LLMs certainly hold potential, but as we’ve seen time and time again in tech over the last fifteen years, the hype and greed of unethical pitchmen has gotten way out ahead of the actual locomotive. A lot of people in “tech” are interested in money, not tech. And they’re increasingly making decisions based on how to drum up investment bucks, get press attention and bump stock, not on actually improving anything.
The result has been a ridiculous parade of rushed “AI” implementations that are focused more on cutting corners, undermining labor, or drumming up sexy headlines than improving lives. The resulting hype cycle isn’t just building unrealistic expectations and tarnishing brands, it’s often distracting many tech companies from foundational reality and more practical, meaningful ideas.
Mc Donald’s already has customer self serve kiosks and mobile apps with the full menu that limit you as to which items you can add or remove.
How did they screw this up and leave things open ended for the LLM?
IE why was the LLM not referencing a list of valid options with every request and then replying with what the possible options are. This is something LLMs are actually able to do fairly well, then layer on top the EXACT same HARD constraints they already have on the kiosk and mobile app to ensure orders are valid?
That wouldn’t even need AI. Thats just a fancy switch statement with a pleasant voice.
An LLM can somewhat smooth over variances in language without having to have all possible variances known just the valid options and the raw input.
- I would like a Big Mac, no lettuce, no tomato, no cheese.
- I would like a Big Mac, no vegies, hold the cheese.
- I would like a Big Mac, no vegies, no dairy
That’s the joke. Nearly every proposed implementation of AI isn’t actually solving a real business or tech problem. It’s just the next snake oil, like block chain, quantum computing, etc. There are real, valid use cases for all of those things. But most companies have no idea what they really are, how they might help, and even if they could help, what it would take to implement to see real results.
