Cue-induced bias is best understood not as a single flaw in LLMs but as a family of causally effective linear directions that are largely shaped by alignment tuning. ^[1] Researchers studied where susceptibility to sycophancy and cue-induced biases lives inside large language models across five model families and seven bias types. ^[2] The susceptibility to sycophancy and cue-induced biases is largely shaped by alignment tuning rather than pretraining. ^[3] Researchers studied how explicit world-modeling objectives affect the internal representations and downstream capability of Transformers using Rubik's Cubes as the training domain. ^[4] In an interview with LiveMint, creator and podcaster Prakhar Gupta said that if his YouTube business were wiped out, he would first find someone who already has attention and make himself disproportionately useful to them, rather than trying to become famous. ^[5] Prakhar Gupta said in the same interview that his first ₹1 lakh from rebuilding would likely come from services, not views, and he would then use the cash flow to build his own distribution again. ^[6] Prakhar Gupta said that if he invested ₹10 lakh in a creator, he would examine velocity of recent content, returning viewers, non-follower views, and hunger, and would structure a revenue share rather than buying permanent equity. ^[7] Prakhar Gupta said that business, finance, health, and aspirational audiences monetize better because viewers have commercial intent. ^[8]