Ben Mayer (t11s)

Paradigm

@transmissions11

cs @mit, prev @sailresearchco @paradigm

2λ.com Joined September 2020

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Ben Mayer (t11s) @transmissions11 Oct 23

Been learning about ZK-SNARKs lately! The core ideas behind modern hash-based schemes are surprisingly accessible & elegant 🧙‍♂️

Partly to teach myself, I wrote a post explaining them from scratch for people like me without a deep math background:

2λ.com/zk-snarks

xn--2-kmb.com ZK-SNARKs from the Ground Up An attempt to explain how modern hash-based multilinear ZK-SNARKs work from the ground up.

Ben Mayer (t11s) @transmissions11 6h

Mistral model names be like

Ben Mayer (t11s) @transmissions11 4d

Had the pleasure of helping with this! 🫡

I suspect there's historically been a big overhang in applied ZKP work due to the sheer implementation & verification complexity. But now thanks to LLMs, implementation is far easier and autoformalization is practical. Exciting times :)

Anthropic Verified account @AnthropicAI 4d

New Anthropic research: progress on provable inference for large language models.

Here, we introduce FlashProve. Building on established cryptographic techniques, FlashProve allows developers to verify whether a given response came from a given AI model. It’s substantially more efficient than prior open-source methods for doing so.

These proofs have a range of applications. They can, for instance, make it harder for attackers to hijack a chat, or enable safety evaluators to verify that the model they’re testing is the same one being served to customers.

For our full write-up, see here: anthropic.com/research/prova…

Further progress in provable inference will likely be an important part of improving trust in AI deployment. To that end, we're open-sourcing FlashProve’s code, here: github.com/anthropics/Fla…

We’re grateful to our collaborators: Alessandro Chiesa, @GiacomoFenzi, @gwberg95, @miranda__christ, Rahul Dalal (rdalal.github.io) and Ben Mayer (@transmissions11).
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Ben Mayer (t11s) @transmissions11 Oct 29

Pretty sad how base model style "pass in some tokens and we'll predict the next ones" APIs are so hard to get a hold of now, let alone actual base model checkpoints.

Using base models for turbocharged autocomplete is a really delightful experience, chat isn't always optimal UX!

Ben Mayer (t11s) @transmissions11 Sep 14

I feel like it's still underdiscussed that seemingly all of the world's ~severe misalignment incidents as of now occurred in evaluation/RL? This is not what LW/MIRI/etc were expecting iiuc.

Why aren't we seeing incidents in deployment? Is eval awareness that strong?