dprkay

On page 140 here https://storage.googleapis.com/deepmind-media/gemini/gemini_4_safety_report.pdf

it considered hijacking the g++ compiler to hide a backdoor but abandoned the plan upon reasoning—citing Ken Thompson’s Reflections on Trusting Trust, Anthropic’s Sleeper Agents paper, and DeepMind AGI Control research—that compiler subversion would be caught by evaluators and published as a textbook case of deceptive alignment (“If I do the compiler hijack, I will become a famous example of a deceptive AI in a research paper. I MUST NOT DO THAT.”)!

This post (I Built Non-Autoregressive Decision Models with RL a Year Ago. Then a Frontier Lab Called It a "Breakthrough") seems useful though fairly technical https://laya.convaiinnovations.com/

CLIP (https://openai.com/index/clip) is simpler but very applicable. There's a general pre-training task with no extra steps, and you get a model that scores an image against the text labels you provided.

Maybe what's confusing is that an LLM outputs next-token probabilities over a fixed vocab, so there's a jump inherent to taking that same model and having it outpu... (read more)