Everybody is trying to use W|A as though it's Orac (Blakes7) but this is an NLP layer (not a particularly impressive one, it seems) atop a calculating encyclopedia. When it is able to latch on to some encyclopedic value it is able to make calculations with it. At first glance it seems useful for scientists, however, they already have much more domain specific and sophisticated models that they are already using. For example, knowing where the ISS is relative yo my location, for anyone that this matters to, they already have the software, for the rest of us its little more than a novelty. For the average person the data is not accessible enough unless you learn to speak its language.
Its another Powerset, trying to provide more accessible pathways to data tables. NLP seems to be a very tough nut to crack because Powerset is embarrassingly poor at this (despite some very clever people working on the problem) and W|A follows in their footsteps. Given sufficient data and much better parsing of that data this could be useful. Comparing it to Google is pointless because Google is a search engine, and W|A is not. W|A is a knowledge retrieval engine. CIA World Factbook on steroids.
I think the project should get government funding, expand the datasets dramatically and it will become another way to lookup facts and perform calculations on those facts. A useful tool for people in their everyday lives, but the sophistication needs to exponentially expand to have 'everyday usefulness', for example, if I can do queries like 'trend crime rates in San Francisco by neighborhood', or, 'aggregate opinions on canon 5dII, summarize' etc.
We are looking at something very primitive, but the concept is one very worthy of further research. When we figure a way for data models on any topic to be represented in a consistent and universally accessible format (akin to what Wikipedia is as a human NLP level) and these nuggets be shared such that an engine like W|A can process them we will really be on to something...
Its another Powerset, trying to provide more accessible pathways to data tables. NLP seems to be a very tough nut to crack because Powerset is embarrassingly poor at this (despite some very clever people working on the problem) and W|A follows in their footsteps. Given sufficient data and much better parsing of that data this could be useful. Comparing it to Google is pointless because Google is a search engine, and W|A is not. W|A is a knowledge retrieval engine. CIA World Factbook on steroids.
I think the project should get government funding, expand the datasets dramatically and it will become another way to lookup facts and perform calculations on those facts. A useful tool for people in their everyday lives, but the sophistication needs to exponentially expand to have 'everyday usefulness', for example, if I can do queries like 'trend crime rates in San Francisco by neighborhood', or, 'aggregate opinions on canon 5dII, summarize' etc.
We are looking at something very primitive, but the concept is one very worthy of further research. When we figure a way for data models on any topic to be represented in a consistent and universally accessible format (akin to what Wikipedia is as a human NLP level) and these nuggets be shared such that an engine like W|A can process them we will really be on to something...