Artificial Intelligence

Artificial Intelligence (AI) changes how we work and will redefine the relationship between man and machine. It has incredible growth potential, for both business and personal uses. Info Support, as an innovative solution provider, is working hard to be at the front of AI developments. Therefore research in the domain of Artificial Intelligence is vital and we keep challenging and facilitating our people to do research within this domain.

Research Ambitions

Ambitions are research questions of which the answers will give us the opportunity to determine the future. Are you a master’s student and would you like to significantly contribute to our thought leadership position in the AI domain? Please reach out to Joop Snijder, Head of Research Artificial Intelligence, for more information about how you can help.

Advancing Explainable AI Across Diverse Data Domains

At the Info Support Research Center AI, we aim to pioneer advancements in Explainable AI (XAI) or Transparent AI across various data types, including tabular data, time-series forecasting, computer vision, and more. XAI stands as a beacon of clarity in the often opaque landscape of artificial intelligence, where the inner workings of complex algorithms—traditionally seen as “black boxes”—remain inscrutable even to their creators. Our goal transcends the mere interpretation of AI decisions; we aim to demystify the processes leading to these decisions across various data domains, thereby fostering a deeper trust and understanding among users.

By broadening the scope of XAI to encompass these diverse data types, we are committed to unlocking new levels of transparency and trust in AI technologies. Our research aims to enhance the interpretability of AI models and empower users with the knowledge and confidence to engage with AI systems more effectively.

Green AI: Balancing Performance with Environmental Sustainability

In the rapidly evolving landscape of Artificial Intelligence (AI) and Machine Learning (ML), pursuing excellence in performance and innovation has often overshadowed the critical consideration of environmental sustainability. Green AI emerges as a pivotal research domain, advocating for the development of AI and ML systems that excel in their tasks and do so with minimal environmental impact. This research ambition delves into the multifaceted challenge of designing high-performing, energy-efficient, and environmentally friendly AI models. It addresses the growing concern over the carbon footprint associated with training complex AI models, which consume vast amounts of computational resources and energy in their quest for accuracy and sophistication. The goal of Green AI is not merely to mitigate these environmental impacts but to redefine the paradigms of AI efficiency and effectiveness within sustainable boundaries.

Elevating MLOps and LLMOps for Scalable and Trustworthy AI Solutions

Our ambition in MLOps and LLMOps is to refine and standardize the processes of deploying and maintaining machine learning models in production environments. This includes automating the integration and delivery pipelines, ensuring model quality and performance through continuous testing and monitoring, and facilitating seamless collaboration among data scientists, developers, and IT professionals.

In the domain of LLMOps, we focus on addressing the unique challenges posed by deploying and managing large language models. These models, characterized by their vast size and complexity, require specialized strategies for efficient scaling, updating, and customization. Our research seeks to develop best practices and tools for managing large language models, ensuring they remain accurate, relevant, and aligned with ethical standards over time.

Are you interested in working in this area?

Don’t hesitate to reach out! Contact Joop Snijder, Head of Research Artificial Intelligence. Or apply directly to one of our assignments.

More about Joop Snijder

Joop Snijder is a leading expert in the field of artificial intelligence (AI) and currently serves as the Chief Technology Officer (CTO) at Aigency, an AI expertise label of Info Support. With over 10 years of experience in AI, Joop is a passionate advocate for explainable and interpretable AI, which helps companies leverage the power of this advanced technology to drive innovation and growth.

In addition to his role at Aigency, Joop is a sought-after speaker and the host of the popular AIToday Live podcast. He shares his extensive knowledge of AI with business and IT professionals, explores the latest trends and developments in the world of AI, and provides valuable insights and actionable strategies for his listeners.

Throughout his career, Joop has worked on numerous AI projects, from developing solutions for industry-specific problems to leading large-scale research initiatives.

Artificial Intelligence Publications