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Aleph Alpha. The retrospective case.
Analyzing Aleph Alpha’s strategic pivot, leadership changes, and recent merger with Cohere to understand Europe’s AI development challenges.
Engineering Is Automated. Research Is the Residual.
Recent benchmarks show AI has automated most engineering tasks in AI R&D, leaving research as the remaining challenge. Impacts on innovation and institutions are emerging.
Software engineering. The canonical case.
Recent data shows a 40% drop in junior developer hiring, with senior engineers mostly augmented by AI. The sector reveals a bifurcated impact of AI on jobs.
OpenEuroLLM. The third path.
OpenEuroLLM, a major EU-funded project, aims to develop multilingual large language models through a pan-European consortium, facing significant compute challenges.
The Coding Singularity Is Real — and Steeper Than Clark Presented
New data confirms AI’s coding capabilities have advanced faster, accelerating the recursive loop toward the coding singularity, with deployment still unfolding.
Mistral. The fourth path.
Mistral raises $830M in March 2026, becoming Europe’s strongest commercial AI firm with $400M ARR, but still trails US leaders in reasoning capabilities.
Minerva. The opposite path.
Italy’s Minerva-3B, trained from scratch on 2.5 trillion tokens, scored just 4.9% on Italian exams, raising questions about native-language investment in European AI.
The Forecast Is the Plan.
Major AI labs publicly commit to automating AI research by 2026, signaling a strategic shift towards automated development and potential industry-wide implications.
AMÁLIA · The Three Hard Questions.
Portugal’s €5.5M AMÁLIA LLM faces three key structural questions about openness, native data, and goals, raising concerns for European sovereign AI efforts.
