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Comment by nopinsight | Hacker News Reader

> I still tend to think of these things as big autocomplete word salad generators.

What exactly would be your bar for reconsidering this position?

Taking some well-paid knowledge worker jobs? A founder just said that he decided not to hire a junior engineer anymore since it would take a year before they could contribute to their code base at the same level as the latest version of Devin.

Also, the SOTA on SWE-bench Verified increased from <5% in Jan this year to 55% as of now. [1]

Self-awareness? There are some experiments that suggest Claude Sonnet might be somewhat self-aware.

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A rational position would need to identify the ways in which human cognition is fundamentally different from the latest systems. (Yes, we have long-term memory, agency, etc. but those could be and are already built on top of models.)

[1] https://www.swebench.com/

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Not the OP, but my bar would be that they are built differently.

It’s not a matter of opinion that LLMs are autocomplete word salad generators. It’s literally how they are engineered. If we set that knowledge aside, we unmoor ourselves from reality and allow ourselves to get lost in all the word salad. We have to choose to not set that knowledge aside.

That doesn’t mean LLMs won’t take some jobs. Technology has been taking jobs since the steam shovel vs John Henry.

Earlier I was thinking about camera components for an Arduino project. I asked ChatGPT to give me a table with columns for name, cost, resolution, link - and to fill it in with some good choices for my project. It did! To describe this as "autocomplete word salad" seems pretty insufficient.

Autocomplete can use a search engine? Write and run code? Create data visualizations? Hold a conversation? Analyze a document? Of course not.

Next token prediction is part, but not all, of how models are engineered. There's also RLHF and tool use and who knows what other components to train the models.

> Autocomplete can use a search engine? Write and run code? Create data visualizations? Hold a conversation? Analyze a document? Of course not.

Obviously it can, since it is actually doing those things.

I guess you think the word “autocomplete” is too small for how sophisticated the outputs are? Use whatever term you want, but an LLM is literally completing the input you give it, based on the statistical rules it generated during the training phase. RLHF is just a technique for changing those statistical rules. It can only use tools it is specifically engineered to use.

I’m not denying it is a technology that can do all sorts of useful things. I’m saying it is a technology that works only a certain way, the way we built it.

This product launch statement is but an example of how LMMs (Large Multimodal Models) are more than simply word salad generators:

“We’re Axel & Vig, the founders of Innate (https://innate.bot). We build general-purpose home robots that you can teach new tasks to simply by demonstrating them.

Our system combines a robotic platform (we call the first one Maurice) with an AI agent that understands the environment, plans actions, and executes them using skills you've taught it or programmed within our SDK.

If you’ve been building AI agents powered by LLMs before, and in particular Claude Computer use, this is how we intend the experience of building on it to be, but acting on the real world!

…

The first time we put GPT-4 in a body - after a couple tweaks - we were surprised at how well it worked. The robot started moving around, figuring out when to use a tiny gripper, and we had only written 40 lines of python on a tiny RC car with an arm. We decided to combine that with recent advancements in robot imitation learning such as ALOHA to make the arm quickly teachable to do any task.”

https://news.ycombinator.com/item?id=42451707

> If we set that knowledge aside, we unmoor ourselves from reality

The problem is that this knowledge is an a priori assumption. If we're exercising skepticism, it's important to be equally skeptical of the baseless idea that our notion of mind does not arise from a markov chain under certain conditions. You will be shocked to know that your entire physical body can be modelled as a markov chain, as all physical things can.

If we treat our a prioris so preciously that we ignore flagrant, observable evidence just to preserve them -- by empirical means we've already unmoored ourselves from reality and exist wholly in the autocomplete hallucinations of our preconceptions. Hume rolls over in his grave.

> You will be shocked to know that your entire physical body can be modelled as a markov chain, as all physical things can.

My favorite part of hackernews is when a bunch of tech people start pretending to know how very complex systems work despite never having studied them.

I'm assuming you're in disagreement with me. In which case I'm going to point you towards the literal formulation of quantum mechanics being the description of a state space[1]. The universe as a quantum markov chain is unambiguously the mathematical orthodoxy of contemporary physics, and is the defacto means by which serious simulations are constructed[2].

It's such a basic part of the field, I'm doubtful if you're talking about me in the first place? Nobody who has ever interacted with the intersection of quantum physics and computation would even blink.

[1] - Refer to Mathematical Foundations of Quantum Mechanics by Von Neumann for more information.

[2] - Refer to Quantum Chromodynamics on the Lattice for a description of a QCD lattice simulation being implemented as a markov chain.

There it is again.

> Taking some well-paid knowledge worker jobs? A founder just said that he decided not to hire a junior engineer anymore since it would take a year before they could contribute to their code base at the same level as the latest version of Devin

A junior engineer takes a year before they can meaningfully contribute to a codebase. Or anything else. Full stop. This has been reality for at least half a century, nice to see founders catching up.

https://techcrunch.com/2024/12/14/klarnas-ceo-says-it-stoppe...

It's a different founder. Also, this founder clearly limited the scope to junior engineers specifically because of their experiments with Devin, not all positions.

> word salad generators.

>> What exactly would be your bar for reconsidering

The salad bar?

Most jobs are a copy pasted CRUD app (or more recently, ChatGPT wrapper), so there is little surprise that a word salad generator trained on every publicly accessible code repository can spit out something that works for you. I'm sorry but I'm not even going to entertain the possibility that a fancy Markov chain is self-aware or an AGI, that's a wet dream of every SV tech bro that's currently building yet another ChatGPT wrapper.

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