[hnthrowaway6543]

Article feels pointless. Anyone who still thinks in 2024 that LLMs have actual intelligence, or are anywhere close to AGI, is a lost cause.

This particular sufficiently advanced technology has been around long enough now that it is no longer indistinguishable from magic.

[giantg2]

"Anyone who still thinks in 2024 that LLMs have actual intelligence, or are anywhere close to AGI, is a lost cause."

Or they are a double digit percentage of those that hold a VP or higher title.

[hnthrowaway6543]

Execs and VPs going all-in on stupid shit they don't understand isn't anything new. Blockchain ring a bell? How about this quote from October 2022: "By 2026, 25% of people will spend at least one hour a day in the metaverse for work, shopping, education, social and/or entertainment, according to Gartner."

[nickpsecurity]

“This particular sufficiently advanced technology has been around long enough now that it is no longer indistinguishable from magic.”

I wouldn’t say that. They don’t even really know how it works. Papers are periodically written challenging a fundamental claim about them, like in training or reasoning.

What we do know also isn’t clear or formulaic enough for reliable predictions of model behavior. That’s why they do all the “YOLO’s.” It is more an art form than a science.

I think a few principles about them are well-understood. We know how to assess what models can and can’t do well. Past that, there’s a lot of unknown in them. Both the experimenters and the field of mechanistic interoperability are trying to figure out the rest.

[jmull]

I thought it was quite good; an entirely approachable explanation that nonetheless gets across the essential limitations of the current approach to AI:

When working well, they provide existing answers to questions, rather than thinking up new ones.

[ninetyninenine]

Nobody thinks this.

The controversy is on whether or not LLMs think.

We all know LLMs hallucinate and get things wrong all the time but it also gets things right on prompts with answers where neither prompt nor answer is in the training set.

When it gets such an answer correct and we know the answer has a low probability of being just right by random chance, we actually don’t know if the llm is thinking or not.

All I see are a bunch of people writing qualitative claims using convenient examples and ignoring counter examples.

[leereeves]

> The controversy is on whether or not LLMs think.

It's impossible to answer that question, because we don't really know what "thinking" is and can't define it precisely.

[hnthrowaway6543]

> The controversy is on whether or not LLMs think.

They do not. There is no controversy except by people with a poor understanding of the underlying technology. Whether or not LLMs think is a "debate" in the same sense that whether the earth is flat or a sphere is a debate. Certain people will strongly argue a silly theory, and their arguments can't be refuted because they refuse to, or are incapable of, understanding slightly advanced scientific concepts.

[ninetyninenine]

Not true. There’s huge debates among academics. We understand the technology only from a low level of abstraction. At higher levels of abstraction we don’t completely understand what’s going on and there is evidence of higher order intelligent mechanisms at play here.

[hnthrowaway6543]

> we don’t completely understand what’s going on

No, you don't completely understand what's going on. I suggest reading up on LLM architecture. It's not that complicated.

[ninetyninenine]

I have. The failure is with you and your extracting only the mechanical functionality of LLMs as all an LLM is.

The high level macro structure of what ends up being trained is something nobody understands.

Regardless of WHAT I say, the general consensus among academia and professionals is extremely different from what you characterize. I can cite dozens of research papers contrary to your point in a simple google search:

https://www.sciencedirect.com/science/article/pii/S016028962...

https://www.topbots.com/llm-reasoning-research-papers/

https://arxiv.org/abs/2305.10601

https://arxiv.org/abs/2205.10625

https://arxiv.org/abs/2205.15241

The fact that these research papers exist is testament against your delusional claim that you completely understand how LLMs work just by reading Attention is all you need.

[hnthrowaway6543]

Unfortunately your reading comprehension capability is quite low (which explains why you see LLMs as being potentially intelligent). The usage of the word "thought" in those papers does not actually indicate they believe the LLM is thinking.

[y42]

I agree, but also you have to mention, that knowledge is based on deduction. There is cause and effect, there are simple, logical rules and by "counting votes" you simply keep record of those rules. If you will, fantasy is just the way how you iterate through possible realities. And that's nothing that a ai is not capable of.

[thomasahle]

> Anyone who still thinks in 2024 that LLMs have actual intelligence, or are anywhere close to AGI, is a lost cause.

FTFY: "Anyone who still thinks in 2024 that LLMs aren't intelligent, is a lost cause"

[hnthrowaway6543]

> FTFY: "Anyone who still thinks in 2024 that LLMs aren't intelligent, is a lost cause"

I can understand believing this if you have a poor understanding of math, statistics, logic, and computing; which, in fairness, most people do.

[thomasahle]

People who actually understand math and computing looks at the output of Claude and o1 and see another being doing math and computing. Sometimes failing, sometimes successfully.

Maybe only at high school or college level; but I wouldn't say high school students don't have intelligence.