The claim that kerosene saved sperm whales from extinction is a myth. While kerosene replaced sperm whale oil in lamps and other applications, this shift occurred after whale populations had already drastically declined due to overhunting. The demand for whale oil, not its eventual replacement, drove whalers to hunt sperm whales to near-extinction. Kerosene's rise simply made continued whaling less profitable, not less damaging up to that point. The article emphasizes that technological replacements rarely save endangered species; rather, conservation efforts are crucial.
The blog post argues that SQLite, often perceived as a lightweight embedded database, is surprisingly well-suited for large-scale server deployments, even outperforming traditional client-server databases in certain scenarios. It posits that SQLite's simplicity, file-based nature, and lack of a separate server process translate to reduced operational overhead, easier scaling through horizontal sharding, and superior performance for read-heavy workloads, especially when combined with efficient caching mechanisms. While acknowledging limitations for complex joins and write-heavy applications, the author contends that SQLite's strengths make it a compelling, often overlooked option for modern web backends, particularly those focusing on serving static content or leveraging serverless functions.
Hacker News users discussed the practicality and nuance of using SQLite as a server-side database, particularly at scale. Several commenters challenged the author's assertion that SQLite is better at hyper-scale than micro-scale, pointing out that its single-writer nature introduces bottlenecks in heavily write-intensive applications, precisely the kind often found at smaller scales. Some argued the benefits of SQLite, like simplicity and ease of deployment, are more valuable in microservices and serverless architectures, where scale is addressed through horizontal scaling and data sharding. The discussion also touched on the benefits of SQLite's reliability and its suitability for read-heavy workloads, with some users suggesting its effectiveness for data warehousing and analytics. Several commenters offered their own experiences, some highlighting successful use cases of SQLite at scale, while others pointed to limitations encountered in production environments.
The blog post "Vpternlog: When three is 100% more than two" explores the confusion surrounding ternary logic's perceived 50% increase in information capacity compared to binary. The author argues that while a ternary digit (trit) can hold three values versus a bit's two, this represents a 100% increase (three being twice as much as 1.5, which is the midpoint between 1 and 2) in potential values, not 50%. The post delves into the logarithmic nature of information capacity and uses the example of how many bits are needed to represent the same range of values as a given number of trits, demonstrating that the increase in capacity is closer to 63%, calculated using log base 2 of 3. The core point is that measuring increases in information capacity requires logarithmic comparison, not simple subtraction or division.
Hacker News users discuss the nuances of ternary logic's efficiency compared to binary. Several commenters point out that the article's claim of ternary being "100% more" than binary is misleading. They argue that the relevant metric is information density, calculated using log base 2, which shows ternary as only about 58% more efficient. Discussions also revolved around practical implementation challenges of ternary systems, citing issues with noise margins and the relative ease and maturity of binary technology. Some users mention the historical use of ternary computers, like Setun, while others debate the theoretical advantages and whether these outweigh the practical difficulties. A few also explore alternative bases beyond ternary and binary.
Cosine similarity, while popular for comparing vectors, can be misleading when vector magnitudes carry significant meaning. The blog post demonstrates how cosine similarity focuses solely on the angle between vectors, ignoring their lengths. This can lead to counterintuitive results, particularly in scenarios like recommendation systems where a small, highly relevant vector might be ranked lower than a large, less relevant one simply due to magnitude differences. The author advocates for considering alternatives like dot product or Euclidean distance, especially when vector magnitude represents important information like purchase count or user engagement. Ultimately, the choice of similarity metric should depend on the specific application and the meaning encoded within the vector data.
Hacker News users generally agreed with the article's premise, cautioning against blindly applying cosine similarity. Several commenters pointed out that the effectiveness of cosine similarity depends heavily on the specific use case and data distribution. Some highlighted the importance of normalization and feature scaling, noting that cosine similarity is sensitive to these factors. Others offered alternative methods, such as Euclidean distance or Manhattan distance, suggesting they might be more appropriate in certain situations. One compelling comment underscored the importance of understanding the underlying data and problem before choosing a similarity metric, emphasizing that no single metric is universally superior. Another emphasized how important preprocessing is, highlighting TF-IDF and BM25 as helpful techniques for text analysis before using cosine similarity. A few users provided concrete examples where cosine similarity produced misleading results, further reinforcing the author's warning.
Summary of Comments ( 60 )
https://news.ycombinator.com/item?id=43584303
HN users generally agree with the author's debunking of the "kerosene saved the sperm whales" myth. Several commenters provide further details on whale oil uses beyond lighting, such as lubricants and industrial processes, reinforcing the idea that declining demand was more complex than a single replacement. Some discuss the impact of petroleum on other industries and the historical context of resource transitions. A few express appreciation for the well-researched article and the author's clear writing style, while others point to additional resources and related historical narratives, including the history of whaling and the environmental impacts of different industries. A small side discussion touches on the difficulty of predicting technological advancements and their impact on existing markets.
The Hacker News post titled "Kerosene did not save the sperm whale (2024)" has generated a number of comments discussing the linked article. Several commenters focus on the historical context and accuracy of the claims made in the article about the use of kerosene to refloat beached whales.
One commenter points out that while kerosene might not have been the primary factor in successful refloatings, historical accounts suggest it was used, citing examples from the 19th century. They acknowledge that the article's point about kerosene's potential harm is valid but emphasize the need to differentiate between its use as a flotation aid and its potential harm to the whale's skin. This commenter emphasizes the complexity of historical practices, suggesting that simply dismissing kerosene's use outright might be an oversimplification.
Another commenter digs into the specific example mentioned in the article about a whale refloated in New Jersey in 1902, highlighting the presence of other contributing factors, such as the rising tide. They argue that this demonstrates the difficulty in attributing success solely to kerosene. This commenter focuses on the multifaceted nature of whale rescue attempts, emphasizing that multiple factors likely play a role in any given situation.
Several commenters also discuss the challenges inherent in historical research, particularly the limitations and potential biases present in anecdotal evidence and newspaper reports. They acknowledge that while historical accounts might mention the use of kerosene, this doesn't necessarily prove its effectiveness. This emphasizes the importance of critical analysis when interpreting historical data.
Finally, some comments touch upon the broader topic of whale strandings and the various theories surrounding their causes. They mention factors like navigational errors, changes in ocean currents, and even military sonar as potential contributing factors. This discussion broadens the scope beyond the specific use of kerosene to encompass the larger issue of whale strandings and the complexities of understanding them.
Overall, the comments on Hacker News offer a nuanced perspective on the article's claims, exploring the historical context, the limitations of available evidence, and the complexities involved in interpreting historical accounts of whale rescue attempts. They generally agree with the article's main premise about the dubious effectiveness of kerosene, but also caution against oversimplification and emphasize the need for careful analysis of historical data.