AI News Archive: May 5, 2026 — Part 25

Sourced from 500+ daily AI sources, scored by relevance.

• Attention: What Prevents Young Adults from Speaking Up Against Cyberbullying in an LLM-Powered Social Media Simulation

  Interactive, multi-agent social simulation systems have shown promise for helping users practice navigating various complex social situations across domains. This paper asks: To what extent can such systems help young adult (YA) bystanders speak up publicly against cyberbullying, a task often thwart...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03287v1
• The Fragility of AI Companionship: Ontological, Structural, and Normative Uncertainty in Human-AI Relationships

  As generative AI chatbots become more personalized and emotionally responsive, they increasingly serve as companions, friends, and romantic partners. Yet these relationships are accompanied by significant uncertainty: users question the AI's identity and agency, the authenticity of its emotional res...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03367v1
• Can AI Help You Get Over Your Breakup? One Session with a Belief-Reframing Chatbot Shows Sustained Distress Reduction

  Romantic breakups are among the most common and intense sources of psychological distress. We evaluated *overit*, a single-session AI chatbot that uses cognitive reappraisal to address breakup distress, informed by memory reconsolidation theory. In a pre-registered randomized controlled trial, 254 a...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03261v1
• KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Code

  Formal verification provides the highest assurance of software correctness and security, but its application to large-scale, evolving systems remains a major challenge. While large language models (LLMs) have shown promise in automating proof generation, they often fail in real-world settings due to...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03822v1
• GPUBreach: Privilege Escalation Attacks on GPUs using Rowhammer

  NVIDIA GPUs with GDDR memories have been shown susceptible to Rowhammer-based bit-flips, similar to CPUs. However, Rowhammer exploits on GPUs have been limited to injecting untargeted bit-flips in victim data like weights of machine learning models, to degrade model accuracy, unlike CPU exploits sho...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03812v1
• The Infinite Mutation Engine? Measuring Polymorphism in LLM-Generated Offensive Code

  Malware authors have traditionally relied on polymorphic techniques to produce variants in the same malware family, complicating signature-based detection. Integrating generative AI into offensive toolchains enables attackers to synthesize structurally diverse payloads with identical behavior, raisi...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03619v1
• MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents

  Persistent external memory enables LLM agents to maintain context across sessions, yet its security properties remain formally uncharacterized. We formalize memory poisoning attacks on retrieval-augmented agents as a Stackelberg game with a unified evaluation framework spanning three attack classes ...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03482v1
• ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection

  The rise of Large Language Model (LLM) agents, augmented with tool use, skills, and external knowledge, has introduced new security risks. Among them, prompt injection attacks, where adversaries embed malicious instructions into the agent workflow, have emerged as the primary threat. However, existi...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03378v1
• SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents

  LLM-Agents have evolved into autonomous systems for complex task execution, with the SKILL.md specification emerging as a de facto standard for encapsulating agent capabilities. However, a critical bottleneck remains: different agent frameworks exhibit starkly different sensitivities to prompt forma...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03353v1
• Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours

  AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a primary defense, current approaches force operators into manual, library-specific workflows. Operators spend weeks hand-crafting workflows - assembl...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.04019v1
• Graph Reconstruction from Differentially Private GNN Explanations

  Regulatory frameworks such as GDPR increasingly require that ML predictions be accompanied by post-hoc explanations, even when raw data and trained models cannot be released. Differential privacy (DP) is the standard mitigation for the residual privacy risk of releasing these explanations. We show t...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03388v1
• Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystems

  Dependency confusion attacks exploit a structural gap in software distribution: once a package is installed, there is no cryptographic proof of which registry distributed it. Every existing defense is configuration-based and fails silently when misconfigured. We present a cryptographic distribution ...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03309v1
• Mitigating False Positives in Static Memory Safety Analysis of Rust Programs via Reinforcement Learning

  Static analysis tools are essential for ensuring memory safety in Rust programs, particularly as Rust gains adoption in safety-critical domains. However, existing tools such as Rudra and MirChecker suffer from high false positive rates, which diminish developer trust, increase manual review effort, ...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.04000v1
• Beyond Rules: LLM-Powered Linting for Quantum Programs

  As quantum computing transitions from theoretical experimentation to its practical application, the reliability of quantum software has become a critical bottleneck. Traditional static analysis techniques for quantum programs, primarily rule-based linters, are increasingly inadequate; they struggle ...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03943v1
• Multi-Agent Systems for Root Cause Analysis in Microservices

  Recent advances in large language models (LLMs) have enabled early attempts to automate root cause analysis (RCA) in microservice-based systems (MSS). Yet, prior works typically rely on a linear reasoning process that proceeds along a single diagnostic path. In this paper, we propose LATS-RCA, an LL...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03505v1
• Deep Graph-Language Fusion for Structure-Aware Code Generation

  Pre-trained Language Models (PLMs) have the potential to transform software development tasks. However, despite significant advances, current PLMs struggle to capture the structured and relational attributes of code, such as control flow and data dependencies. This limitation is rooted in an archite...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03689v1
• ProgramBench: Can Language Models Rebuild Programs From Scratch?

  Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain, and grow codebases over extended periods with minimal human oversight. Such settings require models to make high-level software architecture decision...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03546v1
• MiniMind-O Technical Report: An Open Small-Scale Speech-Native Omni Model

  MiniMind-O is an open 0.1B-scale omni model built on the MiniMind language model. It accepts text, speech, and image inputs, and returns both text and streaming speech. The release includes model code, checkpoints, and the main Parquet training datasets for text-to-audio, image-to-text, and audio-to...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03937v1
• Beyond Similarity Search: A Unified Data Layer for Production RAG Systems

  Retrieval-Augmented Generation (RAG) systems have become the standard architecture for grounding large language models in organizational knowledge. Yet production deployments consistently expose a gap between clean prototype performance and real-world reliability. This paper identifies three root ca...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03275v1
• Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems

  Reasoning-intensive retrieval aims to surface evidence that supports downstream reasoning rather than merely matching topical similarity. This capability is increasingly important for agentic search systems, where retrievers must provide complementary evidence across iterative search and synthesis. ...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.04018v1
• Domain-Adaptive Dense Retrieval for Brazilian Legal Search

  Brazilian legal retrieval is heterogeneous, covering case law, legislation, and question-based search. This makes training dense retrievers a trade-off between stronger domain specialization and broader robustness across retrieval types of search. In this paper, we explore this trade-off using three...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.04005v1
• Aspect-Aware Content-Based Recommendations for Mathematical Research Papers

  Content-based research paper recommendation (CbRPR) has seen advances in computer science and biomedicine, but remains unexplored for mathematics, where paper relatedness is more conceptual than explicit textual or citation-based similarity. Mathematics papers may be connected through shared proof t...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03861v1
• Revisiting General Map Search via Generative Point-of-Interest Retrieval

  Point-of-Interest (POI) retrieval aims to identify relevant candidates from massive-scale POI databases, serving as a cornerstone for diverse location-based services. However, in general map search scenarios, conventional POI retrieval methods are increasingly challenged by underspecified user queri...

  📄 ResearchMay 5, 2026http://arxiv.org/abs/2605.03397v1
• Comparative single-cell transcriptomic roadmap of mammalian fetal ovarian development

  Early ovarian development establishes the cellular basis of female reproduction, yet its cellular composition and developmental dynamics remain poorly characterized across mammalian species. Here, we generated a cross-species single-cell transcriptomic atlas of early female gonadal development in cattle (E38-E112), human (PCW6-16), and mouse (E11.5-E18.5), integrating 107,930 cells across comparable developmental windows, spanning sex determination and early ovarian differentiation. We identified 11 shared gonadal cell types across three species, including germ cells and granulosa cells, and uncovered a previously undescribed bovine-specific cell population with steroidogenic features, suggesting species differences in ovarian somatic lineage development. Epigenetic regulators exhibited dynamic activation in germ cells and granulosa cells. Developmental trajectory analysis revealed shared and species-specific genes associated with germ cell and granulosa cell development, including con

  📄 ResearchMay 5, 2026https://www.biorxiv.org/content/10.64898/2026.05.01.721341v1?rss=1
• immuneKG: An Immune-Cell-Aware Knowledge Graph Framework for Target Discovery in Immune-Mediated Diseases

  Biomedical knowledge graphs have emerged as foundational infrastructure for AI-driven drug discovery, yet their translational impact on novel target identification in immune-mediated diseases remains limited. Here we present immuneKG, a multimodal knowledge graph centred on autoimmune diseases, constructed through biologically meaningful feature reprogramming of disease nodes to enable deep mechanistic modelling of immune-related disorders. immuneKG introduces a new entity class immune_cell, and four original directed relation types, together adding 9,105 novel triples absent from all existing biomedical KG schemas. Disease nodes are endowed with three novel modal feature sets quantifying immune homeostatic imbalance: autoantibody profiles, cytokine signatures, and HLA genotypes, complemented by systemic involvement scores and genetic features. The graph encompasses over 407,000 training triples across 7,287 entities and 32 relation types. Applied to inflammatory bowel disease (IBD), i

  📄 ResearchMay 5, 2026https://www.biorxiv.org/content/10.64898/2026.04.30.721823v1?rss=1
• Transfer Learning Enables Drug-Target Interaction Prediction in Data-Scarce One-Carbon Metabolism

  Predicting drug-target interactions (DTIs) with deep learning offers opportunities to accelerate drug discovery, yet performance is constrained by the scarcity of target-specific training data. This is a particular challenge for mitochondrial one-carbon (1C) pathway enzymes, which are attractive therapeutic targets but remain pharmacologically understudied. Mitochondrial 1C metabolism supplies glycine, reducing equivalents, and 1C units critical for nucleotide synthesis, and has emerged as a key pathway in cancer and fibrosis. SHMT2 and MTHFD2, two key 1C enzymes, support collagen production in fibroblasts, blocking either prevents TGF-{beta}-induced glycine and collagen accumulation. Here, we developed transfer learning-based deep learning models to predict interactions between approved drugs and SHMT2 or MTHFD2 despite minimal target-specific training data, pre-training on large datasets from related enzymes before fine-tuning to these targets. Virtual screening of the DrugBank libra

  📄 ResearchMay 5, 2026https://www.biorxiv.org/content/10.64898/2026.04.30.721937v1?rss=1
• Machine learning approaches for the identification and analysis of enterotoxin genes in Staphylococcus aureus genomes

  Staphylococcus aureus produces a broad range of enterotoxins that act as superantigens, disrupting host immune responses and resulting in a myriad of clinical symptoms. However, large-scale analyses determining enterotoxin gene diversity, lineage structure and isolate metadata remain scarce. We analysed 15,887 S. aureus RefSeq genomes using a machine learning pipeline combining profile Hidden Markov Model-based enterotoxin gene identification, lineage typing, gene profile-based strain clustering and association rule mining using a broad range of gene and metadata features. This approach identified 35 distinct enterotoxin genes and five variant forms, including two putative novel enterotoxin genes, sel34 and sel35. HDBSCAN clustering distinguished 45 enterotoxin gene profile groups, revealing strong associations between the two major egc enterotoxin gene cluster variants (OMIWNG and OMIUNG) and Clonal Complex membership: CC5, CC22 and CC45 with OMIWNG; CC30 and CC121 with OMIUNG. Integr

  📄 ResearchMay 5, 2026https://www.biorxiv.org/content/10.64898/2026.05.01.722155v1?rss=1
• DOMINO: Learning Domain Co-occurrence for Multidomain Protein Design

  Multidomain proteins arise through the reuse and recombination of structural domains, yet natural architectures represent a sparse, structured sample of the possible domain-combination space. Here, we introduce DOMINO, a two-stage framework that learns domain co-occurrence from TED-annotated multidomain proteins and uses the learned patterns to generate new multidomain sequences. DOMIN, a contrastive retrieval model, embeds domains into a latent compatibility space and retrieves candidate partners for a query domain from a TED-derived domain pool, including pairings not observed in the TED-derived co-occurrence set. DOMO, a conditional autoregressive sequence model, converts each retrieved domain pair into a full-length protein sequence by jointly generating the specified domain regions and the non-domain sequence context between and around them. DOMIN recovers hierarchical patterns of natural domain co-occurrence and expands the observed CATH homologous-superfamily co-occurrence netwo

  📄 ResearchMay 5, 2026https://www.biorxiv.org/content/10.64898/2026.05.01.721929v1?rss=1
• Microsoft, Google push AI agent governance into enterprise IT mainstream

  Microsoft and Google are adding new controls for AI agents, as enterprise IT teams try to keep up with tools that can access corporate data and act across business applications. Microsoft’s Agent 365 , announced last November and made generally available for commercial customers on May 1, is designed to help organizations discover, govern, and secure AI agents, including those operating across Microsoft, third-party SaaS, cloud, and local environments. Google’s new AI control center for Workspace, announced this week, focuses more specifically on giving administrators a centralized view of AI usage, security settings, data protection controls, and privacy safeguards within Workspace. The timing reflects a shift in enterprise AI use . Many companies are no longer just testing chatbots, but are beginning to use agents that can reach corporate systems and carry out tasks on behalf of users. Analysts said the shift changes how CIOs and CISOs should think about AI agents inside the enterpri

  🌐 MovesMay 5, 2026https://www.computerworld.com/article/4167054/microsoft-google-push-ai-agent-governance-into-enterprise-it-mainstream.html
• Low-Hallucination RAG for Mathematical Question Answering: A Trustworthy Generation Method Based on Retrieval Hygiene, Step-Tree Reasoning, and Symbolic-Solver Feedback

  Despite the remarkable advancements of Large Language Models (LLMs), their application in the mathematical domain is frequently hindered by “hallucinations,” characterized by logical inconsistencies, numerical fabrication, and the inability to handle ...

  📄 ResearchMay 5, 2026https://dl.acm.org/doi/10.1145/3803730.3803757
• DeepXL Corp

  AI fraud detection for documents, IDs, and images

  🧰 ToolsMay 5, 2026https://www.producthunt.com/products/deepxl-ai?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+the500feed+%28ID%3A+283491%29
• Apple can’t make chips fast enough, but that’s only part of the story

  Apple has held “exploratory” talks about manufacturing processors for its devices in the US, Bloomberg reports . The move seems to reflect Apple’s need to secure additional chip supplies to meet growing demand for its products, but could also represent a contingency plan to reduce the company’s reliance on Taiwan Semiconductor Manufacturing Company (TSMC’s) advanced manufacturing facilities in Taiwan. I doubt this means Apple doesn’t want to work with TSMC, nor does it mean TSMC is cooling on Apple. I suspect company management is far more concerned about what might happen in the event China attacks TSMC’s home nation. Contingency planning That concern seems legitimate in the context of unravelling of international relations and a recently-disclosed warning the CIA gave to tech leaders back in 2023. Executives from Apple, AMD, and Qualcomm were all warned that China might attack Taiwan. Such an attack would comprise a huge threat to the entire tech industry . Speaking at the World Econ

  🌐 MovesMay 5, 2026https://www.computerworld.com/article/4167296/apple-cant-make-chips-fast-enough-but-thats-only-part-of-the-story.html
• Apple could turn to Samsung as a plan B for its iPhone and Mac chips

  Intel could play a part as well.

  🌐 MovesMay 5, 2026https://www.androidauthority.com/apple-us-chip-manufacturing-samsung-intel-3663509/
• Apple Eyes Intel and Samsung as Backup US Chipmakers

  Apple has held "exploratory" talks with Intel and Samsung about manufacturing the main processors for its devices in the United States, reports Bloomberg ($). Apple is said to have had early-stage talks with Intel about using its chipmaking services, while Apple executives have reportedly visited a Samsung plant under construction in Texas that will also make advanced chips. The talks are said to be preliminary, and no orders have been made so far, according to the report's sources who asked not to be identified. Apple is also said to have concerns about using technology that is not made by its longtime chip partner, Taiwan Semiconductor Manufacturing Company (TSMC), so the talks could still go nowhere. Apple is said to be seeking potential additional suppliers beyond TSMC as a way to avoid recent shortages almost entirely driven by the current build-out of AI data centers. Heavy demand for Mac mini and Mac Studio models - sought-after because of their suitability for running local AI

  🌐 MovesMay 5, 2026https://www.macrumors.com/2026/05/05/apple-talks-intel-samsung-us-chipmakers/
• Chief of Staff to the Managing Director of AI

  Chief of Staff to the Managing Director of AI Built In

  🌐 MovesMay 5, 2026https://builtin.com/job/chief-staff-managing-director-ai/8996379
• Intel is bringing a chip to every computing category at Computex. The last time it could do that, it was the company everyone was trying to catch.

  Intel will arrive at Computex 2026 in Taipei on 2 June with something it has not had in a decade: a product in every computing category built on a single manufacturing story. Panther Lake, the laptop chip launched at CES in January, is expanding to handhelds with Arc G3 and Arc G3 Extreme processors designed […] This story continues at The Next Web

  🌐 MovesMay 5, 2026https://thenextweb.com/news/intel-computex-2026-18a-panther-nova-lake-ai-pc
• ATxSummit 2026 Brings Global Leaders to Singapore to Chart AI's Future Across Asia

  ATxSummit 2026 Brings Global Leaders to Singapore to Chart AI's Future Across Asia The Straits Times

  🌐 MovesMay 5, 2026https://www.straitstimes.com/paid-press-releases/atxsummit-2026-brings-global-leaders-to-singapore-to-chart-ais-future-across-asia-20260505
• Facing AI, data and scale imperatives at the 2026 GEOINT Symposium

  Facing AI, data and scale imperatives at the 2026 GEOINT Symposium SpaceNews

  🌐 MovesMay 5, 2026https://spacenews.com/facing-ai-data-and-scale-imperatives-at-the-2026-geoint-symposium/
• Oracle will patch more often to counter AI cybersecurity threat

  Oracle plans to issue security patches for its ERP, database, and other software on a monthly cycle, rather than quarterly, to respond to the increased pace of AI-enabled software vulnerability discovery. Other software vendors, notably Microsoft, SAP, and Adobe, already release patches on a monthly beat, always on the second Tuesday of each month . Oracle, though, is taking an off-beat approach: It will release the first of its monthly Critical Security Patch Updates (CSPUs) on May 28, the fourth Thursday, and after that, it will release its patches on the third Tuesday of each month — a week after the other vendors — with the next batches arriving on June 16, July 21, and August 18, it said earlier this week . The new CSPUs “provide targeted fixes for critical vulnerabilities in a smaller, more focused format, allowing customers to address high-priority issues without waiting for the next quarterly release,” Oracle said. It will issue a cumulative Critical Patch Update each quarter,

  🌐 MovesMay 5, 2026https://www.cio.com/article/4167337/oracle-will-patch-more-often-to-counter-ai-cybersecurity-threat-2.html
• Stack AV unveils new autonomous truck after years in stealth mode

  The company was founded by former Argo AI executives after that venture shut down in 2022.

  🌐 MovesMay 5, 2026https://www.bizjournals.com/pittsburgh/news/2026/05/05/stack-av.html?ana=brss_6150
• AssemblyAI Voice Agent API vs OpenAI Realtime API: Which should you use?

  Compare AssemblyAI Voice Agent API and OpenAI Realtime API

  🌐 MovesMay 5, 2026https://assemblyai.com/blog/assemblyai-voice-agent-api-vs-openai-realtime-api
• ‘Without me, OpenAI wouldn’t exist,’ says Elon Musk as courtroom clash with Sam Altman turns personal — and exposes a deeper fight over who really built the company behind ChatGPT

  Elon Musk’s claim that OpenAI wouldn’t exist without him lays bare a deeply personal battle with Sam Altman over credit, control, and the future of the company behind ChatGPT.

  🌐 MovesMay 5, 2026https://www.techradar.com/ai-platforms-assistants/chatgpt/without-me-openai-wouldnt-exist-says-elon-musk-as-courtroom-clash-with-sam-altman-turns-personal-and-exposes-a-deeper-fight-over-who-really-built-the-company-behind-chatgpt
• Build a voice research agent with Render Workflows and AssemblyAI

  Build a voice research agent with Render Workflows and AssemblyAI

  🌐 MovesMay 5, 2026https://assemblyai.com/blog/voice-agent-render-workflows
• Build Voice Agents in Your AI Coding Tool

  Build voice agents faster with the dg CLI, MCP server, and the deepgram/skills repo. Three agentic engineering tools that make Deepgram a first-class citizen in Claude Code, Cursor, Windsurf, Codex, and Aider.

  🌐 MovesMay 5, 2026https://deepgram.com/learn/agentic-engineering-tools-for-voice-ai-builders
• A Reference-Free Scoring Framework for Question Answering: Evidence-Based Credibility Assessment

  Evaluating question answering (QA) systems traditionally relies on human-annotated reference answers, a paradigm that faces practical limitations in real-world, dynamic applications where references are unavailable, expensive to produce, or quickly become

  📄 ResearchMay 5, 2026https://dl.acm.org/doi/10.1145/3803730.3803759
• There’s a big new AI startup in town. Meet Blitzy and its Boston investors.

  There’s a big new AI startup in town. Meet Blitzy and its Boston investors. The Boston Globe

  🌐 MovesMay 5, 2026https://www.bostonglobe.com/2026/05/05/business/blitzy-ai-software-cambridge-unicorn-startup/
• 'AI creates jobs': Nvidia CEO Jensen Huang once again says workers have nothing to fear

  Nvidia CEO Jensen Huang says AI is the "United States’ best opportunity to re-industrialize".

  🌐 MovesMay 5, 2026https://www.techradar.com/pro/ai-creates-jobs-nvidia-ceo-jensen-huang-once-again-says-workers-have-nothing-to-fear
• Deepfake fraud: How AI scams threaten Middle East businesses

  Deepfake fraud: How AI scams threaten Middle East businesses

  🌐 MovesMay 5, 2026https://www.khaleejtimes.com/business/tech/deepfake-fraud-how-ai-scams-threaten-middle-east-businesses
• Spot deepfakes: How to avoid AI scams and protect your money

  Spot deepfakes: How to avoid AI scams and protect your money

  🌐 MovesMay 5, 2026https://www.khaleejtimes.com/business/tech/spot-deepfakes-how-to-avoid-ai-scams-and-protect-your-money
• Google readies ‘AI Ultra Lite’ plan and explicit ‘usage limits’ for Gemini

  Google is quietly preparing a new “AI Ultra Lite” subscription tier to slot between its $20 Pro and $250 Ultra plans, plus a dedicated dashboard for subscribers to see their remaining token budget. more…

  🌐 MovesMay 5, 2026https://9to5google.com/2026/05/05/google-ai-ultra-lite-gemini-usage-limits/