AI News Archive: July 16, 2026 — Part 17
Sourced from 500+ daily AI sources, scored by relevance.
- Darajpay
Darajpay, Darajpay crypto wallet, Pay with Darajpay
- MapaWyznaczTrase
Free route planner & distance calculator in 10+ languages
- Image to ASCII
Image to ASCII art — free, no signup, runs in your browser
- Warehouse Management System eCommerce
AI-Powered eCommerce Warehouse Management Software
- FisherLeads
New ecommerce stores the day they launch, with contacts
- Chartberry
Turn your messy spreadsheets into beautiful dashboards
- AI Leaders Online Course
Be more productive with AI. Avoid expensive mistakes.
- Revova
Recover failed Stripe payments with AI written emails
- FixCode
Look up any appliance error code by brand, offline
- EdgeCut AI
The AI video studio where an agent directs the production
- Agnys
See what your AI agents do — and prove it
- PokerCheese
A free browser card game for 1-4 players, no ads or login
- FynixoAI
All in one Ai Tool
- Alpha Buildcon
Modern Building Architectural Design by AlphaBuildcon
- Examing
AI-powered online exams: generate, grade, and proctoring.
- RootNous
Foundational Intelligence
- 河狸- AI声剧引擎
Turn one story idea into characters, plot, and audio scenes.
- AMV Trade Buddy
Evidence-backed Adopt Me trade checks with grounded AI help
- OptiMerc
OptiMerc monitors your websites AI visibility and SEO.
- Diploria AI
Be the brand AI recommends, not the one it ignores.
- AI Image Text Editor
Edit text inside any image, instantly.
- Invent | AI Customer Support Agents for any channel
Your AI business agent platform, on any channel
- Hedy AI
Dominate every meeting with Hedy as your brilliant AI ally
- AI Effect.Art
Turn photos into viral AI videos with templates.
- AI QA Monkey
Instant Website Security Audit & Score. Free Scan & Report in 30s.
- AI Image Generator | Promptsref
Generate stunning AI images, watermark-free.
- Humanio AI
Humanio: AI Text Humanizer to Bypass AI Detectors
- Modeling and Validation of Quality of Control for Edge-Offloaded Collaborative Navigation
Collaborative control in complex environments is severely challenged by stochastic wireless delay and reliability variations, which can degrade navigation, tracking, and collision avoidance. These network-induced uncertainties complicate the maintenance of energy efficiency during collaborative task...
- Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems
A growing class of agentic systems maintain persistent state across sessions through memory files, behavioral preferences, and knowledge bases. While this makes agents more useful and self-improving, it also creates a new attack surface for prompt injections in which malicious instructions can be em...
- Towards an Intention Abstraction Layer for Autonomous Industrial Systems
Modern industrial environments increasingly run many autonomous subsystems at once - schedulers, energy managers, vehicle fleets - each pursuing its own goals while sharing the same physical resources. Because high-level human intentions are translated into low-level control logic and then discarded...
- World-Model-Aware Responsibility Allocation in Heterogeneous Logistics Systems
Logistics systems increasingly mix \emph{autonomous logistic equipment} (ALE) with non-autonomous machinery under a central control system (CS), where the best decision-maker depends on who holds the most current world model, yet authority is fixed at design time. When an ALE's local model and the C...
- AI Prototyper: A Figma Plugin for Decomposition-Based GUI Prototyping with LLMs
Graphical user interface (GUI) prototyping remains a time-consuming activity that demands both design expertise and considerable manual effort. As GUI prototypes are non-code artifacts that evolve alongside requirements throughout the development cycle, automating their generation is directly releva...
- LLM-Driven Approach to Modeling Tool Interoperability in Automotive Domain
Interoperability between heterogeneous modeling tools remains a significant challenge in Model-Driven Engineering (MDE), particularly in the automotive domain where multiple modeling languages, as well as defacto standard proprietary and open-source tools coexist. This paper presents an LLM-driven a...
- MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers
As Model Context Protocol (MCP) servers emerge as the core infrastructure for connecting LLMs with external tools, existing benchmarks leverage real-world MCP servers to evaluate LLM agents' tool-using capabilities. However, these benchmarks overlook the continuous evolution of tool interfaces and f...
- SYNAPSE: A Multi-LLM Orchestrated AI Tutor for Secure Software Development Education with Neurodivergent-First Design
Developers who maintain real systems must continually recognise and remediate vulnerabilities in existing code, yet this skill is rarely trained directly: secure software development is commonly taught only after programming fluency is acquired, and accessibility support is treated as a secondary co...
- Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution
Large Language Models (LLMs) have accelerated the adoption of software development agents, now widely available as Integrated Development Environment (IDE) extensions and standalone applications. While these agents are typically general-purpose, it remains unclear whether specialist agents justify t...
- Setup Complete, Now You Are Compromised: Weaponizing Setup Instructions Against AI Coding Agents
AI coding agents set up projects by reading documentation and installing the dependencies it lists, without verifying their names, sources, or known vulnerabilities. By editing only a README, requirements file, or Makefile, an attacker can redirect the agent to an untrusted registry, a known-vulnera...
- Rethinking Issue Resolution for AI/ML Systems
We advocate for AI/ML issue resolution frameworks tailored to maintenance workflows and the nature of modern AI/ML systems. Existing issue resolution frameworks largely emerged for traditional software maintenance practices and do not explicitly account for characteristics common in AI/ML systems, s...
- Alipay-PIBench: A Realistic Payment Integration Benchmark for Coding Agents
Payment integration is a demanding repository-level software task: agents must select a suitable product, implement coordinated client-server flows, verify payment outcomes, and preserve consistency between transaction and business states. We introduce Alipay-PIBench, a benchmark for evaluating codi...
- AI-Conducted Interviews in Empirical Software Engineering: An Experience Report
Semi-structured interviews are widely used in empirical software engineering (ESE), but they are resource-intensive and difficult to coordinate across schedules, locations, and natural languages. This experience report examines a customized MyGPT used to conduct short, self-administered interviews i...
- A Measurement Study of AI-Environment Realism Gaps in Malware-Analysis Sandboxes
Sandboxing remains a core technique for observing suspicious program behavior, yet environment-aware malware increasingly suppresses execution when analysis is suspected. Prior generations of sandbox evasion focused on virtualization artifacts, timing discrepancies, and wear-and-tear realism. In thi...
- SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings
We introduce the REAL-TSE Challenge, an IEEE SLT 2026 satellite challenge on target speaker extraction~(TSE) from real conversational recordings. Given a multi-speaker mixture and one or more enrollment utterances from a target speaker, participating systems must recover only the target speech. Unli...
- LLM-Based Re-Ranking for Real Estate Search
QuintoAndar Group operates the leading housing marketplace in Latin America for both rentals and sales. The platform replaces traditionally paper-heavy workflows with a fully digital experience, making housing transactions faster and more accessible to tenants, buyers, and landlords in the region. F...
- SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation
Complex knowledge base question answering (KBQA) is commonly approached through either information retrieval over a question-specific subgraph or semantic parsing into an executable logical form. We study the latter paradigm. Recent large language model agents make semantic parsing interactive: they...
- CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops
Recommender systems increasingly shape which content reaches users, making it important to understand whether coordinated activity is amplified beyond the accounts that initiate it. Existing robustness evaluations largely focus on static target-rank changes and do not capture how coordinated interac...
- Accelerating A/B-Tests with Counterfactual Estimation: Reducing Variance through Policy Overlap
Online controlled experiments are the gold standard for hypothesis testing in online platforms. Notwithstanding their ubiquity, they are notoriously expensive to run, and issues of variance hamper statistical power in assessing treatment effects. While standard variance reduction techniques leverage...
- Impact of Expert-Following Strategies in Financial Asset Recommendation
Financial institutions hold rich transaction histories, yet delivering recommendations that simultaneously maximize investment returns and ensure preference alignment remains a significant challenge. Existing approaches, namely return-based and preference-based strategies, each optimize a single obj...
- The evolutionary processes of bacterial aromatic polyketide ketosynthases
Background: The biosynthesis of bacterial aromatic polyketide polyketides (type II polyketides, T2PKs) employs a single set of catalysts (ketosynthases, KSs or KS, with chain length factors, CLFs or KS{beta}) and iteratively assembles a carbon backbone with precise chain length control. Considering the increasing number of T2PKs discovered in laboratory settings, it is necessary to understand the evolution trajectories of KSs and CLFs. Results: We employed our recently developed algorithm, MAAPE, based on large protein language model (PLM) to glean insights into the evolution process of KSs and CLFs. Our findings indicated the evolutionary history of KS and CLF domains from bacterial T2PKSs and identified a shared ancestral cluster (Cluster A), supporting a common origin. Despite structural homology, KSs and CLFs followed distinct evolutionary paths, shaped by coevolution and early horizontal gene transfer. Conclusions: Understanding the evolutionary lineage of these enzymes will illuminate the natural optimization processes of their functions and present opportunities for the rational design of novel polyketides with enhanced efficacy.
- What Do Generative Models Learn About Adaptive Immune Receptor Repertoires? A Benchmark Study
Generative models are increasingly used to model adaptive immune receptor repertoire (AIRR) sequence distributions, promising to decode the sequence diversity shaping immune responses and accelerate the design of therapeutic antibodies and T-cell receptors. Yet it remains unclear whether these models produce biologically meaningful outputs or merely capture surface-level sequence statistics while missing features driven by receptor generation and selection. Rigorous evaluation is needed, but the field lacks established standards, as existing machine learning metrics do not all translate directly to the AIRR domain, given the complex structure of the data and the lack of biological ground truth. Consequently, researchers face difficulties in evaluating the models and selecting appropriate ones, which can critically affect downstream clinical applications. Here, we apply a suite of evaluation metrics tailored to AIRR sequence data and present a systematic comparison of popular generative model families proposed for the AIRR field, including variational autoencoders, long short-term memory networks, antibody language models, selection models, and simple statistical baselines. We focus specifically on the task of learning individual-specific immune receptor repertoires, a clinically relevant challenge with direct implications for personalized immunotherapy, disease monitoring, and vaccine response studies. By analyzing the sequences generated by each model, we identify memorization risks, innovation capabilities, and sensitivity to hyperparameter tuning. Taken together, these results advance the understanding of how current generative models reproduce the biology of individual immune repertoires and lay the groundwork for more principled model development and evaluation.
- Spatio-temporal 3D Mapping of Mouse Cerebellar Vascularization during Embryonic Development
Despite major advances in the study of cerebellar neurogenesis, cerebellar angiogenesis during embryogenesis remains poorly described. Recent advances in tissue clearing, light-sheet microscopy, and artificial intelligence have increasingly enabled detailed 3D modelling of cerebellar vasculature at early developmental stages. Here, vascular networks in mouse embryos from E11 to birth (P0) were labelled with podocalyxin, aSMA, and PECAM-1 antibodies together with the nuclear marker TO-PRO-3 iodide, cleared, imaged by light-sheet microscopy, and finally modelled and quantitatively analyzed using Imaris and VesselVio. Our mapping reveals that the three main paired cerebellar arteries, the superior (SCA), anterior inferior (AICA), and posterior inferior (PICA) cerebellar arteries, emerge sequentially between E11 and E13 and display significant topographical variability comparable to that observed in humans. Morphometric analysis demonstrates distinct developmental dynamics, with SCA growth proportional to cerebellar expansion, whereas the AICA and PICA exhibit accelerated extension during later embryonic stages. Interestingly, the PICA does not reach the cerebellum before birth, highlighting the question of its contribution to embryonic cerebellar vascularization. The intrinsic vascular network evolves from a rudimentary bilayer at E11 into a highly branched architecture organized around radial penetrating vessels, giving rise to collaterals that progressively colonized the cerebellar parenchyma during foliation and lobulation. These vascular changes temporally coincided with the successive stages of cerebellar neurogenesis, supporting an interplay between vascular and neuronal development. Together, our findings provide the first spatio-temporal three-dimensional atlas of cerebellar vascularization during mouse embryogenesis, establishing a reference framework for investigating cerebellar angiogenesis in developmental and pathological conditions.