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Perplexity bolsters AI search security with sandboxing and content scanning

作者 PulseAugur 编辑部 · [2 个来源] ·

Perplexity has enhanced its AI search engine with new security features for its 'Computer' functionality. These updates include parallel scanning of external content by ML classifiers and a BrowseSafe model before agents execute tasks. Additionally, file connector data is encrypted, and uploaded files are automatically deleted after seven days, with all tasks running in hardware-isolated sandboxes. AI

影响 Enhances user trust and data privacy for AI-powered search tools, potentially encouraging wider adoption.

排序理由 The cluster describes product updates and security enhancements for an existing AI tool, not a new model release or fundamental research.

在 X — Perplexity 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Perplexity bolsters AI search security with sandboxing and content scanning

报道来源 [2]

  1. X — Perplexity TIER_1 English(EN) · perplexity_ai ·

    External content is scanned in parallel by ML classifiers and the BrowseSafe model before agents act on it.

    External content is scanned in parallel by ML classifiers and the BrowseSafe model before agents act on it. File connector data is encrypted in transit and at rest, uploaded files automatically delete after 7 days, and more. Read more on the blog: https://t.co/gAomEQkvxi

  2. X — Perplexity TIER_1 English(EN) · perplexity_ai ·

    Computer is secure by default. Every task runs in its own hardware-isolated sandbox with VPC-level storage and compute separation.

    Computer is secure by default. Every task runs in its own hardware-isolated sandbox with VPC-level storage and compute separation. Agents are authenticated with short-lived proxy tokens instead of raw API keys. https://t.co/ohIjY3dboB

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