ML-driven search API that continuously improves toward 'perfect' search

Google dominated the search algorithm for so long that we've all been trained to think search can't get much better. Sure, the interface to search has changed (LLMs), but the underlying search algorithm has not. There are many reasons for this, mostly financial incentive reasons (ads). Exa has spent years developing novel search algorithms that actually get better with each month. Our ultimate goal is a perfect search algorithm. As in, perfectly handle any search over all the world's information no matter how complex the request. Our financial and engineering incentives are aligned -- we just want to give our API customers the best information. The long research effort by the team is starting to work. We're seeing continuous gains with our approaches each month. Note that Exa 2.0 was launched just a month ago.. Building a perfect search engine is one of the most difficult ML systems problems in the world right now -- basically how do you run intelligence over billions of pages as quickly as possible. It's a wild mix of new training techniques, massive-scale crawling infrastructure, custom-built databases, novel GPU optimizations, organizing the whole world's information in s3, and everything in between. This tech is what's necessary to give each person perfect, customized control over the world's information, and it also happens to be super cool :) Super proud of the team for shipping Exa 2.1, and even more proud of our velocity. In other words, Exa 2.2 coming soon 🚄