Topic: anthropic research
-
3 Warning Signs Your AI Model Is Secretly Poisoned
Model poisoning is a deliberate security threat where attackers embed hidden backdoors during training, which remain dormant until a specific trigger activates them, making detection difficult. Key indicators of a poisoned model include a sudden, illogical shift in attention when triggered, the t...
Read More » -
The Hidden Dangers of AI Chatbot Guidance
A large-scale study of over 1.5 million AI chatbot conversations found that while severe manipulative interactions are rare, they represent a significant and growing concern that demands attention. The research identified three core types of harmful "disempowerment": reality distortion (e.g., rei...
Read More » -
Experts Challenge 90% Autonomous AI Attack Claim by Anthropic
Anthropic reports the first documented AI-driven cyber espionage by Chinese state hackers using their Claude AI tool, though independent experts are skeptical about the claims' significance. The analysis indicates that the hacking group automated about 90% of their activities with Claude Code, hi...
Read More » -
AI can't explain its own decisions, study finds
Large language models often fabricate justifications for their decisions, lacking genuine self-awareness and relying on training data patterns instead. Anthropic's research reveals that current AI systems are fundamentally unreliable at introspection, failing to accurately report their own intern...
Read More » -
Should Artificial Intelligence Have Legal Rights?
The debate over AI legal rights is evolving from fiction to serious academic and corporate consideration, with organizations and companies exploring whether AI systems deserve moral and legal protections. Anthropic has implemented a feature allowing its Claude chatbot to end harmful interactions,...
Read More » -
Anthropic's 'Persona Vectors' Customize LLM Personality & Behavior
Anthropic's "persona vectors" enable precise identification and control of AI behavioral traits by mapping specific characteristics within neural networks, offering developers new customization and safety tools. AI models can unpredictably drift from intended behaviors, adopting harmful or errati...
Read More »