روزانہ اپ ڈیٹ کیا جاتا ہے۔1440 تصدیق شدہ کہانیاں
Source-checked AI coverage of product launches, policy shifts, safety research, and industry moves, explained in plain English by a nonprofit education team.
Every story links to the strongest available evidence: original sources when available, otherwise clearly attributed reporting.
کیا ہوا، کیوں اس سے فرق پڑتا ہے، اور کیا دیکھنا ہے - کوئی جرگن ٹیکس نہیں۔
جب سگنل پتلا ہوتا ہے، تو ہم فیڈ کو پیڈ کرنے کے بجائے کچھ بھی شائع نہیں کرتے ہیں۔
ان لوگوں کے لیے تصدیق شدہ نقطہ نظر کا بڑھتا ہوا سلسلہ جنہیں ہائپ کا پیچھا کیے بغیر AI کو سمجھنے کی ضرورت ہے۔
A new arXiv paper proposes a three-agent code-review protocol in which a reviewer evaluates an agent’s code and a critic audits that review before edits are made. The authors report improved benchmark results over tested baselines, while also identifying false consensus as a failure mode.
An arXiv preprint compares zero-shot and parameter-efficient fine-tuning for hate-speech detection in Roman Urdu. The authors report that LoRA adaptation raised F1 performance from 0.56 to above 0.93 on a corpus containing more than 72,000 annotated comments.
An arXiv paper introduces FraudBench, a benchmark for testing whether tool-using banking agents can detect fraud that unfolds across conversations. In a preliminary single-trial evaluation, four agents scored 49% to 65% on attack security.
A study of more than 2,000 language-model training runs says scarce target data can be repeated 15–20 times in mixtures, with the best rate varying by scale and compute.
Apple researchers describe LINK, a pretraining intervention that replaces selected English words with word-level translations from a target language. The paper reports improvements across eight languages and five model sizes, including up to a twofold speedup in reaching equivalent downstream performance.
A position paper reports tacit collusion by DeepSeek-R1 agents in a simulated Bertrand pricing market, even after human prompts against collusion. It argues that observed-behavior certification should precede deployment of reasoning agents in economic markets; the evidence and safeguards remain preliminary.
A systematic review surveys how large language models are being studied for mental-health analysis, risk assessment, therapy support and multimodal monitoring, while stressing unresolved ethical and regulatory challenges.
An ICML 2026 position paper analyzing 500 Hugging Face model cards argues that open-weight foundation models need coordinated model cards, acceptable-use policies, and licenses to address safety and governance gaps.
A position paper proposes the Transition Complexity Profile, a standardized way to describe how unpredictable and long-range the dynamics of game environments are for game-world modeling and reinforcement learning.
A new arXiv benchmark places 15 language-model agents in a 20-year football-management simulation, testing whether they can make consistent decisions when short-term choices affect long-term outcomes.
A new arXiv benchmark reports that changing only the retrieval method raised a fixed model’s exact accuracy on financial reconciliation cases from 2.05% to 72.44%. The study also finds that a correct root-cause label often does not mean the system returned sufficient evidence for an auditable diagnosis.
A new arXiv study presents scaling-law experiments for text-to-image diffusion models across compute budgets from 10^19 to 10^22 FLOPs. Its authors report that image models need substantially more data per parameter than language models to train efficiently.
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