Gencovery, we strictly enforce data isolation between workspaces. This means that there is no possibility for communication or interaction between different workspaces. Each workspace is fully isolated to maintain the utmost confidentiality and security of the data within it.
Where may I find help to use Constellab?
For comprehensive documentation and helpful tips on Constellab™, we invite you to visit the official Constellab™ Community website at https://constellab.community. This platform serves as a valuable resource, providing users with access to a wealth of information and guidance to enhance their experience with Constellab™.
What is Constellab for Education Program?
Gencovery initiated "Constellab for Education", a program aiming at promoting the education of AI and data science among students, schools, and universities. We encourage you to get in touch with us to explore the opportunities available to receive credits for learning and utilizing AI and data science through Constellab.
Why education is so important in the democratization of Artifical Intelligence?
Data plays a central role in various sectors of our society. With the rise of generative AI, everyone is affected. However, only a limited number of people truly understand what AI is and how to effectively utilize it. We believe it is essential to foster the development of open technologies to democratically promote the learning and application of AI. By doing so, we can empower individuals to create innovative services, while also working towards reducing social inequalities worldwide.
What is artificial intelligence?
Artificial Intelligence (AI) refers to the field of computer science and technology that focuses on creating intelligent machines capable of performing tasks that typically require human intelligence. AI systems are designed to mimic human cognitive abilities, such as learning, reasoning, problem-solving, perception, and decision-making. AI encompasses a broad range of techniques and approaches, including machine learning, natural language processing, computer vision, expert systems, and robotics. Machine learning, in particular, is a subset of AI that enables systems to learn from data and improve their performance over time without explicit programming. This allows AI systems to adapt and make predictions or decisions based on patterns and insights derived from large datasets. AI technology is used in various domains, such as healthcare, biotechnology, finance, transportation, manufacturing, and many others. It has the potential to revolutionize industries, automate repetitive tasks, enhance decision-making processes, and drive innovation. However, ethical considerations, including fairness, transparency, and accountability, are crucial when developing and deploying AI systems to ensure their responsible and beneficial use.
What is generative artificial intelligence?
Generative Artificial Intelligence (Generative AI) refers to a branch of artificial intelligence focused on creating or generating new and original content. It involves the development of algorithms and models that have the ability to generate realistic and meaningful outputs, such as images, text, music, or even video, that resemble human-created content. For instance, Chat-GPT (Generative Pre-trained Transformer) is a famous conversational AI based on generative AI.
What is conversational artificial intelligence?
Conversational artificial intelligence (AI) is a field of Generative AI. It refers to technologies, like chatbots or virtual agents, which users can talk to. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages. Chat-GPT (Generative Pre-trained Transformer) is a famous conversational AI.
Who are the major leaders in conversational AI?
In the field of conversational AI, several organizations and researchers have made significant contributions and are considered leaders in the field. While the landscape continues to evolve rapidly, some of the notable leaders and institutions in conversational AI include: Microsoft-OpenAI alliance: OpenAI is a research organization focusing on artificial general intelligence. They have developed influential models such as GPT (Generative Pre-trained Transformer) and GAN (Generative Adversarial Network). Microsoft, through OpenAI is integrating OpenAI's models into its business and consumer products (GitHub, Office, Bing). Google Brain: Google Brain is Google's AI research team that has made significant contributions to Generative AI. Google has developed Bard, which is a conversational AI service. It is meant to function similarly to ChatGPT, with the biggest difference being that Google's service will pull its information from the web. Meta: The AI research division of Meta conducted research in various areas, including Generative AI, and have made contributions to models like LLaMA (Large Language Model Meta AI). Meta positioned LLaMA as a "responsible" alternative to the advanced AI chatbots from the Microsoft-OpenAI alliance and Google's Bard.
How does Constellab takes energy and ecological transition into account?
Constellab™ strategically incorporates innovative solutions to mitigate the energy impact of cloud computing, aligning with the principles of green computing. Differentiating ourselves from existing compute infrastructures, we have developed a unique capability to optimize the initiation of cloud server shutdowns based on real-time compute load analysis. Our observation reveals that local computing infrastructures are utilized for less than three months annually. With this insight, we firmly believe that the cloud presents an efficient solution for consolidating green computing practices. We are thus committed to democratizing green computing practices by offering accessible solutions, empowering businesses that do not have the means or expertise to proactively address these environmental considerations. Constellab™ is dedicated to pioneering innovation in the industry, driving a paradigm shift towards a greener future. Leveraging the inherent scalability and efficiency of the cloud, we provide comprehensive services that facilitate the widespread adoption of eco-friendly practices. Together, we can pool green computing resources effectively and foster sustainable practices across diverse sectors, contributing to a more environmentally conscious computing ecosystem.