The first five dictionaries I tried do not agree, and I didn't bother trying more.
The first gave "the ability to learn, understand, and make judgments or have opinions that are based on reason", by which no, these bots are not intelligent.
> the ability to learn, understand, and make judgments or have opinions that are based on reason
Agentic systems do this all the time. For example, I can point an agent at my codebase, and it will learn, understand, and make judgements based on that input. If this weren't happening, then agentic coding wouldn't work.
I also have a so called "pocket calculator" left over from when I went to school. Is this false? Have I been fooled by a little box of logic gates?
That half-adder circuit in there is especially suss. It's really just manipulating 1s and 0s, but -and I've been explicitly told this- no one cares how it actually does it; so long as the truth table matches up. There is no understanding of mathematics going on.
There is no single transistor in the whole thing that knows how to do so much as add 1+1. If I put it in the chinese room, I still wouldn't know how it did it. Clearly the entire premise must be false! ;-)
These kinds of stories probably read very differently for someone who uses Opus and Fable agents all day and goes "ohhh, I saw this in miniature last week; this and this and this must have happened" , vs someone who tried free-tier Gemini flash one rainy Sunday, got hallucinated at, and concludes it must all be a scam.
> That half-adder circuit in there is especially suss. It's really just manipulating 1s and 0s, but -and I've been explicitly told this- no one cares how it actually does it; so long as the truth table matches up.
"so long as the truth table matches up." Yup. Now try getting your chatbot's output to match up.
Your calculator was designed to tell truth. Your chatbot was designed to tell a mash up of whatever its creators managed to scrape from the internet.
LLMs are very explicitly designed to "understand, and make judgments or have opinions that are based on reason". The learning part is debatable, as is the level of success achieved
The mash-up of the entire internet is the mechanism by which they attempt to achieve the goal, not the goal itself. And it's only the first training step
> LLMs are very explicitly designed to "understand, and make judgments or have opinions that are based on reason".
I think you've mistaken the sales pitch for the design. Not even the enclopedia anyone can edit comes remotely near that:
"A large language model (LLM) is an AI model (typically a neural network) trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts.[1] They are the basis for many modern chatbots, such as ChatGPT, Claude, Gemini, Grok, and DeepSeek.
LLMs are typically based on transformer architecture.[2] Generative pre-trained transformers (GPTs) are a type of LLM that is pre-trained to predict the next word.[3] GPTs are then often fine-tuned to follow instructions and to behave as assistants.[4]
Biased or inaccurate training data can make an LLM's output less reliable. Benchmark evaluations for LLMs attempt to measure model reasoning, factual accuracy, alignment, and safety."
I'd argue "analyze text" alone requires understanding, judgements and opinions. They also seem like prerequisites to "following instructions and behaving as assistants". The wikipedia quote is not using the same words, but I don't read it disagreeing with me
I'm not at all claiming that LLMs are good at understanding, judging and having opinions based on reason. I'm merely claiming that is what companies like OpenAI and Anthropic are trying to create when they make LLMs. It is what they are designing, and their fine-tuning is very directly designed to make LLMs better at these tasks (unlike the pre-training, which is just imparting the sum of all human writing)
I read all these think-pieces about how AI lack intelligence, yet I cannot help but notice these "not-intelligent machines" keep doing more things that used to be considered "uniquely human" and which humans used to do in order to demonstrate to each other how intelligent we are.
No. But no-one is seriously suggesting intelligence is needed for persistent code fuzzing. Just as no-one is suggesting its needed for computerised chess.
all your actions in current context are based on your past actions and experience, so for all I know you're next token predictor as well, but likely with exponentially more parameters
And yet this "next-token predictor" is able to churn out well tested, valuable solutions, to complex problems. If you want to downplay that as nothing more than a fancy auto-complete, be my guest, I lose nothing from that.
As pointed out in a previous comment of mine, it meets the definition of "intelligent", my last response is regarding the claim that I've been "fooled".
> And yet this "next-token predictor" is able to churn out well tested, valuable solutions, to complex problems.
Same for countless computer programs from Excel to Google web search. Intelligence has nothing to do with it.
Throw an unimaginable amount of computer power at a problem, and there will always be people who cannot imagine the results to be anything but the creations of intelligence.
> the ability to acquire and apply knowledge and skills.