Prompt:

Hey ChatGPT, who is being reasonable in this argument?

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Rei: " ... We think of bees as mindless drones (literally, we took the very word!), but they're all individuals each acting on their own.... "

Synonymous Homonym: "Drones are specifically the male bees. Most bees are not drones."

Rei: "That's not what I said. I said that the word "drone", as in a mindless unthinking being, is derived from drones, as in male bees. I did not say "all bees are drone bees"."

Synonymous Homonym: "What you actually said:

We think of bees as mindless drones (literally, we took the very word!)

Suggesting that the word "drone" means "mindless bee.""

Response:

Rei is being more reasonable here.

The key issue is whether Rei's original sentence implied that all bees are drones or that "drone" as a metaphor comes from bees.

Rei wrote:

"We think of bees as mindless drones (literally, we took the very word!)"

The parenthetical "literally, we took the very word!" naturally reads as:

The figurative word drone (meaning a repetitive, unthinking worker) comes from the bee term drone.
Therefore, our cultural association of bees with "dronelike" behavior is reflected in language.

That is a claim about etymology, not about bee taxonomy.

Synonymous Homonym's first correction:

"Drones are specifically the male bees. Most bees are not drones."

is technically true, but it doesn't actually address what Rei was saying. Rei wasn't claiming that all bees are male drones.

Then Synonymous Homonym shifts to:

"Suggesting that the word 'drone' means 'mindless bee.'"

This doesn't accurately paraphrase Rei either. Rei never said the word means "mindless bee." The sentence only suggests that the metaphorical sense of "drone" is derived from the bee term.

If I were judging the exchange, I'd say:

Synonymous Homonym's factual statement is correct: drones are male bees.
But it's responding to a claim Rei didn't make, making it a misreading.
Rei's clarification directly matches the ordinary reading of the original sentence.

So the stronger interpretation is that Synonymous Homonym misunderstood the original remark, and Rei's correction is justified.

Or to put it more simply: you're attacking a straw man (a claim I never made) because you cannot defend your actual scientifically inaccurate comments about bees having half-hour memories.

You are confusing "forgetting" with "disruption".

I am not.

Your entire argument was that bees have short-term memories. The example you cited demonstrates precisely the opposite - that bee memory is if anything too durable>/i>, such that bees will refuse won't even bother searching for their hive if it has been moved, that they always go back to the spot where they remember it being last.

However, what you are choosing to ignore is that, once a bee has been accepted into a different hive, it becomes part of that hive

That's like claiming that if you move to a different city, you've "forgotten" where you used to live.

When a bee, due to a navigation error or its previous hive being gone, enters a different hive (drifting), it absorbs the pheromones of the new hive. It is now chemically marked as belonging to that hive. Chemicals are communication to bees, just as much as vocal commands are to you. Bees do not learn all of the other bees in their hive, they don't have some sort of rolodex. If you smell like hive A, you're allowed into hive A. If you smell like hive B, you're allowed into hive B. Bees don't particularly "care" which hive they're in; they have their own individual motives and drives, which simply involve being in "a" hive. Once they're marked as belonging to hive B, they can no longer enter hive A (at least not safely).

Note in the above what has nothing to do with any of this? Memory. It's just about smell. Memory is about where the hive can be found after foraging (which is also about memory) - and it remains, even after drifting (they'll continue to return to the same spot - again, even if the new hive is moved). Smell is about which hive you can enter. Or for a summary version:

1) A bee leaves the hive to go foraging

2) It remembers where the best spot to visit is (usually from having gone there before, but occasionally from having seen a waggle dance) and what flowers (shapes, smells, sizes, etc) will be yielding best there at what times of day, and what areas to NOT go to, where there may be threats. This information persists for days, weeks, or even the bee's entire life. It can target an area to an accuracy of a couple hundred meters, and then begins a search.

3) When done, it returns back to where it remembers that the hive should be (this memory is highly persistent, and can only be reset by an orientation flight.

4) The bee starts by using the sun and broad navigational features as with outbound flights to get to within a couple hundred to a few dozen meters (the "visual catchment area"), then gradually switches to small-scale features and searching. This is all based on memory.

5) For the final approach, the bee relies on a mix of sight (remembered), sound (generic), and smell. The latter is not a learned trait, it's "whatever you happen to smell like". While it's usually described as recognizing the smell of their sisters, that's not exactly right. The actual underlying mechanism not so much learning what something does smell like as it being unable to detect what they do smell like

The mechanism the same as how humans become unable to notice their own body odour or perfume: sensory adaptation. Because they're constantly smelling themselves, their brain learns to tune out their own smell. However, it doesn't tune out the smells of others. When they return to their own hive, the scent is something that they're adapted to tune out. But when they arrive at a different hive, they're hit with a scent that they're not adapted to, and that they can detect.

If you want to put it in human terms, the underlying mechanism is "this hive thinks you're stinky, that one doesn't smell you because you've all been around each other for so long".

If you want to call sensory adaptation "forgetting", then you're going to need to call human sensory adaptation "forgetting" as well. And again, none of this has anything to do with actual memory tasks, such as navigation and how to find the best flowers. Bee memory is exceptional with them.

Who said the word "small"?

(My personal hot take is that, both for copyright reasons ("Purpose and Character of the Use", aka for-profit, is a critical factor in determining copyright violation, such as from scraping), and general moral reciprocity argument (closed commercial models extracts profit from the commons without giving back), closed source trainers should fundamentally be required to give back to the commons in some meaningful way)

... some public ownership of compute, to offer out for grants to Open Source development, so that the commons can better keep up with the closed source providers?

I'm sorry that the genitals of people you neither know nor are dating bother you so much, dude.

Do you also spend this much time thinking about the genitals of children, like so many of your ilk?

Bluesky knows full well it's not operating a real federated service

Better tell that to Blacksky, Eurosky, etc.

The vast majority of people stay on the primary PDS, relay, etc namely because Bluesky hasn't proven itself to be some evil overlord pursuing insidious goals. If that were to ever occur, people would just migrate. Unlike with ActivityPub (Mastodon), ATProto allows for true migration. Your content isn't tied and linked to a specific server - it's more like a URL on an arbitrary domain, and you can just change the "domain" (the PDS). Everything is timestamped and cryptographically signed, so if you download a backup of your content, you can just reupload it somewhere else and it continues to remain linked into the whole ecosystem.

More to the point, primary Bluesky servers have gone down and third parties like Blacksky remained operational, very much demonstrating that the network is federated.

Also, re: this from the header:

" and by the end of October last year, it had reportedly seen a 40% drop in daily mobile active users over the past 12 months."

... is cherry picking. If you graph users, you'll see that - like most sites - new users tend to arrive in big "spikes", triggered either by events at other social media platforms, or major news cycles (such as elections). Most new users to a site are not "sticky". Some drop off in days, some in weeks, some in months, etc, but this slowly levels out, and the rest are "sticky". With Bluesky, usually half or so of new users stick around, which is an unusually high percentage. If you measure from a new-arrivals spike, of course you see a "dropoff", but you see that for any site. The question is, how is the long-term trend of users that stick around? If you cancel out the spike pattern, Bluesky has a long-term population of around 600k daily posters / 1M daily likers / 300k daily followers.

What you can say is there haven't been any big new user spikes since late 2024 / early 2025. That said, there kinda was some serious news going on in late 2024 / early 2025....

The extra fingers will come in handy when climbing.

Imagine being like that and spending that much of your day thinking about other people's genitals.

1) You said "AI hype is dying", not "AI companies aren't profitable" Undergoing an insane sustained ~10x/yr exponential growth trajectory over 3 1/2 years , and that rate even accelerating now, is in no way "dying"

2) It is absolutely not normal for companies undergoing rapid rates of growth, let alone such an insane rate, to be profitable. Scaleup generally means you lose money hand-over-fist, as scaleup is extremely expensive (no less so in this field!). And yet:

3) Anthropic may actually pull it off this quarter.

Their margins are like 40%. That's all users combined, not just paying users. Inference is cheap to serve; compare what the closed commercial operators like Anthropic charge vs. what the open source models (an actually competitive for-profit marketplace) charge, for models of equivalent size. The closed models rob you blind. But people pay it because their models are the best.

(BTW, the main thing that's driving it now isn't random people asking questions on the website or in an app in their phone. It's software developers).

Zoophiles with a thing for large cats must get so frustrated by such ads.

Remember, the AI hype is dying

Better tell that to Anthropic's annualized revenue growth.

Dec 2022: $10M
Dec 2023: $100M (10x in 12 months)
Jan 2025: $1B (10x in 13 months)
May 2025: $3B
Oct 2025: $7B
Dec 2025: $9B
Feb 2026: $14B
Mar 2026: $19B
Apr 2026: $30B
May 2026: $47B

Here's the crazy thing: initially, SpaceX / X.AI didn't acquire the servers. Tesla had the contract for them, and then Tesla just gave those rights to X.AI. Tesla is a public company, while X.AI was Musk's private company, founded so that he wouldn't have to share any AI profits with Tesla.

Now, Musk's excuse was that Tesla's datacentre wasn't ready yet, and it cost Tesla nothing. But of course, there was a massive backlog on servers; the rights to early delivery of servers was incredible value. It let X.AI jump to the head of the line. Tesla could have sold those servers or the rights to them at a huge markup.

If you don't like your honey having been regurgitated, there are alternatives for getting honey...

Drones are specifically the male bees. Most bees are not drones.

That's not what I said. I said that the word "drone", as in a mindless unthinking being, is derived from drones, as in male bees. I did not say "all bees are drone bees".

And an individual bee has limited memory. They even forget which hive they are from after a while if they don't return to it.

You are confusing "forgetting" with "disruption".

Bees have both a geospatial "mental map" (based on landmarks, the sun, etc) and a chemical fingerprint (they recognize their nestmates' smell). Concerning their geospatial memory, not only is it not poor, the main problem with it is that it's too stubborn. If you move a hive 20 meters away, the bees will fly back to the same empty location where their hive used to be and wait there. They don't adapt well to change because they have a long-term memory of "the hive was here".

If a beekeeper wants to move a hive, they have to trigger an "orientation flight" to get the bees to learn the new location (this typically involves locking them inside their hive for several days to disrupt their routine). During an orientation flight, the bees will learn the new hive location, and then they'll subbornly remember that location long-term, even if you move the hive again.

As for recognizing their nestmates, this is again based on smell. A bee being isolated for days or weeks will still be recognized by guard bees at the entrance and welcomed in. However, guards will sometimes let in bees that don't belong to that hive as well, if e.g. they're passive and laden with pollen and nectar; they haven't "forgotten" their scent, they're just "forgiving" of mistakes if there's a reward to be had (bees sometimes make navigation errors, esp. if all nest boxes are similar in shape/colour or due to wind, and enter the wrong hive)

I'll repeat: bees do NOT have a short memory. This is a myth. It's not true. The very example you gave is actually an example of bee memory being too rigid.

It's IMHO amazingly impressive how dense information can be stored within neural networks. Even a comparably tiny LLM can store more information than the human brain, despite the brain's theoretical storage being far higher due to its vast number of connections (ANNs are better at information density, we're better at learning from limited datasets). The tiny LLM will crush humans at a quiz in virtually anything except said human's particular areas of expertise. Storing information as a superposition of states across a large number of neurons and connections (whether we're talking artificial or biological) is an immensely space-efficient way to do so, and the human mind is nowhere near the limits of information storage capability.

There is no technical reason why a given organism, such as a bee, could not achieve far denser information representations in order to be able to do more with its limited neural capacity (though there are always tradeoffs). One of the reasons that ANNs learn slower-but-denser is the use of a very low learning rate with a very large amount of data that covers the same topic from many different angles, giving the weights ample time to explore different possible circuits in parallel and seeing which ones predict reality the best ("learn everything all at once" vs. "learn this thing NOW"). Bees aren't tasked with learning anywhere nearly as diverse things as a human is and spend all day doing the same basic job (the same information "from different angles"), so it seems quite possible that their greater "information specialization" as they go about their day may be able to lead to denser representations of said information.

BTW, at risk of a tangent (your comment about non-neuron cells playing roles), it's been really interesting to me seeing how a key difference between artificial and biological learning has been clearing up. In biological neural networks, weight cannot flip sign (Dale's Principle). In the general case, a neuron is either excitatory or inhibitory (usually a small number of inhibitory neurons per cluster of excitatory neurons); it can't change from one to the other even if learning would favour that. At a first glance, that would seem to cripple learning capability (and definitely does if you implement that in ANNs). But what appears to actually happen in biological neural networks is a sort of horizontal learning, co-dependent synaptic plasticity, between excitatory and inhibitory neurons. Instead of merely weakening an excitatory connection down to zero and then being able to go no further, learning simultaneously weakens the excitatory connections and strengthens the inhibitory connections. The excitatory neurons are the primary drivers of information storage and processing, but the inhibitory neurons adjust the baseline to give them the flexibility to express negative net activations as needed.