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platformengineering.org | ||
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www.superannotate.com
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| | | | | Discover how to build domain-specific LLMs with expert-labeled data, fine-tuning, and evaluation workflows to deploy high-accuracy AI in production. | |
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emilymstark.com
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| | | | | In my last blog post, I discussed why people often view the web as a uniquely unsuited platform for implementing end-to-end encryption (E2EE). This view is that the web doesn't offer a long-term trustable notion of what the application is. In that earlier post, I explored the idea of treating the application as untrustworthy and isolating sensitive data from it. In this post, I'm going to pontificate on whether web applications are truly less trustworthy than native applications, especially in an E2EE setting, and if so, how we should bridge the gap. The gap is narrower than it appears at first glance, especially with desktop applications. To close it, though, the devil is in the (UX- and deployment-related) details. | |
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lisilinhart.info
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| | | | | AI's role in coding is set to expand, integrating synthesized code and automated suggestions into the developer's toolkit. While this promises greater accessibility for non-traditional coders, expertise will remain essential. | |
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www.harness.io
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| | | Harness MCP Server: Bridging AI systems and DevOps via secure and efficient communication. | ||
