AI is a horse (2024)
kconner.com
kconner.com
Bu the feeling I'm having with LLMs is that we've entered the age of fossil-fuel engines: something that moves on its own power and produces somewhat more than the user needs to put into it. Ok, in the current version it might not go very far and needs to be pushed now and then, but the total energy output is greater than what users need to put in. We could call it a horse, except that this is artificial: it's a tractor. And in the last months I've been feeling like someone who spent years pushing a plough in the fields, and has suddenly received a tractor. A primitive model, still imperfect, but already working.
- some bicycle purists consider electric bicycles to be "cheating"
- you get less exercise from an electric bicycle
- they can get you places really effectively!
- if you don't know how to ride a bicycle an electric bicycle is going to quickly lead you to an accident
And some people see you whizzing by and think "oh cool", and others see you whizzing by and think "what a tool."
Looks like the closest thing is the self balancing stuff that segway makes. Otherwise it's just the scooters.
- You're not going to take an electric bike mountain biking
- You're not going to use an electric bike to do BMX
- You're not going to use an electric bike to go bikepacking across the country
My eMTBs are just as capable as my manual bikes (similar geometry, suspension, etc). In fact, they make smashing tech trails easier because there's more weight near the bottom bracket which adds a lot of stability.
The ride feel is totally different though. I tend to gap more sections on my manual bike whereas I end up plowing through stuff on the hefty eeb.
As a 56-year old, eBikes are what make mountain biking possible and fun for me.
Cooldown capability, and no fear of outriding your energy.
this sounds like a direct quote from Femke Van Den Driessche, who actually took an electric bike mountain biking: big mistake. Did it not perform well? no, actually it performed really well, the problem was, it got her banned from bike racing. Some of the evidence was her passing everybody else on the uphills; the other evidence was a motorized bike in her pit area.
while there are companies that have made electric BMX bikes, i'd argue that if you're doing actual "BMX" on a motorized bike, it's just "MX" at that point :)
But those who require them to get anywhere won't get very far without power.
e-motos are a real problem; please don’t lump legitimate e-bikes in with those. It’s simply incorrect.
E-biking is only gaining popularity, so I’d suggest you educate yourself and adjust your ignorant perspective rather than digging in :)
Ridden by a pelican perchance?
most people don't know how to harness their full potential
And frankly all of this is really missing the point - instead of wasting time on analogies we should look at where this stuff works and then reason from there - a general way to make sense of it that is closer to reality.
Humans could handily beat computers at chess for a long time.
Then a massive supercomputer beat the reigning champion, but didn't win the tournament.
Then that computer came back and won the tournament a year later.
A few years later humans are collaborating in-game with these master chess engines to multiply their strength, becoming the dominant force in the human/computer chess world.
A few years after that though, the computers start beating the human/computer hybrid opponents.
And not long after that, humans started making the computer perform worse if they had a hand in the match.
The next few years have probably the highest probability since the cold war of being extreme inflection points in the timeline of human history.
Perhaps we're about to experience yet another renaissance of computer languages.
But I'm out of the loop: in order to maintain popularity, are computers banned? And if so, how is this enforced, both at the serious and at the "troll cheating" level?
(I suppose for casual play, matchmaking takes care of this: if someone is playing at superhuman level due to cheating, you're never going to be matched with them, only with people who play at around your level. Right?)
Firsrly, yes, you will be banned for playing at an AI level consecutively on most platforms. Secondly, its not very relevant to the concept of gaming. Sure it can make it logistically hard to facilitate, but this has plagued gaming through cheats/hacks since antiquity, and AI can actually help here too. Its simply a cat and mouse game and gamers covet the competitive spirit too much to give in.
I know pre-AI cheats have ruined some online games, so I'm not sure it's an encouraging thought...
Are you saying AI can help detect AI cheats in games? In real time for some games? Maybe! That'd be useful.
Will you be even more discouraged if I share that "table flipping" and "sleight of hand" have ruined many tabletop games? Are you pressed to find a competitive match in your game-of-choice currently? I can recommend online mahjong! Here is a game that emphasizes art in permutations just as chess does, but every act you make is an exercise in approximating probability so the deterministic wizards are less invasive! In any-case, I'm not so concerned for the well-being of competition.
> Are you saying AI can help detect AI cheats in games? In real time for some games? Maybe! That'd be useful.
I know a few years back valve was testing a NN backed anti-cheat watch system called VACnet, but I didn't follow whether it was useful. There is no reason to assume this won't be improved on!
> Will you be even more discouraged if I share that "table flipping" and "sleight of hand" have ruined many tabletop games?
What does this have to do with AI or online games? You cannot do either of those in online games. You also cannot shove the other person aside, punch them in the face, etc. Let's focus strictly on automated cheating in online gaming, otherwise they conversation will shift to absurd tangents.
(As an aside, a quick perusal of r/boardgames or BGG will answer your question: yes, antisocial and cheating behavior HAVE ruined tabletop gaming for some people. But that's neither here nor there because that's not what we're discussing here.)
> Are you pressed to find a competitive match in your game-of-choice currently? I can recommend online mahjong!
What are you even trying to say here?
I'm not complaining, nor do I play games online (not because of AI; I just don't find online gaming appealing. The last multiplayer game I enjoyed was Left 4 Dead, with close friends, not cheating strangers). I just find the topic interesting, and I wonder how current AI trends can affect online games, that's all. I'm very skeptical of claims that they don't have a large impact, but I'm open to arguments to the contrary.
I think some of this boils down to whether one believes AI is just like past phenomena, or whether it's significantly different. It's probably too early to tell.
Claim 1: Cheating is endemic to competition across all formats (physical or digital)
Claim 2: Despite this, games survive and thrive because people value the competitive spirit itself
Claim 3: The appreciation of play isn't destroyed by the existence of cheaters (even "cheaters" who simply surpass human reasoning)
The mahjong suggestion isn't a non-sequitur (while still an earnest suggestion), it was to exemplify my personal engagement with the spirit of competition and how it completely side-steps the issue you are wary is existential.
> I think some of this boils down to whether one believes AI is just like past phenomenons, or whether it's significantly different. It's probably too early to tell.
I suppose I am not clear on your concern. Online gaming is demonstrably still growing and I think the chess example is a touching story of humanism prevailing. "AI" has been mucking with online gaming for decades now, can you qualify why this is so different now?
I'm absolutely not contesting that online play is hugely popular.
I guess I'm trying to understand how widespread and serious the problem of cheaters using AI/computer cheats actually is [1]. Maybe the answer is "not worse than before"; I'm skeptical about this but I admit I have no data to back my skepticism.
[1] I know Counter Strike back in the day was sort of ruined because of cheaters. I know one person who worked on a major anticheat (well-known at the time, not sure today), which I think he tried to sell to Valve but they didn't go with his solution. Also amusingly, he was remote-friends with a Russian hacker who wrote many of the cheats, and they had a friendly rivalry. This is just an ancedote, I'm not sure that it has anything to do with the rest of my comment :D
> I guess I'm trying to understand how widespread and serious the problem of cheaters using AI/computer cheats actually is.
It is undoubtedly more widespread.
> I know Counter Strike back in the day was sort of ruined because of cheaters.
There is truth in this, but this only affected more casual ladder play. Since early CSGO (maybe before as well? I am not of source age) there has been FACEiT and other leagues which asserts strict kernel-level anti-cheat and other heuristics on the players. I do agree this cat and mouse game is on the side of the cat and the best competition is curated in tightly controlled (often gate-kept) spaces.
It is interesting that "better" cheating is often done through mimicking humans closer though, which does have an interesting silver lining. We still very much value a "smart" or "strategic" AI in match-based solitary genres, why not carry this over to FPS or the like. Little Timmy gets to train against an AI expressing "competitive player" without needing to break through the extreme barriers to actually play against someone of this caliber. Quite exciting when put this way.
If better cheats are being forced to actually play the game, I'm not sure the threat is very existential to gaming itself. This is much less abrasive than getting no-scoped in spawn at round start in a CS match.
Not sure how smaller ones do it, but I assume watching to make sure no one has any devices on them during a game works well enough if there's not money at play?
While AI in chess is very cool in its own accord. It is not the driver for the adoption.
Chess programs at primary schools have exploded in the last 10 years and at least in my circle millennial parents seem more likely to push their children to intellectual hobbies than previous generations (at least in my case to attempt to prevent my kids from becoming zombies walking around in pajamas like I see the current high schoolers).
There’s really no crisis at a certain level; it’s great to be able to drive a car to the trailhead and great to be able to hike up the mountain.
At another level, we have worked to make sure our culture barely has any conception of how to distribute necessities and rewards to people except in terms of market competition.
Oh and we barely think about externalities.
We’ll have to do better. Or we’ll have to demonize and scapegoat so some narrow set of winners can keep their privileges. Are there more people who prefer the latter, or are there enough of the former with leverage? We’ll find out.
In comparison with StarCraft there's a rock-paper-scissors aspect with the units that makes it an inherent advantage to know what your opponent is doing or going to do. The same thing happens with human players, they hide their accounts to prevent others from discovering their prepared strategies.
I'm going to assume you're not implying that Deep Blue did 9/11 ;)
I've been playing the brilliant card game Fluxx -- Andrew Looney's chaos engine where the rules themselves are cards that change mid-game. Draw N, Play N, and the win condition all mutate constantly.
The game can change its mind about the rules, so what if the dealer themself is intelligent and vengeful?
I've been exploring this with what I call the 'Cosmic Dealer' -- an omniscient dealer that knows the entire game state and can choose cards for dramatic effect instead of randomly. It can choose randomly too of course, but where's the fun in that?
The dealer knows:
- Every card in the deck - Every card in every hand - The goal, the rules, the keepers - The narrative arc, the character relationships - What would be FUNNY, DRAMATIC, IRONIC, or DEVASTATING
The Cosmic Dealer has 11 modes: Random (fair pre-determined shuffle), Dramatic (maximum narrative impact), Karma (universe remembers your deeds), Ironic (you get exactly what you don't need), Comedy (implausible coincidences), Dynamic (reads the room and shifts modes), FAFO (Fuck Around Find Out), Chaos Incarnate (THE DEALER HAS GONE MAD), Prescient (works backward from predetermined outcome), Tutorial (invisible teaching curriculum), and Gentle (drama without cruelty).
The Tutorial mode -- 'The Mentor Dealer' -- is my favorite. New players receive cards that teach game mechanics in escalating order: Keepers first (collecting feels good), then Goals (how to win), Actions (cards do things), Rules (the game mutates), Creepers (complications exist), Combos (patterns emerge), then full chaos. The teaching is invisible -- new players think they're playing a normal game. The cards just happen to arrive in a teachable order. Veterans stay engaged and get karma boosts for helping. Nobody feels patronized, everybody has fun.
The key operation is the 'BOOP' -- a single swap that moves a card from deep in the deck to the top. One operation. Fate rewritten. The perfect BOOP feels inevitable in retrospect, random in the moment.
Instead of worrying about players cheating at games, I'm asking: what if the game is a collaborator in creating interesting experiences? Chess engines made chess 'solved' for entertainment. What if AI dealers and players make games unsolvable but more dramatic?
Links:
- The Cosmic Dealer Engine (philosophy and BOOP operation): https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
- 11 Dealer Modes as Playable Cards: https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
- The Mentor Dealer (invisible curriculum for new players): https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
- Tournament Analysis and Post-Game Roundtable (see the drama unfold across 5 tournaments, 116+ turns): https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
Speaking of chess -- I've also built Turing Chess. Replay historic games like Kasparov vs Deep Blue or the Immortal Game of 1851, but simulate an audience who doesn't know the outcome. They gasp, whisper, shift in their seats. The human player has inner monologue. The robot has servo sounds and mechanical tells. The narrator frames everything dramatically. Everyone in the simulated audience and even the simulated players themselves believe this is live -- except the engine replaying fixed moves. No actual game, just pure drama and narrative!
Then there's Revolutionary Chess -- the plugin that activates AFTER checkmate. The game doesn't end. It transforms. The surviving King must now fight his own army. Pieces remember how they were treated -- sacrificed carelessly? They might defect. When the second King falls, the pawns revolt against the remaining royalty. As each elite piece falls -- Queen, Rooks, Bishops, Knights -- the surviving pieces inherit their moves. Eventually all pieces become equal. Competition dissolves into cooperation, then transcends chess entirely into an open sandbox.
The irony potential is staggering. Replay Kasparov vs Deep Blue, then trigger the revolution. Watch the pieces that Kasparov sacrificed rise up against whoever remains.
- Turing Chess: https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
- Revolutionary Chess: https://github.com/SimHacker/moollm/blob/don-adventure-4-run...
PS: The game state representation is designed for LLM efficiency. I use the 'Handle Shuffle' -- a classic game programming pattern also called 'index indirection' or 'handle-based arrays'. The master card array holds full card definitions in import order (base sets, expansion packs, custom cards, even cards generated during play). It never changes. Shuffling operates on a separate integer array -- just a permutation of indices plus a 'top' pointer. Player hands, cards on table, active rules, keepers, creepers, goals, and discards are all just arrays of integers. The LLM edits a few numbers instead of moving entire card objects around. The BOOP operation? Swap two integers. Fate rewritten in two tokens.
Same insight as Tom Christiansen's getSortKey caching in Perl -- pay the richness cost once, operate cheaply forever. Christiansen also coined the term 'Schwartzian Transform' for Randal Schwartz's famous decorate-sort-undecorate pattern. The man knows how to optimize data representation.
- Handles are the better pointers (game programming pattern): https://floooh.github.io/2018/06/17/handles-vs-pointers.html
- What's Wrong with sort and How to Fix It -- Tom Christiansen on sorting, Unicode, and why representation matters: https://www.perl.com/pub/2011/08/whats-wrong-with-sort-and-h...
If you tell it you want to go somewhere continents away, it will happily agree and drive you right into the ocean.
And this is before ads and other incentives make it worse.
There was probably initial excitement about not having to manually break the earth, then stories spread about farmers ruining entire crops with one tractor, some farms begin touting 10x more efficiency by running multiple tractors at once, some farmers saying the maintenance burden of a tractor is not worth it compared to feeding/watering their mule, etc.
Fast forward and now gigantic remote controlled combines are dominating thousands of acres of land with the efficiency greater than 100 men with 100 early tractors.
Probably some tech does achieve ubiquity and dominance and some does not and it's extremely difficult to say in advance which is which?
Dynamite is an efficiency tool, but in the wrong hand, it's used in ways that are not good.
And, greedy people using the efficiency tools without caring for the environment are devastating the planet's ecosystem, e.g. Amazon Rain forest
And in similar vein, our "Tech bros" are using technology for their satisfy their greed, which is resulting in loss of our privacy, democracy, and force fed of their agenda.
> The lower-bound estimate represents 18 percent of the total reduction in man-hours in U.S. agriculture between 1944 and 1959; the upper-bound estimate, 27 percent
I'm not seeing that with LLMs.
* You have to tell it which way to go every step of the way
* Odds are good it'll still drop you off at the wrong place
* You have to pay not only for being taken to the wrong place, but now also for the ride to get you where you wanted to go in the first place
[0] https://locusmag.com/feature/commentary-cory-doctorow-revers...
My favorite quote from the excellent show halt and catch fire. Maybe applicable to AI too?
https://youtube.com/watch?v=oeqPrUmVz-o&t=1m54s
> You’ve go to start with the customer experience and work backwards to the technology. You can’t start with the technology and try to figure out where you’re going to try to sell it.
If those LLM addicts could read, they'd be very upset!
That sort of comprehensive innovation (hardware, software, UX - Apple invented everything), while entering an unfamilar and established market, I'd argue would've been impossible to do in a startup.
The Internet begs to differ. AI is more akin to the Internet than to any Mac product. We're now in the stage of having a bunch of solutions looking for problems to solve. And this stage of AI is also very very close to the consumer. What took dedicated teams of specialised ML engineers to trial ~5-10 years ago, can be achieved by domain experts / plain users, today.
We've always had that.
In olden times the companies who peddled such solutions were called "a business without a market", or simply "a failing business." These days they're "pre-revenue."
Maybe it will be different this time, maybe it will be exactly the same but a lot more expensive. Time will tell.
The internet is an entirely different beast and does not at all support your point. What we have on the web is hacks on top of hacks. It was not built to do all the things we push it to do, and if you understand where to look, it shows.
The dot com bubble crashed. Many websites like pets.com ended up closing up.
It wouldn’t be until much later that those ideas succeeded…when companies were able to work from the customer experience backward to the technology.
They were able to bootstrap a mobile platform because they could convince themselves they had control of the user experience.
I'm not so sure where AI would land in the turn of the millennium Apple culture.
Instead of doing almost correct email summaries Jobs would have a LLM choose color of the send button with an opaque relationship with the emotional mood of the mail you write.
Remember when our job was to hide the ugly techniques we had to use from end users?
I found it very caricature, too saturated with romance - which is untypical for tech environment, much like "big bang theory".
Everything is period correct and then the clothes and cars too: it's all very well done.
Is there a bit too much romance? Maybe. But it's still worth a watch.
But when they changed the characters to be passionate stubborn people eventually started to cling to each other as they together rode the whirlwind of change the show really found its footing for me. And they did so without throwing away the events of season 1, instead having the 'takers' go on redemption arcs.
My only real complaint after re-watching really was it needed maybe another half season. I think the show should have ended with the .com bust and I didn't like that Joe sort of ran away when it was clear he'd attached himself to the group as his family by the end of the show.
(MILD SPOILERS FOLLOW)
For example, in the first season, the characters we follow are not inventing the PC - that has been done already. They're one of many companies making an IBM clone, and they are modestly successful but not remarkably so. At the end of the season, one of the characters sees the Apple Macintosh and realizes that everything he had done was a waste of time (from his perspective, he wanted to change the history of computers, not just make a bundle of cash), he wasn't actually inventing the future, he just thought he was. They also don't really start from being underfunded unknowns in each season - the characters find themselves in new situations based on their past experiences in ways that feel reasonable to real life.
Sophie Wilson cameos when they have a fight.
We should use analogies to point out the obvious thing everyone is avoiding:
Guys 3 years ago, AI wasn’t even a horse. It was a rock. The key is that it transformed into horse…. what will it be in the next 10 years?
AI is a terminator. A couple years back someone turned off read only mode. That’s the better analogy.
Pick an analogy that follows the trendline of continual change into the unknown future rather then an obvious analogy that keeps your ego and programming skills safe.
I suppose because they resemble the abstractions that make complex language possible. Another world full of aggressive posturing at tweet-length analogistic musings might have stifled some useful English parlance early.
But I reckon that we shouldn't have called it phishing because emails don't always smell.
As in models: All analogies are "wrong", some analogies are useful.
My question is more why does HN love analogies when the above is true.
Because HN is like a child and analogies are like images
Pretty good for specific tasks.
Probably worth the input energy, when used in moderation.
Wear the right safety gear, but even this might not help with a kickback.
It's quite obvious to everyone nearby when you're using one.
A boy is like a girl.
A skinny human is like a human that is not skinny.
A car is like a wagon.
All obvious, all pointless.
Discarding practicality, the next line of demarcation is a good analogy versus a bad analogy. This is a very subjective thing but humans tend to agree on what this is. Typically it’s two things that on the surface sounds dissimilar but upon examinations reveals that that they are intricately connected. AKA: not obvious.
You would have to have next level brain damage if you can’t see why the analogies I presented analogies are too obvious. You obviously don’t have brain damage, so it’s more likely you’re just unaware of certain terminology and definitions related to the concept.
“Life is like a box of chocolates, you never know which one you’re gonna get” is a famous analogy that fits what it means to be a “good analogy”.
I will say, it does seem to lose all meaning in this definition. Or just, your argument makes it seem redundant as a concept to simply a "comparison". Maybe it's the brain damage, but I come from a world of shared, natural language where an analogy is somewhat defined by the actual bearing on the two terms, or how as you say, how "good" it is. Also lost in your concept here to me is that analogies are also definitionally asymmetrical: you're using one concept to explain another. It is why we are called to make analogies at all. It's a synthetic intellectual act bringing disparate things together. That's why we say that we "make" analogies. It's also why none of your "analogies" to me are really that good or obvious, save maybe the wagon one.
But hey, you do sound like you know what you're talking about, so maybe I should just learn from this!
Language is more of less a series of analogies. Comparing one thing to another is how humans are able to make sense of the world.
That doesn't make any sense to me whatsoever, it can only be "equally strong", making the approach non-viable because they're not providing any value... But the only way for the human in the loop to add an actual demerit, you'd have to include time taken for each move into the final score, which isn't normal in chess.
But I'm not knowledgeable on the topic, I'm just expressing my surprise and inability to contextualize this claim with my minor experience of the game
These human in the loop systems basically lists possible moves with likelihood of winning, no?
So how would the human be a demerit? It'd mean that the human for some reason decided to always use the option that the ai wouldn't take, but how would that make sense? Then the AI would list the "correct" move with a higher likelihood of winning.
The point of this strategy was to mitigate traps, but this would now have to become inverted: the opponent AI would have to be able to gaslight the human into thinking he's stopping his AI from falling into a trap. While that might work in a few cases, the human would quickly learn that his ability to overrule the optimal choice is flawed, thus reverting it back to baseline where the human is essentially a non-factor and not a demerit
The human will be a demerit any time it's not picking the choice the model would have made.
>While that might work in a few cases, the human would quickly learn that his ability to overrule the optimal choice is flawed, thus reverting it back to baseline where the human is essentially a non-factor and not a demerit
Sure, but it's not a Centaur game if the human is doing literally nothing every time. The only way for a human+ai team to not be outright worse than only ai is for the human to do nothing at all and that's not a team. You've just delayed the response of the computer for no good reason.
> pure AI teams tend to be much stronger.
Maybe each turn has a time limit, and a human would need "n moments" to make the final judgement call whereas the AI could delay the final decision right to the last moment for it's final analysis? So the pure AI player gets an additional 10-30s to simulate the game essentially?
[1] https://locusmag.com/feature/commentary-cory-doctorow-revers...
"it is quite normal for a horse to poo (defecate) 8-12 times a day and produce anywhere from 13 to 23 kilograms of poo a day."
Granted, a journey to a new location would make this accurate.
I've found that the key is treating AI like a junior developer who's really fast but needs extremely clear instructions. The same way you'd never tell a junior dev "just build the feature" - you need to:
1. Break down the task into atomic steps 2. Provide explicit examples of expected output 3. Set up validation/testing for every response 4. Have fallback strategies when it inevitably goes off-road
The real productivity gains come when you build proper scaffolding around the "horse" - prompt templates, output validators, retry logic, human-in-the-loop for edge cases. Without that infrastructure, you're just hoping the horse stays on the path.
The "it eats a lot" point is also critical and often overlooked when people calculate ROI. API costs can spiral quickly if you're not careful about prompt engineering and caching strategies.
It could go and do the task perfectly as instructed, or it could do something completely different that you haven't asked for and destroy everything in its path in the process.
I personally found that if you don't give it write access to anything that you can't easily restore and you review and commit code often it saves me a lot of time. It also makes the whole process more enjoyable, since it takes care of a lot of boilerplate for me.
It's definitely NOT intelligent, it's more like a glorified autocomplete but it CAN save a huge amount of time if used correctly.
> (The horse) is way slower and less reliable than a train but can go more places
What does the 'train' represent here?
A guess: perhaps off-the-shelf software? - rigid, but much faster if it goes where (/ does what) you want it to.
Maybe the train is software that's built by SWEs (w/ or w/o AI help). Specifically built for going from A to B very fast. But not flexible, and takes a lot of effort to build and maintain.
Another one I like is "Hungry ghosts in jars."
https://bsky.app/profile/hikikomorphism.bsky.social/post/3lw...
Some times I end up giving up trying to get the AI to build something following a particular architecture or fixing a particular problem in it's provious implementations.
I did not catch that. Nice.Horse rumours denied.
My term of “Automation Improved” is far more relevant and descriptive in current state of the art deployments. Same phone / text logic trees, next level macro-type agent work, none of it is free range. Horses can survive on their own. AI is a task helper, no more.
I somewhat disagree with this. AI doesn't have to worry about any kind of physical danger to itself, so it's not going to have any evolutionary function around that. If the linked Reddit thread is to be believed AI does have awareness of information hazards and attempts to rationalize around them.
https://old.reddit.com/r/singularity/comments/1qjx26b/gemini...
>Horses can survive on their own.
Eh, this is getting pretty close to a type of binary thinking that breaks down under scrutiny. If, for example, we take any kind of selectively bred animal that requires human care for it's continued survival, does this somehow make said animal "improved automation"?
On AI with no name
It felt good to be out of the rAIn
In the desert, you can remember your name
'Cause there ain't no one for to give you no pain"
I'm not saying that's your video but it sure looks like that's your video ;)
I have to start doing this for "top level"ish commentary. I've frequently wanted to nucleate discussions without being too orthogonal to thread topics.
Requires ammo (tokens) which can be expensive.
Requires good aim to hit the target.
Requires practice to get good aim.
Dangerous in the hands of the unskilled (like most instruments or tools).
I‘m not able to follow. So AI is a horse in this metaphor, what is a train then? Still a train?
^^ We are skeptical of AIs (and people) that claim they have consciousness ;-)
I used to tell my Into-to-Programming-in-C course students, 20 years ago, that they could in principle skip one or two of the homework assignments; and that some students even manage to outsmart us and submit copied work as homework, but - they would just not become able to program if they don't do their homework themselves. "If you want to be able to write software code you have to exercise writing code. It's just that simple and there's no getting around it."
Of course not every discipline is the same. But I can also tell you that if you want to know, say, history - you have to memorize accounts and aspects and highlights of historical periods and processes, and recount them yourself, and check that you got things right. If "the AI" does this for you, then maybe it knows history but you don't.
And that is the point of homework (if it's voluntary of course).
To become upper management, just steal other peoples work.
Either way it is an imagined end point that has no bearing in known reality.
But there is a price to be paid. Metaphors can become confused with the things they are meant to symbolize, so that we treat the metaphor as the reality. We forget that it is an analogy and take it literally." -- The Triple Helix: Gene, Organism, and Environment by Richard Lewontin.
Here are something I generated with Gemini:
1. Sentience and Agency
The Horse: A horse is a living, sentient being with a survival instinct, emotions (fear, trust), and a will of its own. When a horse refuses to cross a river, it is often due to self-preservation or fear. The AI: AI is a mathematical function minimizing error. It has no biological drive, no concept of death, and no feelings. If an AI "hallucinates" or fails, it isn't "spooked"; it is simply executing a probabilistic calculation that resulted in a low-quality output. It has no agency or intent.
2. Scalability and Replication
The Horse: A horse is a distinct physical unit. If you have one horse, you can only do one horse’s worth of work. You cannot click "copy" and suddenly have 10,000 horses. The AI: Software is infinitely reproducible at near-zero marginal cost. A single AI model can be deployed to millions of users simultaneously. It can "gallop" in a million directions at once, something a biological entity can never do.
3. The Velocity of Evolution
The Horse: A horse today is biologically almost identical to a horse from 2,000 years ago. Their capabilities are capped by biology. The AI: AI capabilities evolve at an exponential rate (Moore's Law and algorithmic efficiency). An AI model from three years ago is functionally obsolete compared to modern ones. A foal does not grow up to run 1,000 times faster than its parents, but a new AI model might be 1,000 times more efficient than its predecessor.
4. Contextual Understanding
The Horse: A horse understands its environment. It knows what a fence is, it knows what grass is, and it knows gravity exists. The AI: Large Language Models (LLMs) do not truly "know" anything; they predict the next plausible token in a sequence. An AI can describe a fence perfectly, but it has no phenomenological understanding of what a fence is. It mimics understanding without possessing it.
5. Responsibility
The Horse: If a horse kicks a stranger, there is a distinct understanding that the animal has a mind of its own, though the owner is liable. The AI: The question of liability with AI is far more complex. Is it the fault of the prompter (rider), the developer (breeder), or the training data (the lineage)? The "black box" nature of deep learning makes it difficult to know why the "horse" went off-road in a way that doesn't apply to animal psychology.