imudojuiwọn ojoojumọ1797 daju itan
Agbegbe AI ti a ṣayẹwo orisun ti awọn ifilọlẹ ọja, awọn iyipada eto imulo, iwadii aabo, ati awọn gbigbe ile-iṣẹ, ṣalaye ni ede Gẹẹsi nipasẹ ẹgbẹ ẹkọ ti kii ṣe èrè.
Gbogbo itan ni asopọ si ẹri ti o lagbara julọ ti o wa: awọn orisun atilẹba nigbati o wa, bibẹkọ ti o han gbangba.
What happened, why it matters, and what to watch — without the jargon.
Nigbati awọn ifihan agbara jẹ tinrin, a jade ohunkohun kuku ju òwú kikọ sii.
Source-checked AI stories, newest first, for people who need to understand AI without chasing hype.
A new approach to training multimodal large language models (MLLMs) eliminates the need for extensive task-specific supervision.
This work examines emoji-augmented prompts as a test case for gaps in safety evaluation of large language models (LLMs).
Modern e-commerce platforms often operate search, recommendation, personalization, and CRM systems independently, limiting opportunities for proactive customer re-engagement.
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.
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.
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.
A new arXiv preprint presents FACET, a framework for generating executable terminal tasks whose instructions, environments, solutions and verifiers are designed to remain consistent.
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.
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.
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.
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.googleAmazon Bedrock now offers OpenAI’s GPT-5.6 Sol, Terra, and Luna models in more than 25 AWS Regions, with geographic and global routing options that expand the available compute pool.
Alaye ti o wulo ni ọsẹ kọọkan
Gba awọn iroyin AI ti a ṣayẹwo ti ọsẹ naa, data atilẹba, awọn irinṣẹ to wulo, awọn yiyan ẹkọ, ati awọn iṣẹ AI tuntun.
Igbanisise ọjọgbọn AI kan tabi ṣe ifilọlẹ ọja AI ti o wulo? Fi si iwaju awọn eniyan ti o wa nibi lati kọ ẹkọ ati ṣe.
Firanṣẹ iṣẹ AI kan Fi ohun elo AI silẹ