So fossil fuels better? Nuclear works great for France.

Start chewing. You literally admitted it in your own comment: “Sure, it’s not something humans had gotten to yet.” That is the definition of a novel discovery. You are arguing that because the AI used logic and existing data to reach the conclusion, it doesn’t count. By that definition, no human scientist has ever had a novel idea either since we all build on existing data and patterns. The AI looked at the same data humans had, saw a pattern humans missed, and created a solution humans didn’t have. That is novelty. But honestly it is hard to take your analysis of these papers seriously when you just argued in the comment above that protein folding involves “10^2 combinations.” You realize 10^2 is just 100 right? You think complex biology is a list shorter than a grocery receipt. If your math is off by about 300 zeros I am not sure you are the best judge of what these models are actually capable of.

​I was almost with you on the whole expert act until the part where you said we feed the model “10^2 combinations of amino acids.” ​You realize 10^2 is literally just 100, right? ​You are writing paragraphs acting like the smartest guy in the room, but you think protein folding gets solved by checking a list shorter than a grocery receipt. That is honestly hilarious. ​It kind of explains your whole point though. No wonder you think it is just a “simple sorting mechanism” if you think the dataset is that small. You might want to check the math before the next lecture because being off by about 300 zeros makes the arrogance look a bit silly.

A decade in the space is impressive. It shows dedication and time invested. That alone deserves recognition.

Still, the points you are repeating are familiar. They are recycled claims from years ago. If the goal is to critique novelty, repeating the same arguments does not advance it.

You say LLMs have zero intentional logic. That is true if by intentional logic you mean human consciousness or goals. It is false if you mean emergent behaviors and the ability to combine information in ways no single source explicitly wrote. Eliminating nuance with absolute terms makes it easy to dismiss valid evidence.

Calling someone an AI fanboy signals preference for labels over analysis. That approach does not strengthen an argument. Specific examples do. Concrete failures, reproducible tests, or papers are what advance discussion.

It is also not accurate to suggest that anyone pitches LLMs as supreme beings. Most people treat them as complex tools that produce surprising results. Their speed, scale, and capacity to identify patterns exceed human ability, but they remain tools. Critiquing them as if they were gods is a strawman.

If you want this discussion to matter, show a single reproducible example where an LLM fails in a way your logic cannot explain. Otherwise, repeating slogans and metaphors only illustrates a resistance to evidence.

I am not here to argue for ideology. I am here to examine claims. That is a choice. It is also a choice to resist slogans and demand specificity. Fun, fun. Another fun day.

Meanwhile, I’m just wondering who’d want to live that goddamn long 🤣 they’re absolutely pathological.

Big-league bigly its a big fucking club and we ain’t in. It

Reddit is kinda dead it now

At least the more of us are loud the safer each of us are. So free Luigi and may the proles get a little something without society collapsing. Either way it’s definitely a good show…

You’d think they’d have moved on by now. Well. Oh well.

Yep they now get paid for the data we have them. I have no sympathy lol. At least these models can’t actually store it all losslessly by any stretch of the imagination. The compression factors would have to be like 100-200X+ anything we’ve ever been able to achieve before. The numbers don’t work out. The models do encode a lot though and some of it is going to include actual full text data etc but it’ll still be kinda fuzzy.

I think we do need ALL OPEN SOURCE. Not just for AI, but I know on that point I’m preaching to the choir here lol

They should. Maybe all the angry people here would go bliss out. Lol

What’s AI? Fuck what AI? Which one? What kind?

Lol this is a good one. I love my LLMs but this is it. The problem is most people don’t even think at all anyway. Most of the time I don’t either. If we’re honest with ourselves, we’re still just barely advanced apes.

I don’t get marketing. The more gets shoved the father I retreat and ignore. I’ll let em run on YouTube sometimes just so the advertiser has to pay out the fraction of a penny on a wasted ad. Actually, how about we do this!

Let’s build software that goes around watching ads constantly so it makes their numbers go all to hell.

Cool they should setup their own hidden services! 😂

The funny thing is we hallucinate all our answers too. I don’t know where these words are coming from and I am not reasoning about them other than construction of a grammatically correct sentence. Why did I type this? I don’t have a fucking clue. 😂

We map our meanings onto whatever words we see fit. If I had a dollar for every time I’ve heard a Republican call Obama a Marxist still blows my mind.

Thank you for saying something too. Better than I could do. I’ve been thinking about AI since I was a little kid. I’ve watched it go from at best some heuristic pathfinding in video games all the way to what we have now. Most people just weren’t ever paying attention. It’s been incredible to see that any of this was even possible.

I watched Two Minute Papers from back when he was mostly doing light transport simulation (raytracing). It’s incredible where we are, but baffling people can’t see the tech as separate from good old capitalism and the owner class. It just so happens it takes a fuckton of money to build stuff like this, especially at first. This is super early.

Just like us. Sometimes it’s better to have bullshit predictions than none.

We should understand that 99.9% of what wee say and think and believe is what feels good to us and we then rationalize using very faulty reasoning, and that’s only when really challenged! You know how I came up with these words? I hallucinated them. It’s just a guided hallucination. People with certain mental illnesses are less guided by their senses. We aren’t magic and I don’t get why it is so hard for humans to accept how any individual is nearly useless for figuring anything out. We have to work as agents too, so why do we expect an early days LLM to be perfect? It’s so odd to me. Computer is trying to understand our made up bullshit. A logic machine trying to comprehend bullshit. It is amazing it even appears to understand anything at all.

Uhm. Have you ever talked to a human being.

Can you help me with problems this complex? Idk maybe we could use it to help make things better. Just most people prompt like things I can’t say because they aren’t nice. Oh by the way. Can you do it right now for $0 please? Thanks!

Edit. Also need it done now. If you’re reading this you were too slow.

Asking the chat models to have self-disccusion and use/simulate metacognition really seems to help. Play around with it. Often times I am deep in a chat and I learn from its mistakes, it kinda learns from my mistakes and feedback. It is all about working with and not against. Because at this time LLMs are just feed forward neural networks trained on supercomputer clusters. We really don’t even know what they are capable of fully because it is so hard to quantify, especially when you don’t really know what exactly has been learned.

Q-learning in language is also an interesting methodology I’ve been playing with. With an imagine generator for example though, you can just add (Q-learning quality) and you may get more interesting and quality results. Which itself is very interesting to me.