Tapping a wheel of cheese is a traditional method used to assess its quality and maturity, particularly for hard cheeses like Parmesan. The process involves using a small hammer or tool to strike the wheel at various points, listening to the resulting sounds and vibrations. A trained ear can interpret these sounds to determine the presence of cracks, voids, or inconsistencies within the cheese, as well as gauge its texture and overall ripeness. While not a foolproof method, tapping provides valuable insights into the internal structure of the cheese without cutting into it, helping cheesemakers and affineurs ensure quality and select the best wheels.
Frustrated with slow turnaround times and inconsistent quality from outsourced data labeling, the author's company transitioned to an in-house labeling team. This involved hiring a dedicated manager, creating clear documentation and workflows, and using a purpose-built labeling tool. While initially more expensive, the shift resulted in significantly faster iteration cycles, improved data quality through closer collaboration with engineers, and ultimately, a better product. The author champions this approach for machine learning projects requiring high-quality labeled data and rapid iteration.
Several HN commenters agreed with the author's premise that data labeling is crucial and often overlooked. Some pointed out potential drawbacks of in-housing, like scaling challenges and maintaining consistent quality. One commenter suggested exploring synthetic data generation as a potential solution. Another shared their experience with successfully using a hybrid approach of in-house and outsourced labeling. The potential benefits of domain expertise from in-house labelers were also highlighted. Several users questioned the claim that in-housing is "always" better, advocating for a more nuanced cost-benefit analysis depending on the specific project and resources. Finally, the complexities and high cost of building and maintaining labeling tools were also discussed.
NIST's Standard Reference Material (SRM) 2387, peanut butter, isn't for spreading on sandwiches. It serves as a calibration standard for laboratories analyzing food composition, ensuring accurate measurements of nutrients and contaminants like aflatoxins. This carefully blended and homogenized peanut butter provides a consistent benchmark, allowing labs to verify the accuracy of their equipment and methods, ultimately contributing to food safety and quality. The SRM ensures that different labs get comparable results when testing foods, promoting reliable and consistent data across the food industry.
Hacker News users discuss NIST's standard reference peanut butter (SRMs 2387 and 2388). Several commenters express amusement and mild surprise that such a standard exists, questioning its necessity. Some delve into the practical applications, highlighting its use for calibrating analytical instruments and ensuring consistency in food manufacturing and testing. A few commenters with experience in analytical chemistry explain the importance of reference materials, emphasizing the difficulty in creating homogenous samples like peanut butter. Others discuss the specific challenges of peanut butter analysis, like fat migration and particle size distribution. The rigorous testing procedures NIST uses, including multiple labs analyzing the same batch, are also mentioned. Finally, some commenters joke about the "dream job" of tasting peanut butter for NIST.
Summary of Comments ( 17 )
https://news.ycombinator.com/item?id=43644970
Hacker News users discussed the practicality and cultural significance of cheese wheel tapping. Some commenters debated the efficacy of tapping for assessing quality, suggesting other methods like drilling and plugging might be more reliable for determining internal defects. Others highlighted the performative aspect, arguing it's primarily for show or tradition, particularly for hard cheeses where tapping yields limited information. The rhythmic and visual appeal of the process was also noted, along with its potential to engage customers. A few users shared anecdotes about witnessing cheese tapping firsthand, and others wondered about regional variations in the practice. There was also brief discussion about the tools used, such as hammers and mallets, and the specific sounds produced.
The Hacker News post "Why Tap a Wheel of Cheese?" with the link to https://www.cheeseprofessor.com/blog/cheese-wheel-tapping has several comments discussing the cheese-tapping process.
Many commenters focused on the practicality and limitations of the tapping method. One commenter expressed skepticism about the reliability of tapping as a sole indicator of quality, especially given the variability in cheese wheels and the subjective nature of interpreting the sounds. They suggested tapping is more likely used in conjunction with other assessment techniques like coring. Another commenter with admitted limited experience echoed this sentiment, emphasizing that tapping is likely just one piece of the puzzle alongside visual inspection and smell. This commenter also highlighted the article's acknowledgment of tapping's limits.
The discussion also touched upon the tools used. One user inquired about the specific hammer used, pointing out the differences compared to a typical meat tenderizer. Another user hypothesized that the small hammer shown in the article's video might be insufficient for larger wheels, prompting speculation about the use of larger mallets and the potential risks of damaging the cheese with excessive force.
Some comments offered additional insights into the cheesemaking process. One commenter, identifying as a cheesemaker, described the use of tapping to detect unwanted gas formation during aging, specifically mentioning the issue of "blowing" in hard cheeses. Another user extrapolated this point, mentioning other defects that tapping might reveal, such as cracks, which could compromise the cheese's aging process or structural integrity.
The conversation expanded beyond the practicalities to include anecdotal experiences. One commenter shared a story about a broken cheese wheel that went unnoticed and ended up costing them significantly, adding a real-world consequence to the importance of cheese assessment.
Finally, a few comments injected a touch of humor. One commenter jokingly suggested using machine learning to analyze the tapping sounds, a nod to the tendency to apply technology to traditional practices. Another commenter quipped about using a more forceful "Hulk smash" approach to cheese inspection.
Overall, the comments section offers a range of perspectives, from skeptical inquiries to expert insights and humorous asides, creating a robust discussion around the seemingly simple act of tapping a cheese wheel.