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While I recognize the efforts in developing natural language to SQL translation systems, I remain skeptical. The core of my concern lies in the inherent nature
by kulikalov 3y ago
While I recognize the efforts in developing natural language to SQL translation systems, I remain skeptical. The core of my concern lies in the inherent nature of natural language and these models, which are approximative and lack precision. SQL databases, on the other hand, are built to handle precise, accurate information in most cases. Introducing an approximative layer, such as a language model, into a system that relies on precision could potentially create more problems than it solves, leading me to question the productivity of these endeavors in effectively addressing real-world needs.
- samstave 3y agoReverse idea: Use this to POPULATE sql based on captured NLP "surveillance" -- for example, build a DB of things I say as my thing listens to me, and categorize things, topics, place, people etc mentioned. Keep count of experiencing the same things.... When I say I need to "buy thing" build table of frequency for "buy thing" etc... Effectively - query anything you've said to Alexa and be able to map behaviors/habits/people/things... If I say - Bob's phone number is BLAH. It add's bob+# to my "random people I met today table" with a note of "we met at the dog park" Narrate yourself into something journaled. Makes it easy to name a trip "Hike Mount Tam" then log all that - then have it create a link in the table to the pics folder on your SpaceDrive9000.ai and then you have a full narration with links to the pics that you take.
- pietz 3y agoI think you have a point. I also think people who share this mindset and keep sticking with it will have a tough future. The technical benefits and potentials clearly outshine the problems and challenges. That's also true in this example. You just have to let go of some principles that were helpful in the past but aren't anymore.
- kulikalov 3y agoWhat technical benefits?
- bamboozled 3y agoYour project manager can be an expert with SQL now too…and the novelty factor is high because using makes it feel like you’re in a “sci-fi” movie?
- pietz 3y agoA translation engine between natural language and SQL means that everyone can communicate with a SQL database now. That's huge. Soon also DB people will use it to get the response for complex questions and queries. It's just more natural and way faster. With technology like this, there is little reason to even know SQL anymore as the average developer. Just like today, the average developer doesn't know how databases work because the cloud takes care of it. We're moving up on the abstraction ladder and tomorrow all you need to know for SQL is to ask the right question.
- bamboozled 3y agoWhat’s funny is SQL was supposed to be the natural language everyone uses to communicate with. Few bothered to learn it.
- spennant 3y ago"Few"? I guess I must be one of the olds.
- thom 3y agoThe key here is to always have some structured intermediate layer that can allow people to evaluate what it is the system thinks they're asking, short of the full complexity of SQL. You'll need something like this for disambiguation anyway - are "Jon Favreau movies" movies starring or directed by Jon Favreau? Or do you mean the other Jon Favreau? Don't one-shot anything important end to end from language. Use language to guide users towards unambiguous and easy to reason about compositions of smaller abstractions.
- totalhack 3y agoI think AI to direct SQL will have use cases, but I personally have found it more of a fun toy than anything close to the main way I would interact with my data, at least in the course of running a business. I am a fan of a semantic layer (I made an open source one but there are others out there), and think having AI talk to a semantic layer has potential. Though TBH a good UI over a semantic layer is so easy it makes the natural language approach moot. https://github.com/totalhack/zillion https://github.com/totalhack/zillion