cyberivy

Search results for “Open Source AI”

Full-text search across every article: title, summary, plain-language explanation, and the complete text — archived stories included. Typos are fine.

297 results for “Open Source AI”

  1. Open Deep Research makes research agents easier to rebuild

    #Open Deep Research#Research Tools#Open Source AI

    What this is about Open Deep Research by David Zhang is an open-source project for iterative research with search engines, web scraping, and large language models. It is not a polished SaaS product and not a replacement

  2. Langflow flaw shows the real risk of exposed AI workflows

    #AI Security#Langflow#CVE-2026-55255

    capacity. What Langflow actually does Langflow is an open-source platform for AI workflows. Users build flows from nodes: a model, a data source, a prompt, a tool call and an output step. These flows can be edited

  3. Microsoft Agent Governance Toolkit: guardrails for AI agents

    #Microsoft#Agent Governance Toolkit#AI Security

    What this is about Microsoft Agent Governance Toolkit is an open-source toolkit for runtime governance of autonomous AI agents. Microsoft describes the project as an MIT-licensed monorepo with packages for policy

  4. NHS closes GitHub repositories over AI security risks

    #AI Security#Open Source#NHS

    11, 2026 while the organization assesses how strongly new AI models can analyze code, architecture notes and configuration details. This is not a routine product story. It exposes a real clash between two security

  5. MIT tests risky image models without producing banned content

    #AI Safety#MIT#Model Auditing

    accuracy on the studied model variants. Why it matters Open model weights and cheap fine-tuning are useful for designers, researchers, and small teams. The same openness also makes it easier to adapt a base model for

  6. E2B gives AI agents safe cloud computers

    #E2B#AI Agents#Sandboxing

    What this is about E2B is infrastructure for AI agents that need to do more than suggest code. The tool provides isolated cloud sandboxes that can be started and controlled through JavaScript and Python SDKs. In effect,

  7. Context7 gives coding agents current documentation

    #Context7#Upstash#MCP

    tool surface. That matters for developers because most AI-coding failures are not dramatic. They often come from small API changes, outdated imports, wrong configuration names, or examples from another version. Context7

  8. SnapOtter runs file processing and local AI on your network

    #SnapOtter#Self-hosted AI#Local AI

    What this is about SnapOtter is an open-source, self-hosted file-processing platform. It combines conventional work such as conversion, compression, and PDF editing with local AI functions for OCR, transcription,

  9. Lightpanda rebuilds browser automation for AI agents

    #Lightpanda#Browser Automation#AI Agents

    What this is about Lightpanda Browser is an open-source headless browser that is not based on Chromium or WebKit. The team is developing it in Zig specifically for web automation and AI agents. This matters because

  10. Onyx brings team knowledge and AI search into one system

    #Onyx#Enterprise Search#Open Source AI

    What this is about Onyx is an open AI platform for teams that brings internal documents, connected applications, and language models into one interface. Users can ask questions about company knowledge, create agents,

Browse all AI news in the archive