I’m calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field’s history. Agents cannot program, and it’s taking longer and longer to realize that they can’t. They are a highly sophisticated statistical model designed to mimic the distribution of programming. The output is broken, but in a way that’s getting harder and harder to detect. Which is exactly what you’d expect from an increasingly accurate statistical model.
Sure, and at that level of accuracy it’s also a description of how humans work. I didn’t invent these words myself, I’m just stringing them together based on a stochastic process my brain was trained into.
Like LLMs, some of my speech is semi-random initialization (dada wawa googoo), some of that is mimicry (some of that is mimicry), some of that is reinforcement learning (downvotes incoming), and some of that is the output of a subprocess that uses the same systems prompted at the meta-level and without verbalization (maybe they won’t get the analogy between thinking and LLM scratchpads… how about I use this space to clarify).
Calling an LLM a stochastic parrot has the same social-emotional role as calling a human an animal. Yes, it is correct. But people can infer the connotation.
Humans are animals. LLMs randomly generate text based on the corpus they were trained on and the conversation so far, so stochastic parrot is an accurate description.
LLMs don’t learn. Humans do. LLMs generate text randomly using a massive matrix. Humans don’t; you lied. An LLM is incapable of lying because it has no understanding of truth. It just bullshits convincingly all the time. It’s very very good at it, but it’s all hallucinated for the LLM, true or false.
Expecting your random word generator to tell you truths is insane. The training measure is “sounds right” not “is right”. It passes if it sounds like the other discourse it read. Just like the confident drunk guy at the pub who thinks he knows everything passes of he convinces the other drunk guys at the pub.
Whereas humans learn at school and on the job and the training measure is “your teacher or supervisor approves”. LLMs were not trained on truth or accuracy. Trusting in them and treating them as equivalent to human intelligence, as you and a whole bunch of other folks do, is profoundly unsound, and soon the necessary price rises to pay for the processing costs (let alone the vast, vast, vast, vast, vast debts on the infrastructure) are going to make most slophouses which jettisoned their human talent go out of business. And very, very few people indeed will be sorry at that point.
Meanwhile LLM slop is shitting in github all day long, every day, and shitting on the internet, and it will eat it’s own shit and produce crappier shit.
Your analogies don’t change the truth, and that is that LLMs don’t know the difference between sounds correct and is correct any more than MAGA voters know the difference between sounds good to me and is good for me.
What do you mean LLMs don’t learn? How do you think they became capable of stringing a sentence together?
They don’t learn during a deployment, but neither do humans; humans only learn during sleep. The behaviors a human exhibits while “learning” in the moment are just stochastic parrot behaviors based on their immediate context window, if the human doesn’t sleep in time the event can slip out of their context window and they don’t learn despite having acted as if they do.
You seem to be very naive about human learning in general. What makes the “truth” of school lessons greater than the “truth” of an LLM’s curated dataset it is reinforcement learned on? Have you ever seen actual evidence that mitochondria exist, or are you just stochastically parroting your biology teacher?
I also oppose LLMs in almost all applications (live translation being an example of a good application). But please oppose it with arguments based in reality.
You’re confusing constructing the LLM, which is done with an actual AI (neural network) and a massive corpus of text (stolen from millions of humans in the greatest intellectual theft in history) and running the LLM, which is done with a random number generator and a massive matrix of probable next words.
They don’t learn. They don’t change. They’re as random next time as this time.
False and false. Soooo much pseudoscience.
Wrong again.
If that were true, most people would learn very badly first thing in the morning and get better and better later in the day. I think you’ll find that most school teachers would vehemently disagree with your nonsense conclusions.
Then again, perhaps by “doesn’t sleep in time” you mean stays up all night, then admittedly they might function less well cognitively but (a) we tend not to regularly torture humans that way and (b) you’re massively overstating the role of sleep in the learning process.
No, you seem to be very naive indeed, to extremes, about the intelligence and reliability of LLMs. When I ask them about general things that I know about, I tend to get the right answer about 60%-70% of the time. Why would I believe it when I didn’t know the answer. To trust an LLM to tell you the truth about stuff you aren’t checking when it clearly blags nonsense so frequently when you are is really really stupid.
Most teachers tend to consistently teach the content of the syllabus rather than randomise what they say to classes based on the preceding conversation. They reinforce and update their prior knowledge by also learning from the mark schemes of the tests and exams their students sit.
No. I trust my teachers. I am rational to do so. I don’t trust LLMs. You are irrational to do so.
You are utterly deluded and have bought the hype. You seem unable to distinguish between distinct things and are dismissing a large amount of evidence that your “just as good as a human” is a crap-spewing shit machine, no more honest than donald J trump, and with no less sharting.