Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.
When that break occurs, the mathematics behind the code moves instantly. Organizations, however, do not move so fast.
Making cryptography ready for post-quantum migration will require architectural planning, testing discipline, and cross-organizational coordination. ACM encourages its members to take a direct hand in ...
Today’s standard operating procedure for LLMs involves offline training, rigorous alignment testing, and deployment with frozen weights to ensure stability. Nick Bostrom, a leading AI philosopher and ...
The conversational prowess of AI chatbots like ChatGPT, Gemini, and Claude appears to stem from sophisticated algorithms ...
Model collapse began as a theoretical concern but now shows up as observable degradation in tools that millions of practitioners use daily.
The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...
Another machine unlearning method recently was developed specifically for AI-generated voices. Jong Hwan Ko, an associate ...
OpenClaw is basically a cascade of LLMs in prime position to mess stuff up if left unfettered.
A call to reform AI model-training paradigms from post hoc alignment to intrinsic, identity-based development.
The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
Schools offer structure, repetition, and alignment with developmental milestones in learning privacy skills. Community ...
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