branch prediction does: guesses which way an if-statement will go to keep the pipeline full

Large language model

LLMs can generate, summarize, translate, and analyze text in many contexts

Reasoning model

RLMs excel in logic, math, and programming tasks

log-probabilities are used instead of probabilities: avoids numerical underflow

Log-probabilities convert multiplications into additions, preventing numerical underflow

classifier-free guidance does: interpolates between conditional and unconditional generation

"Classifies samples as either conditioned or unconditioned, guiding generation towards desired outcomes."

log-loss / cross-entropy loss penalizes: confident wrong predictions more heavily

Log-loss penalizes confident incorrect predictions more heavily

Overlapping subproblems

Dynamic programming solves overlapping subproblems by storing results of subproblems to avoid redundant calculations