The HIV competition is the only example where Goldbloom believes his platform has been used to host a competition in biotechnology, where he acknowledged that Kaggle “is not being used as extensively as we might like.” They then applied their models to the second set, where they don’t have the answers, and their answers were compared with actual outcomes,” Goldbloom explained. Participants would train their models on the first set where they’ve got the answers. “We gave players the genetic markers, but we withheld the information on whether or not viral load increased or decreased. In the HIV competition, which incorporated data from about 2,000 patients, Kaggle revealed to players the extent of the viral load increases or decreases of the first 1,000 patients, though not in the other 1,000 patients. Whereas if you open up a problem as a competition,” Goldbloom pointed out, “people don’t come to the problem with the same preconception about what ought to work and therefore try off-the-wall things that sometimes end up doing very well.”Īnother reason competitions work, he said, is the presence on Kaggle of a golf-like “leaderboard” listing the top 10 players and their scores as the competition progresses: “Participants drive performances to what we call the frontier of what’s possible.” “The scientific literature tends to slightly improve incrementally, where somebody tries something, and that sets the tone for what comes next. “When you open a problem to a wide audience, people have not seen that problem before, and they therefore apply techniques that have not been applied before. Anthony Goldbloom, Kaggle’s founder and CEO, told GEN that the HIV competition ended up advancing knowledge on progression of the virus beyond what was previously known. Raimondi wrote an algorithm that predicted outcomes with 78% accuracy compared to 70% accuracy for the previous best models.
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