AI News Today — Part 5
May 10, 2026 · Sourced from 500+ daily AI sources, scored by relevance.
- MISP-Bench: Decomposing User-Provided False Priors into Answer, Rationale, and Guard Effects
Large language models in clinical and educational settings routinely receive user-provided context containing incorrect prior beliefs. Existing benchmarks measure aggregate susceptibility to such priors but do not disentangle which structural component (the asserted answer, the supporting rationale, or their combination) drives the damage, nor test whether safety meta-prompts such as "verify the reasoning firs" consistently mitigate it. We introduce MISP-Bench, a factorial benchmark of 1,724 audited multiple-choice items (1,430 MedMCQA medical + 294 GSM8K quantitative) evaluated under 13 prompt conditions across 10 open-weight instruction-tuned models (1B-27B) in chain-of-thought and direct modes, with approximately 1.33M audited response records across three runs per condition. Distractors were generated by GPT-5.4 and the model was excluded from the evaluated set to prevent circular evaluation. Targeted and arbitrary distractor subsets yield similar aggregate Misinformation Damage In
- WPS | AI Summarizer
Turn long content into clear, concise summaries.
- The German National Cohort: Ophthalmological Assessment, Baseline Profile and Potential for AI-based Eye Research
Objective: To describe the ophthalmic examination protocol within the German National Cohort (NAKO) / NAKO Gesundheitsstudie, to report the baseline profile of participants undergoing ophthalmological assessment, and to illustrate the potential of these data as a population-based open resource for artificial intelligence (AI) research in eye health. Design: Baseline analysis of ophthalmic data within the nationwide, population-based multicenter prospective NAKO study. Participants: 48,460 adults in the ophthalmological level 2 module of 205,053 adults enrolled in NAKO, aged 19-74 years, with mean age 48.9 {+/-} 12.5 years and 52.7% male. Methods: All participants underwent standardized assessments of a wide range of biomedical examinations and detailed questionnaire-based data collection, including non-dilated color fundus imaging, visual acuity testing, recording of a brief ocular history. Ocular and systemic health measures were summarized using descriptive statistics. Fundus image q
- Artificial intelligence for detecting bipolar disorder in electronic health records of patients with affective diagnoses: a diagnostic accuracy study
Background: Bipolar disorder (BD) is frequently underdiagnosed, particularly in patients presenting with depressive disorders, leading to delays in appropriate treatment. Artificial intelligence (AI) applied to electronic health records (EHRs) may improve early detection by identifying clinically relevant symptom patterns. Objective: To evaluate the diagnostic performance of a natural language processing (NLP)-based AI model for detecting BD-related features in EHRs of patients with affective diagnoses. Methods: A retrospective diagnostic accuracy study was conducted using 500 EHRs from a psychiatric referral hospital in Bogota, Colombia (2020-2024). The model extracted 18 predefined clinical domains from unstructured text and classified patients into four risk categories. Diagnostic performance was assessed in a validation subset of 100 records using independent psychiatric evaluation as the reference standard. Sensitivity, specificity, positive and negative predictive values, F1-scor
- SEIR-IoT cyber-physical architecture with dual parametric coupling for epidemic scenario simulation using synthetic biomedical signals
This study presents a proof-of-concept cyber-physical architecture integrating a SEIR epidemiological model (Susceptible-Exposed-Infectious-Recovered), implemented in MATLAB, with a simulated Internet of Things (IoT) acquisition and transmission stage based on the ESP32 microcontroller and the ThingSpeak platform. The system generates synthetic biomedical signals of body temperature and peripheral oxygen saturation (SpO2), structured across three levels: circadian variation, scheduled pathological episodes, and Gaussian noise. These signals feed a dual parametric coupling function that dynamically updates the SEIR transmission parameter as a combined function of body temperature and oxygen saturation deviations from their clinical reference values. The proposed architecture is organized into four functional phases: measurement, communication, computational processing, and feedback. Five simulated clinical scenarios were evaluated, ranging from normal conditions (T = 36.5 {degrees}C, Sp
- Scalable deep-learning-based inference of time-varying transmission dynamics from outbreak phylogenies
Infectious disease dynamics can be inferred from pathogen genomic data using phylodynamic methods, but the applicability of many such approaches to large data sets is constrained by computational cost. Recent deep-learning approaches to phylodynamics have improved scalability, yet challenges remain when genetic divergence is limited during fast spreading outbreaks. To address this, we use pathogen-specific models to show that deep-learning models trained on outbreak-like phylogenies can accurately estimate the reproductive number (R) when both the birth-death model and the expected phylogenetic resolution are matched to the target pathogen, highlighting the importance of realistic training conditions. Focusing on three major respiratory pathogens of public health importance (SARS-CoV-2, seasonal human influenza virus, and respiratory syncytial virus (RSV)), we introduce PhyloRt, a scalable framework for estimating the time-varying reproductive number (Rt) from large outbreak phylogenie
- Tailgrids 3.0
Open-source React UI library for Tailwind and AI Workflow
- Adject 2.0
Create hyperrealistic product visuals with AI
- Notion 3.4
New dashboards, connectors, sidebar & smarter AI agents
- AgentPeek
Claude Code and Codex in your Mac notch
- LumiChats Offline(free)
Your AI, fully offline with Zero data collection & 100% free
- Keel
An AI assistant whose memory belongs to you
- Atlasly
AI agents for architecture
- Cohesivity
Backend Infra for AI agents
- PrimeCompass.ai
AI-Powered quality intelligence from live application
- Agent Memory System
Open Source Context Infrastructure for AI Agents
- AndalibAI
Turn missed calls to Money
- MakerLoft
AI app builder. Backend included.
- AI-powered Intercompany Elimination
Close faster. Sign off smarter.
- Fluiq
LLM observability, evals & optimize in two lines of Python
- Balto. Build
The editorial AI engine for founders and creators.
- Playlist Name AI
AI playlist name generator for mood, genre & any occasion.
- AI App Store Screenshots
Free and Open Source App Store screenshot designer using AI
- Resido AI
Real estate intelligence, powered by AI.
- Meridian Learn
AI-native Coursera, personalized to you
- Luna AI
Study any subject. Anytime. Anywhere.
- SRTGen.com
Professional AI Subtitles for Your Viral Videos
- Fud AI - Calorie Tracker
AI calorie tracking from photos, labels, text, and voice
- Mirror Test
Get anonymous feedback from friends about yourself.
- Hermes Agent Helper
Deploy your private AI agent in minutes.
- Sidekick - AI Chat Bot
AI Tools, Assistants, Characters in One App.
- Half of UK children own AI toys despite parental safety fears, survey finds
A new survey has revealed half of children in the UK own an AI-enabled toy or device
- DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge
DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge PCMag Middle East
- DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge
DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge PCMag UK
- DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge
DOGE Used ChatGPT to Cut $100m of Humanities Funding, Says Judge PCMag Australia
- Who’s a good boy? AI can’t replace doggie actors, director says
Who’s a good boy? AI can’t replace doggie actors, director says The Straits Times
- AI fruit affair videos stir backlash after chicken brand copies trend
Artificial intelligence-generated videos featuring personified fruits caught in affairs and broken relationships are drawing millions of views on Korean social media, turning bizarre melodrama into one of the latest short-form trends. But the trend is now facing scrutiny after a major fried chicken franchise copied the format in an advertisement, then deleted the video and apologized following criticism that it had borrowed from provocative content easily accessible to children. Pelicana, a nati