Someone Stole My Startup Idea – Part 2: They Raised Money With M. In my 21 years of startups, I had my ideas “stolen” twice.
See part one for the first time it happened. This time it was serious. As a reminder, this post is not legal advice, it’s not even advice. It’s just a story about what happened to me. Customer DevelopmentWe were starting Epiphany, my last company. I remember presenting our ideas for Marketing Automation to one VP of Marketing in a large Silicon Valley company. Fast ForwardFast forward nine months. By now we had found a few customers and learned a lot more about the market from them and other prospects. Are These Your Slides? And who was this competitor? I felt like I had just been kicked in the stomach. Disbelief, Anger, Resignation and AcceptanceMy cofounders and I went through the stages of disbelief, anger, resignation and acceptance.
We consciously didn’t ask potential customers to sign a Non-Disclosure Agreement (NDA). Finally, we concluded, “You can’t drive forward by looking in the rear-view mirror.” Lessons Learned. Locality sensitive hashing. Locality-sensitive hashing (LSH) is a method of performing probabilistic dimension reduction of high-dimensional data.
The basic idea is to hash the input items so that similar items are mapped to the same buckets with high probability (the number of buckets being much smaller than the universe of possible input items). This is different from the conventional hash functions, such as those used in cryptography, as in the LSH case the goal is to maximize probability of "collision" of similar items rather than avoid collisions. [1] Note how locality-sensitive hashing, in many ways, mirrors data clustering and Nearest neighbor search. Definition[edit] An LSH family [1] [2] [3] is defined for a metric space , a threshold and an approximation factor . Is a family of functions which map elements from the metric space to a bucket. . , using a function which is chosen uniformly at random: if , then (i.e., and collide) with probability at least ,if , then with probability at most .
Sherlock: Plagiarism Detector. What is Sherlock?
Sherlock is a program which finds similarities between textual documents. It uses digital signatures to find similar pieces of text. A digital signature is a number which is formed by turning several words in the input into a series of bits and joining those bits into a number. Sherlock works on text files such as essays, computer source code files, and other assignments in digital form. It will even work with Tar files, but not compressed archives such as Gzipped or Zipped files (you'll have to unzip those files first). How do I download it? There are some files you can download here: sherlock.c - source code for the Sherlock program, in Unix text file format. makefile - a Unix makefile.
How do I compile it? If using Unix or Linux, just type "make". How do I use it? Sherlock is a command-line program. Sherlock *.txt. CopyTracker : The free plagiarism detection tool. Why do we care about plagiarism? - By Meghan O'Rourke - Sla.