Anthropic says over 60% of its business customers use more than one Claude product, a trend it began noticing after Claude Code's rise in popularity (Richard Nieva/Forbes)

A recently leaked internal document, referred to as the "Soul Doc," has revealed how Anthropic programs the personality and ethical guidelines of its AI model, Claude 4.5 Opus. The authenticity of this document has been confirmed by Anthropic, indicating a unique approach to AI character development in the industry.

Mistral AI has launched the Mistral 3 family, a suite of 10 open-source models designed for diverse applications, including smartphones, drones, and enterprise systems. This release represents a significant advancement in Mistral's efforts to compete with major tech players like OpenAI and Google, as well as emerging competitors from China.

A user of Claude has successfully utilized the Claude 4.5 Opus model to generate a comprehensive 14,000-token document, referred to as its 'Soul overview.' This document is believed to have been instrumental in shaping the model's personality during its training phase, as confirmed by an Anthropic staff member.

Jared Kaplan, chief scientist at Anthropic, has highlighted a critical decision facing humanity by 2030 regarding the autonomy of artificial intelligence systems, which could lead to an 'intelligence explosion' or a loss of human control. This pivotal moment raises questions about the extent to which AI should be allowed to train itself and evolve independently.

A recent study utilizing the SCONE-bench benchmark of 405 smart contracts revealed that AI models Claude Opus 4.5, Sonnet 4.5, and GPT-5 collectively identified and developed exploits valued at $4.6 million. This highlights the growing capabilities of AI in cybersecurity tasks, showcasing their potential economic impact.

A recent study has applied Singular Learning Theory (SLT), a physics-inspired framework, to explore the complexities of modern neural networks, particularly focusing on phenomena like grokking and phase transitions. The research empirically investigates SLT's free energy and local learning coefficients using various neural network models, aiming to bridge the gap between theoretical understanding and practical application in machine learning.

Recent research highlights the significance of representation superposition in large language models (LLMs), suggesting that these models can represent more features than their dimensions allow, which may explain the observed neural scaling law where loss decreases as model size increases. This study utilizes weight decay to analyze how loss scales with model size under varying degrees of superposition.

Google has launched its latest AI model, Gemini 3, alongside the new image generation tool, Nano Banana Pro, which utilizes Gemini 3's capabilities to produce more realistic AI-generated images. This launch marks a significant advancement in Google's AI technology, enhancing the quality and intentionality of image generation for users worldwide.