by Dennis Landman Grootschalige taalmodellen (Large Language Models, LLMs) hebben de afgelopen jaren opmerkelijke resultaten geboekt op het gebied van tekstgeneratie, vraagbeantwoording en logisch redeneren. Modellen zoals GPT-3, PaLM en meer recent Llama-3.1 (met 405 miljard parameters) vertonen nieuwe capaciteiten...
Read moreby Dennis Landman This article examines a six-phase blueprint for enterprise transformation through artificial intelligence (AI), emphasizing the alignment of AI with business strategy, organizational readiness, capability building, implementation, and sustainable scaling. The framework is discussed in the context of...
Read moreExecutive Summary Public sector digital transformation in the Netherlands and Europe is shaped by complex negotiations involving government agencies, regulators, technology vendors, and international partners. The Lewicki & Hiam Negotiation Matrix – which outlines five strategies (competing, collaborating, compromising, avoiding,...
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Discover how the Splunk Data-to-Everything Platform helps the Dutch Court System deliver useful insights, more uptime and faster response times to critical events. — Read on www.splunk.com/en_us/customers/success-stories/de-rechtspraak.html
We often say customers are our best storytellers at Splunk, and it’s certainly the case with our latest EMEA customer case study in the form of the Dutch court system, De Rechtspraak. Hear more from Splunk VP EMEA, Frederik Maris Read more…
by Dennis Landman Reframing AI Failure and Success in Government Artificial intelligence (AI) is increasingly integrated into public sector decision-making, influencing everything from welfare systems to law enforcement. While AI’s failures—especially concerning bias and discrimination—have been widely discussed, Kempeneer, Ranchordás, Read more…
Discover why robust data architecture is the critical foundation for scalable AI solutions, with practical insights from enterprise implementations across industries and a strategic roadmap for success.
By Dennis Hieronder volgt een analyse van het artikel “AI-Powered Lawyering – AI Reasoning Models, Retrieval Augmented Generation, and the Future of Legal Practice”. Deze studie onderzoekt hoe twee nieuwe AI-technologieën – een redeneermodel (o1‑preview) en een RAG‑gebaseerde tool (Vincent Read more…
By Dennis Landman Introduction The landscape of information technology architecture has undergone a profound transformation in recent years. As organizations increasingly pivot toward data-driven strategies and adopt artificial intelligence solutions, the traditional boundaries of IT architecture are expanding at an Read more…
Recent AI advancements from January 2025 are reshaping legal tech with breakthroughs in reasoning, retrieval, research automation, and small-model efficiency. Key research includes improvements in Retrieval-Augmented Generation (RAG) for legal document analysis, System 2 reasoning in LLMs for deeper legal interpretation, AI research assistants for automating legal research, and small AI models excelling in math, making AI more accessible. These innovations signal a shift towards smarter, more efficient AI that can enhance legal research, contract analysis, and decision-making processes, democratizing AI-powered legal tools for firms of all sizes.
The article explores the failures of ontologies in artificial intelligence, citing issues such as fragmentation, lack of interoperability, and poor usability as barriers to effective knowledge representation. It proposes a structured roadmap for sustainable ontology development, emphasizing federated governance and AI-driven adaptability. By integrating real-time decision-making mechanisms, the research aims to transition ontologies from static models to dynamic systems that enhance AI reasoning and utility in various domains.
by Dennis Landman Large Language Models (LLMs) like ChatGPT, Claude, and Gemini are revolutionizing software development. They can refactor code, debug issues, optimize performance, and even architect entire systems. However, the quality of their output depends on the precision of Read more…