3 ms·

I find it interesting that the project team had been implementing several "improvements" that actually worsened performance, and that it took an intern to figur

• Piskvorrr 8y ago
  Says so in the article. Essentially "we do this because everybody else does, therefore it's good." Note the title "ML practitioners" - it's used akin to alchemy these days: if the stars are right, it works.
• currymj 8y ago
  not turned on by default but they are sort of a default choice for vision tasks. it may also be that they were useful on an earlier iteration of the model, and only became harmful later. nobody’s quite sure why anything works, though. hence comparisons to alchemy — we have lots of cool empirical results, and a highly elaborated set of theories and ideas trying to explain what works and what doesn’t, but in fact these theories often fail to make correct predictions. So the only way to make progress is constant blind experimentation.
• oldgradstudent 8y ago
  You're right to put the "improvements" in scare quotes. He improved the performance in normal conditions, but he might have made the performance outside normal catastrophic. When you can't kill anyone more often than once in 100 million miles, this might not be the right tradeoff.