My mind is still blown in how words and concepts can be translated into high dimensional vertexes and through the math of their position and direction retain their meanings, and even be changed into the correct alternate versions by doing calculations on them. That doesn’t mean the vectors understand what they represent, but there’s some core level of meaning there. Same with LLMs. No thinking, they screw up stuff that a reasoning being would figure out. Yet there’s something in even the simplest local model that is far more than just autocompleting sentences. That is part of the mechanics, but not nearly enough to describe it.
I turn off all AI functions because they just get in my way and are frustrating when I’m working.
Occasionally I will use it to format or prep a document template.
AI has gotten better. I pasted in about 10 phrases I’d captured in a meeting for a project, and asked to to prep the document with sections etc.
I expected a generic template with some garbage.
It actually inferred a lot from the project notes and built a 5 page project scope, and included things such as testing parameters and thresholds for acceptance. Which were actually good criteria for the product. It also split it into sensible phases with close out criteria and triggers for next phase.
It suggested avenues of adjustment to make the product work along with back up ideas and the risk levelsof each.
Overall it nailed the product plan and phases and had really sensible suggestions, even with such limited input as a few rough notes.
It did better than most of my colleagues, and what I expected would be 2 days of my time researching and typing, was max 4 hours.
About 1/2 hour setup and generate, and the rest was me moving sentences around, or deleting stuff that might not be 100% relevant.
I just wish we had gotten to this state of things in a better way. Maybe it couldn’t have happened, but at least then we wouldn’t know what we missed and still have what we’ve lost.
My mind is still blown in how words and concepts can be translated into high dimensional vertexes and through the math of their position and direction retain their meanings, and even be changed into the correct alternate versions by doing calculations on them. That doesn’t mean the vectors understand what they represent, but there’s some core level of meaning there. Same with LLMs. No thinking, they screw up stuff that a reasoning being would figure out. Yet there’s something in even the simplest local model that is far more than just autocompleting sentences. That is part of the mechanics, but not nearly enough to describe it.
I turn off all AI functions because they just get in my way and are frustrating when I’m working.
Occasionally I will use it to format or prep a document template.
AI has gotten better. I pasted in about 10 phrases I’d captured in a meeting for a project, and asked to to prep the document with sections etc.
I expected a generic template with some garbage.
It actually inferred a lot from the project notes and built a 5 page project scope, and included things such as testing parameters and thresholds for acceptance. Which were actually good criteria for the product. It also split it into sensible phases with close out criteria and triggers for next phase.
It suggested avenues of adjustment to make the product work along with back up ideas and the risk levelsof each.
Overall it nailed the product plan and phases and had really sensible suggestions, even with such limited input as a few rough notes.
It did better than most of my colleagues, and what I expected would be 2 days of my time researching and typing, was max 4 hours.
About 1/2 hour setup and generate, and the rest was me moving sentences around, or deleting stuff that might not be 100% relevant.
I just wish we had gotten to this state of things in a better way. Maybe it couldn’t have happened, but at least then we wouldn’t know what we missed and still have what we’ve lost.