Article URL: https://portswigger.net/research/css-the-bomb-inside-your-inbox Comments URL: https://news.ycombinator.com/item?id=49230066 Points: 5 # Comments: 0
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Open-source cross-platform framework Codename One has merged on-device AI capabilities and Model Context Protocol (MCP) support via a loopback socket in its latest release. The AI surface is organized into three packages covering vision tasks like OCR and face detection, language operations such as translation and identification, and reusable inference sessions for custom TensorFlow Lite models. Android leverages ML Kit while Apple platforms use Vision, Core Image, and Natural Language frameworks, with CPU fallback available where hardware acceleration is absent. All processing runs locally on the device, meaning no images, text, or tensors are sent to Codename One's servers, offering a narrower data exposure path for sensitive content. The MCP channel, designed primarily as a debugging tool, listens only on a loopback socket, limiting its exposure as a potential external control interface.
A self-taught developer with a civil engineering background built a personal AI assistant over time, expanding it into a complex system with memory layers, routing logic, caching, and quality monitoring. Through hands-on experimentation, they discovered that most failures stemmed not from the AI model itself but from the surrounding infrastructure handling sessions, context, and tool calls. They found that prompt cache hit rates depend heavily on request structure stability rather than model capability, achieving around 66–80% cache hits only after standardising prefixes. Routing requests to cheaper models also proved unreliable in multi-turn conversations, where full context and memory are needed to interpret follow-up messages correctly. The developer concludes that real-world agent performance is shaped by workload design and system architecture, not by benchmark results.
A bug in redis-py, the Python client for Redis, caused spurious MaxConnectionsError exceptions in asynchronous cluster setups despite connection capacity being available. The issue arose when a closed connection marked for reconnect was deferred to a background task, leaving a brief window where the pool appeared full to concurrent requests. During this single event-loop gap, any new acquire attempt would incorrectly find the free queue empty and the connection count at its limit. The fix, proposed in PR #4256 addressing issue #4247, ensures that already-closed connections skip the background disconnect task and immediately return their slot to the free pool. A deterministic regression test using asyncio.Event objects was also added to reproduce the exact race condition and verify the corrected behavior.
Article URL: https://www.cnbc.com/2026/08/09/israeli-startup-irregular-linked-to-ai-hacks-openai-anthropic-meta.html Comments URL: https://news.ycombinator.com/item?id=49231022 Points: 13 # Comments: 3
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