1. Apple introduces M4 chip
Total comment counts : 98
Summary
Apple has announced the introduction of the M4 chip, which will be used in the new iPad Pro. The chip is built using second-generation 3-nanometer technology and enables the thin design of the iPad Pro. It features a new display engine that enhances the precision, color, and brightness of the Ultra Retina XDR display. The M4 chip has a new CPU with up to 10 cores and a 10-core GPU that supports hardware-accelerated ray tracing and mesh shading. It also includes Apple’s fastest Neural Engine ever, capable of up to 38 trillion operations per second. The M4 chip delivers a significant leap in performance over the previous iPad Pro with the M2 chip.
Top 1 Comment Summary
The article discusses Apple’s AI strategy of placing inference and learning on edge devices, such as their M4 chip. The strategy aligns with their privacy-first approach, as it avoids sending data to the cloud for processing. Processing AI at the edge offers a better user experience by minimizing latency and dependence on network connectivity. The author welcomes this strategy, as it prevents centralization of AI power in the hands of a few cloud providers.
Top 2 Comment Summary
The article explains that the M4 chip from Apple’s silicon lineup has made significant improvements in both the central processing unit (CPU) and graphics processing unit (GPU), resulting in leading performance per watt. M4 achieves the same performance as the previous M2 chip but at only half the power consumption. Furthermore, when compared to the latest PC chip in a lightweight laptop, M4 can deliver the same performance using only a quarter of the power. The article speculates on whether this impressive progress is due to Apple’s engineering or advancements in TSMC’s 3nm process.
2. A 100x speedup with unsafe Python
Total comment counts : 15
Summary
The article discusses the use of “unsafe Python” to optimize numpy code for image resizing. The author compares the speed of OpenCV’s resizing function to pygame’s resizing function and finds that OpenCV is much faster. However, when using numpy arrays with pygame’s function, the performance is significantly slower. The author discovers that the difference in performance is due to the strides, which determine how data is laid out in memory. By understanding and adjusting the strides, the author is able to achieve a 100x speedup in the code.
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This article discusses the issue of array striding and its impact on programming languages like Go and Rust. The author highlights the problem of multidimensional arrays and the lack of support for subarrays, flattening, and sparse arrays. This results in the need for collection classes and format conversion, causing inefficiencies for users of such arrays. The article points out that languages like FORTRAN and Matlab still have a stronghold in number-crunching due to their better support for arrays.
Top 2 Comment Summary
The article discusses a performance problem in pygame Surface data and offers potential solutions. The author suggests that changing the layout of the pygame Surface data is not possible, and copying the C++ code of cv2.resize is not desirable due to platform-specific optimizations. Instead, it is recommended to submit a pull request to opencv to fix the performance issue for all developers and users. The article provides a link to the specific code section where the author believes the fix should be implemented. The author also suggests using gdb to track down the slow code and obtain a stack trace to identify the issue with the image format.
3. Secure Randomness in Go 1.22
Total comment counts : 17
Summary
This article talks about the improvements made to Go 1.22 in terms of random number generation. It explains the distinction between statistical randomness and cryptographic randomness and how Go is now using a cryptographic random number source in math/rand to improve randomness and prevent developers from accidentally using math/rand instead of crypto/rand. The article also discusses the limitations and drawbacks of previous random number generators, such as linear congruential generators (LCGs), and why they are not suitable for generating truly random numbers. Overall, the update in Go 1.22 aims to provide better randomness and enhance security in applications that require random number generation.
Top 1 Comment Summary
The article discusses how the programming language Go aims to prioritize secure coding practices. It specifically addresses a common mistake involving the predictability of the math/rand global generator, which can lead to serious security issues. The article gives an example of how this mistake was made in the code of a project called rclone, where the use of a secure random number generator was inadvertently changed to a deterministic one. The article applauds Go for deprecating math/rand’s Read function in version 1.20, thus reducing the risk of such security vulnerabilities.
Top 2 Comment Summary
The article is about efficient secure random number generator algorithms, specifically in relation to Go API design. It is part of a series of blog posts on the go.dev website. The post provides information on different algorithms and their implementations for generating random numbers securely and efficiently.
4. Design docs at Google (2020)
Total comment counts : 29
Summary
The article discusses the use of design docs in Google’s software engineering culture. Design docs are informal documents created by the primary author(s) of a software system or application before starting the coding project. These docs outline the high-level implementation strategy, key design decisions, and trade-offs considered. Design docs serve several functions in the software development lifecycle, including early identification of design issues, achieving consensus, addressing cross-cutting concerns, scaling knowledge, and forming an organizational memory. While design docs don’t follow strict guidelines, they should provide a rough overview of the project landscape, goals and non-goals, and trade-offs made. Best practices include using system-context diagrams, sketching API details, discussing data storage, avoiding excessive code, and linking to prototypes. The shape of a design doc depends on the constraint of the solution space.
Top 1 Comment Summary
The author of the article left Google due to what they perceive as an excessive focus on design documentation. When the author created a high-level document for a simple task, a colleague told them that this was not the way things were done and advised them to explore more alternatives. The colleague stated that this was necessary to demonstrate broad consideration. The author also mentions the presence of “fake work” at Google and expresses regret about joining the wrong team.
Top 2 Comment Summary
The author feels that design documents at Google are often written with the promotional committee in mind, rather than focusing on the audience of people who are actually working on the system the document is about.
5. How Python asyncio works: recreating it from scratch
Total comment counts : 8
Summary
The article discusses asyncio, a trendy topic in Python that is used to handle I/O-bound programs. It explains that asyncio is built on top of Python Generators, which are used to make code more memory efficient. Generators are defined as functions that use the yield statement to return data. The article also introduces the concept of the event loop, which is responsible for running and managing tasks in asyncio. Sample code is provided to demonstrate how generators can be used within asyncio. Overall, the article aims to help readers understand how asyncio works by building a simplified version using Python generators.
Top 1 Comment Summary
The article discusses the concept of “busy waiting” in event loops. It mentions a toy implementation that handles it correctly by tracking the next-runnable times of tasks in sorted order. If nothing is currently runnable, the event loop can be put to sleep. The implementation was later extended to allow tasks to have dependencies on sockets or other things, enabling the use of select with a timeout.
Top 2 Comment Summary
The article discusses how asyncio in Python allows for the replacement of the event loop with a custom implementation. In Temporal Python, workflows are represented as custom, durable asyncio event loops, enabling the use of asyncio.sleep as durable timers that can resume on another machine. The article also mentions the issue of blocking the asyncio thread with synchronous calls in Python and suggests the need for a static analysis tool to detect thread-blocking calls.
6. Road resurfacing during the daytime without stopping traffic [video]
Total comment counts : 41
Summary
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Top 1 Comment Summary
The article discusses the details of a bridge, with a video providing more information. The bridge is assembled over two nights at a motorway exit, allowing traffic to bypass it. During the first night, the end ramps are assembled and attached together to create a short bridge. On the second night, the ramps are driven apart, the central section is built, and the entire structure is moved to its final location. The bridge has a total length of 236 meters and a working length of 100 meters underneath. It can flex at the sections’ joins and has a turning radius of 2 kilometers.
Top 2 Comment Summary
The article discusses the author’s observation that a large majority of road works they pass have no workers present. The author suggests that Japan has a better approach, with a larger workforce completing the job overnight. The author also mentions the nostalgia of seeing a person using a shovel, a tool that hasn’t changed much since the 19th century.
7. Cold brew coffee in 3 minutes using acoustic cavitation
Total comment counts : 43
Summary
Engineers from UNSW Sydney have developed a method to make cold brew coffee in under three minutes using sound waves. They connected a bolt-clamped transducer with a brewing basket via a metallic horn to create an ultrasonic reactor. The sound waves generate micro-jets that intensify the extraction of aroma and flavours from the ground coffee. The process can double the extraction yield and caffeine concentration compared to unsonicated samples. The technology could be adapted to existing coffee machines, allowing consumers to make cold brew at home in minutes. Additionally, coffee shops and restaurants could produce on-demand brews comparable to the 24-hour cold brews without needing large semi-industrial brewing units. The sensory study showed that a sonication time between one and three minutes creates a coffee comparable to 24-hour cold brew in terms of taste.
Top 1 Comment Summary
The author discovered that many coffee shops are selling cold coffee as cold brew, even though it is actually brewed hot and then refrigerated. Some shops also believe that cold brew must be served cold, which the author found to be untrue. The author was laughed at for asking for a warm cold brew in one shop and another initially refused to warm it up, claiming it would make the coffee sour (which it didn’t). The author questions whether the acidity of cold brew is lower than hot-brewed coffee and wonders about the process of sonic-brew and how it compares to manually agitating cold brew.
Top 2 Comment Summary
The article discusses the author’s experience with a cold brew coffee machine called Osma Pro. Despite the company that created it going out of business and facing criticism for its price point and performance, the author finds their machine to be effective and enjoys using it daily. The article concludes by suggesting that individuals should research their ideas to see if similar products or concepts already exist before claiming them as new.
8. Pyspread – Pythonic Spreadsheet
Total comment counts : 23
Summary
pyspread is a spreadsheet application written in Python that expects Python expressions in its grid cells. It aims to be the most pythonic spreadsheet and allows users to access Python objects from the cells. It is free software released under the GPL v3 license. Users with experience in Python can directly use Python code in the grid, allowing for greater flexibility. The target user group includes individuals like Clara, a research engineer, who wants to compare different parameter sets quickly, and Peter, who uses CSV files to separate data from code and imports specific modules to avoid computational errors. However, pyspread may not be suitable for users like Donna, who are unfamiliar with programming languages, or Jack, who requires parallelized calculations. User questions and feedback can be directed to the pyspread community board on gitter, while contributions and development discussions can be made through the pyspread issue tracker.
Top 1 Comment Summary
The author commends the “Target User Group” section on a homepage for providing clarity on who the app is intended for and who it is not. They believe this information is important in determining whether or not to use or recommend the app. While some app developers may want everyone to use their app or may not want to specify who it is not for, the author appreciates those who provide such information.
Top 2 Comment Summary
The article suggests creating a software distribution that combines the best alternative software for different tasks. It mentions specific software options for tasks such as spreadsheets, word-processing, 3D modeling, and 2D drawing. The author also expresses interest in suggestions for similar software for tasks such as presentations and database work.
9. A book Stanley Kubrick didn’t want anyone to read is being published
Total comment counts : 14
Summary
The article discusses the publication of a book titled “The Magic Eye: The Cinema of Stanley Kubrick” by Neil Hornick, despite the director’s strong opposition to its publication over 50 years ago. Stanley Kubrick, known for his perfectionism and directing classics such as “Spartacus” and “2001: A Space Odyssey,” threatened legal action to prevent the book from being published after reading a draft of it. Kubrick disliked the book’s format, which included discussions of both positive and negative aspects of his films. Despite the legal threats, the book is now being published with three prefaces that highlight Kubrick’s efforts to block its publication. The author, Neil Hornick, was initially shocked by Kubrick’s reaction and believed his criticisms were not extensive. The book offers an unbiased view of Kubrick’s films and provides a different perspective compared to other literature on the director.
Top 1 Comment Summary
The documentary “Filmworker” follows Leon Vitali, an actor who portrayed Lord Bullingdon in Stanley Kubrick’s film “Barry Lyndon.” After working on the film, Vitali became Kubrick’s personal assistant for over 20 years, although some argue he was treated more like a slave. The documentary reveals the shocking mistreatment Vitali endured, including working long hours, neglecting his family, and sacrificing his health. Despite being paid relatively little by Kubrick, Vitali remained loyal to him until his own death in 2022.
Top 2 Comment Summary
The article discusses a situation where a publisher commissioned a book about Stanley Kubrick’s films and gave Kubrick the power to veto its publication if he did not approve. Kubrick exercised this power and ultimately the book was never published.
10. Faster XML Stream Processing in Go (2019)
Total comment counts : 7
Summary
The article discusses XML processing and compares the speed of stream-processing huge XML files in Go, Python, and C. The author presents a baseline implementation using the standard library’s encoding/xml package in Go, which takes 6.24 seconds to process the XML file. They then compare it to the performance of Python implementations using the xml.etree.ElementTree module and the lxml library. The Python implementations are faster than the Go implementation because they utilize C extensions and libraries for faster XML parsing. The author concludes that Go is about 68% slower than Python for parsing large XML files in a streaming fashion. They also implemented the same program using pure C with libxml, which takes just 0.56 seconds to process the XML file.
Top 1 Comment Summary
The article discusses an optimization story related to the performance of a certain type of software. The author points out that, despite achieving good performance, there is still room for improvement. The article also mentions an issue related to slow parsing of a specific encoding, highlighting that no recent work has been done to address it.
Top 2 Comment Summary
The article discusses the results of rerunning a test comparing the performance of different XML parsing libraries on an M1 Mac Pro computer. The test was conducted on code that is six years old. The results show that the performance of Python’s etree library remains the same over the six-year period, while the lxml library has improved and become faster. The Go language’s standard library performs similarly to Python’s standard library and has also improved in performance with the use of the cgo binding. The article provides a detailed procedure for running the tests and generating the results.