AI News Archive: August 29, 2026 — Part 4
Sourced from 500+ daily AI sources, scored by relevance.
- Strumhold
Chord-change practice that listens and scores you
- Asclevor Case Search
Semantic search for clinical case records
- ShimGuard
Verify merged status of PR fixes for closed issues"
- Qivi
Drop anything, get an explainer
- Everloggers
The ultimate social market for buying and selling friends
- qr3.app
Developer-first QR codes with EU DPP support
- RecentBrief
Hear what’s happening, as it happens
- Building AI tools for music creators
Free AI prompt generator for Suno, Udio & more
- ObraFácil
Orçamentos e gestão de obra em minutos, direto do celular.
- taskOverflow
Location based quickly editable visual task mangement system
- KnowledgeNav
Turn intent into outcome.
- TestForce Teacher
Everything you need to transform education.
- OneTwo Demo
Turn a prompt into a product walkthrough video (not trailer)
- Safe Signals
Personal safety, faster — one‑tap alerts. Emergency alerts
- Plumb
Your coding agent says it's done. Plumb checks.
- Real Time Solar System
Live map of the solar system, rocket launches, news and more
- RaylexFlow
Turn conversations into customers with AI & CRM
- AI Automation Offer Builder
Turn one business problem into a safe AI service offer
- WellnovaSport
Health & activity tracking journal
- Edgeable
The fast, simple futures trade copier
- EcoService OS
AI Field Service OS with smart dispatch & photo diagnostics
- HALFTIME — Stop. Recalculate. Ship.
Your AI copilot for building, shipping, and surviving.
- Release Tracker
Plan and manage your music releases in one place
- Silsilah
Private, offline-first family tree app, on-device face match
- Airbridge GO
Turn one app URL into a measurable growth loop
- Mentar
Open-source AI tutor that runs on your PC, not the cloud!
- Crypto Owl: free portfolio tracking app
Simple, free Android app for tracking your crypto portfolio
- DevWars
Battle for attention. Outbid. Knock out. Win clicks.
- BidmySpot
bid-to-rank board for iOS, Android, Web apps
- LaunchOn.it
The pay-to-rank leaderboard with weekly resets
- SmoothTube
YouTube feels at home on Windows.
- Listed Firm
Verified directory for B2B, B2C, SaaS
- ParseBird
ParseBird handles the context layer of your AI stack
- Poker Night
Run your home poker league without the spreadsheet
- SECOPTER SUITE
Herramienta LegalTech - IA de Contratación Pública
- LinkApp
Social media link in bio links app
- UltraCat
Monitor your Mac, control fans, and manage sleep
- KGQ.AI — Curated AI Image Prompts
See the result. Find the prompt. Create faster.
- Modfyr
SEO and AI search readiness for location-based businesses.
- Matteca
Make your favorite AI organize your personal life for you.
- SlumberWave
Mix your own sleep sound. Free forever, no ads.
- Prompt2Post
Turn simple prompts into ready-to-publish posts instantly.
- Claude AI Skills Pack
84 drop-in skills turning Claude Code into a Senior Engineer
- Riink
Discover leads and product insights
- Sarvam AI Content Studio
Dub and clone voices across Indian languages.
- Visual LLM-guided consensus spatial domain detection with L-STAR
Spatial domain detection is a central task in spatial transcriptomics, yet existing methods exhibit highly variable performance across datasets. We introduce L-STAR, a visual LLM-guided, consensus-based framework that leverages the visual reasoning capacity of large language models to adaptively rank and integrate spatial domain detection methods. L-STAR achieves robust and consistently improved performance, outperforming single spatial domain detection methods across diverse datasets.
- Corpusome, a cross-body-site human microbiome corpus for representation learning
Machine-learning models of the human microbiome are trained mostly on stool samples from single cohorts, limiting cross-body-site representation and cross-study generalization. Progress is constrained less by algorithms than by the absence of a harmonized multi-body-site corpus carrying the technical metadata needed to model, rather than ignore, batch structure. Here we release Corpusome, a harmonized two-tier cross-body-site human microbiome corpus for representation learning: a harmonized corpus of 187,546 human microbiome samples integrating standardized profiles from curatedMetagenomicData, the American Gut Project, and the EBI MGnify platform. Corpusome follows a two-tier design preserving both functional depth and cross-body-site breadth: a shotgun tier (22,588 samples, 93 studies) with species- and pathway-level profiles, and a 16S tier (164,958 samples, from a full pull of 708 MGnify studies) with genus-level profiles extending coverage to oral, skin, respiratory, and urogenital sites. It spans six body sites and two modalities, with harmonized metadata for batch-aware modelling. Body-site signal exceeds technical/source variance in the 16S tier by approximately 2.4-fold.
- LazyKiwi AI Video Generator
Create Viral Video & Images with Ready-Made Templates effortlessly
- Engineering a highly active thermophilic F1-ATPase by homolog-guided exploration and machine-learning-assisted prioritization
The rotary motor F1-ATPase has been extensively studied as a model molecular machine, yet rational engineering of its catalytic activity remains challenging because ATP hydrolysis is regulated by long-range intersubunit allostery and large conformational transitions. Here, we developed a homolog-guided engineering strategy to increase the maximum rotation rate of the thermophilic Bacillus PS3 F1-ATPase (TF1). Candidate mutation sites were first identified by comparing TF1 with the homologous enzymes bovine mitochondrial F1 (bMF1) and Paracoccus denitrificans F1 (PdF1), both of which exhibit higher maximum rotation rates than TF1. Systematic exploration of these sites identified four activity-enhancing hotspots, followed by focused hotspot exploration and machine-learning-assisted prioritization of combinatorial mutants. The best mutant, TF1({beta}Y313L/{beta}E332S), exhibited a 1.8-fold higher maximum rotation rate than TF1(WT) while retaining its functional thermostability. Interestingly, activity-enhancing substitutions were not limited to the residues conserved in both bMF1 and PdF1, indicating that the bMF1-PdF1 consensus substitutions effectively identify activity-enhancing hotspots rather than uniquely defining the optimal amino acid. Machine-learning-assisted exploration efficiently prioritized highly active mutants, although the predictive performance was limited by the relatively small training dataset and epistatic interactions among mutations. Kinetic and structural comparisons further provided mechanistic insights into the enhanced catalytic activity of the engineered mutant. Together, these results establish a practical strategy for engineering complex molecular motors by combining homolog-guided hotspot identification with focused hotspot exploration.
- PhotoMentor
Stop guessing if your photo is good. Get instant, objective feedback.