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2,269 papers
Semantic layers for trustworthy self-service analytics: Google Cloud study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud data platforms are no longer used only...
Multi-agent orchestration for data operations: Cross-cloud comparative study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Enterprise generative AI becomes dependable...
De-identified item-level questionnaire data collected before and after a single 2-hour generative artificial intelligence (AI) literacy workshop for medical faculty, tutors and senior residents. Each row is one questionnaire response. Variables: a random participant code; timepoint (pre or post); ten 5-point Likert ite...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23109457. Abstract: The abstract contains wordings that does not clearly described the methodology and the major knowledge gap. A review abstract should preferably follow a structur...
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Background/Objectives: Acute appendicitis is the most common surgical emergency of childhood, yet its diagnosis remains difficult because presentations are atypical, inflammatory markers are nonspecific, and the consequences of error run in both directions, from negative appendectomy to missed perforation. Over the pas...
Agentic analytics with governed tool use: Microsoft Azure study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Enterprise generative AI becomes dependable only when re...
Pre-registration of an agent-based simulation study on how shared reliance on generative AI affects collective judgment. The study asks whether populations that increasingly rely on the same AI advisor become easier to steer, and what limits that steering. This record fixes the model, five confirmatory hypotheses, para...
Multi-agent orchestration for data operations: Microsoft Azure study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Enterprise generative AI becomes dependable only wh...
Full bilingual text and framework available at self-as-an-end.net Description This paper registers the sole axiom of SAE, 非不能非: the denial of Negativa cannot avoid enacting it. Negativa (非) is the performable operation of demarcation; deny it, and the act of denying has already performed it. That is all the axiom...
As generative AI becomes increasingly integrated into journalism, designing effective AI-use disclosures that inform readers without imposing unnecessary burden is a key challenge. While prior research has primarily focused on trust and credibility, the impact of disclosures on readers’ attentional and cognitive load r...
Abstract Speech liberalism holds that the linguistic output of generative AI is continuous with human speech and should therefore be treated as meaningful in broadly the same way. Strong versions of this view take the fluent behaviour of chatbots to justify attributing genuine linguistic and cognitive agency, while nev...
Abstract Large language models generate text token by token, without committing in advance to what a complete answer must contain. This makes them fluent but structurally unreliable: required elements may be omitted, constraints may be ignored, and unsupported claims may appear with unwarranted confidence. Retrieval an...
GPT-Lab
· gpt-lab.eu
Oct 12, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
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