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ML promises to be profoundly weird

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Re: ML promises to be profoundly weird

#441

Post by munificent »

NiloCK wrote: post #378
munificent wrote: post #173

Earlier quoted context omitted.

Agreed, totally! I still write and put stuff online. But it definitely feels different now. It used to feel like I was tending a public garden filled with other people who might enjoy it. It still kind of feels like that, but there are a handful of giant combine machines grinding their way around the garden harvesting stuff and making billionaires richer at the same time. It's not enough to dissuade me from contribut…

> It used to feel like I was tending a public garden filled with other people who might enjoy it. It still kind of feels like that, but there are a handful of giant combine machines grinding their way around the garden harvesting stuff and making billionaires richer at the same time. An underrated upside to being harvested is that your voice has now effectively voted in the formation of the machine's constitution. In…

> time so far is telling that efforts can be made to distill strong, open, public versions of the same.

I do really hope that part of the longer-term answer for AI is LLMs being run locally.

Re: ML promises to be profoundly weird

#442

Post by saghm »

dwallin wrote: post #28

Some people point at LLMs confabulating, as if this wasn’t something humans are already widely known for doing. I consider it highly plausible that confabulation is inherent to scaling intelligence. In order to run computation on data that due to dimensionality is computationally infeasible, you will most likely need to create a lower dimensional representation and do the computation on that. Collapsing the dimension…

They key capability that humans have that I've yet to see in an LLM is the ability to recognize when they would not be capable of doing a task well and refuse to do it poorly instead. The only times I've ever seen LLMs give up on a problem are when the prompting is very explicitly crafted to try to elicit a response like that when necessary or after very long back-and-forth exchanges where they get repeated feedback about unsatisfactory results. I think this has pretty dire implications in terms of what the consequences are for deploying them in any scenario where failure has significant risk or the output can't be immediately audited for correctness.

Re: ML promises to be profoundly weird

#443

Post by d1l »

felipeerias wrote: post #412
Retric wrote: post #370

Earlier quoted context omitted.

> Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. This is just wildly incorrect. People started running out of trees during the early Iron Age. Woodlands have been a managed and often over exploited resource for a long time. Active agriculture vs passive woodlands vs animal grazing has been in constant tension for thousands…

People had been hunting whales for centuries, but industrialisation gave them the means and the motivation to do so until near extinction.

Read Moby Dick some time my friend.

Re: ML promises to be profoundly weird

#444

Post by saghm »

doodpants wrote: post #134

> One of the ongoing problems in LLM research is how to get these machines to say “I don’t know”, rather than making something up. To be fair, I've known humans who are like this as well.

If you change it from asking a question to giving an instruction, how many humans do you know that have trouble saying no to things that aren't reasonable? I'd argue that pretty much every human will refuse to do most things you might instruct them to do, whereas an LLM will happily attempt most things you ask them to do for you, regardless of whether they're capable of succeeding, and it's up to you to figure out if they actually did it right or not. There are tasks where this is extremely useful, but they're ones that are extremely low risk and can easily be audited upon completion. This isn't anywhere near the level of what a human is capable of.

Re: ML promises to be profoundly weird

#445

Post by joefourier »

saghm wrote: post #425
joefourier wrote: post #312

> 2017’s Attention is All You Need was groundbreaking and paved the way for ChatGPT et al. Since then ML researchers have been trying to come up with new architectures, and companies have thrown gazillions of dollars at smart people to play around and see if they can make a better kind of model. However, these more sophisticated architectures don’t seem to perform as well as Throwing More Parameters At The Problem. P…

Literally the paragraph right before the one you quote is this: > I am generally outside the ML field, but I do talk with people in the field. One of the things they tell me is that we don’t really know why transformer models have been so successful, or how to make them better. This is my summary of discussions-over-drinks; take it with many grains of salt. I am certain that People in The Comments will drop a gazilli…

The title of the article is “The Future of Everything is Lies, I Guess” and the first part is literally complaining about LLMs being bullshit machines, while the author proceeds to tell confabulations (or lies) of his own. Is there not a bit of irony in that?

If you’re a non-expert in a field, I don’t think it’s a good sign if you’re writing a 10 part article about that field’s impact on society and getting basic facts wrong. How can I trust that the conclusions will be any more credible?

Re: ML promises to be profoundly weird

#446

Post by hammock »

Retric wrote: post #370
munificent wrote: post #150

There is a whole giant essay I probably need to write at some point, but I can't help but see parallels between today and the Industrial Revolution. Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. That meant that it was fine for things like property and the commons to be poorly defined. If all of us can go hunting in the woo…

> Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. This is just wildly incorrect. People started running out of trees during the early Iron Age. Woodlands have been a managed and often over exploited resource for a long time. Active agriculture vs passive woodlands vs animal grazing has been in constant tension for thousands…

The general point is accurate, don’t take it so literally.

There were more than enough trees until we developed the technology to clear cut in expeditious manner. There were more than enough fish until we developed the technology to pull massive indiscriminate amounts out of the ocean (and/or started polluting our rivers with industry). There was more than enough topsoil until we developed mechanized plows and artificial fertilizer. Etc.

A few hundred years ago or less, a squirrel could get from the Atlantic Ocean to the Mississippi River without ever touching the ground. Not possible today. That’s not a push and pull played out over thousands of years, that’s a one-way trend.

Re: ML promises to be profoundly weird

#447

Post by noosphr »

munificent wrote: post #150

There is a whole giant essay I probably need to write at some point, but I can't help but see parallels between today and the Industrial Revolution. Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. That meant that it was fine for things like property and the commons to be poorly defined. If all of us can go hunting in the woo…

>Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it.

The mammoths disagree.

Re: ML promises to be profoundly weird

#448

Post by jijji »

the authors reference to LLM's as "bullshit machines" is more true the less parameters you have trained in your model....as we scale up to trillions of parameters, add Mixture of Experts (MoE) architecture, this no longer is an accurate statement. Proof in point was yesterdays announcemnt of Mythos 5 model (10T parameters + MoE [1]) by anthropic where it seems to be so good at finding/exploiting vulnerabilities in source code that have been there for decades and only recently uncovered needs to be used to fix these critical vilnerabilities first before it gets released to the public, they even have a project called Glasswing [2] dedicated to letting people fix the thousands of vulnerabilities already found by the model before they release this model to the public, because it's so good at what it does... I think we're a little bit past the point of calling these models "bullshit machines" at this point...

[1] https://www.aimagicx.com/blog/claude-mythos-5-trillion-param...

[2] https://www.anthropic.com/glasswing

Re: ML promises to be profoundly weird

#449

Post by steveklabnik »

navaed01 wrote: post #434
munificent wrote: post #173

Earlier quoted context omitted.

Agreed, totally! I still write and put stuff online. But it definitely feels different now. It used to feel like I was tending a public garden filled with other people who might enjoy it. It still kind of feels like that, but there are a handful of giant combine machines grinding their way around the garden harvesting stuff and making billionaires richer at the same time. It's not enough to dissuade me from contribut…

It does feel like the collaborative, free open nature of the web has gone and the optimism that brought… it feels like no one would build Foursquare today. But then I wonder if I’m just old an jaded and to the younger generation creating content, for them the web is open and expressive- just in a different way

I still use swarm every day, and get teased for it all the time.

"So Steve, you're a millennial. What does it mean to 'be the mayor' of something?"

Re: ML promises to be profoundly weird

#450

Post by mxfh »

Even if nothing substantial come out of this, having shortest paths to the corpus of all human expressions in all languages! and media formats is quite something by itself, what could be the ultimate hard information retrieval tool is hiding those trace behind untracked convolutions is the real shame here. Found so much real information in between less and less hallucinations already that was impossible to retrieve otherwise in that time frame. Basically tokenrank kills pagerank.
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