AI is one of the most powerful tools available today, and as a heavy user, I’ve seen firsthand how transformative it can be. However, there’s a trend right now where companies are trying to force AI into everything, assuming they know the best way for you to use it. They’re focused on marketing to those who either aren’t using AI at all or are using it ineffectively, promising solutions that often fall short in practice.
Here’s the truth: the real magic of AI doesn’t come from adopting prepackaged solutions. It comes when you take the time to develop your own use cases, tailored to the unique problems you want to solve. AI isn’t a one-size-fits-all tool; its strength lies in its adaptability. When you shift your mindset from waiting for a product to deliver results to creatively using AI to tackle your specific challenges, it stops being just another tool and becomes genuinely life-changing.
So, don’t get caught up in the hype or promises of marketing tags. Start experimenting, learning, and building solutions that work for you. That’s when AI truly reaches its full potential.
I think there’s specific industrial problems for which AI is indeed transformative.
Just one example that I’m aware of is the AI-accelerated nazca lines survey that revealed many more geoglyphs that we were not previously aware of.
However, this type of use case just isn’t relevant to most people who’s reliance on LLMs is “write an email to a client saying xyz” or “summarise this email that someone sent to me”.
That’s really neat, thanks for sharing that example.
In my field (biochemistry), there are also quite a few truly awesome use cases for LLMs and other machine learning stuff, but I have been dismayed by how the hype train on AI stuff has been working. Mainly, I just worry that the overhyped nonsense will drown out the legitimately useful stuff, and that the useful stuff may struggle to get coverage/funding once the hype has burnt everyone out.
I suspect that this is “grumpy old man” type thinking, but my concern is the loss of fundamental skills.
As an example, like many other people I’ve spent the last few decades developing written communication skills, emailing clients regarding complex topics. Communication requires not only an understanding of the subject, but an understanding of the recipient’s circumstances, and the likelihood of the thoughts and actions that may arise as a result.
Over the last year or so I’ve noticed my assistants using LLMs to draft emails with deleterious results. This use in many cases reduces my thinking feeling experienced and trained assistant to an automaton regurgitating words from publicly available references. The usual response to this concern is that my assistants are using the tool incorrectly, which is certainly the case, but my argument is that the use of the tool precludes the expenditure of the requisite time and effort to really learn.
Perhaps this is a kind of circular argument, like why do kids need to learn handwriting when nothing needs to be handwritten.
It does seem as though we’re on a trajectory towards stupider professional services though, where my bot emails your bot who replies and after n iterations maybe they’ve figured it out.
Oh yeah, I’m pretty worried about that from what I’ve seen in biochemistry undergraduate students. I was already concerned about how little structured support in writing science students receive, and I’m seeing a lot of over reliance on chatGPT.
With emails and the like, I find that I struggle with the pressure of a blank page/screen, so rewriting a mediocre draft is immensely helpful, but that strategy is only viable if you’re prepared to go in and do some heavy editing. If it were a case of people honing their editing skills, then that might not be so bad, but I have been seeing lots of output that has the unmistakable chatGPT tone.
In short, I think it is definitely “grumpy old man” thinking, but that doesn’t mean it’s not valid (I say this as someone who is probably too young to be a grumpy old crone yet)
I think of AI like I do apps: every company thinks they need an app now instead of just a website. They don’t, but they’ll sure as hell pay someone to develop an app that serves as a walled garden front end for their website.
Most companies don’t need AI for anything, and as you said: they are shoehorning it in anywhere they can without regard to whether it is effective or not.
AI is one of the most powerful tools available today, and as a heavy user, I’ve seen firsthand how transformative it can be. However, there’s a trend right now where companies are trying to force AI into everything, assuming they know the best way for you to use it. They’re focused on marketing to those who either aren’t using AI at all or are using it ineffectively, promising solutions that often fall short in practice.
Here’s the truth: the real magic of AI doesn’t come from adopting prepackaged solutions. It comes when you take the time to develop your own use cases, tailored to the unique problems you want to solve. AI isn’t a one-size-fits-all tool; its strength lies in its adaptability. When you shift your mindset from waiting for a product to deliver results to creatively using AI to tackle your specific challenges, it stops being just another tool and becomes genuinely life-changing.
So, don’t get caught up in the hype or promises of marketing tags. Start experimenting, learning, and building solutions that work for you. That’s when AI truly reaches its full potential.
I think there’s specific industrial problems for which AI is indeed transformative.
Just one example that I’m aware of is the AI-accelerated nazca lines survey that revealed many more geoglyphs that we were not previously aware of.
However, this type of use case just isn’t relevant to most people who’s reliance on LLMs is “write an email to a client saying xyz” or “summarise this email that someone sent to me”.
That’s really neat, thanks for sharing that example.
In my field (biochemistry), there are also quite a few truly awesome use cases for LLMs and other machine learning stuff, but I have been dismayed by how the hype train on AI stuff has been working. Mainly, I just worry that the overhyped nonsense will drown out the legitimately useful stuff, and that the useful stuff may struggle to get coverage/funding once the hype has burnt everyone out.
I suspect that this is “grumpy old man” type thinking, but my concern is the loss of fundamental skills.
As an example, like many other people I’ve spent the last few decades developing written communication skills, emailing clients regarding complex topics. Communication requires not only an understanding of the subject, but an understanding of the recipient’s circumstances, and the likelihood of the thoughts and actions that may arise as a result.
Over the last year or so I’ve noticed my assistants using LLMs to draft emails with deleterious results. This use in many cases reduces my thinking feeling experienced and trained assistant to an automaton regurgitating words from publicly available references. The usual response to this concern is that my assistants are using the tool incorrectly, which is certainly the case, but my argument is that the use of the tool precludes the expenditure of the requisite time and effort to really learn.
Perhaps this is a kind of circular argument, like why do kids need to learn handwriting when nothing needs to be handwritten.
It does seem as though we’re on a trajectory towards stupider professional services though, where my bot emails your bot who replies and after n iterations maybe they’ve figured it out.
Oh yeah, I’m pretty worried about that from what I’ve seen in biochemistry undergraduate students. I was already concerned about how little structured support in writing science students receive, and I’m seeing a lot of over reliance on chatGPT.
With emails and the like, I find that I struggle with the pressure of a blank page/screen, so rewriting a mediocre draft is immensely helpful, but that strategy is only viable if you’re prepared to go in and do some heavy editing. If it were a case of people honing their editing skills, then that might not be so bad, but I have been seeing lots of output that has the unmistakable chatGPT tone.
In short, I think it is definitely “grumpy old man” thinking, but that doesn’t mean it’s not valid (I say this as someone who is probably too young to be a grumpy old crone yet)
I think of AI like I do apps: every company thinks they need an app now instead of just a website. They don’t, but they’ll sure as hell pay someone to develop an app that serves as a walled garden front end for their website. Most companies don’t need AI for anything, and as you said: they are shoehorning it in anywhere they can without regard to whether it is effective or not.