I am so over hearing about AI. It’s getting to the point that I can assume anyone dropping the term at work is an idiot that hasn’t actually used or utilised it.
It’s this LLM phase. It’s super cool and a big jump in AI, but it’s honestly not that good. It’s a handy tool and one you need to heavily scrutinise beyond basic tasks. Businesses that jumped on it are now seeing the negative effects of thinking it was magic from the future that does everything. The truth is, it’s stupid and people need to learn about it, understand it, and be trained in how to use it before it can be effective. It is a tool, not a solution—at least for now anyways.
I equate an AI to an intern. It’s useful for some stuff but if I’m going to attach my name to it I’m going to review it and probably change a lot about it.
There’s one good use case for me: produce a bigload of trialcontent in no time for load testing new stuff. “Make 2000 yada yada with column x and z …”. Keeps testing fun and varied while lots of testdata and that it’s all nonsense doesn’t matter.
I’ve found that testing code or formulas with LLM is a 50/50 now. Very often replying “use function blabla() and such snd so” very detailed instructions while this suggested function just doesn’t exist at all in certain language asked for… it’s still something I’ld try if I’m very stuck tho, never know.
Very often replying “use function blabla() and such snd so” very detailed instructions while this suggested function just doesn’t exist at all in certain language asked fo
I’ve noticed this a lot too—especially for M. But even though it makes up a function, it sometimes inspires a more optimised idea/method that can be more flexible for future datasets.
But most times it starts to massacre things and disregard prompted parameters or even producing an identical suggestion immediately after being told not to, why not to, and reconfirming original parameters of the query.
Some times punching in the same prompts five times for five iterations produces completely different results, but one may be on the right track and I can code the rest. It helps to set it’s personality first, so it’s sharing ideas it’s seen out there, rather than trying to please.
At the least, it’s a big time saver. Gone are the days where I get a few days spare to work on solving a complex problem through trial and discovery, so it’s an excellent tool for reducing testing time and speeding up the route to an optimised method.
I am so over hearing about AI. It’s getting to the point that I can assume anyone dropping the term at work is an idiot that hasn’t actually used or utilised it.
It’s this LLM phase. It’s super cool and a big jump in AI, but it’s honestly not that good. It’s a handy tool and one you need to heavily scrutinise beyond basic tasks. Businesses that jumped on it are now seeing the negative effects of thinking it was magic from the future that does everything. The truth is, it’s stupid and people need to learn about it, understand it, and be trained in how to use it before it can be effective. It is a tool, not a solution—at least for now anyways.
I equate an AI to an intern. It’s useful for some stuff but if I’m going to attach my name to it I’m going to review it and probably change a lot about it.
There’s one good use case for me: produce a bigload of trialcontent in no time for load testing new stuff. “Make 2000 yada yada with column x and z …”. Keeps testing fun and varied while lots of testdata and that it’s all nonsense doesn’t matter.
I’ve found that testing code or formulas with LLM is a 50/50 now. Very often replying “use function blabla() and such snd so” very detailed instructions while this suggested function just doesn’t exist at all in certain language asked for… it’s still something I’ld try if I’m very stuck tho, never know.
I’ve noticed this a lot too—especially for M. But even though it makes up a function, it sometimes inspires a more optimised idea/method that can be more flexible for future datasets.
But most times it starts to massacre things and disregard prompted parameters or even producing an identical suggestion immediately after being told not to, why not to, and reconfirming original parameters of the query.
Some times punching in the same prompts five times for five iterations produces completely different results, but one may be on the right track and I can code the rest. It helps to set it’s personality first, so it’s sharing ideas it’s seen out there, rather than trying to please.
At the least, it’s a big time saver. Gone are the days where I get a few days spare to work on solving a complex problem through trial and discovery, so it’s an excellent tool for reducing testing time and speeding up the route to an optimised method.