AI News Archive: June 21, 2026 — Part 5
Sourced from 500+ daily AI sources, scored by relevance.
- Babliy
AI agent that sells on WhatsApp in Darija, 24/7
- NemoChat
Privacy-first messenger without phone, email or account
- FileCast: WiFi File Transfer
WiFi Remote & File Presenter
- INCILOG
Incident management for facilities & operational teams
- Moon In Pixels
Track the Moon with beautiful pixel widgets 🌙
- GitSetGo
Play & Learn Git Commands
- FalconAI – TV Search & Stream
Speak or type. Find anything to watch in seconds.
- Telenow ai
Voice Agent platform :Create and deploy agents and workflows
- CleverCV — Your AI Career Copilot
One Master Profile. Tailor your CV in seconds.
- VTubeXR Live2D avatars with AR
VTubeXR enable dual-camera mode for video and live streaming
- InfraCanvas
See your infrastructure as a live canvas.
- Phonest
our phone habits, roasted in one witty daily card
- removr.pro
Watermarkremoval-AI, Fast, Versitle, Cheap, High Quality
- BingSpotAny
Lightweight, telemetry-free Bing & Spotlight wallpapers.
- RIP TEMPLATES
Canva-editable funeral & memorial templates
- Flingo
7-day trial at 4.77₹ — then voice-call 15+ AI personas live
- Journy
Plan Your Perfect Travel Adventure
- Fused Air Conditioning and Electrical
One Call. Two Trades. Zero Hassle.
- GradePilot
Tagline: 20 free grade calculators for students free
- Expert Movers
movers
- mr-protect.com
1st AI to block explicit content & webcam sex on every app.
- Upsoma Restro
Turn Every Restaurant Order Into a Repeat Customer
- Side Hustle AI Coach
Build your side hustle with AI coaching and guided roadmaps
- Ai Powered Unicode to Inpage Converter
Ai Live Unicode to Urdu InPage Converter and vice versa
- Viral Pin AI
Create Viral Pinterest Pins, Titles & SEO Content with AI
- 25+ Free Online Tools + AI Assistant
An assistant and tool that help you out throughout the day
- coverletter.my
Use AI to study company hires and build cover letters
- TrackSensei
AI production mentor that knows your mix inside out.
- Seamless Texture Generator
Turn any prompt or image into seamless, ready-to-use textures.
- Flaq AI | Image to Video
Animate any image with AI in seconds.
- Stylery AI
Try any look. Still you.
- Kane CLI By TestMu AI
Kane CLI: Browser Automation for AI-Driven Testing | TestMu AI
- GENATATORs: ab initio Gene Annotation With DNA Language Models
Inference of gene structure and location from genome sequences - known as de novo gene annotation - is a fundamental task in biological research. However, sequence grammar encoding gene structure is complex and poorly understood, often requiring costly transcriptomic data for accurate gene annotation. In this work, we benchmark current solutions and develop new methods of gene annotation. We show that pretrained DNA language model (DNA LM) embeddings do not capture the features necessary for precise gene segmentation, and that task-specific fine-tuning remains essential. We comprehensively evaluate the impact of model architecture, training strategy, receptive field size, dataset composition, and data augmentations on gene segmentation performance. We revisit standard evaluation protocols, showing that commonly used per-token and per-sequence metrics fail to capture the challenges of real-world gene annotation. We introduce and theoretically justify new biologically grounded metrics, along with benchmarking datasets that better capture annotation quality. We show that fine-tuned DNA LMs outperform existing annotation tools, generalizing across species separated by hundreds of millions of years from those seen during training, and providing segmentation of previously intractable non-coding transcripts and untranslated regions of protein-coding genes. Our results thus provide a foundation for new biological applications centered on accurate gene annotation.
- BioBrain: A Multi-Agent Framework for Natural Language Driven Quantitative Microscopy Data Analysis
Advances in fluorescence microscopy have dramatically expanded the range of biological questions that can be addressed, enabling quantitative observations of molecular interactions and cellular dynamics with unprecedented spatial and temporal resolution. However, the growing complexity of imaging data has outpaced our ability to analyze them. Despite numerous computational methods exist, they often rely on specialized software environments, heterogeneous data formats, and technical expertise, limiting adoption and widening the gap between data acquisition and quantitative biological interpretation. Here we introduce BioBrain, a multi-agent framework that translates natural-language analytical goals into executable and reproducible microscopy analysis pipelines. Instead of generating analysis code, BioBrain assembles validated analytical methods and can expands its analytical capabilities by integrating existing laboratory scripts into a unified conversational framework. Every selected method and inferred parameter is transparently reported, ensuring traceable and reproducible analyses. On two-channel total internal reflection fluorescence and three-dimensional lattice light-sheet benchmarks, BioBrain exactly reproduces expert-derived results when parameters are specified and degrades predictably and traceably when they are not, while frontier language models generated large, model-dependent quantitative errors despite completing without warning. BioBrain offers a practical path for closing the widening gap between data acquisition and biological discovery, enabling experimental scientists to communicate with computational analysis in the language of biology rather than the language of software.
- Pixten
Restore, enhance, and upscale photos with AI
- Antibody-Antigen Affinity Prediction with Chain-Aware Protein Language Modeling
Motivation: Antibody-antigen affinity determines which antibodies advance in therapeutic discovery, repertoire analysis and affinity maturation, but experimental measurements are sparse relative to the scale of sequence libraries. Structure-based predictors can exploit interface geometry when reliable complexes are available, yet early discovery often requires ranking many heavy-light chain pairs against antigens for which no complex structure exists. Existing sequence-based models are scalable, but frequently compress heavy and light chains into a single antibody representation or concatenate antibody and antigen features obscuring the chain-specific and epitope-specific signals that drive binding. Results: We present AbAffinity, a sequence-only chain-aware three-stream architecture that maintains heavy chain, light chain and antigen as distinct streams. It integrates frozen ESM-2 embeddings with heavy-chain CDR-focused pooling, heavy-light self-attention, adaptive fusion gating and gated cross-attention, training only a compact interaction module. On the SAAINT-DB benchmark, AbAffinity achieves strong predictive performance under ten-fold cross-validation and maintains robust accuracy on novel antigens. It consistently outperforms recent sequence-based models across external benchmarks including SAbDab, AB-Bind and SKEMPI 2.0. Ablation studies highlight the contributions of chain-specific representations, CDR-focused pooling and the gated interaction pathway. Integrated Gradients attributions recover known paratope and epitope residues at structurally validated interfaces. AbAffinity provides a lightweight, explainable sequence-first framework for antibody triage and prioritisation when structural information is limited or unavailable.
- Kelhe
Risk scoring for autonomous AI agents.
- restoo
The control center for your restaurant
- Vox
Vox: Next-Gen Social Web App (Beta)
- Anthropic is under pressure
Inside: Last week's AI, caught up in 5
- 76-year-old woman killed when a Tesla ‘running on auto-pilot’ crashed into her Texas home
The 76-year-old was ‘super healthy’ and ‘would have made it to 100,’ her daughter said
- US scientist John Jumper to leave Google DeepMind for Anthropic
US scientist John Jumper to leave Google DeepMind for Anthropic
- Trump no longer views Anthropic as national security threat
Says AI company responded "very quickly" and "responsibly."
- Are You ’Mass Affluent’ Not ‘Truly Rich’? Sorry, Your Wealth Manager Might Be AI Now
The world of finance is automating, but if you're rich enough, it's reportedly more human than ever.
- Kansas City Pushes Ahead With Facial Recognition on Buses
Kansas City Pushes Ahead With Facial Recognition on Buses PCMag Australia
- Honor Magic V6 - AI Enhancement Pictures
Honor Magic V6 - AI Enhancement Pictures PCMag Middle East
- UK to fund AI weather forecasting as ‘super’ El Niño threatens wave of climate shocks
Exclusive: ‘Our new partnership with the Met Office will help countries protect against extreme weather events’
- Apple’s era of wearable intelligence begins in 2027 and cameras will be a big part of it
Apple's next big AI push may not come through your phone at all. A new report suggests the company is preparing camera-equipped AirPods and its first smart glasses, signaling a major shift toward wearable intelligence.
- Agent 37 Cloud
Give every customer their own Hermes or OpenClaw agent
- Atomic Mail Agentic
Let your agents read, send, and react to email autonomously