Recent benchmarks show AI can automate most engineering tasks in AI R&D, leaving research as the remaining challenge, with implications for future innovation.
The Latest
Engineering Is Automated. Research Is the Residual.
Software engineering. The canonical case.
Recent data shows a 40% drop in junior developer hiring since 2022, with seniors increasingly augmented by AI, revealing a bifurcated labor market in software engineering.
OpenEuroLLM. The third path.
OpenEuroLLM, a major EU-funded project, aims to develop multilingual open-source LLMs. Despite progress, compute limitations remain a key challenge.
The Coding Singularity Is Real — and Steeper Than Clark Presented
New data confirms rapid AI progress in coding, indicating the coding singularity is unfolding faster than previously estimated, with broad implications for software development.
Mistral. The fourth path.
Mistral, a venture-funded European AI firm, has achieved significant commercial success with $400M ARR and key enterprise clients, challenging traditional institutional models.
Minerva. The opposite path.
Italy’s Minerva project trained from scratch on 2.5 trillion tokens but scored only 4.9% on Italian academic tests, challenging assumptions about scale and language-specific AI.
The Forecast Is the Plan.
Major AI labs publicly commit to automating AI R&D by 2026, signaling a shift from aspiration to strategic execution with significant implications for the industry.
AMÁLIA · The Three Hard Questions.
Portugal’s €5.5M AMÁLIA model is operational, outperforming some benchmarks, but key structural questions remain unanswered, raising policy and research concerns.
The Atlas. What the framework is.
An overview of the Post-Labor Transition Atlas, an empirical framework analyzing AI-driven labor displacement, policy responses, and structural alternatives as of 2026.
Fair-value appraisals for used GPUs and AI hardware
New approach proposes manual fair-value appraisals for used GPUs and AI hardware to improve resale pricing accuracy in secondary markets.