> One of the risks of LLMs is that a lot of tasks go from "an expert could do this easily given a few weeks" to "anyone who thinks to ask an LLM can do this easily and get results the same day"
replyBy that logic, all problems are solved with LLMs, though.
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replyAutomated License plate readers are a half century old at this point: https://en.wikipedia.org/wiki/Automatic_number-plate_recogni...
replywhy wouldn't codex or claude just reach for whatever FOSS https://github.com/openalpr/openalpr
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replyYes, an ALPR is basically just a glorified [thing that an ALPR does]
replyDropbox stock is trading at 50% of its initial price 5y ago when it went public, maybe the public markets also don't understand the difference between rsync and Dropbox.
replyI honestly can't tell if this is ragebait or you believe this.
replyMy friend, if you have a database of license plates extracted from single images taken by multiple cameras, YOU ARE TRACKING UNIQUE VEHICLES ACROSS A REGION.
Terabytes of data don't matter because you don't need to search terabytes, you need to search a few MB of text data. You don't even have to store the original video.
But you don't have such a database.
replyYou’re moving the goalposts. The original point of this thread is that Flock AI technology is hardly needed to efficiently search traditional video footage for license plates.
replyOk, so you don’t understand that ALPR is two commodity technologies: object detection and OCR.
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reply> Assuming they have access to terabytes of regional video surveillance but don't have their own compute besides what the LLM will buy for them
replyAmazing how you can move the goalposts to make things impossible, isn't it? Where in the world did "without compute" come from? Are they not even allowed a decent desktop computer?