HN user
Precisely my point. Say for examples planes, trains or automobiles, humans may make way more errors than a computer does but you can bet your bottom dollar the threshold for allowing computers to autonomously control the above is way higher. Because the expectation is that if it is a computer it ought do it far better/safer.
Because Claude isn't a human the perception of it is different.
Humans can fly planes, computers too can fly planes. I'm not going to give the same leeway to a 'computer' flying a plane that I would to a human. Because we understand that humans are just that, humans. The demands placed on a computer are so very different.
LLM's are the primary cause of SO decline. Largely due to LLM's having scraped SO (and everything else available on the WWW). It's the reason there is a decline in traffic across the web i.e. Wikipedia. LLM's surface the required search query or info directly.
Exactly this!
LLM's are replacing your 'brain' i.e. the deepest most amazing part of you. The potential value of this to business is astronomical!
No there won't be an explosion of new software, a minor blip perhaps and even this one of diminishing returns (each cycle of LLM improvements requiring less and less human input).
If there are 25 million software developers today then the ROI by OpenAI, Anthropic et al pays off if in a few years time only 15 million developers are needed. That 10 million is the ROI and that is likely to be you.
I think you missed my point I'm not denying the code does not produce a function of effect. The code however is uninteresting because almost anyone can also generate it.
I'm interested in the source code to Quake but not in the source code to an LLM generated Quake equivalent, I love to hear about the Fast Inverse Square Root formula in Quake that Id software wrote but I'm unmoved by the generated LLM version.
Attempting to illustrate why your analogy is flawed and explain myself a little better I would add that there are quantitive things and qualitative things. If the object was to remove some volume of earth (quantitive) then whether it is moved by a Caterpillar or by 100 men with shovels does not matter.
If you're 'no longer looking at the code' or 'looping everything' then you are implicitly moving towards a more quantitive outlook of software development. How it does so becomes less and less meaningful and why would you even care?
Who says you need a boss or other human coworkers?
I didn't. However most people on here and around the world are employed I am merely pointing out that your employer dictates so much of what you do.
Start your own consultancy.
Great, but realise then that you are talking about creating a business. Which is a whole other field altogether. You can have a business in software, or in legal, or mining etc. But that's a different conversation. It's about business and not about software or LLM's.
That's such a naive take, the joy of helping the customer ha! That's a situation your employer sets up for you!
Try reading your sentence above and swapping in 'EMPLOYEE':
'These LLMs are like EMPLOYEES. The customer cannot tell the difference between EMPLOYEE painted and LLM generated at even a short distance. '
If it's code built by an LLM it's almost inherently uninteresting in that 'anyone' can also generate the same slop. Beyond the initial novelty the 'achievement' really doesn't stretch that far.
Your slop, my slop, their slop it's all 'slop' and no one can really care about slop. The novelty is wearing thin fast
What is 'reasoning' or IQ or more importantly consciousness are very difficult open questions in science.
An approach that might shed some light is instead to define what consciousness ISN'T or what thinking ISN'T. Naively let us say consciousness is NOT a large list of weights (i.e. an LLM).
The uncanny emergent ability of an LLM depends entirely on training data. A mathematical model is used to match output against training data (via loss functions etc). The training data contains all the human ingenuity, logic, rational, patterns and features.
Try giving an LLM model the alphabet ALONE and see what it comes up with? Why are you able to immediately reason that given the alphabet alone it could not 'reason', 'think' or produce much of anything useful.
To address briefly the idea of reasoning and something assembling reasoning somehow implying the same thing. Try the following thought experiment. Given a simulated world (e.g. The Matrix), no matter how good the simulation you would not actually get WET.
Written by AI and not nearly as impressive at all. Such a shame because I thought someone had spent real time and effort producing this. The output is commoditised and now neither important nor precious. Damn near anyone could repeat it.
You are correct, it was flagged almost immediately and I'm unsure why (though my conspiratorial brain kicked in attempting to turn up answers). In any case and perhaps as a consequence I feel it hasn't gotten the traction it should have. FYI I submitted the article from my own account after seeing it flagged.
I would like to point out the exceptional quality of the writing itself which forced me to peruse other posts on the blog.
Defining consciousness is one of the most difficult outstanding problems in the whole of science please see: https://en.wikipedia.org/wiki/Hard_problem_of_consciousness
An approach that might shed some light is instead to define what consciousness ISN'T. Naively let us say consciousness is NOT a large list of weights (i.e. an LLM).
The uncanny emergent ability depends entirely on training data. A mathematical model is used to match output against training data (via loss functions etc). The training data contains all the human ingenuity, logic, rational, patterns and features.
Try giving an LLM model the alphabet ALONE and see what it comes up with?
LLM's don't 'think' nor do they 'reason'.
If I can 'speak' for the OP:
I keep trying to ride a bike but I keep falling off
I do not think this analogy is apt.
The core issue is that AI is taking away, or will take away, or threatens to take away, experiences and activities that humans would WANT to do.
The article is lamenting the disappearing of something meaningful for the OP. One can feel sad for this alone. It is not an equation to balance: X is gone but Y is now available. The lament stands alone. As the OP indicates with his 'pragmatism' we now collectively have little choice about the use of AI. The flood waters do not ask they take everyone in their path.
I find it interesting, the comments on this post (not just this particular comment per se) and the sheer inability to relate or ATTEMPT to relate to another persons experience or feeling. The post itself articulated a viewpoint and experience, your having a different one does not negate the other. Nor does your perspective mean the other does not exist. I'm dumbfounded at many of the comments.
Here are some clipped comments that I pulled from the overall post
I don't get it.
I'm using LLMs to code and I'm still thinking hard.
I don't. I miss being outside, in the sun, living my life. And if there's one thing AI has done it's save my time.
Then think hard? Have a level of self discipline and don’t consistently turn to AI to solve your problems.
I am thinking harder than ever due to vibe coding.
Skill issue
Maybe this is just me, but I don't miss thinking so much.
The last comment pasted is pure gold, a great one to put up on a wall. Gave me a right chuckle thanks!!!
We know what an LLM is in fact you can build one from scratch if you like. e.g. https://www.manning.com/books/build-a-large-language-model-f...
It's an algorithm and a completely mechanical process which you can quite literally copy time and time again. Unless of course you think 'physical' computers have magical powers that a pen and paper Turing machine doesn't?
Many people are throwing around that they don't "think", that they aren't "conscious", that they don't "reason", but I don't see those people sharing interesting heuristics to use LLMs well.
My digital thermometer doesn't think. Imbibing LLM's with thought will start leading to some absurd conclusions.
A cursory read of basic philosophy would help elucidate why casually saying LLM's think, reason etc is not good enough.
What is thinking? What is intelligence? What is consciousness? These questions are difficult to answer. There is NO clear definition. Some things are so hard to define (and people have tried for centuries) e.g. what is consciousness? That they are a problem set within themselves please see Hard problem of consciousness.
But you could make the exact same argument for a human mind?
It would be an argument and you are free to make it. What the human mind is, is an open scientific and philosophical problem many are working on.
The point is that LLM's are NOT the same because we DO know that LLM's are. Please see the myriad of tutorials 'write an LLM from scratch'
Fundamentally these shortcomings cannot be addressed.
They can and are improved (papered over) over time. For example by improving and tweaking the training data. Adding in new data sets is the usual fix. A prime example 'count the number of R's in Strawberry' caused quite a debacle at a time where LLM's were meant to be intelligent. Because they aren't they can trip up over simple problems like this. Continue to use an army of people to train them and these edge cases may become smaller over time. Fundamentally the LLM tech hasn't changed.
I am not saying that LLM's aren't amazing, they absolutely are. But WHAT they are is an understood thing so lets not confuse ourselves.
I don't understand why this point is NOT getting across to so many on HN.
LLM's do not think, understand, reason, reflect, comprehend and they never shall. I have commented elsewhere but this bears repeating
If you had enough paper and ink and the patience to go through it, you could take all the training data and manually step through and train the same model. Then once you have trained the model you could use even more pen and paper to step through the correct prompts to arrive at the answer. All of this would be a completely mechanical process. This really does bear thinking about. It's amazing the results that LLM's are able to acheive. But let's not kid ourselves and start throwing about terms like AGI or emergence just yet. It makes a mechanical process seem magical (as do computers in general).
I should add it also makes sense as to why it would, just look at the volume of human knowledge (the training data). It's the training data with the mass quite literally of mankind's knowledge, genius, logic, inferences, language and intellect that does the heavy lifting.
I fully agree with your sentiments. People really need to study a little!
LLM's have surpassed being Turing machines? Turing machines now think?
LLM's are known properties in that they are an algorithm! Humans are not. PLEASE at the very least grant that the jury is STILL out on what humans actually are in terms of their intelligence, that is after all what neuroscience is still figuring out.
Am I supposed to want to code all the time? When can I pursue hobbies, a social life, etc.
I feel you. It's a societal question you're posing. Your employer (most employers) deal in dollars. A business is evaluated by its ability to generate revenue. That is the purpose of a business and the fiduciary duty of the CEO's in charge.
I tend to agree with your assessment. The increase in demand cannot possibly equal the loss from AI.
Given projections of AI abilities over time AI necessarily creates downward pressure on new job creation. AI is for reducing and/or eliminating jobs (by way of increasing efficiency).
AI isn't creating 'new' things, it's reducing the time needed to do what was already being done. Unlike the automobile revolution new job categories aren't being created with AI.
Lots of users seem to think LLM's think and reason so this sounds wonderful. A mechanical process isn't thinking, certainly it does NOT mirror human thinking. The processes being altogether different.
This type of naive response really is bothersome!
Humans are probabilistic systems?! You might want to inform the world's top neuroscientists and philosophers to down tools. They were STILL trying to figure this out but you've already solved it! Well done.
The definition is broad for now this will do: Logic is the study of correct reasoning.
It hasn't learned any LOGIC. It has 'learned' patterns from the input.
AI companies and corporations in general control your politicians so taxing isn't going to happen.
Please do read up on how farmers are doing with this race to the bottom (it hasn't been pretty). Mega farms are a thing because small farms simply can't compete. Small farmers have gone broke. The parent comment is trying to highlight this.
If LLM's turn out the way C-Suite hopes. Let me tell you, you will be in a world of pain. Most of you won't be using LLM's to create your own businesses.