The gap between what Anthropic uses internally and what gets released publicly is something every AI lab has. Mythos just made that gap visible and documented it in 244 pages.
RESEARCH
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Equitable AI Transition Playbook Released at India AI Summit
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The Equitable AI Transition Playbook, developed in partnership with the International Labour Organisation, was released at the #IndiaAIImpactSummit2026, alongside the Voluntary Guiding Principles for Reskilling in the Age of AI, endorsed by 23 countries. Preparing the global
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AI Safety Concerns Block Broad Deployment Despite Strong Performance
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93.9% SWE-bench and a 27-year-old OpenBSD bug found autonomously and the decision was still not to ship broadly. That's a data point about how seriously the internal assessment of the risks was taken.
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Model Capacity and Data Memorization Risk in AI Systems
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Pero a mayor capacidad del modelo más riesgo de memorización.
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Volunteer needed for AI safety testing and vibe checks
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i volunteer to vibe check all of the super dangerous models on normal tasks @AnthropicAI @OpenAI put me in the game!
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Benchmarking AI Models: Balancing Accuracy with Cost Efficiency
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Aquí siempre en el equipo de Noam, ojalá más y más benchmarks se reportarán cruzando accuracy con coste!
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Anthropic Model Card: Evaluation Overfitting Risks Assessment
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2) Tal y como reportan en el propio Model Card hay riesgo de que estas evaluaciones hayan sido vistas por el modelo durante el pre-entrenamiento (a.k.a overfitting) y eso desvirtúa la interpretación de las métricas. Trabajo honesto el de Anthropic en la Model Card en muchos de
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Power as Status Symbol: The AI Model Release Dilemma
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the new status symbol is making a model so powerful you can’t release it
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Mythos Model Evaluation: Why Single Benchmark Reporting Matters
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Respecto a Mythos me han preguntado por qué en el vídeo de Youtube no he hecho mención a esta gráfica que todos estas comentando, y hay un par de motivos por el que descarté hablar de ello tras leer la Model Card. 1) Reportar la eficiencia de un modelo sobre un único benchmark
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The AI Timeline: Artificial Intelligence and Machine Learning Evolution
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The #AI Timeline by @Python_Dv #ArtificialIntelligence #MachineLearning #ML #Technology
→ View original post on X — @ronald_vanloon, 2026-04-09 12:18 UTC