captainclam

What's the tell? It doesn't seem AI generated to me but I may not be a great judge.

I don't think the quality of discussion about social media suffers from lack of specification. Whether or not you consider HN to be social media, or wherever your decision boundary is, doesn't change that most of the conversation does apply to the general class of apps/websites that have become de-facto short form video platforms. Which lots of people use, so the effects of use are consequential and worth discussing.

The conversations on consciousness though...oh man. I have to steel myself before diving into that mess.

I use the firefox extension "Unhook" to completely hide suggested content on Youtube. Really effective, I kindof can't believe how much time I spent getting suckered into watching video essays that absolutely did not deliver.

Just to be clear, your comment had a general statement about how you perceived the motivations of "people buying vinyl". That's what I was responding to. (People using VHS filters on social media is by definition social signalling so no comment there lol).

And I completely agree with your point about touting film as "easier" than digital. That's a stretch.

There are plenty of people who sincerely enjoy the aspects that make older tech less convenient or practical. Maybe it's an appreciation for the engineering or "comprehensibility," often it's because older tech produces unique outputs that can't be adequately captured by newer technology.

Reducing people's interest to "social signalling" comes off as dismissive.

Not asking adversarially at all here: what do you mean by resisting with "real numbers" without media campaigns, social media, or protesting? What do the vested parties actually do to secure their second amendment rights? Do you just mean having large voting blocs?

Author really should have figured out a better word than "vanity."

It looks to me like OpenAI's image pipeline takes an image as input, derives the semantic details, and then essentially regenerates an entirely new image based on the "description" obtained from the input image.

Even Sam Altman's "Ghiblified" twitter avatar looks nothing like him (at least to me).

Other models seem much more able to operate directly on the input image.

You must not end up reading much scientific literature then.

lol

The two dogs I know that share this behavior are border collies.

The seahorse emoji is one of the canonical "Mandela effects". These are things that a large group of people collectively (mis)remember, but turn out to have never existed. Classic examples include the cornucopia in the Fruit of the Loom label (never there), and the wording on car mirrors "objects in the mirror may be closer than they appear." (There's no record of 'may be closer', just 'are closer').

Unfortunately, the discussion around Mandela effects gets tainted by lots of people being so sure of their memory that the only explanation must be fantastical (the timeline has shifted!), giving the topic a valence of crazy that discourages engagement. I find these mass mis-rememberings fascinating from a psychological perspective, and lacking satisfying explanation (there probably isn't one).

So here we're seeing LLMs "experiencing" the same mandela effect that afflicts so many people, and I sincerely wonder why? The obvious answer is that the training data has lots of discussions about this particular mandela effect, ie people posting online "where is the seahorse emoji"? But those discussions are probably necessarily coupled with language that ascertains 'no, the seahorse emoji does not exist.' That's why the discussion is there in the first place! so why does the model take on the persona of someone that is sure it does exist? Why does it steer the models into such a weird feedback loop?

I've always been surprised by the official homeless population count, but it turns out there's a lot more to it.

The department of HUD generates this ~771K figure from a "point-in-time" estimate, a single count from a single night performed in January. They literally have volunteers go out, count the number of homeless people they observe, and report their findings.

It's not hard to imagine why this is probably a significant undercount. There is likely a long tail of people that happened to be in a situation that night where they were not able to be counted (i.e. somewhere secluded, sleeping in a friend's private residence that night, etc).

Even if these numbers are correct, to my mind a "crisis" is still more characterized by the trend than the numbers in absolute. From the first link you provided, we saw a 39% increase in "people in families" experiencing homelessness, and 9% in individuals. A resource from the HUD itself suggests a 33% increase in homelessness from 2020-2024, 18% increase from 2023-2024. That is far apace of the population increase in general.

https://www.huduser.gov/portal/sites/default/files/pdf/2024-...

And even then, I would say many people would suggest that the change in visible homelessness they've experienced in the last 10 years would amount to "crisis" levels, at least relative to the past.

It's completely fair to argue that it is not in fact a crisis, but claiming that it is certainly not "baseless."

Wow, there really is an xkcd for everything.

My read is that the author is saying it would have been really nice if there had been a really good protocol for storing data in a rich semantically structured way and everyone had been really really good at adhering to that standard.

Is that the main thrust of it?

It's very easy to imagine a world where all these things are solved, but it is a worse world to live in overall.

I don't think it is "bad" to be sincerely worried that the current trajectory of AI progress represents this trade.

To be clear, I'm pretty sure the half-trillion figure is the projected combined investment between SoftBank, OpenAI, Oracle, and MGX. Not public, US tax-payer dollars.

If that's not what you meant my apologies. Reason I'm quick to point this out is I think some of the writing/headlines around are suggestive of this misconception.

Sounds like there's not enough tax revenue!

This is one of the many many experiences in the tapestry of people figuring out how to use this new tool.

There will be many such cases of engineers losing their edge.

There will be many cases of engineers skillfully wielding LLMs and growing as a result.

There will be many cases of hobbyists becoming empowered to build new things.

There will be many cases of SWEs getting lazy and building up huge, messy, intractable code bases.

I enjoy reading from all these perspectives. I am tired of sweeping statements like "AI is Making Developers Dumb."

Exactly. If the whole "deep research" thing pans out, and we have models that can reliably produce proper literature reviews in 10 minutes...that alone will be an enormous boon to research.

Then add all the practical/mundane tasks that you mentioned, and you've got quite the multiplier.

Crucially, this doesn't just require noise but it requires "taste."

I tend to fall back on music creation as an example of this notion. Lots of innovation in music is experimentation/exploration of "noise," (not necessarily literal white noise) but requires the ear of a discerning musician who ultimately goes "Ooh! I liked that" or passes a "generated sample" by.

This is where I wonder if LLMs can ever innovate. I'm not sure they can develop "taste" for things outside of their distribution. However, I could just as easily be convinced that humans can't either, and sophisticated "taste" is just the exploration of obscure regions of the combinatorial space generated from previously observed samples!

Especially with the proliferation of generative AI, I anticipate something of a tech backlash in the next decade, and performatively NOT looking at one's phone will be part of it.

I'm sure that this already exists to some extant in certain subgroups, but I'd bet a small amount of money that this will grow to be a visible trend.

Just a fun thought!

Definitely interesting, but I'm not so sure that such a study can yet make strong claims about AI-based work in general.

These are scientists that have cultivated a particular workflow/work habits over years, even decades. To a significant extent, I'm sure their workflow is shaped by what they find fulfilling.

That they report less fulfillment when tasked with working under a new methodology, especially one that they feel little to no mastery over, is not terribly surprising.

What is dogfooding?

"Elon Musk Ally Tells Staff ‘AI-First’ Is the Future of Key Government Agency" from Wired

https://archive.is/jyFCy

This isn't unequivocal proof, but the broad goal automation lends itself pretty strongly to LLMs, and oh boy what LLM technology do you think they want to use.

semantics shmemantics.

This was one of the rather many areas where Star Trek failed to really consider the implications of its concepts, probably because it would simply break the world building.

This is true of pretty much all scifi! It's funny seeing super-futuristic depictions of star-fighter pilots and combatants with firearms and its just...so crushingly evident that humans will not have supremacy in these arenas very shortly.

Frank Herbert must have anticipated this complication and side-stepped the whole issue by preemptively canonizing the Butlerian Jihad.

Haha, I've had the same thoughts, that of course computers/AI/droids of that conversational capacity were conscious. You'd be a brute not to think that!

And all of a sudden, LLMs absolutely have the command of natural language that once seemed such an obvious indicator of sentience, and now I find myself one of those bigots who don't believe in robot rights!

I'm being silly, but I do think there are implications here with respect to the future debate on AI sentience. I guess I once thought there would be this threshold where the reality of an AI's inner experience became blatantly obvious, but I see now that this is going to be a profoundly thorny problem.

Who knows, maybe in several decades we'll have a consciousness-o-meter that demonstrates that LLMs have had some degree of awareness all along.

Oh never mind then.

I am sincerely curious about your thoughts on the origins of mitochondria, and how you came to feel so strongly about it.