Sounds emitted by plants under stress are airborne and informative: Cell
We found that plants emit sounds, and that stressed plants—both drought-stressed (Dry) and cut plants (Cut; see STAR Methods)—emit significantly more sounds than plants of any of the control groups (p < e−6, Wilcoxon test for each of the 12 comparisons with Holm-Bonferroni correction). Three controls were used for each plant species and treatment: recording […]
brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI’s GPT-4.
In applications where a user is interacting with a model dynamically, such as chatting with the model, there will typically be portions of the prompt that are never intended to be seen by the user. These hidden portions may occur anywhere, though there is almost always a hidden prompt at the start of a conversation. […]
gyroflow/gyroflow: Video stabilization using gyroscope data
Gyroflow is an application that can stabilize your video by using motion data from a gyroscope and optionally an accelerometer. Modern cameras record that data internally (GoPro, Sony, Insta360 etc), and this application stabilizes the captured footage precisely by using them. It can also use gyro data from an external source (eg. from Betaflight blackbox). […]
布币 – 维基百科，自由的百科全书
布币来源于农具铲子，铲子在上古汉语中称为“钱”。汉语中用“钱”来称呼货币的做法由此产生，延续至今。 Source: 布币 – 维基百科，自由的百科全书
RLHF: Reinforcement Learning from Human Feedback
A narrative that is often glossed over in the demo frenzy is the incredible technical creativity that went into making models like ChatGPT work. One such cool idea is RLHF (Reinforcement Learning from Human Feedback): incorporating reinforcement learning and human feedback into NLP. Source: RLHF: Reinforcement Learning from Human Feedback
Language Interoperability From the Ground Up
With the knowledge you have built up of calling conventions, instruction sets, object files and FFI libraries, you should now be well equipped to explore how languages not mentioned in this post would call functions written in other languages. Source: Language Interoperability From the Ground Up
MRSK (Zero Downtime Web Application Deployment Tool)
The key feature is one that I care about deeply: it enables zero-downtime deploys by running all traffic through a Traefik reverse proxy in a way that allows requests to be paused while a new deployment is going out—so end users get a few seconds delay on their HTTP requests before being served by the […]
Scale is Poison
Scale dehumanizes. Resisting the pull of scale is a recipe for a happy life. Source: Scale is Poison
Payments 101 for a Developer · juspay/hyperswitch Wiki
Source: Payments 101 for a Developer · juspay/hyperswitch Wiki
光刻机等精密控制系统中会用到哪些自动控制技术（算法等）？ – 知乎
我对直线电机的控制略有研究，因此较为了解粗扫描过程。在该过程中，最常用的控制方式是iterative learning control（ILC），即迭代学习控制。迭代学习控制本身是一个前馈控制方案，通过多次“试运行”收集系统中的干扰和噪声，之后人为地将产生的控制信号直接输出给直线电机，以达到提前补偿系统误差的效果。目前，很多研究ILC的文章，其应用场景就是光刻机或者晶圆扫描平台。2020年IFAC世界大会上Technische Universiteit Eindhoven的Maarten Steinbuch教授组介绍了他们对晶圆扫描平台采用的主要控制方法就是ILC。因为Maarten Steinbuch教授的实验室和ASML有着深度合作，我估计ASML在实际的光刻机上也用了该控制方法。我们都知道，目前世界上的唯一的光刻机巨头就是ASML，但是在几年之前，光刻机领域彼时还有两个巨头，即佳能和尼康。University of Califonia，Berkeley的Masayoshi Tomizuka教授组和尼康有着密切的合作，他们之前用的精密控制方法也多是ILC。此外，我了解到的哈工大的谭久彬院士组也做光刻机方面 Source: 光刻机等精密控制系统中会用到哪些自动控制技术（算法等）？ – 知乎