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What Learning by Doing Looks Like - by Brian Potter
More generally, when a technology is first being developed, its behavior and performance won’t be understood particularly well. There won’t be an obvious “theory” of the technology or any sort of body of knowledge surrounding it — how manipulating various aspects of it changes its performance, how different parameters relate to each other, what governs the ultimate ceiling on it, and so on. As more experience is accumulated with a technology, beyond simply learning what works and what doesn’t, practitioners will gradually develop more sophisticated models of how it works, and use those models to push performance even further.What Learning by Doing Looks Like - by Brian Potter
For a given technological concept in the arc of PDC bit evolution, it’s striking how non-obvious the best way to implement it is. The idea behind PDC bits sounds straightforward enough: use drill bits with cutters made of extremely hard synthetic diamond. But there are an enormous number of ways that such an idea can be implemented. What should the size and shape of the cutters be? How should they be arranged on the drill bit? What material should you attach the cutting disks to, and what should the bit body be made of? What type of drilling fluid should be used, and how should you direct the flow of it over the drill bit? What drilling parameters — RPMs, bit weight, torque, type of downhole motor — work best, and in what types of rock? When a technology is first developed, there’s often very little that can guide you other than trial and error. PDC bits progressed in large part by testing out bits, seeing how they behaved, and gradually modifying them in response. The specific implementation details of a technology matter a great deal, aren't obvious, and take time, effort, and experience to figure out.A toast to the error detectors
Scientists are very quick to say that science is self-correcting, but those who do the work behind this correction often get accused of damaging their field, or worse. My impression is that many error detectors are early-career researchers who stumble on mistakes made by eminent scientists, and naively think that they are helping by pointing out those problems — but, after doing so, are treated badly by the community.Computer crashes repeatedly in final 4 minutes of Apollo landing
The MIT team located the source of the error with only two or three hours to spare. In anticipation of a possible abort, Aldrin had insisted that the spacecraft’s rendezvous radar remain turned on. This system pointed upward, allowing it to track Collins in the command module. During the descent, the dial for the rendezvous radar had been turned to the wrong setting. Normally, this shouldn’t have caused a problem. But because of a design defect, every once in a while the system would bombard the computer with unnecessary requests. It was the worst kind of error: erratic, subtly dangerous, and difficult to reproduce.How to Turn Your Mistakes into an Advantage | Yale Insights
One group was then told that when Best Scoops’ supplier announced a shift to lower-quality beans on its website, Best Scoops preventively found a new supplier. A second group was told that Best Scoops mistakenly used the lower-quality beans until realizing the error and correcting it. Those in the second group, in which Best Scoops erred, reported Best Scoops as more likely to achieve its goals. Other experiments of similar design demonstrated a greater willingness to purchase from companies that made and corrected mistakes compared to those that simply prevented mistakes. Underlying this behavior is a simple chain of assumptions. First, people believe that correcting an error requires greater change to the status quo than preventing one, and therefore greater effort. Second, people tend to associate greater effort with a greater commitment to goals, and so a higher likelihood of achieving them.Uncovering errors in biomedical research results: New fact-checker ensures scientists cook with the right ingredients -- ScienceDaily
In a cohort of 155 research papers, the new fact-checker combined with manual analysis identified 25 per cent of papers as having sequence errors. The researchers were testing on a suspected group of the papers so while the figure doesn't reflect a baseline error rate, the numbers are still startling. "That's quite a lot of wrong sequences in a small group of papers and there will be many more out there, unfortunately, given that nucleotide sequence reagents have been described in literally hundreds of thousands of biomedical publications," said Professor Byrne.Corner cases and documentation
One day, Lauren was playing with the MIT command module simulator’s display-and-keyboard unit, nicknamed the DSKY (dis-key). As she toyed with the keyboard, an error message popped up. Lauren had crashed the simulator by somehow launching a prelaunch program called P01 while the simulator was in midflight. There was no reason an astronaut would ever do this, but nonetheless, Hamilton wanted to add code to prevent the crash. That idea was overruled by NASA. “We had been told many times that astronauts would not make any mistakes,” she says. “They were trained to be perfect.” So instead, Hamilton created a program note—an add-on to the program’s documentation that would be available to NASA engineers and the astronauts: “Do not select P01 during flight,” it said. Hamilton wanted to add error-checking code to the Apollo system that would prevent this from messing up the systems. But that seemed excessive to her higher-ups. “Everyone said, ‘That would never happen,’” Hamilton remembers. But it did.The mistake that led to the invention of CorningWare
Dr. Stookey had not planned to invent it. Experimenting at Corning one day in 1953, he put photosensitive glass into a furnace, intending to heat it to 600 degrees.“When I came back, the temperature gauge was stuck on 900 degrees, and I thought I had ruined the furnace,” he said in an interview several years ago. “When I opened the door to the furnace, I saw the glass was intact and had turned a milky white. I grabbed some tongs to get it out as fast as I could, but the glass slipped out of the tongs and fell to the floor. The thing bounced and didn’t break. It sounded like steel hitting the floor.”
For the preserving of that force we have to thank not the foresight of those recording companies but their ignorance and even philistinism when it came to black culture. They knew next to nothing about the music and even less about what new trends in it might appeal to consumers. Nowhere was this truer than at Paramount. These were businessmen, Northern and Midwestern, former salesmen. Their notions of what was a hit and what was not were a Magic Eight Ball. So, when the mid-1920s arrived, and Paramount went looking farther afield for new acts, they compensated by recording everything and waiting to see what sold. Not everything, but a lot. A long swath of everything. The result was an unprecedented, never-to-be-repeated, all-but-unconscious survey of America’s musical culture, a sonic X-ray of it, taken at a moment when the full kaleidoscopic variety of prerecording-era transracial forms hadn’t yet contracted. Hundreds of singers, more thousands of songs.