Just pretending that AI doesn't exist or doesn't matter is one way to go.
I think we might be getting close to an era where some people section off areas of land or the internet and ban AI and humanoid robots in that area. I know there are a lot of people who want that.
The problem is that AI is getting better and better at impersonating humans.
Eventually you may see a convergence, where the New Luddite Zoos are just more constrained variations of the normal Human Zoos. Enforced by superhuman AI.
Being aware about something is not the same as actively participating in that for work and is also different from doing it for education or entertainment.
Mastodon's UI is horrible. At least for people who never used Xitter. Why did a new company (at a moment of Mastodon initial release) copied already ancient and by then pointless limitations? Character limit, linear feed, tags in text, no advanced formatting etc. And then there are registration problem (where to register), the retention/safety problem (what if a benevolent admin of your instance nuked your account, now what?), the discovery problem etc. I'm permanently baffled at the decision process of Mastodon developers.
Mastodon is just as bad, it suffers from the same problem as most of the Fediverse it inspired, admins of large instances bitchfighting with one another and holding their users hostage...
1. Popularity != Merit and this site is not different. A lot of worthy posts get ignored.
2. Even though I find most of the AI posts interesting, I agree that tags and the ability to filter by tags would be really great. But it's probably a ton of work and additional system load.
He was extremely skeptical of the capabilities of AI for years but eventually came around to calling it truly capable after testing advanced LLMs.
He is still an AI skeptic in as many ways that he can reasonably be, but doesn't deny the raw ability. Actually he thinks it will eclipse humans and he is a doomer.
He sees it as being an extremely empty type of intelligence though.
But I hope that people who have an intuitive understanding of contemporary machine learning (not me) will sometimes watch videos like this and think about things at a higher level. LLMs have a LOT of assumptions built in.
I'd wager that the vast majority of the ML research community, especially anyone interested in "AGI", is familiar with Hofstader's work. And I don't think anyone working on contemporary language models would argue that they are somehow an assumption-less "pure" model--the particular inductive bias of the Transformer has been studied by a huge number of researchers and continues to be, and the same is true for things like training data bias.
I think the Hofstader's view of modern LLMs is actually a deeply human and touching one. Looking at his work over the years, his curiosity has always veered towards human thought. He could have written GEB with a focus on completely different examples of self-reference, but he chose three striking humans from history. When he's describing modern systems as "empty intelligence", I think there's a little bit of heartbreak in his perspective, because he sees them as fundamentally different from humans in a way that leaves the part he loves--the "I" in the loop--out of the equation. He gave an interview a few years ago where he explains his feeling as being "diminished" not in a "What will I do if I'm not the best at math?" kind of way, but more specifically as he puts it, that humans are "imperfect, flawed structures".
There is no reason to believe that the transformers couldn't be doing something close to what copycat does (especially with thinking tokens), as an emergent phenomenon of the sheer size of the corpus. The architecture is certainly capable of encoding the actions in copycat anyways.
> He sees it as being an extremely empty type of intelligence though.
My instinctive reaction to claims like this is, is it really any different from humans? Why?
Current LLMs have a lot of limitations. The pretraining without the ability to learn beyond their context is a big one. Every prompt is literally instantiating a new instance of the intelligence. If you take these limitations into account, it's not at all clear to me that they're all that different from humans when it comes to the fundamentals: we learn from training data, we respond according to what we've learned.
In fact, many humans resemble the pretrained model quite closely - they do most of their learning in their early years, and don't update much after that except in relatively limited ways. You do get lifelong learners, but they're the exception.
Taking all this into account, why is the one kind of intelligence "extremely empty" whereas the other is not? Is this not just anti-machine bias when it comes to intelligence?
Cheaper than an entry level human. But I've never used a model that size for development so idk if they could replace it. The work I do with even nemotron 550b, it's so dumb it's infuriating. Same with the free Google one (for anything sanitized/generic)
I have it on my 7900xtx but haven't compared it just yet. I might though. Honestly what I need is a lack of knowledge trained into the model. Maybe 27b will be better. I need it to want ground truth data, not hallucinate based on quantized distilled documents from training.
This is really interesting and a fun read, but the way they mix in dated psychology around this historical figure in a serious way without much reference to subsequent work adds up to pretension.
They're not weird at all given his worldview. It's Nazism. From his book to his public statements and actions, he consistently expresses this. The only thing he does not do is use the literal language that is not accepted. But the meaning and actions are the same. People are in denial.
There is rapid progress in generality in humanoid robotics though. I think within the next year or less we will get the ChatGPT moment for humanoid robots. If you look at progression of capabilities such as the recent Skild AI demos.
There are simply no technologies today that can replicate the density, precision, and versatility of human touch sensors. Until then, there is simply no way to create generally capable robots that can operate at the level of a human.
And unlike LLMs, advancement is held back by physical limitations like materials science, so progress has been and will continue to be much slower.
What task do you think that humanoid robots can't do? Also, we don't need fully equivalent touch to get useful performance.
If you look you will see a really broad range of tasks accomplished already, including thing like manipulating screws, picking up pills, inserting wire harnesses, folding clothes, putting away dishes. And there are several companies with built in or component advanced touch sensors like Figure or leading edge touch sensor companies like SynTouch and GelSight.
Peel an orange? Crack an egg? Thread a needle? (Heh, drive a car...) There's a huge range of tasks that a non-specialized, general purpose robot simply cannot do yet. I'd be easier to enumerate the things they can do than the things they can't given the current state of the art.
Sure, build an orange peeling machine and it'll do great. But that's not what we're talking about here.
As for those demos videos we often see, those are very highly choreographed demonstrations. Show me a real life humanoid robot operating free form on a factor floor and doing those things and I'll be impressed.
And to be clear, this is not meant to understate what's been accomplished. I'm just saying the path for advancement is a lot harder and based in physical rather than computational limitations, which are much harder to overcome and go much slower. We simply cannot look at the growth curve of LLMs and expect robotics to advance at the same rate.
peeling an orange and cracking an egg already demonstrated. Figure 02 worked on BMW's actual Spartanburg production line for about 1,250 hours running 10-hour shifts.
keep paying attention, you will see how wrong you are about it being physical limitations as the physical AI continues to rapidly improve.
I agree that LLMs are unlikely to be the final form for AGI, but what you are talking about is orthogonal to the IQ and for most cases general utility. It's like looking at a savant chained to a workstation reading tasks from a conveyor belt and saying that it will never have human level capabilities.
I think we might be getting close to an era where some people section off areas of land or the internet and ban AI and humanoid robots in that area. I know there are a lot of people who want that.
The problem is that AI is getting better and better at impersonating humans.
Eventually you may see a convergence, where the New Luddite Zoos are just more constrained variations of the normal Human Zoos. Enforced by superhuman AI.
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