Compare Cuil and Google!
By on
July 28th, 2008
Menlo Park based Cuil launched yesterday with an index of 120 billion web pages, making them arguably the most comprehensive search engine on the web (Google doesn’t disclose the size of their index, although they claim to know about a trillion unique web pages). They’ve also dropped one of the “l’s” from their name - previously the company was “Cuill.” Either way, it’s pronounced “cool.”
The super-stealth search project was founded by highly respected search experts. Husband and wife team Tom Costello (CEO) and Anna Patterson (VP Engineering) were joined by Russell Power. Patterson and Power are also ex-Google employees, and the company has been the subject of intense speculation over the last couple of years.
Much of the secret sauce of Cuil is in the way they index the web and handle actual queries by users. Both are costly to scale, and Cuil claims to have found a way to massively reduct those costs. That allows them to run the search engine a lot cheaper, even at Google-scale should it ever reach that point. By some estimates, Google spends a billion dollars a year to run the back end infrastructure of it’s search business.
Cuil also claims to have better search results than Google and others based on how they index websites. They do not simply catalog keywords on a site and then rank the site based on its importance. They also work to understand how words are related (France - cheese - wine, for example), to return more relevant results to users. This is a semantic approach to search, but very different from Powerset’s natural language approach. Powerset uses artificial intelligence to try to understand what sentences on a website actually mean. Cuil, by comparison, simply tries to properly categorize and file a web page, even if the category name doesn’t appear on the site.
That means users search the same way they always have, but Cuil will try to return better results via refinements in a “explore by category” module to the right of results. A search for dogs, for example, will return category results for “water dogs,” “crossbreed,” “cocker spaniel,” etc. Some of these related terms do not include the term “dog.”
Cuil is experimenting with a new type of search interface as well. Results are shown in three columns and contain an image and more summary text than existing search engines. In addition to refinement by category, Cuil will recommend related searches via tabs across the top of search results. A search for New York, for example, also has tabbed results for recommended refinements like New York Times, New York City, New York Yankees, etc.:
Cuil also says that they will put user privacy at the top of their business objectives. User IP addresses are not recorded to their servers, they say, and cookies are not used to associate a computer with queries. The data is simply dumped as it is created. That means user data cannot be turned over to others, whether its via blind stupidity or lawsuits.
Cuil has raised $33 million over two rounds of financing from Greylock, Madrone Capital Partners and Tugboat Ventures.
However, if you test this Cuil search engine carefully you will see that Cuil is an excellent search engine, particularly since it is all of an hour old. But it doesn’t appear to have the depth of results that Google has, despite their claims. And the results are not nearly as relevant.
A search for Dog returns 280 million results on Cuil and 498 million on Google. Judging relevance of results is subjective, but Google returns Wikipedia as the first result, then dog.com. Cuil returns Dog.com, wikipedia isn’t listed on the first page of results. Both are meaningful results, but Google is better.
More searches, Cuil v. Google: Apple (83 m v. 571 million) - neither mention the fruit. France (102 m v. 1.5 billion) - Cuil’s category refinement makes their results better for this query. Stonehenge (800k v. 8.5 million). Silicon Valley (3.2 m v. 24 m). Techcrunch (600k v. 6.5 m).
It seems pretty clear that Google’s index of web pages is significantly larger than Cuil’s unless we’re randomly choosing the wrong queries. Based on the queries above, Google is averaging nearly 10x the number of results of Cuil.
And Cuil’s ranking isn’t as good as Google’s based on the pure results returned from both queries. Where Cuil excels is with the related categories, which return results that are extremely relevant. With Google, we’ve all gotten used to trying a slightly different search to get the refined results we need. Cuil does a good job of guessing what we’ll want next and presents that in the top right widget. That means Cuil saves time for more research based queries.
And the truth is that Cuil is only an hour old at this point, Google has had a decade to perfect their search engine.
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