当今社会各行各业都充满着竞争，为此各个公司也都在拼命加班以保持在市场中的地位。但是仍有一些神仙公司在保持着955的工作模式，本文详细整理了几家这样的神仙公司，快来看看都是哪些公司上榜了吧。 Source: 955工作制，神仙公司名单！
Source: [2309.04902] Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-Art A comprehensive survey and guide for applying ML object detection to various industrial applications.
Get ready to dive deep into the inner workings of the Objective-C language and runtime! Each post delves into a specific aspect of the language and explores the details of its implementation. I hope you’ll find this valuable to demystify the language, tackle tricky bugs, and optimize your code for performance. Source: Michael Tsai – Blog – Objective-C Internals
In short: The people you’re talking to aren’t the people who are doing the actual work, The people who are doing the work have no industry experience And the numbers they’re basing their analysis on are probably whatever they found on google. Source: A retiring consultant’s advice on consultants | Hacker News
The only thing that we have come up with (so far!) that fully explains this picture is that the hypothesis is correct: the model is rapidly learning to recognise examples even just seeing them once. Let’s work through each part of the loss curve in turn… Source: fast.ai – Can LLMs learn from a single example?
If you, like me, resent every dollar spent on commercial PDF tools, you might want to know how to change the text content of a PDF without having to pay for Adobe Acrobat or another PDF tool. I didn’t see an obvious open-source tool that lets you dig into PDF internals, but I did discover a few useful facts about...
This brief tutorial shows where some of the most used and quoted sysctl/network parameters are located into the Linux network flow, it was heavily inspired by the illustrated guide to Linux networking stack and many of Marek Majkowski’s posts. Source: GitHub – leandromoreira/linux-network-performance-parameters: Learn where some of the network sysctl variables fit into the Linux/Kernel network flow. Translations: 🇷🇺
As we iterated on FigJam in the early days, we’d fix issues reactively, in response to customer reports or changes in production metrics. But we knew there was a better way. With the help of our new testing framework, we wrote tests covering the majority of essential user flows, and automatically found issues before they hit production—most often before they...
In a milestone for artificial intelligence (AI), the AI system “Swift”, designed by UZH researchers, has beaten the world champions in drone racing – a result that seemed unattainable just a few years ago. The AI-piloted drone was trained in a simulated environment. Real-world applications include environmental monitoring or disaster response. Source: High-speed AI Drone | | UZH