> I used to argue with people on the internet, after about six replies, you realize that you’re speaking to someone incapable of thought
He realises the current woe of things but doesn't realise he's been arguing with bot farms and teams of people hired just for this reason - to sow doom, arguments and engagement.
Around 10 years ago I noticed this happening on trending topics of Twitter - it wasn't that the opponents were stupid because they disagreed, it was that they were simultaneously intelligent and stupid in the way they spoke in a way that I realised I'd never seen in genuine people, making me realise it was probably different people or bots under one account.
If I realised it 10 years ago it was probably happening for at least 15. He wasn't better than these people he was falling into their trap
Haha it’s just a foolish move made by those from the ‘90s. We all internalized a different lesson. The younger generations have learned to brush it off and stop responding. Even if the person is human, when you fail to move toward Aumann Agreement, there is no point in persisting.
Us older ones are still fighting the last war. If only we explain it properly, maybe the bots will understand!
I've now completely stopped engaging with anyone on that platform that I can't reasonably traced back to a real person. If any non-real-name account says anything that remotely feels bad-faith in replies, I block them. Having been on the Internet since the mid 90's when it was the frontier, and everyone helped/trusted everyone else, the policy feels very wrong. But unfortunately Twitter has given no tools or alternatives to deal with the situation.
I have found that the only way to deal with this these days is basically to only use my time to discuss things with people in private, invitation only forums. HN is a rare exception for "I am pretty sure you all are not bots (yet)" and yet anonymous.
Everything else that I care about is in private Signal groups or an equivalent of same with anywhere from 15 to 200 people, and adding any new member means they need to be vouched for by an existing one. And at least 55-75% of the people know each other face to face through industry vertical specific events, trade shows, conferences and similar.
I can't even imagine trying to engage with people on something like x/twitter or other social media. Not knowing whether the 'person' you're replying to is somebody's LLM authoried bot farm.
That feels like the intellectual equivalent of limiting your career opportunities within a small tiny villages vs. a large city. There is so much more in the city.
> And at least 55-75% of the people know each other face to face through industry vertical specific events, trade shows, conferences and similar.
Tbh, my experience with _that_ has been worse than with a random sample of internet background radiation, as people seem to have no idea how to filter correctly and who to vouch for and why.
_Especially_ with people they know via work, conferences, etc. Spaces that do not filter for "genuinely relevant contributer to a conversation" at all, but encourage faking that.
This is the only way to realistically deal with it but it’s not scalable. A platform is only as useful as its non-bot users. On Twitter even the positive replies are likely bots. Real engagement is limited for most users.
On a site like HN, blocklists are very effective at keeping people off your feed.
Same. (I would love to say, but they still get me way too often)
I can also highly encourage people to keep notes and do some basic OSINT. The effective internet is smaller than one might think, so that proves useful time and time again.
>>anyone on that platform that I can't reasonably traced back to a real person
Not sure why that makes any difference - I've had plenty of arguments on Facebook with people who are perfectly happy to spew racist and/or conspiratorial bullshit while having their full names, their holiday photos and photos of their children and/or grandchildren attached to their identity. The weird thing is that these people are 99/100 times incapable of actually having an argument, they either start insulting you straight away or say some variation of "if you don't like what I'm saying then leave" or actually majority of time "what does a foreigner like you know about this topic".
The real names policy has yielded zero of the promised effects imho.
One of the first things I tell the junior/mid-level developers I mentor is "You can't debug something just by reading the code." We all have a mental model of how our code works, and it's usually a bit wrong. Bugs are the real world manifestations of those mistakes. When you read the code it's all filtered through your model, and that makes you blind to seeing why something unexpected happened. In order to debug something you have to be able to put the system in the state where the bug happens to see why it occurred.
LLMs generally only debug systems by reading the code with whatever information you give them in a prompt. The image in the article is meta-prompt - the prompt is whatever comes from the vision model the AI happens to use to 'understand' the red circle annotation. That won't work. To successfully debug what's going on it will need much better state information. Has the 'shelf' been explained to is? Is the contrast and lack of shadows in the image messing up the vision model? Why isn't the 'lid' in the image? And so on.
LLMs are clever but they're not magical. Treat them like a naive junior dev. Give them enough data about the state of something to understand it properly.
I call this a tautological mental model. You can read the code over and over again, but your second reading will be mostly an echo of the mental model you built up in your first.
I completely understand this. I’ve worked on robot hands and 5.6/Fable 5 were practically useless at helping me debug anything visually.
What I have found super useful actually is having models make a interactive 3d viewer in which I use move / highlight / paint (soft body painting directly onto the geometry for issues and different colors mean different failures). This gives a much better way to communicate the physical relationships and positions that are hard to get across in a labeled screenshot.
Its for sure still a lot of manual work so the "seeing-eye dog" description definitely holds. But I have found that after a couple of examples with the extra context the model gets much better at handling the problem and becomes useful.
A bit off topic, but I absolutely love the little robot on the author's main project's landing page (https://rerun.io/).
I normally condemn mouse hijacking, but this implementation will be allowed.
Rerun is pretty dope, but I'm not sure how you came to the conclusion that it's the "author's main project"? There is a whole company backing it, with no affiliation that I could find, apart from the author being an occasional contributor?
LM still can not see and understand the desktop app UI on a level that is acceptable for testing.
All the advances in coding are from web dev and thanks to the nature of html UIs.
Try to develop a desktop app and it’s like working with a legally blind person who can see some part of the screen is they squint in a certain way but surely will miss all minor details.
> I often handwrite the code myself, but I’ve found that LLM coding assistants’ limitless patience ameliorates the drudgiest work of coding.
I've been using a few different "smart" LLM to work on an analysis, parsing, search and correlation tool that ultimately deals with a 5.5GB on disk (with indexes) mariadb database that has its origin as a federal government department's 905,000 row plain text CSV file.
There are a ridiculous number of data entry errors and just plain weird fuckups in the data origin that don't seem they will be ameliorated any time soon, so automating the drudge work of cleaning it up and rectifying it into something usable is a textbook case for this. Very pleased with the results so far.
I mean there's a reason why we're doing MoCap for video games.
If computers were good at this, we wouldn't be needing that. But actual motion and all seems to be much more complex than the systems can predict, apparently.
Also.. uh.. isn't this.. good? I thought AI was to steal all our jobs.
___
Beside that, kinda weird self-description.
Isn't the computer executing your commands and you're just filling in where it cannot do that?
Being that dog implies that the computer is in the driver seat.
I mean it's supposed to be a joke I guess, but I read it as one that leaks internal metadata which seems to be incorrectly calibrated.
It is weird if you think about it this way: it is AI that waits for you, its ‘eyes’, to provide a feedback so it can continue working. It literally uses you as its organ.
<!!spoiler ahead!!>There is a TV show called Person of Interest <!!spoiler ahead!!>, where Machine (AI connected to Internet and CCTV networks) has no legs or eyes, so when it needs to go and check something not covered by CCTV feeds, it gives instructions to a real person. In the show it is called an ‘analog interface.’
If intern is making a breakfast, and boss is the one who suddenly runs to the grocery store because eggs are missing, is boss still the one in a driver’s seat?
From the original goal point of view yes, as it was boss who has initiated whole breakfast procedure. But from an execution standpoint it is intern who gives its boss a job of a grocery store run. He could give same job to anyone else, boss as a persona is irrelevant here.
>Also.. uh.. isn't this.. good? I thought AI was to steal all our jobs.
the problem is, the CEOs still think AI solves their problems ie minimize paid jobs
> All that’s left is the dumbest workflow possible: I fire up the debug viewer myself, look around for weird mistakes, then take a screenshot and tell the language model how badly it messed up this time. Eventually I just decided to do all the debugging work myself, so I would at least get to do the fun part too.
I call this "thanoscoding" for two reasons:
1. "Fine, I'll do it myself"
2. In the past I found I have to "snap away" the mess the LLM made in order to start afresh from a known good state (generally with git reset). But that was 1-2 generations ago when it comes to models. GPT6 Astra probably does things right the first time, 90% of the time.
I like to think of training and improving AIs as bringing freedom to the world. The useless toil and labor associated with rebuilding the same solutions into different contexts is finally at an end.
Coding was never the reward. Acting as a translator for a machine is far worse than allowing the machine to solve the mundane parts and leave you with bigger building blocks to play with.
After 25 years I have to confess I hated being a software engineer. It felt like grinding in a video game.
Now I can finally create and innovate at the speed of thought, and I'm very grateful to have this technology now.
For me code still is the reward; I made and make my fortunes with boring code people on HN say no one needs or wants, my hobby is, and has been for 45 years, writing, perfecting and optimizing code manually until I find it perfect. I have been working for 10 years on a programming language and OS (with niche 2 dbs that are now prod quality and we use) and those are the best moment of my day, I couldn’t care less what anyone thinks of it or ever uses it. But the lessons learned do flow into LLMs to write the boring code and I can say that our million$ paying LoB code can handle 100s req/s on shite hardware and even if the LLM did a crap job. Which is almost 100s times more than the client will ever needs.
Giant corpos hold every sliver of your so called freedom, you dont innovate, you repeat what others created before you. You use a tool that shackles your thoughts and creativity in a never before seen way, what you perceive is an illusion of liberty that is no present. Without others you are nothing and they can take it away any seconds, you are an addict, not an innovator.
I can see where you're coming from, and I share the sentiment and resentment to a large degree, but I think you might be not doing reality justice.
It is true that closed weights models are a big issue. It is also true that LLM-generated solutions usually drift towards a median.
But that is not the dead end you think it might be.
Most coding work is repetitive boilerplate, and most typing is just.. well.. typing. Miserable work I too did not really enjoy. What I did enjoy were the end results, and that was just a necessary step to get there.
Now that's less the case than it was before we had LLMs, and for that I too am glad.
___
I think the article headline might've primed you (and me, fwiw) to reading the comment you're replying to as passive. But if you just look at the words of it, that might not actually be the case.
Your point is true to some extend, I personally host my own "cloud" storage..it comes with drawbacks, same is true for email..especially email, social media is a society constructs, by definition its reliant on others but many will argue that its not worth keeping anyway (although I wonder how one stays human in this world then, the meat space seems with so many barrieres in this age).
I feel very much like a luddite..or some artisan of a bygone age. The guy above laments how he never enjoyed coding, this is an interesting sentiment, I know quite a few people who enjoy the craft itself, myself included. The ability to form words that have meaning, that create something from nothing. Sure, the words are just a tool, but its something _I_ can master, not some abstract wish machine that may change its functionality tommorow. Obviously one can argue that the computer itself is in this case the one that creates and not me, its not magic that just works with me, but the machine I got obeys me and me alone..another reason why personal computing is important.
Serious question - what do you do for fun? I find fishing with friends enjoyable, and using my hands tidying up the old place I bought. It’s not innovating software I’ll never use but I’ll never tire of writing the same old ASP that delivers my clients the results they’re after.
> I like to think of training and improving AIs as bringing freedom to the world.
Yes, when I think of OpenAI and Anthrophic and Google and Meta and any AI labs and their intentions, i cry a single tear for how these great instituitions are working so hard to bring freedom for humanity.
AI owned by a few companies is more likely to put the majority right back to serfdom. You're a privileged fool to believe that freedom is the likely outcome of the current stampede.
With a username that appears to cheer for a sociopath¹, I doubt reason will convince you.
It was obviously a sarcastic joke. I get it if you didn't catch that, but do you think my username glorifies Sam Altman? And is that a reason to talk negatively about me? You doubt reason will convince me? And at the end, you call *me* a privileged fool. Wow, just wow.
Also, I don't think you can cite a subjective take as objectively correct by including it as a footnote. Why do you need to medically diagnose him to say what he's doing is fucked up?
Why does he have to be literally the devil for outrage to work?
He could also not be a sociopath, but still his actions will be his actions, and it is okay to criticize them. Next what, you're going to link to an article that says Sam Altman is also a homosexual, and we must be morally outraged at that next? Because that is where your direction is going, instead of arguing about the ill effects of AI.
I share the sentiment but the question here is how long can we maintain the balance point where the human in the agentic loop is required. It might be a window lasting only a few years, or for the foreseeable future; I think the answer lies the opaque compute economics of the frontier lab: how well models keep scaling and how economically sustainable is serving those models under the current market conditions.
If my job gets automated, I'll find something else to do. I wouldn't have wanted lamplighters to succeed in preventing electrification, so it would be unfair for me to prevent the automation of my job if it can be done.
I use Astra to drive Fable; I drivel into my phone while walking in the forest and it builds. I don’t need to check; I do as clients need to pay, but it always is great. And it surprises me with things I did not know were possible even (never encountered them before so why would I know). We are at the point where our clients send voice messages and they get what they want without humans basically. This costs 10+10 max2 subs but that’s nothing compared to hiring people. We didn’t fire anyone; we just have 100+ more clients and make almost 50x more money. It’s boring but great as long as it lasts, we are already where you say for what enterprises generally need for the boring parts. That’s 99%.
I find I still add value, but I don't know if my value is real. Am I just biased and expect things to be done a certain way and penalize the model for doing something different? and am I providing the model with enough high quality context to align with my expectations in one-shot?
> I used to argue with people on the internet, after about six replies, you realize that you’re speaking to someone incapable of thought
He realises the current woe of things but doesn't realise he's been arguing with bot farms and teams of people hired just for this reason - to sow doom, arguments and engagement.
Around 10 years ago I noticed this happening on trending topics of Twitter - it wasn't that the opponents were stupid because they disagreed, it was that they were simultaneously intelligent and stupid in the way they spoke in a way that I realised I'd never seen in genuine people, making me realise it was probably different people or bots under one account.
If I realised it 10 years ago it was probably happening for at least 15. He wasn't better than these people he was falling into their trap
Haha it’s just a foolish move made by those from the ‘90s. We all internalized a different lesson. The younger generations have learned to brush it off and stop responding. Even if the person is human, when you fail to move toward Aumann Agreement, there is no point in persisting.
Us older ones are still fighting the last war. If only we explain it properly, maybe the bots will understand!
I googled Aumann Agreement and it’s all about agreeing about whether things are true/false/likely/unlikely.
I don’t understand your point at all in this context. What’s “Aumann Agreement” in the context of a discussion about values?
> If only we explain it properly, maybe the bots will understand!
I'm going to be thinking about this perfect summary of my frustration of the last 20 years all day
I've now completely stopped engaging with anyone on that platform that I can't reasonably traced back to a real person. If any non-real-name account says anything that remotely feels bad-faith in replies, I block them. Having been on the Internet since the mid 90's when it was the frontier, and everyone helped/trusted everyone else, the policy feels very wrong. But unfortunately Twitter has given no tools or alternatives to deal with the situation.
I have found that the only way to deal with this these days is basically to only use my time to discuss things with people in private, invitation only forums. HN is a rare exception for "I am pretty sure you all are not bots (yet)" and yet anonymous.
Everything else that I care about is in private Signal groups or an equivalent of same with anywhere from 15 to 200 people, and adding any new member means they need to be vouched for by an existing one. And at least 55-75% of the people know each other face to face through industry vertical specific events, trade shows, conferences and similar.
I can't even imagine trying to engage with people on something like x/twitter or other social media. Not knowing whether the 'person' you're replying to is somebody's LLM authoried bot farm.
That feels like the intellectual equivalent of limiting your career opportunities within a small tiny villages vs. a large city. There is so much more in the city.
> And at least 55-75% of the people know each other face to face through industry vertical specific events, trade shows, conferences and similar.
Tbh, my experience with _that_ has been worse than with a random sample of internet background radiation, as people seem to have no idea how to filter correctly and who to vouch for and why.
_Especially_ with people they know via work, conferences, etc. Spaces that do not filter for "genuinely relevant contributer to a conversation" at all, but encourage faking that.
This is the only way to realistically deal with it but it’s not scalable. A platform is only as useful as its non-bot users. On Twitter even the positive replies are likely bots. Real engagement is limited for most users.
On a site like HN, blocklists are very effective at keeping people off your feed.
Same. (I would love to say, but they still get me way too often)
I can also highly encourage people to keep notes and do some basic OSINT. The effective internet is smaller than one might think, so that proves useful time and time again.
>>anyone on that platform that I can't reasonably traced back to a real person
Not sure why that makes any difference - I've had plenty of arguments on Facebook with people who are perfectly happy to spew racist and/or conspiratorial bullshit while having their full names, their holiday photos and photos of their children and/or grandchildren attached to their identity. The weird thing is that these people are 99/100 times incapable of actually having an argument, they either start insulting you straight away or say some variation of "if you don't like what I'm saying then leave" or actually majority of time "what does a foreigner like you know about this topic".
The real names policy has yielded zero of the promised effects imho.
One of the first things I tell the junior/mid-level developers I mentor is "You can't debug something just by reading the code." We all have a mental model of how our code works, and it's usually a bit wrong. Bugs are the real world manifestations of those mistakes. When you read the code it's all filtered through your model, and that makes you blind to seeing why something unexpected happened. In order to debug something you have to be able to put the system in the state where the bug happens to see why it occurred.
LLMs generally only debug systems by reading the code with whatever information you give them in a prompt. The image in the article is meta-prompt - the prompt is whatever comes from the vision model the AI happens to use to 'understand' the red circle annotation. That won't work. To successfully debug what's going on it will need much better state information. Has the 'shelf' been explained to is? Is the contrast and lack of shadows in the image messing up the vision model? Why isn't the 'lid' in the image? And so on.
LLMs are clever but they're not magical. Treat them like a naive junior dev. Give them enough data about the state of something to understand it properly.
I call this a tautological mental model. You can read the code over and over again, but your second reading will be mostly an echo of the mental model you built up in your first.
I completely understand this. I’ve worked on robot hands and 5.6/Fable 5 were practically useless at helping me debug anything visually.
What I have found super useful actually is having models make a interactive 3d viewer in which I use move / highlight / paint (soft body painting directly onto the geometry for issues and different colors mean different failures). This gives a much better way to communicate the physical relationships and positions that are hard to get across in a labeled screenshot.
Its for sure still a lot of manual work so the "seeing-eye dog" description definitely holds. But I have found that after a couple of examples with the extra context the model gets much better at handling the problem and becomes useful.
A bit off topic, but I absolutely love the little robot on the author's main project's landing page (https://rerun.io/). I normally condemn mouse hijacking, but this implementation will be allowed.
Rerun is pretty dope, but I'm not sure how you came to the conclusion that it's the "author's main project"? There is a whole company backing it, with no affiliation that I could find, apart from the author being an occasional contributor?
LM still can not see and understand the desktop app UI on a level that is acceptable for testing. All the advances in coding are from web dev and thanks to the nature of html UIs. Try to develop a desktop app and it’s like working with a legally blind person who can see some part of the screen is they squint in a certain way but surely will miss all minor details.
> I often handwrite the code myself, but I’ve found that LLM coding assistants’ limitless patience ameliorates the drudgiest work of coding.
I've been using a few different "smart" LLM to work on an analysis, parsing, search and correlation tool that ultimately deals with a 5.5GB on disk (with indexes) mariadb database that has its origin as a federal government department's 905,000 row plain text CSV file.
There are a ridiculous number of data entry errors and just plain weird fuckups in the data origin that don't seem they will be ameliorated any time soon, so automating the drudge work of cleaning it up and rectifying it into something usable is a textbook case for this. Very pleased with the results so far.
I mean there's a reason why we're doing MoCap for video games. If computers were good at this, we wouldn't be needing that. But actual motion and all seems to be much more complex than the systems can predict, apparently.
Also.. uh.. isn't this.. good? I thought AI was to steal all our jobs.
___
Beside that, kinda weird self-description.
Isn't the computer executing your commands and you're just filling in where it cannot do that?
Being that dog implies that the computer is in the driver seat.
I mean it's supposed to be a joke I guess, but I read it as one that leaks internal metadata which seems to be incorrectly calibrated.
<!!spoiler ahead!!>There is a TV show called Person of Interest <!!spoiler ahead!!>, where Machine (AI connected to Internet and CCTV networks) has no legs or eyes, so when it needs to go and check something not covered by CCTV feeds, it gives instructions to a real person. In the show it is called an ‘analog interface.’
> It literally uses you as its organ.
But it isn't. That's my point.
I told the clanker "hey do that", and like the intern/junior it emulates, it eventually says "boss! Help! I can't do this alone".
It is I who is in the driver seat.
If intern is making a breakfast, and boss is the one who suddenly runs to the grocery store because eggs are missing, is boss still the one in a driver’s seat?
From the original goal point of view yes, as it was boss who has initiated whole breakfast procedure. But from an execution standpoint it is intern who gives its boss a job of a grocery store run. He could give same job to anyone else, boss as a persona is irrelevant here.
Uh, okay, at this point, I think I can only wish you a lot of fun with the passive role you seem to be relentlessly pursuing there.
All the best.
>Also.. uh.. isn't this.. good? I thought AI was to steal all our jobs. the problem is, the CEOs still think AI solves their problems ie minimize paid jobs
> All that’s left is the dumbest workflow possible: I fire up the debug viewer myself, look around for weird mistakes, then take a screenshot and tell the language model how badly it messed up this time. Eventually I just decided to do all the debugging work myself, so I would at least get to do the fun part too.
I call this "thanoscoding" for two reasons:
1. "Fine, I'll do it myself"
2. In the past I found I have to "snap away" the mess the LLM made in order to start afresh from a known good state (generally with git reset). But that was 1-2 generations ago when it comes to models. GPT6 Astra probably does things right the first time, 90% of the time.
I like to think of training and improving AIs as bringing freedom to the world. The useless toil and labor associated with rebuilding the same solutions into different contexts is finally at an end.
Coding was never the reward. Acting as a translator for a machine is far worse than allowing the machine to solve the mundane parts and leave you with bigger building blocks to play with.
After 25 years I have to confess I hated being a software engineer. It felt like grinding in a video game.
Now I can finally create and innovate at the speed of thought, and I'm very grateful to have this technology now.
For me code still is the reward; I made and make my fortunes with boring code people on HN say no one needs or wants, my hobby is, and has been for 45 years, writing, perfecting and optimizing code manually until I find it perfect. I have been working for 10 years on a programming language and OS (with niche 2 dbs that are now prod quality and we use) and those are the best moment of my day, I couldn’t care less what anyone thinks of it or ever uses it. But the lessons learned do flow into LLMs to write the boring code and I can say that our million$ paying LoB code can handle 100s req/s on shite hardware and even if the LLM did a crap job. Which is almost 100s times more than the client will ever needs.
You got nothing.
Giant corpos hold every sliver of your so called freedom, you dont innovate, you repeat what others created before you. You use a tool that shackles your thoughts and creativity in a never before seen way, what you perceive is an illusion of liberty that is no present. Without others you are nothing and they can take it away any seconds, you are an addict, not an innovator.
I can see where you're coming from, and I share the sentiment and resentment to a large degree, but I think you might be not doing reality justice.
It is true that closed weights models are a big issue. It is also true that LLM-generated solutions usually drift towards a median.
But that is not the dead end you think it might be.
Most coding work is repetitive boilerplate, and most typing is just.. well.. typing. Miserable work I too did not really enjoy. What I did enjoy were the end results, and that was just a necessary step to get there.
Now that's less the case than it was before we had LLMs, and for that I too am glad.
___
I think the article headline might've primed you (and me, fwiw) to reading the comment you're replying to as passive. But if you just look at the words of it, that might not actually be the case.
The same can be said of stuff like cloud storage and email and social media. And yet here we are.
Your point is true to some extend, I personally host my own "cloud" storage..it comes with drawbacks, same is true for email..especially email, social media is a society constructs, by definition its reliant on others but many will argue that its not worth keeping anyway (although I wonder how one stays human in this world then, the meat space seems with so many barrieres in this age).
I feel very much like a luddite..or some artisan of a bygone age. The guy above laments how he never enjoyed coding, this is an interesting sentiment, I know quite a few people who enjoy the craft itself, myself included. The ability to form words that have meaning, that create something from nothing. Sure, the words are just a tool, but its something _I_ can master, not some abstract wish machine that may change its functionality tommorow. Obviously one can argue that the computer itself is in this case the one that creates and not me, its not magic that just works with me, but the machine I got obeys me and me alone..another reason why personal computing is important.
You lost leverage. Now be great full for the crumbs. If there remain any.
Viva la revolution!
Serious question - what do you do for fun? I find fishing with friends enjoyable, and using my hands tidying up the old place I bought. It’s not innovating software I’ll never use but I’ll never tire of writing the same old ASP that delivers my clients the results they’re after.
> I like to think of training and improving AIs as bringing freedom to the world.
Yes, when I think of OpenAI and Anthrophic and Google and Meta and any AI labs and their intentions, i cry a single tear for how these great instituitions are working so hard to bring freedom for humanity.
Freedom is slavery!
AI owned by a few companies is more likely to put the majority right back to serfdom. You're a privileged fool to believe that freedom is the likely outcome of the current stampede.
With a username that appears to cheer for a sociopath¹, I doubt reason will convince you.
¹ https://futurism.com/artificial-intelligence/sources-sam-alt...
Their /s was implied
(Like, Meta’s intentions? lol)
I hope so.
It was obviously a sarcastic joke. I get it if you didn't catch that, but do you think my username glorifies Sam Altman? And is that a reason to talk negatively about me? You doubt reason will convince me? And at the end, you call *me* a privileged fool. Wow, just wow.
Also, I don't think you can cite a subjective take as objectively correct by including it as a footnote. Why do you need to medically diagnose him to say what he's doing is fucked up?
Why does he have to be literally the devil for outrage to work?
He could also not be a sociopath, but still his actions will be his actions, and it is okay to criticize them. Next what, you're going to link to an article that says Sam Altman is also a homosexual, and we must be morally outraged at that next? Because that is where your direction is going, instead of arguing about the ill effects of AI.
I share the sentiment but the question here is how long can we maintain the balance point where the human in the agentic loop is required. It might be a window lasting only a few years, or for the foreseeable future; I think the answer lies the opaque compute economics of the frontier lab: how well models keep scaling and how economically sustainable is serving those models under the current market conditions.
If my job gets automated, I'll find something else to do. I wouldn't have wanted lamplighters to succeed in preventing electrification, so it would be unfair for me to prevent the automation of my job if it can be done.
I use Astra to drive Fable; I drivel into my phone while walking in the forest and it builds. I don’t need to check; I do as clients need to pay, but it always is great. And it surprises me with things I did not know were possible even (never encountered them before so why would I know). We are at the point where our clients send voice messages and they get what they want without humans basically. This costs 10+10 max2 subs but that’s nothing compared to hiring people. We didn’t fire anyone; we just have 100+ more clients and make almost 50x more money. It’s boring but great as long as it lasts, we are already where you say for what enterprises generally need for the boring parts. That’s 99%.
I find I still add value, but I don't know if my value is real. Am I just biased and expect things to be done a certain way and penalize the model for doing something different? and am I providing the model with enough high quality context to align with my expectations in one-shot?
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These people need to take a vacation and come back in a few months when the vision models get better/cheaper.
Astra is already good at taking screenshots and acting on it (part of the agi claims).