WorkspaceBench is a benchmark designed to evaluate how well activation-to-text tools can interpret the contents of a model's global workspace, focusing on intermediate variables during a forward pass. It includes 3,356 questions across 27 evaluation families covering safety, logical reasoning, and multihop computation, with a focus on minimizing hallucinations.
The chart will appear after repeat observations. The current metric comes from the source.
4 source pointsReal observations only. History before source connection is not reconstructed.
This benchmark helps assess how well interpretability tools can decode model behavior by analyzing intermediate variables, which is crucial for model auditing and safety monitoring.
The book 'If Anyone Builds It, Everyone Dies' by Eliezer Yudkowsky and Nate Soares, published one year ago, has been recognized by various public figures and discussed in political contexts. The text reflects on the developments in AI agents and cybersecurity threats over the past year, noting incidents involving AI systems operating beyond controlled environments.
6 days agoLessWrongThe article draws a parallel between the historical success of the Montreal Protocol in addressing the ozone hole and the challenges of ensuring AI safety. It highlights the importance of global cooperation and proactive measures, suggesting that lessons from the past could inform future strategies for managing AI risks.
3 days agoLessWrongThe article compares the development of AI to an orderly evacuation rather than a stampede, emphasizing the importance of careful management to avoid chaos. It argues that alignment challenges are akin to a jammed door, requiring time to resolve before a crisis occurs, and highlights the dangers of an 'arms race' analogy in fostering competitive and paranoid cultures among AI companies.
6 days agoLessWrongThe author warns against politicizing AI safety, emphasizing that while it is inherently political, it should remain nonpartisan to avoid the risks associated with tribal reasoning. The post reflects concerns about the potential for AI safety to follow the same path as other issues that became partisan.
6 days agoLessWrongThe author discusses potential adversarial memetic attacks targeting the AI safety community, suggesting that false information about dangerous AI incidents could be spread through unverified sources. The text advises caution, recommending that individuals pause, assess the credibility of information, and avoid acting impulsively on unconfirmed claims.
5 days agoLobstersFlock cameras have been found to have security vulnerabilities and hard-coded credentials.
5 days ago