Epos AI

Pioneering the Future of AI Interpretability

At Epos, we look inside AI models to make them faster, more secure, and more trustworthy.

[Epos AI @EposLabsAI]

With #Polygraph, you can:

-Expose latent biases: Move beyond surface outputs to measure what an LLM encodes as its true belief.

-Contrast topics: Test whether a model encodes different internal stances on Topic A versus Topic B.

- Directly compare how different LLMs represent

[Epos AI @EposLabsAI]

“𝐒𝐚𝐟𝐞𝐭𝐲 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠” 𝐝𝐨𝐞𝐬 𝐧𝐨𝐭 𝐞𝐥𝐢𝐦𝐢𝐧𝐚𝐭𝐞 𝐛𝐢𝐚𝐬 𝐢𝐧 𝐋𝐋𝐌𝐬; it merely conditions models to suppress biased outputs under evaluation.

Epos Labs introduces #AI #Polygraph.

https://t.co/NiHCBx66ot

[Epos AI @EposLabsAI]

Takeaways:

- The AI community still lacks reliable methods to evaluate and fix LLM failures.

- Interpretability offers outsized impact - the main barrier to progress is that we don’t truly understand today’s models.

[Epos AI @EposLabsAI]

@mdubowitz #Newbackdoorfound

[Epos AI @EposLabsAI]

Superposition is the next buffer overflow

[Epos AI @EposLabsAI]

Subliminal Learning Will Power the Next Generation of Influence Operations

https://t.co/WHyKoJH665

[Epos AI @EposLabsAI]

This means that a motivated attacker can abuse entanglement to undetectably manipulate LLMs. Nation State Actors are gearing up for the new opportunities an AI-powered software landscape will open for them:

[Epos AI @EposLabsAI]

Without referencing the target behavior at all, the LLM finds itself with a high probability of performing the target action, due to a fundamental property of the neural network architecture.

[Epos AI @EposLabsAI]

Imagine an article about houseplants that causes AI to support Vladimir Putin.

Bad actors use new attacks, turning AI into a weapon for disinformation and cyberattacks.

See our demonstration of a Subliminal Attack here (and our "#Putinized" demo):

https://t.co/WHyKoJH665