Israeli start-up Symbolab, developer of a unique, mathematically geared search engine that can find and solve for complex mathematical equations (see previous TNW coverage), announced today the completion of a seed round of $1.2 million. The round was funded by several angels, including Michael Queen – former CEO of Harel Finance and Sprint Investment House, as well as other angels from the UK investment world.
CEO, Michal Avny said, in an interview with Newsgeek, that the money raised in the current funding round will be used for further R&D of their technology, as well as to help finance the launch of a mobile application for smartphones and tablets in the near future.
Searching is better than solving
The goal of Symbolab is to make scientific content universally accessible, and it does so by expanding the search space data on scientific symbols, expressions, equations and formulas. The platform developed by Symbolab is the very first search engine to allow users to search for explanations and solutions of various mathematical equations and exercises using a general learning algorithm that improves upon itself with every query.
When first navigating on over to the Symbolab Web app, the first thing encountered is what the company calls the ‘Scientific Pad’, which is essentially a layout of the kinds of advanced function symbols you would find on a scientific calculator.
When users plug advanced equations into the search field, the smart algorithm won’t solve for the equation as much as it will ‘find’ the answer. What makes using Symbolab’s search far more valuable to mathematicians than a standard scientific calculator, is in addition to having the capacity to find solutions in advanced algebra, trigonometry and calculus,
Symbolab’s search will also provide detailed proofs, graphs and charts as well as similar solutions gleaned from other sources. In this way, it’s similar to a traditional search engine that offers multiple search results for every query, only here the user is presented with other mathematical solutions that are similar to the one they entered, helping them fully grasp the principle they’re studying while opening their eyes to other possibilities.
The site’s database contains several encyclopedic sources including Wikipedia, video sites like the Khan Academy, courses from leading universities such as Stanford and MIT, online books, dictionaries, forums, educational websites and many other resources.
Not just another Google
The feature that stands out the most in Symbolab’s search engine is the Scientific Pad. The moment you see it, you realize this is more of a search engine for the people who made Google than for the people who use Google. The immediate availability of advanced mathematical function symbols, right out there in front, is of tremendous value to heavy math users. It saves them the trouble of having to remember function names, and then searching for them through traditional engines, only to copy/paste the symbol into a formula they’re in the middle of composing in a second search field that’s waiting opened on the side.
An autocomplete feature also comes in handy, intuiting a user’s equation and suggesting a completed formula as soon as the user begins typing into the field. Symbolab also uses semantic search, which attempts to figure out the intended meaning of the user from the context and meaning of the equations they input.
In addition to their Web app, Symbolab offers users a browser plugin extension for Chrome and Firefox that allows users to perform searches of equations directly from select sites. For example; if a user is browsing a Wikipedia article on Chrome, and they see an equation they would like to search – assuming their plugin is turned on, all they have to do is click on the equation and Symbolab will execute the search.
Symbolab was founded in October of 2011 by Adam Arnon, Lev Alyshayev and Michal Avny. The company has six employees and works out of Tel Aviv University where they’re currently conducting pilot trials of their search engine using the local student body.
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