False positives mean you're throwing away genuinely unique items that hash the same. If you use a 256 bit Bloom filter to process a billion items, you'll get ex

False positives mean you're throwing away genuinely unique items that hash the same. If you use a 256 bit Bloom filter to process a billion items, you'll get exactly 256 results that are indeed unique. The rate of false positives you require out of the data structure is key. If your program is correct with a 20% false positive rate, you're golden. If the goal is more or less 0, look elsewhere. The author addresses precision, but not in a way that questions whether a Bloom filter is indeed the right tool for the job.