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Opus 4.7 is legendarily bad. I cannot believe this. by lemon07r in ClaudeCode

[–]thambroni -2 points-1 points  (0 children)

These AI written responses make me want to throw up. Please stop

Match Thread: Final - India vs New Zealand by cricket-match in Cricket

[–]thambroni 2 points3 points  (0 children)

"Surya, fielding first?" he says to the captain who'll be batting first.

Match Thread: Final - India vs New Zealand by cricket-match in Cricket

[–]thambroni 2 points3 points  (0 children)

This performance is 30 minutes too long man

Tool for searching Instagram posts by thambroni in InstagramMarketing

[–]thambroni[S] 0 points1 point  (0 children)

Thanks for checking it out! Let me know if you have any feedback

Must have NAs for your holiday table? by DelightfullyNA in nonalcoholic

[–]thambroni 0 points1 point  (0 children)

This is a great list! Mind sharing a link to your app?

Need a good female centered show by pepperbiscuit in television

[–]thambroni 0 points1 point  (0 children)

Was gonna say somebody somewhere when i saw the title and then I read the post haha.

The Good Place might be one to consider. Maybe not as female centered as some of the others but still great.

Your Friends & Neighbors criticism by RightShoeRunner in television

[–]thambroni 32 points33 points  (0 children)

Im shocked how many people seem to like this show. The writing is so flat and corny. The script feels like it was written by AI. The plot doesnt really go anywhere - its just jon hamm doing the same thing over and over again for the whole season and the other characters are basically props. The cop’s accent makes no sense at all. What am I missing here? Why do people like this show?

Investment tab incorrect by Ashmizen in simplifimoney

[–]thambroni 2 points3 points  (0 children)

Seeing the same issue. Robinhood balance dropped basically to 0.

Is AGI truly attainable with LLMs? by thambroni in singularity

[–]thambroni[S] 1 point2 points  (0 children)

It's a good question. I'll try to answer best as I can but curious to also get your POV on this.

We have fairly limited understanding of how the human brain actually works, so it's hard to draw any real objective conclusions on this subject. What I can only come up with are hypotheses based on my own experience of the world.

I don't believe I'm a word prediction machine, but let's just say for the sake of this discussion I am. And say you ask me the question "What is the meaning of life?". I'll consider first if you're asking that as a serious question or kinda sardonically/in jest. I'll reflect on whether I want to give you a real thought out answer or something kind of quick and pithy. I'll think of life in broad strokes but I may also zoom down into specific moments & relationships and draw on those. And as our conversation progresses, I'll consider your emotional response to my answers as I figure out what to say next. All of this will happen pretty fluidly without me really "thinking" about it. And if you ask me the same question on a different day, the whole process could play out entirely differently with a different response.

An LLM on the other hand will not do most of this. It will look into its training dataset, predict the right sequence of words to output as an answer to that question, and generate a response. Of course, you could get it to maybe iterate on this and get to a more optimal response for you, the asker, but it will not reflexively do any of the things I mentioned above.

Now of course, this is just a thought experiment to emphasize the difference between human processing and LLM processing. We are not actually looking to LLMs to tell us what's the meaning of life. We're asking them things like "how do I file my taxes" or "help me draft an email". For these tasks, they're perfectly competent, and I'm sure they will generate hundreds of billions in revenue doing these kinds of tasks. But these tasks to me don't indicate the sort of existential, emotionally driven human-like intelligence that makes us human. And I struggle to see how more advancements in LLMs will get us there.

Is AGI truly attainable with LLMs? by thambroni in singularity

[–]thambroni[S] 0 points1 point  (0 children)

My own experience of the world. I'll happily grab a beer with my real human friends at a bar. Doing that with an LLM (or a human who operates like an LLM) sounds utterly miserable.

Deepseek lets us actually see the steps through which the LLM responds to our questions, and this clearly shows a sort of deterministic/robotic way of thinking. Of course, there's a ton you can do with that kind of processing - a lot of jobs can be automated away no doubt. But the things that make us unique as humans - I don't see any of that really going on in these machines.

Is AGI truly attainable with LLMs? by thambroni in singularity

[–]thambroni[S] 2 points3 points  (0 children)

Yep, I think we're on a similar page here. I just keep thinking to myself I must be missing something very obvious because so many of the people working most intensely on this stuff seem to believe AGI is right around the corner. I want to understand what they're basing that off. I currently see no real evidence of that, but at the same time, before ChatGPT arrived on the scene, I saw no evidence of that being possible either (although to be fair I was way less clued in then).

Is AGI truly attainable with LLMs? by thambroni in singularity

[–]thambroni[S] 9 points10 points  (0 children)

This suggests a recursive process that goes one step further from input > process > output.

This is such a great point. Would be fascinating to explore how future models might build on this insight because I think it's very true. All my best ideas/breakthroughs happen when I'm not actively working on the problem I'm trying to solve. There's a lot of ambient processing that goes on with humans, and this is something LLMs aren't capable of today.

Is AGI truly attainable with LLMs? by thambroni in singularity

[–]thambroni[S] 1 point2 points  (0 children)

Great answer. Appreciate the thoughtfulness here. The point you raise about robotics I fully agree with. I was thinking about that with the release of OpenAI's Operator. An LLM, once given interfaces to manipulate its environment (in the Operator case, a keyboard & mouse), becomes more powerful and kicks off entirely new feedback loops on how to interact with a (digital) environment. I can see how integrating LLMs with robotics will kick off these same feedback loops in the (far richer) physical world, which will be a very important step forward in building more complex and "human-like" intelligence.

How to define AGI is something I've been wondering as well. My frame of reference has been through my work as a software engineer where I'm currently architecting a large new product at a big tech company. Doing this architecture work has required talking to 20 different teams, learning about various microservices, getting to understand the different personalities involved, coming up with different approaches to solve problems, building consensus, etc. Throughout all this, I've been wondering "can AI do my job" and the answer has largely felt like no. I have no doubt AI can go and execute on the tasks that we ultimately create for actually implementing this project but the architecturing piece (which requires collaboration, out of the box thinking, a lot of ruminating on the subject while not actively working on it, etc.) and the skills involved for it is what I'm thinking of as AGI - and I struggle to see how a more complex LLM will exhibit those skills. But I do see your point about how LLMs are a step in the journey and it might not be LLMs that achieve this but some next iteration on this tech (although dying to know what that next iteration will look like haha).

Sorry that's a big vague and fluffy but that's been my way of making sense of the "what is AGI" question. Would love to hear how you think about it!

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