OpenAI raises $122B at $852B valuation, signalling strong investor appetite for AI - Yahoo! Finance Canada
<a href="https://news.google.com/rss/articles/CBMiigFBVV95cUxPOEgxbUdjVEJoVHpydUY1SUFWb3RmZDBQYXJTLVMwbGlUV2Qwb0ZkVTRtbkRpNmJmQXpTLTk0LVIxNU5WVkU0YVFoNUk1Z0dmNG1YRkNEc2FlWkR6NWN3ODBSRDRfdGR2eUEzYTE1RzJnUWJCZGZ6eURDRldvQjVtTWpJSi1Gd0I1N3c?oc=5" target="_blank">OpenAI raises $122B at $852B valuation, signalling strong investor appetite for AI</a> <font color="#6f6f6f">Yahoo! Finance Canada</font>
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valuationPreliminary Explorations on Latent Side Task Uplift
TL;DR . This document presents a series of experiments exploring latent side task capability in large language models. We adapt Ryan’s filler token experiment into a more AI Control-like setup with main task and side task and find that Claude Opus 4.5 can solve harder arithmetic problems latently when it has a longer trajectory. This shifts its 50% accuracy threshold from ~5-step to ~6-step problems after 240 lines of irrelevant output. However, we don’t observe strong evidence to believe that current generation of models generally benefit much from wider parallel compute enabled by longer trajectories with the exception of Opus 4.5. Code is made available here GitHub . Longer Agent Outputs Can Increase Side Task Capability. Claude Opus 4.5's latent arithmetic accuracy as a function of pro

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