Sheila Lennon asked my opinion on the Nova Spivack’s recent writing about Wolfram Alpha, and posted my response, as well as other notes. Wolfram Alpha is the latest brainchild of Mathematica creator, Stephan Wolfram, and is a stealth project to create a computational knowledge engine. To repeat my response:
First of all, it’s not a new form of Google. Google doesn’t answer questions. Google collects information on the web and uses search algorithms to provide the best resources given a specific search criteria.
Secondly, I used Mathematica years ago. It’s a great tool. And I imagine that WolframAlpha will provide interesting answers for specific, directed questions, such as “what is the nearest star” and the like. But these are the simplest of all queries, so I’m not altogether impressed.
Think of a question: who originated the concept of “a room of one’s own”. Chances are the Alpha system will return the writing where the term originated, Virginia Woolf’s “A Room of One’s Own”, and the author, Virginia Woolf. At least, it will if the data has been input.
But one can search on the phrase “A room of one’s own” and get the Wikipedia entry on the same. So in a way, WolframAlpha is more of a Wikipedia killer than a Google killer.
Regardless, when you look via Google, then you get link to Wikipedia, but you also get links to places where you can purchase the book, links to essays about the original writing, and so on. You don’t get just a specific answer, you also get context for the answer.
To me, that’s power. If I wanted answers to directed questions, I could have stayed with the Britannica years ago.
Nova Spivack’s writing on the Alpha is way too fannish. And too dismissive of Google, not to mention the human capacity for finding the exact right answer on our own given the necessary resources.
Again, though, all we have is hearsay. We need to try the tool out for ourselves. But other than helping lazy school kids, I’m not sure how overly useful it will be. If it’s free, yeah. If it’s not, it will be nothing more than a novelty.
I also beg to differ with Nova, when he states that Wolfram Alpha is like plugging into a vast electronic brain. Wolfram Alpha isn’t brain-like at al.
The human brain is amazing in its ability to take bits and pieces of data and derive new knowledge. We are capable of learning and extending, but we’re really shite, to use the more delicate English variation of the term when it comes to storing large amounts of data in an easily accessible form.
Large, persistent data storage with easy access is where computers excel. You can store vast amounts of data in a computer, and access it relatively easily using any number of techniques. You can even use natural language processing to query for the data.
Google uses bulk to store information, with farms of data servers. When you search for a term, you typically get hundreds of responses, sorted by algorithms that determine the timeliness of the data, as well as its relevancy. Sometimes the searches work; sometimes, as Sheila found when querying Google for directions to cooking brown rice in a crockpot, the search results are less than optimum.
Wolfram Alpha seems to take another approach, using experts to input information, which is then computationally queried to find the best possible answer. Supposedly if Sheila asked the same question of Wolfram Alpha, it would return one answer, a definitive answer about how to cook brown rice in a crockpot.
Regardless, neither approach is equivalent to how a human mind works. One can see this simply and easily by asking those around us, “How do I cook brown rice in a crockpot?” Most people won’t have a clue. Even those who have cooked rice in a crockpot won’t be able to give a definitive answer, as they won’t remember all the details—all the ingredients, the exact measurements, and the time. We are not made for perfect recall. Nor are we equipped to be knowledge banks.
What we are good at is trying out variations of ingredients and techniques in order to derive the proper approach to cooking rice in a crockpot. In addition, we’re also good at spotting potential problems in recipes we do find, and able to improve on them.
So, no, Wolfram Alpha will not be like plugging into some vast electronic brain. And we won’t know how well it will do against other data systems until we all have a chance to try the application, ourselves. It most likely will excel at providing definitive answers to directed questions. I’m not sure, though, that such precision is in our best interests.
I also Googled for a brown rice crockpot recipe, using the search term, “brown rice crockpot”. The first result was for RecipeZaar, which lists out several recipes related to crockpots and brown rice. There was no recipe for cooking just plain brown rice in a crockpot among the results, but there was a wonderful sounding recipe for Brown Rice Pudding with Coconut Milk, and another for Crocked Brown Rice on a Budget that sounded good, and economical. I returned to the Google results, and the second entry did provide instructions on how to cook brown rice in a crockpot. Whether it’s the definitive answer or not, only time and experimentation will tell.
So, no, Google doesn’t always provide a definitive answer to our questions. If it did, though, it really wouldn’t much more useful than Wikipedia, or our old friend, the Encyclopedia Britannica. What it, and other search engines provide is a wealth of resources for most queries that not only typically provide answers to the questions we’re asking, but also provide any number of other resources, and chances for discovery.
This, to me, is where the biggest difference will exist between our existing search engines and Wolfram Alpha: Alpha will return direct answers, while Google and other search engines return resources from which we can not only derive answers but also make new discoveries. As such, Alpha could be a useful tool, but I’m frankly skeptical whether it will become as important as Google or other search engines, as Nova claims. I don’t know about you all, but I get as much from the process of discovery, as I do the result.
Nova released a second article on Wolfram Alpha, calling it an answer engine, as compared to a search engine. In fairness, Nova didn’t use the term “Google killer”, but by stating the application could be just as important as Google does lead one to make such a mental leap. After all, we have human brains and are flawed in this way.
As for artificial intelligence, I wrote my response to it on Twitter: It astonishes me that people spend years and millions on attempting to re-create what two 17 year olds can make in the back seat of a car.