AI
Frontier models, applied AI, and the industries adopting them.
Edited by Aleksi Virtanen
AI
Agents that charmed investors in staged demos fail in predictable ways once they meet messy data, unreliable tools, and long task horizons. The failure modes are now well documented, and they are rarely about the model.
Martin Anderson · 23 September 2026 · 8 min
AI
Companies spend weeks benchmarking language models against public leaderboards, then deploy them into workflows the benchmarks never measured. The evaluation that matters happens after the contract is signed.
Martin Anderson · 21 September 2026 · 6 min
AI
Large language models advertise fluent global coverage. European enterprises and public bodies discover that performance drops sharply once systems leave English behind.
Aleksi Virtanen · 17 September 2026 · 7 min
AI
Foundation models are increasingly interchangeable. The systems that measure their failures under real constraints have become the only defensible advantage.
Martin Anderson · 16 September 2026 · 6 min
AI
Frontier labs still hold the hardest reasoning work. Everything below that line has quietly migrated to models companies can host themselves.
Martin Anderson · 15 September 2026 · 9 min
AI
Machine learning models are running out of human text and images. Generating artificial data offers a temporary reprieve, but recursive training risks irreversible decay.
Andy Oram · 15 September 2026 · 7 min
AI
Contamination, saturation and selective reporting have made public leaderboards a weak guide to production behaviour. Evaluation researchers are rebuilding around task-specific suites.
Martin Anderson · 14 September 2026 · 8 min
AI
Organizations spend heavily on frontier language models only to find their systems stumble on basic document search. Retrieval architecture, not generative intelligence, remains the critical bottleneck.
Martin Anderson · 14 September 2026 · 7 min
AI
The case for running a two billion parameter model on a laptop or a factory controller has very little to do with saving money, and a great deal to do with latency and control.
Aleksi Virtanen · 13 September 2026 · 6 min
AI
Token prices drop with every model release. Yet enterprise invoices remain stubbornly flat as complexity, context sprawl, and utilization gaps absorb the savings.
Martin Anderson · 13 September 2026 · 6 min
AI
Public supercomputers in Finland, Italy and Spain have given the continent real training capacity. Allocation policy, not silicon, is the constraint that will decide whether European labs benefit.
Martin Anderson · 12 September 2026 · 8 min
AI
Finnish, Norwegian, Danish and Icelandic model quality has improved sharply. The economics of maintaining those models have not improved at all.
Martin Anderson · 9 September 2026 · 7 min
AI
Software teams are deploying autonomous AI agents to run complex workflows. In live production environments, these systems tend to break in predictable, costly ways.
Martin Anderson · 6 September 2026 · 7 min
AI
Obligations for general purpose models and high risk systems are now operational. The practical burden falls on documentation and evaluation, not on model architecture.
AJ Dellinger · 5 September 2026 · 9 min
AI
The continent did not produce a frontier lab. It produced a credible tier of open weight and deployable-on-premise providers, and that is where European enterprise demand actually is.
Martin Anderson · 28 August 2026 · 7 min
AI
Municipal and agency procurement in Denmark, Norway and Finland has quietly produced the clearest set of AI contract terms in use anywhere on the continent.
Andrew Singer · 21 August 2026 · 6 min
AI
Frontier closed models still dominate the reasoning heavy tier. For high volume, latency sensitive, cost sensitive workloads, open weights are now the boring choice.
Martin Anderson · 25 June 2026 · 6 min
AI
The category that was supposed to be automated first has instead absorbed AI as a productivity layer. What that means for the next wave of clinical AI.
Andy Oram · 12 June 2026 · 8 min