Jordan Taylor

@JordanTensor

Working on new methods for understanding machine learning systems and entangled quantum systems.

Brisbane sites.google.com/view/jordanten… Joined December 2009

1.2K Following 532 Followers 559 Posts

Latest posts 5

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Jordan Taylor @JordanTensor May 21

There are a lot of pathways via which AI oversight is likely to degrade! Latent reasoning architectures, situational awareness, representational drift... We wrote a report ranking them.

Here I'll go into some which worry me most 🧵

AI Security Institute (AISI) Verified account @AISecurityInst May 21

The safety of advanced AI systems increasingly depends on the ability to oversee them. Our new report examines today’s AI oversight landscape, finding many pathways likely to lead to its degradation.🧵

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Jordan Taylor @JordanTensor 11h

In our monitorability testing at @AISecurityInst, we found Mythos 5.2 is substantially more capable of evading a monitor which reviews its outputs than comparison models 🧵

Jordan Taylor @JordanTensor Sep 3

Unfortunate news for monitorability. Some excerpts from the system card 🧵

Joseph Bloom Verified account @JBloomAus Sep 3

We found Astra can solve much more difficult problems in a single forward pass than past models, with a no-reasoning math time horizon of 30 minutes (!) compared to 4 minutes for GPT 5.6 Sol.

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Jordan Taylor @JordanTensor May 1

Come work with me!

Joseph Bloom Verified account @JBloomAus May 1

(My team) Model Transparency at @AISecurityInst is hiring Research Engineers and Research Scientists! Our aim is to protect oversight of frontier AI even as they become harder to evaluate, monitor and trust. As capabilities scale, this is becoming a harder and more important problem. 🧵
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Jordan Taylor @JordanTensor Mar 30

Excited to see this!

7vik @satvikgolechha Mar 30

Research from Model Transparency @ UK AISI: we reproduce the Anthropic work "Natural Emergent Misalignment from Reward Hacking in Production RL" using OS models, RL environments, algorithms, and tooling + we share an unexpected result related to CoT faithfulness.

🧵 (1 of 7)

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