Introducing Cross-Layer Transcoders for Qwen3
A New Step Toward Understanding How Qwen3 Represents and Transforms Information
Today, BluelightAI is releasing the first-ever Cross-Layer Transcoders (“CLTs”) for the Qwen3 family of models, beginning with Qwen3-0.6B and Qwen3-1.7B. These CLTs make it possible to examine how Qwen3 encodes concepts, propagates information, and composes meaning across its layers.
Alongside the CLT release, we are launching a dashboard to explore the features discovered. The Qwen3 Explorer provides an interactive environment for studying learned features, tracing activation flows, and visualizing the model through Cobalt’s topological data analysis.
Together, these components make Qwen3 one of the most interpretable open-source model families available.
The Regulatory Horizon for AI Companies: What to Know and How to Prepare
Why it matters
AI is moving from a “nice-to-have” technology into a highly regulated domain. For companies building, deploying, or integrating AI systems, regulatory risk is real: non-compliance can mean substantial fines, reputational damage, increased liability, and market exclusion. At the same time, well-designed governance of AI systems can become a differentiator: trusted, transparent systems earn customer and partner confidence.
Below is a breakdown of the current regulatory regime (global but with emphasis on the EU and U.S.), the exact wording of key provisions you should watch, and compliance steps for AI companies. At the end, you’ll see how BluelightAI’s Cobalt helps embed transparency, auditability, and decision-understanding into your AI stack — helping you reduce regulatory risk and build trust.
Why Your AI Needs Cobalt: Adapt, Diagnose, and Deploy with Confidence
Adapt AI to Your Use Case
The Challenge: Adapting State-of-the-Art Models to Industry-Specific Use Cases is Hard
Transforming a general-purpose model into an AI specialist for your industry is an ongoing process that continues throughout the lifecycle of the model. AI apps and agents are challenging to adapt because the interactions that occur are varied and constantly change with time. Consequently, enterprises are behind the curve in deploying LLM-based specialists and agents because they are not confident in their predictability and reliability (e.g. incorrect responses, hallucinations).
Our Solution: Cobalt – Mechanistic Interpretability for Model Evaluation
BluelightAI is a platform that helps users evaluate, adapt, and improve state of the art models for their use case. This platform provides a hub for comparing datasets, evaluation metrics, and models (open and proprietary) with specific, actionable insights into their capabilities and blind spots.