AI News Archive: May 13, 2026 — Part 19
Sourced from 500+ daily AI sources, scored by relevance.
- Anthropic’s Newest Claude Feature Is Here to Help Small-Business Owners With Their Pain Points
Claude for Small Business will assist with payroll, the books, and more. An Anthropic exec explains precisely how.
- Anthropic courts mom-and-pop shops with Claude for Small Business
Anthropic on Wednesday launched Claude for Small Business, a new package of agentic workflows, skills, and connectors designed to automate business tasks common to smaller companies. Claude for Small Business includes workflows for payroll planning, month-end close, business performance monitoring, and marketing campaign management. It also includes skills, or reusable capability packages for AI agents, focused on cash-flow forecasting, invoice chasing, contract review, lead triage, content strategy, and more, Anthropic says. Users get connectors, or integrations, to commonly used platforms including QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, Microsoft 365, Slack, and others. Small business owners can start using the product by installing a plug-in for Claude CoWork, Anthropic’s general digital platform. Anthropic believes small businesses are increasingly interested in AI but have been underserved by the tech industry. “The software industry has been built for ent
- Anthropic’s latest Claude release turns your Mac into a small business powerhouse
If you run a small business from your Mac, you’ll want to pay attention to Anthropic’s latest Claude release. more…
- 5 Big Myths of AI and Agentic AI
AI has been hyped, feared, and often misunderstood. According to Splunk’s “State of Observability 2025” report, only 18 percent of organizations regularly use emerging AI technologies such as agentic AI. […] The post 5 Big Myths of AI and Agentic AI appeared first on Express Computer .
- Execs admit AI makes them value human workers less
As suits say they're burning cash on brainboxes without seeing results
- Nearly every enterprise is investing in AI, but only 5% say their data is ready
Nearly halfway into 2026, enterprises are beginning to see tangible returns on their AI investments. Yet many are discovering that scaling requires something far less glamorous than flashy frontier models and state-of-the-art benchmarking: Clean, interoperable, governed data. According to a new AI Momentum Survey from Dun & Bradstreet, 97% of organizations report active AI initiatives, but just 5% say their data is ready to support them. This reflects the messy reality of AI as enterprises struggle to move beyond experimentation to operationalization. “You do not need enterprise-wide AI-ready data to launch pilots or isolated AI use cases,” said Cayetano Gea-Carrasco , Dun & Bradstreet’s chief strategy officer. “But you do need it to scale AI reliably across mission-critical workflows and systems.” Early gains seen Organizations are all-in on AI in 2026 and view it as a mission-critical imperative, according to the D&B report. Well over half (67%) are seeing “early signs or pockets” of
- AI is ready to take over Python programming, but not much else
Tests of how well 19 large language models (LLMs) complete and perform complicated multi-step tasks has shown that they are both error-prone and, in many cases, unreliable. The findings are contained in a preprint paper, LLMs Corrupt Your Documents When You Delegate , written by Microsoft researchers Philippe Laban , Tobias Schnabel and Jennifer Neville based on a benchmark they created called DELEGATE-52 that allowed them to simulate workflows that might be part of a knowledge worker’s tasks. The paper is currently under review. They said that the benchmark contains 310 work environments across 52 professional domains including coding, crystallography, genealogy and music sheet notation. Each environment consists of real documents totaling around 15K tokens in length, and five to 10 complex editing tasks that a user might ask an LLM to perform. And, they stated in the paper’s abstract: “Our analysis shows that current LLMs are unreliable delegates: they introduce sparse but severe err
- Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities
Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities PCMag
- Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities
Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities PCMag Australia
- Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities
Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities PCMag UK
- Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities
Microsoft's MDASH AI Security System Finds 16 Windows Vulnerabilities PCMag Middle East
- Microsoft's MDASH AI vulnerability scanner finds four critical Windows RCEs
Tops CyberGym public benchmark.
- Federal government spent more than $800M on AI agreements over 3 years
Federal government spent more than $800M on AI agreements over 3 years Toronto Star
- UAE launches AI academy to train next generation of real estate professionals
UAE launches AI academy to train next generation of real estate professionals Arabian Business
- Abu Dhabi's Phoenix Group partners with DC Max to unlock $8 billion European AI data center opportunity, with Lyon, France as first deployment
Abu Dhabi's Phoenix Group partners with DC Max to unlock $8 billion European AI data center opportunity, with Lyon, France as first deployment Gulf News
- Phoenix Group partners with DC Max to unlock $8 billion European AI data center opportunity
Phoenix Group partners with DC Max to unlock $8 billion European AI data center opportunity
- Abu Dhabi's Phoenix Group partners with DC Max to unlock $8bn European AI data centre opportunity
Abu Dhabi's Phoenix Group partners with DC Max to unlock $8bn European AI data centre opportunity The National
- Abu Dhabi's Phoenix Group, DC Max Partner to Develop 18MW AI Data Center in Lyon, France
Abu Dhabi's Phoenix Group, DC Max Partner to Develop 18MW AI Data Center in Lyon, France Entrepreneur Middle East
- Dubai launches AI parking system with automatic payments and fewer fines
Dubai launches AI parking system with automatic payments and fewer fines Arabian Business
- California Suit Claims OpenAI Chatbot Gave Advice That Led to Fatal Overdose
The parents of a man who died of an accidental drug overdose last year sued OpenAI and its founder and CEO Sam Altman in a California court on Tuesday, alleging the man was coached to take a dangerous combination of …
- Princeton scraps honor code and will supervise exams for first time in 133 years because of AI
Princeton’s honor code was implemented in 1893 after students petitioned to get rid of exam proctors
- Expert reveals phrases to avoid chatbots and ‘speak to a human’
An expert has revealed the key phrases to use to avoid customer service chatbots and speak to a real person instead.
- EconAI: Dynamic Persona Evolution and Memory-Aware Agents in Evolving Economic Environments
The integration of large language models (LLMs) in economic simulations has significantly enhanced agent-based modeling, yet existing frameworks struggle to capture the interplay between short-term optimization and long-term strategic planning. Conventional approaches rely on static data-driven pred...
- The Global Intelligence Corridor: TGI AMIRON Alliance Unveils Multi-Continental Sovereign AI Expansion from the Silk Road to the Panama Canal
The Global Intelligence Corridor: TGI AMIRON Alliance Unveils Multi-Continental Sovereign AI Expansion from the Silk Road to the Panama Canal The Arizona Republic
- Samsung Galaxy Z Fold 8 and Flip 8 may debut with Gemini Intelligence
Gemini Intelligence may finally find its dream home on Samsung's upcoming foldables.
- ‘Gemini Intelligence’ reportedly launching with Galaxy Z Fold 8, Flip 8
Google’s “Gemini Intelligence” updates for Android might arrive on Samsung’s new Galaxy Z Fold 8 and other foldables first, a new report claims. more…
- Governments may shape what AI chatbots say by shaping the web they learn from
Ask an AI model the same political question in two different languages, and you may get two very different responses. A new study in Nature suggests one reason why: governments can indirectly influence large language models (LLMs) by shaping the online media environment, and thus the text those systems learn from.
- Governments may shape what AI chatbots say by shaping the web they learn from (IMAGE)
Governments may shape what AI chatbots say by shaping the web they learn from (IMAGE) EurekAlert!
- AI generates first complete models of proteins in motion (VIDEO)
AI generates first complete models of proteins in motion (VIDEO) EurekAlert!
- SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems
Large language model agents increasingly rely on skill libraries for multi-step tasks, yet these libraries can accumulate persistent defects as skills are added, reused, patched, and linked to changing dependencies. We call this failure mode skill technical debt: library-level defects that may not b...
- RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states under time pressure, underscoring a clear need for reliable AI decision support. Existing ICU benchmarks typically treat historical clinician actions...
- Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications
Multi-agent systems rely on communication for information sharing and action coordination, which exposes a vulnerability to attacks. We investigate single-victim communication perturbation attacks against Multi-Agent Reinforcement Learning-trained systems and propose methods that use gradient inform...
- Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation
Visual evidence selection is a critical component of multimodal retrieval-augmented generation (RAG), yet existing methods typically rely on semantic relevance or surface-level similarity, which are often misaligned with the actual utility of visual evidence for downstream reasoning. We reformulate ...
- D-VLA: A High-Concurrency Distributed Asynchronous Reinforcement Learning Framework for Vision-Language-Action Models
The rapid evolution of Embodied AI has enabled Vision-Language-Action (VLA) models to excel in multimodal perception and task execution. However, applying Reinforcement Learning (RL) to these massive models in large-scale distributed environments faces severe systemic bottlenecks, primarily due to t...
- Respecting Self-Uncertainty in On-Policy Self-Distillation for Efficient LLM Reasoning
On-policy self-distillation trains a reasoning model on its own rollouts while a teacher, often the same model conditioned on privileged context, provides dense token-level supervision. Existing objectives typically weight the teacher's token-level signal uniformly across a chain-of-thought sequence...
- A Multi-Agent Orchestration Framework for Venture Capital Due Diligence
We present a fully automated multi-agent framework for corporate due diligence and market analysis in venture capital. The system runs on an event-driven orchestration architecture, combining Large Language Models (LLMs) with real-time web retrieval to synthesize unstructured data into structured in...
- SHM-Agents: A Generalist-Specialist Integrated Agent System for Structural Health Monitoring
Artificial intelligence is increasingly used to simplify complex tasks. In engineering applications of structural health monitoring (SHM), existing specialized algorithms, while effective, often face high implementation barriers, limited interoperability and complex training procedures. To overcome ...
- ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation
Existing API-based agentic systems for RTL code generation are fundamentally misaligned with industrial practice: they assume a golden testbench is available at generation time, rely on closed-source APIs incompatible with chip vendors' air-gapped security requirements, and cannot be trained on vend...
- EgoForce: Robust Online Egocentric Motion Reconstruction via Diffusion Forcing
With recent advances in embodied agents and AR devices, egocentric observations are readily available as input for real-world interactive online applications. However, egocentric viewpoints can only sporadically observe hands, in addition to the estimated head trajectory. We propose EgoForce, an onl...
- CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy
Geometric estimation including depth estimation and scene reconstruction is a crucial technique for colonoscopy which can provide surgeons with 3D spatial perception and navigation. However, geometric ground truth in colonoscopy is difficult to obtain due to narrow and enclosed space of the colon, w...
- PRISM: Prior Rectification and Uncertainty-Aware Structure Modeling for Diffusion-Based Text Image Super-Resolution
Text image super-resolution (Text-SR) requires more than visually plausible detail synthesis: slight errors in stroke topology may alter character identity and break readability. Existing methods improve text fidelity with stronger recognition-based or generative priors, yet they still face two unre...
- EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents
Voice agents, artificial intelligence systems that conduct spoken conversations to complete tasks, are increasingly deployed across enterprise applications. However, no existing benchmark jointly addresses two core evaluation challenges: generating realistic simulated conversations, and measuring qu...
- QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling
Modeling long-range dependencies in sequential data remains a central challenge in machine learning. Transformers address this challenge through attention mechanisms, but their quadratic complexity with respect to sequence length limits scalability to long contexts. State-space models (SSMs) provide...
- AI meeting notes by Snaply
Free & Private AI meeting notes for you Mac
- Unweighted ranking for value-based decision making with uncertainty
As intelligent systems are increasingly implemented in our society to make autonomous decisions, their commitment to human values raises serious concerns. Their alignment with human values remains a critical challenge because it can jeopardise the integrity and security of citizens. For this reason,...
- Defense at AI speed: Microsoft’s new agentic security system tops leading industry benchmark
The post Defense at AI speed: Microsoft’s new agentic security system tops leading industry benchmark appeared first on Source .
- Our new multi-model agentic security system brings together more than 100 specialized agents across frontier and custom models to find exploitable bugs, delivering top performance on the CyberGym benchmark. We used it ahead of Patch Tuesday to help find and fix 16 vulnerabilities. Today we’re announcing that customers can sign up to test it in private preview. Read more…
The post Our new multi-model agentic security system brings together more than 100 specialized agents across frontier and custom models to find exploitable bugs, delivering top performance on the CyberGym benchmark. We used it ahead of Patch Tuesday to help find and fix 16 vulnerabilities. Today we’re announcing that customers can sign up to test it in private preview. Read more… appeared first on Source .
- Cerebras is coming to AWS
Cerebras integrates with AWS for AI computing
- SAP’s AI offer to legacy customers comes with a catch
More than 20,000 SAP customers are “stuck” on legacy ECC systems due to customizations, according to the CEO of SAP partner MyWave, Geraldine McBride, and many won’t migrate anytime soon. At Sapphire 2026, SAP offered them a path to AI, but only if they commit half their maintenance spend to the cloud first. The offer, confirmed by SAP Chief Strategy Officer Sebastian Steinhaeuser during a media briefing, enables SAP to extend limited AI capabilities to customers still running its software on-premises during their transition to cloud ERP. But it comes with a significant condition: Customers must shift at least 50% of their maintenance spending to the cloud before they can enable Joule assistants on premises. It’s a another small crack in SAP’s resolve: For years, it has been upsetting customers using its legacy systems by telling them the only way to access its latest innovations is to migrate to its latest platform , S/4HANA, in the cloud. “There’s no confusion at all” about the lates
- SAP’s AI promises last year? Most are still rolling out
SAP made bold promises about AI at Sapphire 2025 : Knowledge Graph, Joule Studio, and AI Agent Hub would ship by the end of the year. Those tools are now technically available, but adoption has lagged, and SAP is already announcing version 2.0. “Joule Studio adoption has been minimal compared to what we’d like,” said Manoj Swaminathan , SAP’s chief product officer for Business Suite, in a briefing ahead of this year’s Sapphire. The tool “was limited to content-based experiences,” he said. “Anytime more complex agents were involved, it had limited capabilities.” The issue, according to SAP’s chief AI officer Jonathan von Rüden , was that SAP had favored ease of use over power in its original architecture. “People wanted to see more pro-code flexibility,” he said in an interview at Sapphire 2026. “We had gone with a low-code approach. You could give it extension points and tools, but you couldn’t touch the core of it. Now you can build a custom agent, connect it to your own GitHub.” Cust