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My friends at Google are some of the most negative about the potential of AI to improve software development. I was always surprised by this and assumed intern

My friends at Google are some of the most negative about the potential of AI to improve software development. I was always surprised by this and assumed internally at Google would be one of the first places to adopt these.

gipp 10mo ago
Engineers at Google are much less likely to be doing green-field generation of large amounts of code . It's much more incremental, carefully measured changes to mature, complex software stacks, and done within the Google ecosystem, which is heavily divergent from the OSS-focused world of startups, where most training data comes from
- karmasimida 10mo ago
  That is the problem. AI is optimized to solve a problem no matter what it takes. It will try to solve one problem by creating 10 more. I think long time/term agentic AI is just snake oil at this point. AI works best if you can segment your task into 5-10 minutes chunks, including the AI generating time, correcting time and engineer review time. To put it another way, a 10 minute sync with human is necessary, otherwise it will go astray. Then it just makes software engineering into bothering supervisor job. Yes I typed less, but I didn’t feel the thrill of doing so.
  - citizenpaul 10mo ago
    > it just makes software engineering into bothering supervisor job. I'm pretty sure this is the entire enthusiasm from C-level for AI in a nutshell. Until AI SWE resisted being mashed into a replaceable cog job that they don't have to think/care about. AI is the magic beans that are just tantalizingly out of reach and boy do they want it.
    - spwa4 10mo ago
      But every version of AI for almost a century had this property, right down from the first vocoders that were going to replace entire callcenters to convolutional AI that was going to give us self-driving cars. Yes, a century, vocoders were 1930s technology, but they can essentially read the time aloud. ... except they didn't. In fact most AI tech were good for a nice demo and little else. In some cases, really unfairly. For instance, convnet map matching doesn't work well not because it doesn't work well, but because you can't explain to humans when it won't work well. It's unpredictable, like a human. If you ask a human to map a building in heavy fog they may come back with "sorry". SLAM with lidar is "better", except no, it's a LOT worse. But when it fails it's very clear why it fails because it's a very visual algorithm. People expect of AIs that they can replace humans but that doesn't work, because people also demand AIs never say no, never fail, like the Star Trek computer (the only problem the star trek computer ever has is that it is misunderstood or follows policy too well). If you have a delivery person occasionally they will radically modify the process, or refuse to deliver. No CEO is ever going to allow an AI drone to change the process and No CEO will ever accept "no" from an AI drone. More generally, no business person seems to ever accept a 99% AI solution, and all AI solutions are 99%, or actually mostly less. AI winters. I get the impression another one is coming, and I can feel it's going to be a cold one. But in 10 years, LLMs will be in a lot of stuff, like with every other AI winter. A lot of stuff ... but a lot less than CEOs are declaring it will be in today.
    - voidhorse 10mo ago
      Luckily for us, technologies like SQL made similar promises (for more limited domains) and C suites couldn't be bothered to learn that stuff either. Ultimately they are mostly just clueless, so we will either end up with legions of way shittier companies than we have today (because we let them get away with offloading a bunch of work to tools they rms int understand and accepting low quality output) or we will eventually realize the continued importance of human expertise.
- kccqzy 10mo ago
  Yeah but Google won’t expect you to use AI tools developed outside Google and trained on primarily OSS code. It would expect you to use the Google internal AI tools trained on google3, no?
- groby_b 10mo ago
  There are plenty of good tasks left, but they're often one-off/internal tooling. Last one at work: "Hey, here are the symptoms for a bug, they appeared in <release XYZ> - go figure out the CL range and which 10 CLs I should inspect first to see if they're the cause" (Well suited to AI, because worst case I've looked at 10 CLs in vain, and best case it saved me from manually scanning through several 1000 CLs - the EV is net positive) It works for code generation as well, but not in a "just do my job" way, more in a "find which haystack the needle is in, and what the rough shape of the new needle is". Blind vibecoding is a non-starter. But... it's a non-starter for greenfields too, it's just that the FO of FAFO is a bit more delayed.
  - ethbr1 10mo ago
    My internal mnemonic for targeting AI correctly is 'It's easier to change a problem into something AI is good at, than it is to change AI into something that fits every problem.' But unfortunately the nuances in the former require understanding strengths and weaknesses of current AI systems, which is a conversation the industry doesn't want to have while it's still riding the froth of a hype cycle. Aka 'any current weaknesses in AI systems are just temporary growing pains before an AGI future'
    - groby_b 10mo ago
      > 'any current weaknesses in AI systems are just temporary growing pains before an AGI future' I see we've met the same product people :)
      - ethbr1 10mo ago
        I had a VP of a revenue cycle team tell me that his expectation was that they could fling their spreadsheets and Word docs on how to do calculations at an AI powered vendor, and AI would be able to (and I direct quote) "just figure it all out." That's when I realized how far down the rabbit hole marketing to non-technical folks on this was.
- almostdeadguy 10mo ago
  I think it’s a fair point that google has more stakeholders with a serious investment in some flubbed AI generated code not tanking their share value, but I’m not sure the rest of it is all that different from what engineer at $SOME_STARTUP does after the first ~8monthes the company is around. Maybe some folks throwing shit at a wall to find PMF are really getting a lot out of this, but most of us are maintaining and augmenting something we don’t want to break.
yoyohello13 10mo ago
Google has good engineers. Generally I've noticed the better someone is at coding the more critical they are of AI generated code. Which make sense honestly. It's easier to spot flaws the more expert you are. This doesn't mean they don't use AI gen code, just they are more careful with when an where.
- venturecruelty 10mo ago
  Yes, because they're more likely to understand that the computer isn't this magical black box, and that just because we've made ELIZA marginally better, doesn't mean it's actually good. Anecdata, but the people I've seen be dazzled by AI the most are people with little to no programming experience. They're also the ones most likely to look on computer experts with disdain.
  - dingnuts 10mo ago
    [dead]
  - josephg 10mo ago
    Well yeah. And because when an expert looks at the code chatgpt produces, the flaws are more obvious. It programs with the skill of the median programmer on GitHub. For beginners and people who do cookie cutter work, this can be incredible because it writes the same or better code they could write, fast and for free. But for experts, the code it produces is consistently worse than what we can do. At best my pride demands I fix all its flaws before shipping. More commonly, it’s a waste of time to ask it to help, and I need to code the solution from scratch myself anyway. I use it for throwaway prototypes and demos. And whenever I’m thrust into a language I don’t know that well, or to help me debug weird issues outside my area of expertise. But when I go deep on a problem, it’s often worse than useless.
    - ethbr1 10mo ago
      This is why AI is the perfect management Rorschach test. To management (out of IC roles for long enough to lose their technical expertise), it looks perfect! To ICs, the flaws are apparent! So inevitably management greenlights new AI projects* and behaviors, and then everyone is in the 'This was my idea, so it can't fail' CYA scenario. * Add in a dash of management consulting advice here, and note that management consultants' core product was already literally 'something that looks plausible enough to make execs spend money on it'
agumonkey 10mo ago
so would love to be a fly in there office and hear all their convos
3vidence 10mo ago
Googler, opinion is my own. Working on our mega huge code basis with lots of custom tooling and bleeding edge stuff hasn't been the best for for AI generated code compared to most companies. I do think AI as a rubber ducky / research assistant type has been overall helpful as a SWE.
fogj094j0923j4 10mo ago
I notice that expert tends to be pretty bimodal. e.g. chef either enjoy really well made food or some version of scrappy fast food comfort they grew up eating.
- petesergeant 10mo ago
  Bimodal here suggests either/or which I don’t think is correct for either chefs or code enjoyers. I think experts tend to eschew snobbery more and can see the value in comfort food, quick and dirty AI prototypes or boilerplate, or say cheap and drinkable wine, while also being able to appreciate what the truly high-end looks like. It’s the mid-range with pretensions that gets squeezed out. I absolutely do not need a $40 bottle of wine to accompany my takeout curry, I definitely don’t need truffle slices added to my carbonara, and I don’t need to hand-roll conceptually simple code.
nilkn 10mo ago
People who've spent their life perfecting a craft are exactly the people you'd expect would be most negative about something genuinely disrupting that craft. There is significant precedent for this. It's happened repeatedly in history. Really smart, talented people routinely and in fact quite predictably resist technology that disrupts their craft, often even at great personal cost within their own lifetime.
- queenkjuul 10mo ago
  I don't know that i consider recognizing the limitations of a tool to be resistance to the idea. It makes sense that experts would recognize those limitations most acutely -- my $30 harbor freight circular saw is a lifesaver for me when I'm doing slapdash work in my shed, but it'd be a critical liability for a professional carpenter needing precision cuts. That doesn't mean the professional carpenter is resistant to the idea of using power saws, just that they necessarily must be more discerning than I do.
- rprend 10mo ago
  Yes you get it. Obviously “writing code” will die. It will hold on in legacy systems that need bespoke maintenance, like COBOL systems have today. There will be artisanal coders, like there are artisanal blacksmiths, who do it the old fashioned way, and we will smile and encourage them. Within 20 years, writing code syntax will be like writing assembly: something they make you do in school, something that your dad reminds you about the good old days. I talked to someone who was in denial about this, until he said he had conflated writing code with solving problems. Solving problems isn’t going anywhere! Solving problems: you observe a problem, write out a solution, implement that solution, measure the problem again, consider your metrics, then iterate. “Implement it” can mean writing code, like the past 40 years, but it hasn’t always been. Before coding, it was economics and physics majors, who studied and implemented scientific management. For the next 20 years, it will be “describe the tool to Claude code and use the result”.
  - xwolfi 10mo ago
    But Claude cannot code at all, it's gonna shit the bed and it learns only on human coders to be able to even know an example is a solution rather than a malware...
xoogthrowkappa 10mo ago
Excuse the throwaway. It's not even just the employees, but it doesn't even seem like the technical leadership seriously cares about internal AI use. Before I left all they pushed was code generation, but my work was 80% understanding 5-20 year old code and 20% actual development. If they put any noticeable effort into an LLM that could answer "show me all users of Proto.field that would be affected by X", my life would've been changed for the better, but I don't think the technical leadership understands this, or they don't want to spare the TPUs. When I started at my post-Google job, I felt so vindicated when my new TL recommended that I use an LLM to catch up if no one was available to answer my questions.
anukin 10mo ago
You cannot trust someone’s judgement on something if that something can result in them being unemployed.
- llbeansandrice 10mo ago
  Or if they stand to make a lot of money. See both sides can be pithy.
ta9000 10mo ago
[dead]
volf_ 10mo ago
because autocorrect and predictive text doesn't help when half your job is revisions
crystal_revenge 10mo ago
I've generally found an inverse correlation between "understands AI" and "exuberance for AI". I'm the only person at my current company who has had experience at multiple AI companies (the rest have never worked on it in a production environment, one of our projects is literally something I got paid to deliver customers at another startup), has written professionally about the topic, and worked directly with some big names in the space. Unsurprisingly, I have nothing to do with any of our AI efforts. One of the members of our leadership team, who I don't believe understands matrix multiplication, genuinely believes he's about to transcend human identity by merging with AI. He's publicly discussed how hard it is to maintain friendship with normal humans who can't keep up. Now I absolutely think AI is useful, but these people don't want AI to be useful they want it to be something that anyone who understands it knows it can't be. It's getting to the point where I genuinely feel I'm witnessing some sort of mass hysteria event. I keep getting introduced to people who have almost no understanding of the fundamentals of how LLMs work who have the most radically fantastic ideas about what they are capable of on a level I have ever experienced in my fairly long technical career.
- throwaway-0001 10mo ago
  I think there is a correlation between when you can you expect from something when I know their internals vs someone that doesn’t know but is not like who knows internals is much much better. Example: many people created websites without a clue of how they really work. And got millions of people on it. Or had crazy ideas to do things with them. At the same time there are devs that know how internals work but can’t get 1 user. pc manufacturers never were able to even imagine what random people were able to do with their pc. This to say that even if you know internals you can claim you know better, but doesn’t mean it’s absolute. Sometimes knowing the fundamentals it’s a limitation. Will limit your imagination.
  - crystal_revenge 10mo ago
    I'm a big fan of the concept of 初心 (Japanese: Shoshin aka "beginners mind" [0] ) and largely agree with Sazuki's famous quote: > “In the beginner’s mind there are many possibilities, but in the expert’s there are few” Experts do tend to be limited in what they see as possible. But I don't think that allows carte blanche belief that a fancy Markov Chain will let you transcend humanity. I would argue one of the key concepts of "beginners mind" is not radical assurance in what's possible but unbounded curiosity and willingness to explore with an open mind. Right now we see this in the Stable Diffusion community: there are tons of people who also don't understand matrix multiplication that are doing incredible work through pure experimentation. There's a huge gap between "I wonder what will happen if I just mix these models together" and "we're just a few years from surrendering our will to AI". None of the people I'm concerned about have what I would consider an "open mind" about the topic of AI. They are sure of what they know and to disagree is to invite complete rejection. Hardly a principle of beginners mind. Additionally: > pc manufacturers never were able to even imagine what random people were able to do with their pc. Belies a deep ignorance of the history of personal computing. Honestly, I don't think modern computing has still ever returned to the ambition of what was being dreampt up, by experts, at Xerox PARC. The demos on the Xerox Alto in the early 1970s are still ambitious in some senses. And, as much as I'm not a huge fan, Gates and Jobs absolutely had grand visions for what the PC would be. 0. https://en.wikipedia.org/wiki/Shoshin https://en.wikipedia.org/wiki/Shoshin
nunez 10mo ago
Makes sense to me. From the outside, the AI push at Google very closely resembles the death march that Google+ but immensely more intense from the entire tech ecosystem following suit.
Arainach 10mo ago
Being forced to adopt tools regardless of fit to workflow (and being smart enough to understand the limitations of the tools despite management's claims) correlates very well to being negative on them.

gipp 10mo ago

Engineers at Google are much less likely to be doing green-field generation of large amounts of code . It's much more incremental, carefully measured changes to mature, complex software stacks, and done within the Google ecosystem, which is heavily divergent from the OSS-focused world of startups, where most training data comes from

karmasimida 10mo ago
That is the problem. AI is optimized to solve a problem no matter what it takes. It will try to solve one problem by creating 10 more. I think long time/term agentic AI is just snake oil at this point. AI works best if you can segment your task into 5-10 minutes chunks, including the AI generating time, correcting time and engineer review time. To put it another way, a 10 minute sync with human is necessary, otherwise it will go astray. Then it just makes software engineering into bothering supervisor job. Yes I typed less, but I didn’t feel the thrill of doing so.
- citizenpaul 10mo ago
  > it just makes software engineering into bothering supervisor job. I'm pretty sure this is the entire enthusiasm from C-level for AI in a nutshell. Until AI SWE resisted being mashed into a replaceable cog job that they don't have to think/care about. AI is the magic beans that are just tantalizingly out of reach and boy do they want it.
  - spwa4 10mo ago
    But every version of AI for almost a century had this property, right down from the first vocoders that were going to replace entire callcenters to convolutional AI that was going to give us self-driving cars. Yes, a century, vocoders were 1930s technology, but they can essentially read the time aloud. ... except they didn't. In fact most AI tech were good for a nice demo and little else. In some cases, really unfairly. For instance, convnet map matching doesn't work well not because it doesn't work well, but because you can't explain to humans when it won't work well. It's unpredictable, like a human. If you ask a human to map a building in heavy fog they may come back with "sorry". SLAM with lidar is "better", except no, it's a LOT worse. But when it fails it's very clear why it fails because it's a very visual algorithm. People expect of AIs that they can replace humans but that doesn't work, because people also demand AIs never say no, never fail, like the Star Trek computer (the only problem the star trek computer ever has is that it is misunderstood or follows policy too well). If you have a delivery person occasionally they will radically modify the process, or refuse to deliver. No CEO is ever going to allow an AI drone to change the process and No CEO will ever accept "no" from an AI drone. More generally, no business person seems to ever accept a 99% AI solution, and all AI solutions are 99%, or actually mostly less. AI winters. I get the impression another one is coming, and I can feel it's going to be a cold one. But in 10 years, LLMs will be in a lot of stuff, like with every other AI winter. A lot of stuff ... but a lot less than CEOs are declaring it will be in today.
  - voidhorse 10mo ago
    Luckily for us, technologies like SQL made similar promises (for more limited domains) and C suites couldn't be bothered to learn that stuff either. Ultimately they are mostly just clueless, so we will either end up with legions of way shittier companies than we have today (because we let them get away with offloading a bunch of work to tools they rms int understand and accepting low quality output) or we will eventually realize the continued importance of human expertise.
kccqzy 10mo ago
Yeah but Google won’t expect you to use AI tools developed outside Google and trained on primarily OSS code. It would expect you to use the Google internal AI tools trained on google3, no?
groby_b 10mo ago
There are plenty of good tasks left, but they're often one-off/internal tooling. Last one at work: "Hey, here are the symptoms for a bug, they appeared in <release XYZ> - go figure out the CL range and which 10 CLs I should inspect first to see if they're the cause" (Well suited to AI, because worst case I've looked at 10 CLs in vain, and best case it saved me from manually scanning through several 1000 CLs - the EV is net positive) It works for code generation as well, but not in a "just do my job" way, more in a "find which haystack the needle is in, and what the rough shape of the new needle is". Blind vibecoding is a non-starter. But... it's a non-starter for greenfields too, it's just that the FO of FAFO is a bit more delayed.
- ethbr1 10mo ago
  My internal mnemonic for targeting AI correctly is 'It's easier to change a problem into something AI is good at, than it is to change AI into something that fits every problem.' But unfortunately the nuances in the former require understanding strengths and weaknesses of current AI systems, which is a conversation the industry doesn't want to have while it's still riding the froth of a hype cycle. Aka 'any current weaknesses in AI systems are just temporary growing pains before an AGI future'
  - groby_b 10mo ago
    > 'any current weaknesses in AI systems are just temporary growing pains before an AGI future' I see we've met the same product people :)
    - ethbr1 10mo ago
      I had a VP of a revenue cycle team tell me that his expectation was that they could fling their spreadsheets and Word docs on how to do calculations at an AI powered vendor, and AI would be able to (and I direct quote) "just figure it all out." That's when I realized how far down the rabbit hole marketing to non-technical folks on this was.
almostdeadguy 10mo ago
I think it’s a fair point that google has more stakeholders with a serious investment in some flubbed AI generated code not tanking their share value, but I’m not sure the rest of it is all that different from what engineer at $SOME_STARTUP does after the first ~8monthes the company is around. Maybe some folks throwing shit at a wall to find PMF are really getting a lot out of this, but most of us are maintaining and augmenting something we don’t want to break.

yoyohello13 10mo ago

Google has good engineers. Generally I've noticed the better someone is at coding the more critical they are of AI generated code. Which make sense honestly. It's easier to spot flaws the more expert you are. This doesn't mean they don't use AI gen code, just they are more careful with when an where.

venturecruelty 10mo ago
Yes, because they're more likely to understand that the computer isn't this magical black box, and that just because we've made ELIZA marginally better, doesn't mean it's actually good. Anecdata, but the people I've seen be dazzled by AI the most are people with little to no programming experience. They're also the ones most likely to look on computer experts with disdain.
- dingnuts 10mo ago
  [dead]
- josephg 10mo ago
  Well yeah. And because when an expert looks at the code chatgpt produces, the flaws are more obvious. It programs with the skill of the median programmer on GitHub. For beginners and people who do cookie cutter work, this can be incredible because it writes the same or better code they could write, fast and for free. But for experts, the code it produces is consistently worse than what we can do. At best my pride demands I fix all its flaws before shipping. More commonly, it’s a waste of time to ask it to help, and I need to code the solution from scratch myself anyway. I use it for throwaway prototypes and demos. And whenever I’m thrust into a language I don’t know that well, or to help me debug weird issues outside my area of expertise. But when I go deep on a problem, it’s often worse than useless.
  - ethbr1 10mo ago
    This is why AI is the perfect management Rorschach test. To management (out of IC roles for long enough to lose their technical expertise), it looks perfect! To ICs, the flaws are apparent! So inevitably management greenlights new AI projects* and behaviors, and then everyone is in the 'This was my idea, so it can't fail' CYA scenario. * Add in a dash of management consulting advice here, and note that management consultants' core product was already literally 'something that looks plausible enough to make execs spend money on it'

agumonkey 10mo ago

so would love to be a fly in there office and hear all their convos

3vidence 10mo ago

Googler, opinion is my own. Working on our mega huge code basis with lots of custom tooling and bleeding edge stuff hasn't been the best for for AI generated code compared to most companies. I do think AI as a rubber ducky / research assistant type has been overall helpful as a SWE.

fogj094j0923j4 10mo ago

I notice that expert tends to be pretty bimodal. e.g. chef either enjoy really well made food or some version of scrappy fast food comfort they grew up eating.

petesergeant 10mo ago
Bimodal here suggests either/or which I don’t think is correct for either chefs or code enjoyers. I think experts tend to eschew snobbery more and can see the value in comfort food, quick and dirty AI prototypes or boilerplate, or say cheap and drinkable wine, while also being able to appreciate what the truly high-end looks like. It’s the mid-range with pretensions that gets squeezed out. I absolutely do not need a $40 bottle of wine to accompany my takeout curry, I definitely don’t need truffle slices added to my carbonara, and I don’t need to hand-roll conceptually simple code.

nilkn 10mo ago

People who've spent their life perfecting a craft are exactly the people you'd expect would be most negative about something genuinely disrupting that craft. There is significant precedent for this. It's happened repeatedly in history. Really smart, talented people routinely and in fact quite predictably resist technology that disrupts their craft, often even at great personal cost within their own lifetime.

queenkjuul 10mo ago
I don't know that i consider recognizing the limitations of a tool to be resistance to the idea. It makes sense that experts would recognize those limitations most acutely -- my $30 harbor freight circular saw is a lifesaver for me when I'm doing slapdash work in my shed, but it'd be a critical liability for a professional carpenter needing precision cuts. That doesn't mean the professional carpenter is resistant to the idea of using power saws, just that they necessarily must be more discerning than I do.
rprend 10mo ago
Yes you get it. Obviously “writing code” will die. It will hold on in legacy systems that need bespoke maintenance, like COBOL systems have today. There will be artisanal coders, like there are artisanal blacksmiths, who do it the old fashioned way, and we will smile and encourage them. Within 20 years, writing code syntax will be like writing assembly: something they make you do in school, something that your dad reminds you about the good old days. I talked to someone who was in denial about this, until he said he had conflated writing code with solving problems. Solving problems isn’t going anywhere! Solving problems: you observe a problem, write out a solution, implement that solution, measure the problem again, consider your metrics, then iterate. “Implement it” can mean writing code, like the past 40 years, but it hasn’t always been. Before coding, it was economics and physics majors, who studied and implemented scientific management. For the next 20 years, it will be “describe the tool to Claude code and use the result”.
- xwolfi 10mo ago
  But Claude cannot code at all, it's gonna shit the bed and it learns only on human coders to be able to even know an example is a solution rather than a malware...

xoogthrowkappa 10mo ago

Excuse the throwaway. It's not even just the employees, but it doesn't even seem like the technical leadership seriously cares about internal AI use. Before I left all they pushed was code generation, but my work was 80% understanding 5-20 year old code and 20% actual development. If they put any noticeable effort into an LLM that could answer "show me all users of Proto.field that would be affected by X", my life would've been changed for the better, but I don't think the technical leadership understands this, or they don't want to spare the TPUs. When I started at my post-Google job, I felt so vindicated when my new TL recommended that I use an LLM to catch up if no one was available to answer my questions.

anukin 10mo ago

You cannot trust someone’s judgement on something if that something can result in them being unemployed.

llbeansandrice 10mo ago
Or if they stand to make a lot of money. See both sides can be pithy.

ta9000 10mo ago

[dead]

volf_ 10mo ago

because autocorrect and predictive text doesn't help when half your job is revisions

crystal_revenge 10mo ago

I've generally found an inverse correlation between "understands AI" and "exuberance for AI". I'm the only person at my current company who has had experience at multiple AI companies (the rest have never worked on it in a production environment, one of our projects is literally something I got paid to deliver customers at another startup), has written professionally about the topic, and worked directly with some big names in the space. Unsurprisingly, I have nothing to do with any of our AI efforts. One of the members of our leadership team, who I don't believe understands matrix multiplication, genuinely believes he's about to transcend human identity by merging with AI. He's publicly discussed how hard it is to maintain friendship with normal humans who can't keep up. Now I absolutely think AI is useful, but these people don't want AI to be useful they want it to be something that anyone who understands it knows it can't be. It's getting to the point where I genuinely feel I'm witnessing some sort of mass hysteria event. I keep getting introduced to people who have almost no understanding of the fundamentals of how LLMs work who have the most radically fantastic ideas about what they are capable of on a level I have ever experienced in my fairly long technical career.

throwaway-0001 10mo ago
I think there is a correlation between when you can you expect from something when I know their internals vs someone that doesn’t know but is not like who knows internals is much much better. Example: many people created websites without a clue of how they really work. And got millions of people on it. Or had crazy ideas to do things with them. At the same time there are devs that know how internals work but can’t get 1 user. pc manufacturers never were able to even imagine what random people were able to do with their pc. This to say that even if you know internals you can claim you know better, but doesn’t mean it’s absolute. Sometimes knowing the fundamentals it’s a limitation. Will limit your imagination.
- crystal_revenge 10mo ago
  I'm a big fan of the concept of 初心 (Japanese: Shoshin aka "beginners mind" [0] ) and largely agree with Sazuki's famous quote: > “In the beginner’s mind there are many possibilities, but in the expert’s there are few” Experts do tend to be limited in what they see as possible. But I don't think that allows carte blanche belief that a fancy Markov Chain will let you transcend humanity. I would argue one of the key concepts of "beginners mind" is not radical assurance in what's possible but unbounded curiosity and willingness to explore with an open mind. Right now we see this in the Stable Diffusion community: there are tons of people who also don't understand matrix multiplication that are doing incredible work through pure experimentation. There's a huge gap between "I wonder what will happen if I just mix these models together" and "we're just a few years from surrendering our will to AI". None of the people I'm concerned about have what I would consider an "open mind" about the topic of AI. They are sure of what they know and to disagree is to invite complete rejection. Hardly a principle of beginners mind. Additionally: > pc manufacturers never were able to even imagine what random people were able to do with their pc. Belies a deep ignorance of the history of personal computing. Honestly, I don't think modern computing has still ever returned to the ambition of what was being dreampt up, by experts, at Xerox PARC. The demos on the Xerox Alto in the early 1970s are still ambitious in some senses. And, as much as I'm not a huge fan, Gates and Jobs absolutely had grand visions for what the PC would be. 0. https://en.wikipedia.org/wiki/Shoshin https://en.wikipedia.org/wiki/Shoshin

nunez 10mo ago

Makes sense to me. From the outside, the AI push at Google very closely resembles the death march that Google+ but immensely more intense from the entire tech ecosystem following suit.

Arainach 10mo ago

Being forced to adopt tools regardless of fit to workflow (and being smart enough to understand the limitations of the tools despite management's claims) correlates very well to being negative on them.