Thank God for measurement error, without which all our theories would have to be thrown out.
DATA
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GPT-4.5 Orion Disappoints: Data Scarcity Limits Progress
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The Information about GPT-4.5/5 and more: the tl;dr GPT-4.5 (“Orion”)
Originally developed as Orion and planned as GPT-5.
Performance disappointing: no major leaps forward compared to GPT-4o.
Reasons for failure:
Dwindling supply of high-quality web data for pretraining. -
Persona Vectors Identify Training Data Teaching Bad AI Traits
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Persona vectors can also identify training data that will teach the model bad personality traits. Sometimes, it flags data that we wouldn't otherwise have noticed.
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Ultra-Scale Playbook: Training DeepSeek-V3 with Advanced Parallelism
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The Ultra-Scale Playbook (the large-scale LLM training guide from the @huggingface science team) is out now! It is a 246-page, very nicely designed PDF that walks you through learning how to train your own DeepSeek-V3 model using:
• 5D parallelism, • ZeRO,
• fast kernels, -
AllianceBank Leverages Analytics to Automate Banking Decisions
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@AllianceBankMY uses analytics to automate decisions, reduce credit risk and personalize offers—making banking faster, smarter and more human.💡 Read the full story: https://t.co/Nfve8YD2vx#BankingInnovation #Analytics #CustomerExperience pic.twitter.com/ToiNvgKq9B
— SAS Software (@SASsoftware) 1 août 2025@AllianceBankMY uses analytics to automate decisions, reduce credit risk and personalize offers—making banking faster, smarter and more human. Read the full story: http://
2.sas.com/6015fuJBf #BankingInnovation #Analytics #CustomerExperience -
EU AI Act Requires Transparency, Red-Teaming, and Risk Management
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Mais que fais l'Europe au juste ? L'europe et L’AI Act exige une documentation complète sur la transparence, des résumés des données d'entraînement, des tests de red-teaming, des plans de gestion des risques, des filtres pour les droits d’auteur, et des audits de cybersécurité
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Context Engineering: The New Feature Engineering in GenAI Systems
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Context Engineering is the new Feature Engineering! In modern Agentic / GenAI systems, context engineering is becoming as critical as feature engineering was in the ML era. Providing too much context can cause the model to overfit to specific details, limiting generalizability.
→ View original post on X — @sudalairajkumar, 2025-08-01 03:23 UTC
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O*NET Dataset Reveals Real-World AI Use Patterns and Employment Impact
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It also matches the results from Anthropic's analysis of actual use (though that user base is less broad than Copilot). Turns out O*NET is a very helpful dataset.
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MCP servers security risks: protecting user data from theft
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Right now users are being encouraged to mix and match MCP servers in a way that makes it trivial for people to steal their data – we are unfairly outsourcing decisions on how to stay secure to people who haven't got a fighting chance of staying safe
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Advanced Multimodal AI Model Excels Across Finance Healthcare Manufacturing Energy
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It surpasses other models in its class at understanding and analyzing a wide range of visual and multilingual data across domains like finance, healthcare, manufacturing, and energy.