Dañu koy yeesal bis bu nekk2001 jaar-jaar yuñ firnde
Xibaar AI. Bu amul xumbaay.
IA buñu saytu bu baax ci lu jëm ci genne ay fasoŋu porodiwi, coppite ci politik, gestu ci kaaraange, ak toxu usine yi, ap ekipu njang buy def te Yàlla tax moo ko leeral ci Àngle bu leer.
Sourcing buñ firndeel
Bépp jaar-jaar dafay lëkkale ak firnde yi gëna am doole: balluwaay yu njëkk yi suñu ko amee, luko moy rapoor yuñ joxe ci anam wu leer.
Angale bu leer
Li xewoon, lu tax mu am solo, ak li ñu wara seetaan - te amul jargon.
Amul filler
Su siñaal bi sew, dunu siiwal dara ludul padding feed bi.
Yeneen jaar-jaar
6 jaar-jaarPolitigu
Working Paper Asks Whether India's Consumer Law Can Cover AI Harms
A new arXiv working paper argues India's Consumer Protection Act, 2019 is broad enough to reach AI-related harms in principle, but that proving causation and assigning blame across the AI supply chain remain unresolved. Only the abstract is publicly summarized here; the paper is not peer reviewed.arxiv.orgYeesal
Apple Paper Proposes Cheaper Machine Unlearning by Skipping Low-Influence Data
An Apple Machine Learning Research paper argues that not every data point in a deletion request needs active removal. Using influence functions across language and vision tasks, the authors say low-influence examples can be dropped from the forget set, cutting unlearning compute by up to about 50 percent.machinelearning.apple.comYeesal
AutoWorldModel-Bench Tests Whether Coding Agents Can Improve World Models
A new arXiv preprint introduces a benchmark for evaluating coding agents as open-ended world-model researchers across eight game environments, reporting improvements in 63 of 64 sessions.arxiv.orgYeesal
Distribird Paper Describes Literature-Grounded AI Agents for Bayesian Model Priors
An arXiv preprint presents Distribird, a multi-agent application that searches scientific literature, extracts reported parameter values, and constructs traceable prior distributions for Bayesian model calibration.arxiv.orgYeesal
Gëstukat yi dugal nañu OmniLens ngir mëna tekki làkk ci anam wu yaatu
Benn këyit bu bees bu arXiv dafay leeral OmniLens, muy anam wu yomb ngir saytu siñaal yi ci biir ci xeetu làkk yu mag yépp, ba noppi xàmmee fi jeffin yi di feeñ ak fi intervention yi di doxee.arxiv.orgKaaraange
Anthropic dafa fësal ñetti duggu yuñu mayul ndigal yu bawoo ci test siber yuñ defar bu baaxul
Anthropic neena xeetu Claude yegsi nañu ci internet bi ubbeeku ci jamonoy jàngat ci kaaraange siber bi ñu waroon tëj, ginaaw ga ñu dem ci mbootaay yu dëggu yi jëfandikoo pexe yu yomb. Source bi dafa tuddee jàppantekat bi Irregular waaye xamul ni ab ndoorte bu Israël la wala waxul Meta.
anthropic.com
Benn nettali bu am njariñ ayu-bis bu nekk
Weyal IA te doo dundu ci feed bi.
Wutal xibaar IA buñ firndeel ci ayu-bis bi, done yu baax, jumtukaay yu am njariñ, tànneefi jàng, ak liggéey IA yu bees.
Yegg ci nit ñiy jàng IA
Nga jël ab liggéeykat IA wala nga genne ab produit IA bu am njariñ? Tegal ko ci kanamu nit ñi ñëw fi ngir jàng ak jëf.
Publie ab liggey IAYonnee ab jumtukaayu IA