本文深入探讨了Odin编程语言中最常被误解的功能——上下文系统。作者澄清了上下文系统的真正目的并非减少参数传递或实现动态作用域，而是为了拦截和修改第三方代码的行为。文章详细介绍了上下文系统的核心组件，包括分配器、断言处理程序、日志记录器和随机数生成器等，并解释了为什么选择隐式指针传递而非线程局部变量的设计决策。通过实际案例，作者展示了如何利用上下文系统解决API限制和第三方库无法修改的问题。对于系统程序员和编程语言设计者而言，这篇文章提供了宝贵的见解，展示了如何在语言层面解决实际开发中遇到的挑战。
原文链接：Hacker News
CoolWolf AI Keyboard is a next-generation Android Chinese input method based on deep learning technology. To address the accuracy issues in Pinyin long sentence input, the developer abandoned traditional word frequency and dictionary algorithms in favor of deep learning technology. This keyboard utilizes Pinyin datasets from Hugging Face for preprocessing, employs a Bi-LSTM attention model for training, and runs on Android phones through int8 ONNX conversion. After local optimization, the keyboard significantly improves its running speed while maintaining model performance. This innovative attempt demonstrates the potential of AI technology in the mobile keyboard sector, providing users with a more accurate and smoother Chinese input experience.
Original Link:V2EX Share & Discover
Today, the web version of GPT Image 1.5, an AI-powered image editor, has officially launched. This tool supports simple image editing, text-to-image generation, and image-to-image generation, providing users with a convenient AI image processing experience. After testing, the author noted that compared to Nano Banana Pro, GPT Image 1.5 delivers more natural and impressive lighting effects. The website is available at https://gpt-image-15.com/, and the author also recommends visiting https://ai-nanobanana.com for reference with Nano Banana Pro. Interested readers can visit the site to try it out and provide feedback on any issues like lag or errors to help the author make further improvements. This tool represents a practical application of AI technology in image generation, showcasing the utility of cutting-edge technology, making it perfect for enthusiasts interested in AI image editing to explore.
Original Link:V2EX Share & Discover
Ford recently announced a major strategic shift, discontinuing production of the all-electric F-150 Lightning pickup truck and instead developing a hybrid EREV version with an expected range of over 700 miles. Meanwhile, its $5.6 billion Blue Oval City plant, originally planned to produce electric trucks, has been adjusted to manufacture gas-powered trucks, with production expected to begin in 2029. This shift stems from insufficient market demand, high costs, and regulatory changes. Ford has also dissolved its battery joint venture with SK Innovation and adjusted battery production plans. The article analyzes the challenges facing electric vehicles, including range issues and cultural factors, suggesting that EREVs may be a transitional solution.
Original link:Hacker News
This article explores the application value of outcome-based pricing models in the AI agent field. The author proposes that unlike traditional usage-based billing, charging based on the results achieved by AI agents better reflects their true value. Using customer support AI agents as an example, the article illustrates how to measure outcomes through objective metrics (such as resolving 30% of tickets). However, comments raise implementation challenges: how to clearly define 'outcomes', who acts as the arbiter, how to measure them programmatically, and how clients might underestimate outcome value for economic motives. Despite these challenges, outcome-based pricing still offers a framework for establishing fairer value exchange between AI service providers and clients, driving AI technology toward more practical applications.
Original Link:Hacker News
As the world's most popular embedded database, SQLite's exceptional reliability stems from an extremely rigorous testing system. This article reveals SQLite's testing architecture in detail, including four independent testing frameworks (TCL Tests, TH3, SLT, dbsqlfuzz) that achieve 100% branch test coverage and MC/DC coverage. Through fuzz testing (like AFL, OSS Fuzz, dbsqlfuzz) to discover potential vulnerabilities, and anomaly testing (memory overflow, I/O errors, crash testing) to ensure system stability. The testing code amounts to 590 times the core code, with dynamic analysis tools (Valgrind, Memsys2) and static analysis further ensuring code quality. These testing strategies are not only applicable to database development but also provide valuable references for high-reliability systems such as AI, chips, and autonomous driving.
Original link:Hacker News
According to recent reports, Google's Gemini 3 Flash model has seen a significant price increase compared to its predecessor. Data shows that Gemini 3 Flash is priced at $0.5 per million input tokens and $3 per million output tokens, while the previous Gemini 2.5 Flash was priced at $0.3 per million input tokens and $2.5 per million output tokens. This means the cost of running benchmarks has more than doubled compared to the previous generation. Despite the substantial price hike, reports indicate that Gemini 3 Flash has reduced hallucination issues compared to the 3 Pro version. This pricing strategy reflects the changing cost trends in AI models, making cost considerations a crucial factor for businesses and developers relying on large language models.
Original Link:Linux.do
最新评论
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