Dañu koy yeesal bis bu nekk2290 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
9 jaar-jaarLiggéeyukaay
Bridging Search and CRM: Productionizing AI Product Research Agents for Customer Re-Engagement
Modern e-commerce platforms often operate search, recommendation, personalization, and CRM systems independently, limiting opportunities for proactive customer re-engagement.arxiv.orgYeesal
New benchmark shows Vietnam’s exam rubric can change how language models rank
A paper introduces THPT-Ladder, a 632-item benchmark that applies Vietnam’s 2025 national exam grading scheme to language models and reports materially different scores from standard proportional-accuracy measures.arxiv.orgYeesal
Netflix paper outlines a lifecycle for LLM judges evaluating recommendation explanations
An arXiv paper describes how Netflix built, deployed and continuously monitored an LLM judge for recommendation explanations, reporting viewing and engagement gains in a five-week A/B test involving tens of millions of members.arxiv.orgYeesal
Survey frames self-evolving AI agents as dynamic graph transformations
A new arXiv survey proposes viewing an AI agent’s memories, tools, skills, workflows and relationships as a graph that changes over time, and calls for graph-aware evaluation and governance.arxiv.orgYeesal
FACET proposes an environment-grounded method for training terminal agents
A new arXiv preprint presents FACET, a framework for generating executable terminal tasks whose instructions, environments, solutions and verifiers are designed to remain consistent.arxiv.orgYeesal
SESSE proposes structured decomposition to make LLM judging more auditable
An arXiv preprint introduces SESSE, a training-free framework that breaks an LLM judge’s preference into sub-questions. The authors report near-parity with a chain-of-thought baseline on 1,000 RewardBench examples and criterion-level vote records; generalization, cost, and independent validation remain open questions.arxiv.orgYeesal
IBM team reports AI-written adapters bring thousands of Hugging Face models to Spyre
An IBM Spyre team says coding agents helped create 13 runtime adapters that covered 7,960 of the 10,000 most-downloaded Hugging Face embedding models in its target set, with 6,804 passing end-to-end tests on Spyre. The team says human debugging remained essential.pytorch.orgYeesal
Apple researchers report iterative pseudo-labeling gains for Mandarin-English speech recognition
An Apple research paper describes a three-phase iterative pseudo-labeling method for Mandarin-English code-switching automatic speech recognition and reports Mix Error Rate reductions on two SEAME development subsets.machinelearning.apple.comProduit
Google to let users tune Discover with natural-language requests
Google says users will soon be able to tell Discover what topics and links they want to see more or less of, while new controls also personalize Search and Google News audio briefings.
blog.google
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