• Liability for failing AI: the revised PLDHow the revised Product Liability Directive (PLD) and the AI Act fundamentally change the burden of proof for damage caused by failing AI systems.
• Agentic AI: The Shift to Autonomous AI Systems | LLMNet NewsDiscover what Agentic AI entails, why autonomous AI agents are emerging now, and what the main opportunities and risks are for modern organizations.
• The AI Act in practice: what companies must do in 2026Practical guide to the European AI Act in 2026. Read which obligations, risk classifications, and compliance steps now apply to organizations.
• AI Act timeline: what took effect in 2026The AI Act: what actually came into force in 2026 and what was postponed by the Digital Omnibus? A factual review, verified on 2026-08-07.
• AI assistants in the browser: the impact on browsingHow are AI assistants in browsers and extensions changing our browsing behavior? Read all about the impact on search traffic, publishers, and the associated…
• AI at Dutch municipalities: from pilot to practiceHow Dutch municipalities are deploying AI and language models for service delivery, including GDPR requirements, the algorithm register, and the EU AI Act.
• AI and Copyright: Frameworks, Opportunities, and Pitfalls inWhat is the status of copyright and AI in the EU? Everything about the text and data mining exception, opt-outs, rights to output, and contractual agreements.
• The Impact of AI on the Creative SectorHow image, music, and video generation are transforming the creative sector. An in-depth analysis of the opportunities, the copyright debate, and new…
• AI and Cybersecurity: The Digital Arms Race of the 21stHow attackers and defenders deploy artificial intelligence. An in-depth look at AI-driven phishing, deepfakes, detection systems, and the impact on the…
• AI and energy: why computing power and power consumptionThe impact of AI on our energy consumption is growing rapidly. Discover why AI models require so much power, the latest efficiency trends, and the future of…
• AI in Libraries and Archives: ConsiderationsAn in-depth analysis of deploying artificial intelligence in public libraries and archives, opportunities, and strategic decisions.
• Digital sovereignty in Europe and dependence on AI - llmnet.nlAn in-depth analysis of digital sovereignty and AI dependence in Europe. Explore the AI stack, legal risks, and strategic choices.
• AI and work: which tasks are changing the fastest?Discover which tasks are changing and automating the fastest due to artificial intelligence, which remain human, and what this means for the labor market.
• AI in the Dutch financial sector: opportunities and requirementsHow financial institutions are deploying AI within existing frameworks of model governance, explainability, outsourcing risk, and supervision.
• AI Language Models in Dutch HealthcareA comprehensive and factual analysis of the deployment of AI language models in Dutch healthcare, focusing on reporting, MDR, AI regulation, and privacy.
• AI in education: how schools and universities are using itHow primary education, vocational education (mbo), universities of applied sciences (hbo), and universities are using AI in 2026: from adaptive learning and assessment to privacy, AI Act requirements, and infrastructure.
• AI in education: opportunities and concerns — LLMNet NewsDiscover the impact of artificial intelligence in education. A balanced look at personalized learning, academic integrity, and the redefined role of the…
• AI in industry and manufacturing companies: digitalization | LLMnetAnalysis of AI applications in Dutch manufacturing industry: from predictive maintenance to vision systems, OT integration, and the EU AI Act.
• AI in the Dutch government - state of playHow is the Dutch government using AI as a user and buyer? Read all about transparency, the algorithm register, procurement and societal safeguards.
• AI in the Dutch judiciary: use and limitsDiscover how AI is used in the Dutch judiciary, what legal boundaries apply, and what the trade-offs are for judges and hearings.
• AI standards and ISO norms: what they do and do not doA factual analysis of AI standards and norms. Discover what process standards regulate, how harmonized standards work and what certification means.
• AI Supervision in the NetherlandsDiscover how AI supervision in the Netherlands is organized under the European AI Act. What role do the AP, RDI, and ACM play? Read the full analysis.
• AI for SME services: the practice of small firmsDiscover how small offices and SME service providers use AI for case processing, client contact, and quotes without getting lost in high costs.
• AI legislation outside the EU: an overviewSee how the US, the UK, China and other countries regulate AI outside the EU. Discover the differences in approach and what this means for organizations.
• The race for AI chips and computing powerWhy are AI chips so scarce and expensive? Read all about the GPU race, geopolitical tensions, ASML, Big Tech alternatives, and the impact on the Netherlands.
• Consolidation among AI start-ups: acquisitions and closuresAn analysis of the consolidation phase among AI startups: acquisition structures, margin pressure per stack layer, contract risks, and spreading business risk.
• Context caching: smart storage halves token costsDiscover how context caching works with LLM APIs, why KV caches structurally lower input costs, and how latency and architecture improve as a result.
• Data poisoning in LLM fine-tuningData poisoning is a structural risk in fine-tuning LLMs. Read how manipulation of training data works, how it can be detected, and how to prevent it.
• Datacenters and AI in the NetherlandsAn in-depth analysis of the debate on AI datacenters in the Netherlands: from power consumption and grid congestion to the call for European digital autonomy.
• Data Diversification: Training on Non-English SourcesHow multilingual data diversification improves language models and its impact on tokenizer efficiency, reasoning, and cultural representation.
• NPU chips in the workplace: local AI computing powerNPU chips move AI tasks from the data center to laptops. Read about architectures, power consumption, memory bandwidth, and practical deployability.
• Decentralized Compute Networks for AI Inference ExplainedDecentralized compute networks distribute AI inference across dispersed machines instead of hyperscale data centers. Mechanics, rise, and limits.
• Deepfakes and disinformation: the downside of generative AIDiscover how deepfakes and generative AI fuel disinformation. Read about the technology, risks, detection, and legislation in this in-depth background…
• Direct Preference Optimization: beyond classical RLHFDirect Preference Optimization (DPO) replaces complex RLHF pipelines. Discover the mathematics, stability gains, and practical trade-offs in LLM training.
• Energy and AI: the state of Dutch data centersAn in-depth analysis of the impact of AI on Dutch data centers, grid congestion, energy consumption, and the national infrastructure in 2026.
• Energy use of AI data centers: reading the figuresA thorough analysis of energy figures for AI data centers. Read how PUE, GPU consumption, cooling and grid congestion are measured.
• The EU AI Act at a glance: what changes for creators andA clear explanation of the European AI Act. Learn about the four risk categories, transparency requirements, and the timeline for creators and users of AI.
• 15 free Google AI tools you can use right now | LLMNet NewsGoogle gives away a surprising amount of AI tooling for free: from NotebookLM and AI Studio to Jules and Flow.
• The algorithm register examined: what public bodies report1,530 algorithms from 336 organizations, over 60 percent municipalities, 41 high-risk systems: a repeatable measurement of the register, checked on 2026-08-07.
• The algorithm register examined: what governments reportA thorough analysis of the Dutch Algorithm Register in 2026: what governments register, where the blind spots lie, and how oversight works.
• AI and language models in Dutch greenhouse horticultureHow computer vision, local language models, and autonomous agents are transforming Dutch greenhouse horticulture: from climate control to harvest robotics.
• How Mixture of Experts lowers LLM production costsHow mixture of experts (MoE) lowers the compute and inference costs of LLMs in production without giving up model capacity.
• The rise of small language models (SLMs)Discover why small language models (SLMs) are on the rise. Read about the benefits in terms of efficiency, on-device processing, cost, and privacy.
• Open-weights vs truly open sourceDiscover the crucial difference between open-weights and truly open source AI models. Learn about licensing, user freedoms, and why this debate matters.
• Model weights leaks: the legal status of stolen AIWhat is the legal status of leaked or stolen model weights? Analysis of copyright, trade secrets, unauthorized computer access, and enforcement.
• Why Multimodal Models Are the Next Step | AI News & ResearchAn in-depth look at multimodal AI models: how the simultaneous processing of text, image, and audio enables unprecedented new applications and efficiency.
• Dutch AI Funding: Who Pays for InnovationWho funds Dutch AI innovation? An analysis of public subsidies, venture capital, ROMs, and compute costs for startups and scale-ups in 2026.
• Dutch AI in figures: public sources and dataDiscover how to read and interpret public figures from CBS, DNB and central government ICT on Dutch AI adoption and infrastructure critically.
• Dutch language evaluation: comparing models on Dutch tasksEvaluation of Dutch-language models: DUMB, EuroEval, BEIR-NL, and SQuAD-NL with source and verification date. Verified on 2026-08-07.
• Grid congestion and AI data centers: the state of the queueHow large is the electricity queue and what place do AI data centers occupy in it? Figures from grid operators and the ACM framework, checked on 2026-08-07.
• Open datasets for training language models | AI newsAn analysis of open data collections for language models, the importance of provenance, the challenges of filtering and the specific position of Dutch.
• Open models one year later: licensing since Llama 3What has changed since Llama 3? From community licenses to MIT and Apache 2.0, and what the AI Act exempts. Verified on 2026-08-07.
• The key developments in open-source LLMs | LLMnet.nl NewsDiscover the latest trends in open-source Large Language Models: from efficient small models and on-device AI to key shifts in licensing.
• Market Development: Open Versus Closed Models | llmnet.nlAnalysis of market structure, revenue models, and pricing pressure in open versus closed AI models. Which factors determine the choice for organizations?
• Prompt injection in RAG: the leak in corporate knowledge basesA technical analysis of indirect prompt injection in RAG: how corporate knowledge bases are vulnerable and which architectures protect data.
• Quantization in production: from 16-bit to 4-bit precisionPractical guide to LLM quantization in production. Discover the impact of FP16 to INT4 on VRAM, latency, perplexity, and inference architecture.
• The race for context: why models are getting increasinglyDiscover why AI models are getting increasingly larger context windows, the impact on web applications, and the trade-off between long context and RAG…
• Reasoning Models: The Trend Towards AI That ThinksDiscover how AI reasoning models are raising the bar by thinking step-by-step. Read about the technology, benefits, trade-offs, and practical impact.
• The convergence of AI and roboticsDiscover the impact of embodied AI: how language models bridge the gap between digital intelligence and physical robots in the Dutch industry.
• Speculative decoding: accelerating LLM inferenceDiscover how speculative decoding accelerates LLM inference by combining small draft models with mathematically exact verification, without loss of quality.
• State space models: an alternative to transformers | NewsHow state space models and Mamba offer linear scaling compared with transformers. Read about performance, memory advantages and hybrid architectures.
• Synthetic Data: Why AI Models Are Increasingly Learning fromWhy do AI builders use synthetic data? Discover the benefits (privacy, rare data), the risks like model inbreeding, and the impact on your choice of model.
• Language diversity in LLMs: the position of Dutch | nieuws.llmnet.nlA thorough analysis of language diversity in large language models and the specific position of Dutch in terms of data, tokenization, evaluation and practice.
• Accessibility and AI technology: opportunities and barriersDiscover how AI affects digital accessibility. Learn about the dual role of technology in both lowering and raising barriers.
• Publishers versus AI scrapers: the fight over contentDutch publishers are pushing back against AI scrapers. An analysis of robots.txt, TDM opt-outs, paywalls, and shifting search traffic.
• Why public services choose their own modelsWhy Dutch government agencies and public services are choosing their own open source models, sovereign infrastructure, and local language technology.
• Watermarking in AI Text: How It Works and Its LimitationsAn in-depth analysis of text watermarks in language models: how guided sampling works, what the vulnerabilities are, and how organizations deal with them.
• Web crawling for AI: robots.txt under pressure at publishersWhy the robots.txt protocol no longer suffices against AI scrapers, how publishers are pushing back, and what the legal and technical consequences are in 2026.
• Work and AI: what the labor market figures really showA factual analysis of Dutch and European labour market figures around AI: task shifts, vacancy trends, productivity and regulation in 2026.