At a beach restaurant the other night I kept hearing a loud American voice cut across all conversation, going on and on about “AI” and how it would get into all human “workflows” (new buzzword?). His confidence and loudness was only matched by his obvious lack of understanding of how LLMs actually work.
AI itself too i guess. Also i have to point this out every time but my username was chosen way before all this shit blew up into our faces. Ive used this one on every platform for years.
The whole ex-Mckinsey management layer is at risk. Whole teams of people who were dedicated to producing pretty slides with “action titles” for managers higher up the chain to consume and regurgitate are now having their lunch eaten by AI.
“AI, how do I do <obscure thing> in <complex programming framework>”
“Here is some <language> code. Please fix any errors: <paste code here>”
These save me hours of work on a regular basis and I don’t even use the paid tier of ChatGPT for it. Especially the first one because I used to read half the documentation to answer that question. Results are accurate 80% of the time, and the other 20% is close enough that I can fix it in a few minutes. I’m not in an obscure AI related field, any programmer can benefit from stuff like this.
I really like the idea of an LLM being narrowly configured to filter, summarize data which comes in at a irregular/organic form.
You would have to do it multiples in parallel with different models and slightly different configurations to reduce hallucinations (Similar to sensor redundancies in Industrial Safety Levels) but still, … that alone is a game changer in “parsing the real world” … that energy amount needed to do this “right >= 3x” is cut short by removing the safety and redundancy because the hallucinations only become apparent down the line somewhere and only sometimes.
They poison their own well because they jump directly to the enshittyfication stage.
So people talking about embedding it into workflow… hi… here I am! =D
A buddy of mine has been doing this for months. As a manager, his first use case was summarizing the statuses of his team into a team status. Arguably hallucinations aren’t critical
I would argue that this makes the process microscopically more efficient and macroscopically way less efficient.
That whole process probably is useless, and imagine wasting so much energy, water and computing power just to speed this useless process up and saving a handful of minutes (I am a lead and it takes me 2/3 minutes to put together a status of my team, and I don’t usually even request a status from each member).
I keep saying this to everyone in my company who pushes for LLMs for administrative tasks: if you feel like LLMs can do this task, we should stop doing it at all because it means we are just going through the motions and pleasing a process without purpose. You will have people producing reports via LLM from a one-line prompt, the manager assembling it together with LLM and at vest someone reading it distilling it once again with LLMs. It is all a great waste of money, energy, time, cognitive effort that doesn’t benefit anybody.
As soon as someone proposes to introduce LLMs in a process, raise with cutting that process altogether. Let’s produce less bullshit, instead of more while polluting even more in the process.
At a beach restaurant the other night I kept hearing a loud American voice cut across all conversation, going on and on about “AI” and how it would get into all human “workflows” (new buzzword?). His confidence and loudness was only matched by his obvious lack of understanding of how LLMs actually work.
“Confidently incorrect” I think describes a lot of AI aficionados.
And LLMs themselves.
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AI itself too i guess. Also i have to point this out every time but my username was chosen way before all this shit blew up into our faces. Ive used this one on every platform for years.
Some people can only hear “AI means I can pay people less/get rid of them entirely” and stop listening.
AI means C level jobs should be on the block as well. The board can make decisions based on their output.
The whole ex-Mckinsey management layer is at risk. Whole teams of people who were dedicated to producing pretty slides with “action titles” for managers higher up the chain to consume and regurgitate are now having their lunch eaten by AI.
Just wait until Elon puts AI in those new robots he invented!!!
/s for those who need it…
I’ve noticed that the people most vocal about wanting to use AI get very coy when you ask them what it should actually do.
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“AI, how do I do <obscure thing> in <complex programming framework>”
“Here is some <language> code. Please fix any errors: <paste code here>”
These save me hours of work on a regular basis and I don’t even use the paid tier of ChatGPT for it. Especially the first one because I used to read half the documentation to answer that question. Results are accurate 80% of the time, and the other 20% is close enough that I can fix it in a few minutes. I’m not in an obscure AI related field, any programmer can benefit from stuff like this.
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Because as a social phenomenon it promises to decide for them what it should actually do.
Porn / ai gf. Thats what 90% of ai power users do.
I really like the idea of an LLM being narrowly configured to filter, summarize data which comes in at a irregular/organic form.
You would have to do it multiples in parallel with different models and slightly different configurations to reduce hallucinations (Similar to sensor redundancies in Industrial Safety Levels) but still, … that alone is a game changer in “parsing the real world” … that energy amount needed to do this “right >= 3x” is cut short by removing the safety and redundancy because the hallucinations only become apparent down the line somewhere and only sometimes.
They poison their own well because they jump directly to the enshittyfication stage.
So people talking about embedding it into workflow… hi… here I am! =D
A buddy of mine has been doing this for months. As a manager, his first use case was summarizing the statuses of his team into a team status. Arguably hallucinations aren’t critical
I would argue that this makes the process microscopically more efficient and macroscopically way less efficient. That whole process probably is useless, and imagine wasting so much energy, water and computing power just to speed this useless process up and saving a handful of minutes (I am a lead and it takes me 2/3 minutes to put together a status of my team, and I don’t usually even request a status from each member).
I keep saying this to everyone in my company who pushes for LLMs for administrative tasks: if you feel like LLMs can do this task, we should stop doing it at all because it means we are just going through the motions and pleasing a process without purpose. You will have people producing reports via LLM from a one-line prompt, the manager assembling it together with LLM and at vest someone reading it distilling it once again with LLMs. It is all a great waste of money, energy, time, cognitive effort that doesn’t benefit anybody.
As soon as someone proposes to introduce LLMs in a process, raise with cutting that process altogether. Let’s produce less bullshit, instead of more while polluting even more in the process.