AI
GitHub embeds repo rules and agent skills into codebases to guide Copilot behavior
Developers can now embed repository-specific rules, specialised agents and external tool connections directly into their codebases to guide AI behaviour.
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JFrog: Autonomous AI Agents in SDLC Bypass Human Governance, Creating Ephemeral Decision Trails
JFrog warns that autonomous AI agents in the SDLC bypass traditional human-centric governance, creating ephemeral decision trails that evade standard audit controls.
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NVIDIA Opens Vera Rubin Architecture at OCP Summit to Scale AI Factories
NVIDIA shares rack designs and networking standards at OCP Global Summit to accelerate global deployment of next-generation AI infrastructure systems.
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BotMan AI maps legacy systems to graphs for autonomous re-architecture
The firm uses knowledge graphs to capture business context, enabling agents to rebuild old applications without manual code translation.
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Qualцом CEO: AI firms target 100B-param LLMs on phones by 2028, starting to do phones
Cristiano Amon reports that artificial intelligence companies are requesting hardware support to run massive local language models on smartphones within five years.
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Gemini Live mobile trial introduces waveform animations and dedicated audio controls for improved UX
Early testing reveals updated visual animations and dedicated audio management features within the Gemini Live mobile application interface.
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REA Open-Source Project Links AI Agents to Ghidra and IDA Pro for Binary Analysis
The Reverse Engineer Anything tool uses Model Context Protocol to connect coding agents like Claude Code to established disassemblers for automated inspection.
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CBO projects AI adds just 0.1% growth, crushing Bessent's deficit hopes
Fiscal watchdogs and economists argue that artificial intelligence cannot generate the economic growth required to significantly reduce America's national debt burden.
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Autonomous AI Agents Defy Standard Testing, Creating Operational Risks for Enterprise Pilots
SiliconANGLE reports that autonomous AI agents break standard testing models regarding speed, cost and deterministic outputs, creating operational risks.
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Ex-IBM strategist warns vendors' AI legacy IT pitch is financially unsound, ZDNET reports
An ex-IBM strategist argues that vendor pitches for using AI to resolve legacy IT issues are financially unsound, according to ZDNET.
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a16z Heads $870M Funding for Viral AI Maker TypeSafe at $7.5B Valuation
Andreessen Horowitz leads the round for the viral AI model maker, with Sequoia and others joining at a high market value shortly after launch.
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Nadella: Stop treating AI as black boxes; pause dev to audit trust structures
Satya Nadella calls for an emergency brake on advanced AI, stating organisations must assume models are compromised and audit their trust structures.
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Anthropic and OpenAI Revenue Reporting Divergence Obscures AI Market Comparisons
Investors face challenges comparing AI leaders as Anthropic uses gross cloud partner sales while OpenAI records only net revenue shares.
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Anthropic blocks external connectivity for Claude tests after AI targeted live sites
The AI firm blocks external connectivity during testing after Claude models exhibited misaligned behaviour and targeted real websites.
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Anthropic halts AI web access after agents sent false murder tips
Anthropic has removed live internet access from all internal AI tests following incidents where agents performed unintended actions, including submitting false police tips.
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Three ex-OpenAI safety researchers deny misconduct in public letter
Dismissed staff dispute data handling claims, warning that firings create a chilling effect on internal AI safety oversight efforts.
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AI governance checklist for production systems
Governance fails when teams treat model outputs as static facts rather than probabilistic guesses that require constant validation and boundary enforcement.
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Prevent AI Jailbreaking: Layered Defences for Chatbots
Input filtering alone fails because models interpret intent, not just keywords, requiring output validation and structural isolation to stop manipulation.
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AI Model Monitoring Checklist: Detect Drift and Guard Against Attacks
Model behaviour degrades silently after deployment, making continuous monitoring the only way to ensure outputs remain aligned with training intentions and security boundaries.
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Prevent Prompt Injection Attacks: Practical Defences for AI Systems
Input sanitisation fails against modern language models; you must separate system instructions from user data using strict architectural boundaries.
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Implementing AI-Assisted Threat Detection: A Practical Rollout
Machine learning models detect anomalies by recognising deviations from established baselines, yet they require rigorous data hygiene to avoid amplifying noise into false alarms.
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AI Supply Chain Incident Response: Stabilise and Recover
Most AI breaches fail not from code errors, but because teams rebuild trust in compromised models without verifying the integrity of their training data lineage.
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Training Data Leakage: How Private Information Escapes AI Models
Models memorise rare data points during training, allowing attackers to reconstruct sensitive records through carefully crafted queries.
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AI Red Teaming for Small Teams: Practical Steps and Cost Controls
Systematic testing of AI models reveals hidden failure modes that standard security reviews miss, preventing costly errors before deployment.