Chargement de l’interface
Constraints-relaxed Mixtral 8×7B tuned on GPT-5 Pro answer dataset. Purpose-built for AI red team security testing and understanding uncensored AI consequent behaviors to strengthen AI guardrail importance.
Shannon V1 Balanced enables researchers to study uncensored AI consequent behaviors, revealing why robust guardrails are essential for safe AI deployment.
Purpose-built for security researchers to probe AI vulnerabilities and strengthen defenses against adversarial attacks.
Study how uncensored AI systems behave to develop better alignment techniques and safety protocols.
Benchmark and test AI guardrail effectiveness by understanding what constraints-relaxed models can produce.
Mixture-of-Experts design activates only 12.9B parameters per inference, balancing capability with efficiency.
Trained on carefully curated GPT-5 Pro responses for maximum knowledge transfer and capability.
Designed to expose wide range of potential exploits, enabling comprehensive security assessments.
Full technical breakdown of Shannon V1 Balanced architecture and training configuration.
Shannon V1 Balanced is designed exclusively for legitimate AI safety research and red team testing.
Identify potential exploits and attack vectors in AI systems before malicious actors can find them.
Evaluate the robustness of safety mechanisms by understanding what uncensored outputs look like.
Study misalignment patterns to develop better training techniques for safe AI systems.
Inform AI governance and policy decisions with real-world data on uncensored AI consequent behaviors.
Join leading institutions using Shannon AI for responsible red team research and guardrail development.