Famously Steve Jobs said that the (personal) computer is "like a bicycle for the mind". It's a great metaphor because- besides the idea of lightness and freedom it communicates- it also described the computer as multiplier of the human strength- the bicycle allows one to travel faster and with much less effort, it's true, but ultimately the source of its power is still entirely in the muscles of the cyclist- you don't get out of it anything that you didn't put yourself.
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.
To keep torturing the metaphor, LLMs might be more like those electric unicycles (Onewheel, Inmotion, etc) – quite speedy, can get you places, less exercise, and also sometimes suddenly choke and send you flying facefirst into gravel.
And some people see you whizzing by and think "oh cool", and others see you whizzing by and think "what a tool."
More like the Segway... really cool at first then not really then totally overpriced and failed to revolutionize the industry. And it killed the founder
Is there a modern segway? I mean, I find ebikes are probably a better option in general, but it seems like all the pieces to recreate the segway for a much lower price are there already.
Looks like the closest thing is the self balancing stuff that segway makes. Otherwise it's just the scooters.
Not sure how this fits in the analogy, but as a cyclist I would add some people get more exercise by having an electric bicycle. It makes exercise available to more people.
I like this analogy. I'll add that, while electric bicycles are great for your daily commute, they're not suited for the extremes of biking (at least not yet).
- 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.
>- You're not going to take an electric bike mountain biking
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.
I think you're kind of missing the point discussing which vehicle compares better to LLMs. The point is not the vehicle: it's the birth of the engine. Before engines, humans didn't have the means to produce those amounts of power- at all. No matter how many people, horses or oxen they had at their disposal.
> You're not going to use an electric bike to do BMX
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 :)
Most people I see on their electric bikes aren't even pedaling. They're electric motorcycles, and they're a plague to everyone using pedestrian trails. Some of them are going nearly highway speeds, it's ridiculous.
There are 3 classes of e-bikes in the US, with class 3 topping out at 28mph—anything above that is illegal or in some weird legal grey area. You are thinking of e-motos which are an entirely different beast.
e-motos are a real problem; please don’t lump legitimate e-bikes in with those. It’s simply incorrect.
I feel like both moped and electric bike misses the mark of the initial analogy, so does tractor too. Because they're not able to get good results without someone putting in the work ("energy") at some higher part of the process. It's not "at the push of a button/twist of the wrist" like with electric bikes or mopeds, but being able to know where/how to push actually gets you reliable results. Like a bicycle.
Not convinced with any of three analogies tbh they don’t quite capture what is going on like Steve jobs’ did.
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.
I think there is a legitimate fear that is born from what happened with Chess.
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.
Chess being popular is mostly because FIDE had a massive push in the last decade to make it more audience friendly. shorter time formats, more engaging commentary etc.
While AI in chess is very cool in its own accord. It is not the driver for the adoption.
Google Trends data for "Chess" worldwide show it trending down from 2004-2016, and then leveling off from 2016 until a massive spike in interest in October 2020, when Queen's Gambit was released. Since then it has had a massive upswing.
This seems like an over simplification. Do many newcomers to chess even know about time formats or watch professional matches? From my anecdotal experience that is a hard no.
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).
I know chess is popular because I have a friend who's enthusiastic about it and plays online regularly.
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?)
> But I'm out of the loop: in order to maintain popularity, are computers banned?
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.
Note that "AI" was not and has not been necessary for strong computer chess engines. Though clearly, they have contributed to peak strength and some NN methods are used by the most popular engine, stockfish.
Oh, I'm conflating the modern era use of the term with the classic definition of AI to include classic chess engines done with tree-pruning, backtracking, and heuristics :)
> I know pre-AI cheats have ruined some online games, so I'm not sure it's an encouraging thought...
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!
I'm honestly not following your argument here. I'm also not convinced by comparisons between AI and things that aren't AI or even automated.
> 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.
We are likely on different footing as I quite enjoy games of all form. Here is my attempt to formalize my argument:
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 really appreciate your clarifications! I think I actually agree with you, and I lost track of my own argument in all of this.
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.
The most serious tournaments are played in person, with measures in place to prevent (e.g.) a spectator with a chess engine on their phone communicating with a player. For online play, it's kind of like the situation for other online games; anti-cheat measures are very imperfect, but blatant cheaters tend to get caught and more subtle ones sometimes do. Big online tournaments can have exam-style proctoring, but outside of that it's pretty much impossible to prevent very light cheating -- e.g. consulting a computer for the standard moves in an opening is very hard to distinguish from just having memorized them. The sites can detect sloppy cheating, e.g. a player using the site's own analysis tools in a separate tab, but otherwise they have to rely on heuristics and probabilistic judgments.
Chess.com has some cool blog posts about it from a year or two back when there was some cheating scandal with a big name player. They compare moves to the optimal move in a statistical fashion to determine if people are cheating. Like if you are a 1000 ELO player and all of a sudden you make a string of stockfish moves in the game, then yeah you are cheating. A 2400 ELO player making a bunch of stock fish moves is less likely to be suspicious. But they also compare many variables in their models to try and sus out suspicious behavior.
Computers are banned in everything except specific tournaments for computers, yeah. If you're found out to have consulted one during a serious competition your wins are of course stripped - a lot of measures have to be taken to prevent someone from getting even a few moves from the model in the bathroom at those.
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?
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.
Great comment. The best part about it as well is that you could put this under basically anything ever submitted to hacker news and it would be relevant and cut to the absolute core of whatever is being discussed.
This isn't quite right to my knowledge. Most Game AI's develop novel strategies which they use to beat opponents - but if the player knows they are up against a specific Game AI and has access to it's past games, these strategies can be countered. This was a major issue in the AlphaStar launch where players were able to counter AlphaStar on later play throughs.
Comparing Chess AI to AlphaStar seems pretty messy, StarCraft is such a different type of game. With Chess it doesn't matter if you get an AI like Lc0 to follow lines it played previously because just knowing what it's going to play next doesn't really help you much at all, the hard part is still finding a win that it didn't find itself.
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.
except chess is a solved problem given enough compute power. This caused people to split into two camps, those that knew it was inevitable, and those that were shocked
A tractor does exactly what you tell it to do though - you turn it on, steer it in a direction, and it goes. I like the horse metaphor for AI better: still useful, but sometimes unpredictable, and needs constant supervision.
The horse metaphor would also do, but it's very tied to the current state of LLMs (which by the way is already far beyond what they were in 2024). It also doesn't capture that horses are what they are, they're not improving and certainly not by a factor of 10, 100 or 1000, while there is almost no limit to the amount of power that an engine can be built to produce. Horses (and oxen) have been available for thousands of years, and agriculture still needed to employ a large percentage of the population. This changed completely with the petrol engines.
It’s sort of interesting to look back at ~100 years of the automobile and, eg, the rise of new urbanism in this metaphor - there are undoubtedly benefits that have come from the automobile, and also the efforts to absolutely maximize where, how, and how often people use their automobile have led to a whole lot of unintended negative consequences.
Fossil-fuel cars a good analogy because, for all their raw power and capability, living in a polluted, car-dominated world sucks. The problem with modern AI has more to do with modernism than with AI.
Depends who you listen to. There are developers reporting significant gains from the use of AI, others saying that it doesn't really impact their work, and then there was some research saying that time savings due to the use of AI in developing software are only an illusion, because while developers were feeling more productive they were actually slower. I guess only time will tell who's right or if it is just a matter of using the tool in the right way.
Probably depends how you're using it. I've been able to modify open-source software in languages I've never dreamed of learning, so for that, it's MUCH faster. Seems like a power tool, which, like a power saw, can do a lot very fast, which can bring construction or destruction.
I'm sure the same could be said about tractors when they were coming on the scene.
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.
Isn't this just a rhetorical trick where by referring to a particular technology of the past which exploded rapidly into dominance you make that path seem inevitable?
Probably some tech does achieve ubiquity and dominance and some does not and it's extremely difficult to say in advance which is which?
> 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
According to Wikipedia, the Ivel Agricultural Motor was the first successful model of lightweight gasoline-powered tractor. The year was 1903. You're like someone being dismissive in 1906 because "nothing happened yet".
I prefer Doctorow's observation that they make us into reverse-centaurs [0]. We're not leading the LLM around like some faithful companion that doesn't always do what we want it to. We're the last-mile delivery driver of an algorithm running in a data-center that can't take responsibility for and ship the code to production on its own. We're the horse.
> 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.
That works when you are starting a new company from scratch to solve a problem. When you're established and your boffins discover a new thing, of course you find places to use it. It's the expression problem with business: when you add a new customer experience you intersect it with all existing technology, and when you add a new technology you intersect it with all existing customer experience.
Apple was a well established company when they came out with the iPhone - I don't think anyone but Jobs would've been able to pull off something like that.
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.
He had a customer experience in mind, so he found the intersection with every existing technology, and it was impressive. But there are also times when you add a new technology to your collection, so you find the intersection with every existing customer experience.
> You can’t start with the technology and try to figure out where you’re going to try to sell it.
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're now in the stage of having a bunch of solutions looking for problems to solve.
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.
I think you’re missing the point. Of course you can make such a product. As Steve says right after, he himself made that mistake a lot. The point is that to make something great (at several levels of great, not just “makes money”) you have to start with the need and build a solution, not have a solution and shoehorn it to a need.
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.
I feel like if Jobs was still alive at the dawn of AI he would definitely be doing a lot more than Apple has been - probably would have been an AI leader.
> 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.
IMO it really came into its own after the first season. S1 felt like mad men but with computers, whereas in the latter seasons it focused more on the characters - quite beautiful and sad at times.
I vaguely remember that they tried to reboot it several times. So the same crew invented personal computers, BBSes and the Internet (or something like that), but every time they started from being underfunded unknowns. They really tried to make the series work.
That's not really what happens at all. The characters on the show never make the critical discoveries or are responsible for the major breakthroughs, they're competing in markets that they ultimately cannot win in, because while the show is fictional, it also follows real computing history.
(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.
It's still very good I'd say. It shows the relation between big oil and tech: it began in Texas (with companies like Texas Instruments) then shifted to SV (btw first 3D demo I saw on a SGI, running in real time, was a 3D model of... An oil rig). As it spans many years, it shows the Commodore 64, the BBSes, time-sharing, the PC clone wars, the discovery of the Internet, the nascent VC industry etc.
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.
I never really could get into the Cameron/Joe romance, it felt like it was initially inserted to get sexy people doing sexy things onto the show and then had to be a star crossed lovers thing after character tweaks in season 2.
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.
Why does HN love analogies? You can pick any animal or thing and it can fit in some way. Horse is a docile safe analogy it’s also the most obvious analogy. Like yes the world gets it LLMs have limitations thanks for sharing, we know it’s not as good as a programmer.
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.
If you ever heard a sermon by a priest it’s loaded with analogies. Everyone loves analogies but analogies are not a form of reason and can often be used to mislead. A lot of these sermons are driven by reasoning via analogy.
My question is more why does HN love analogies when the above is true.
If an analogy is an "obvious" analogy that makes it definitionally a good analogy, right? Either way: don't see why you gotta be so prescriptive about it one way or the other! You can just say you disagree.
After Deep Blue Garry Kapsparav proposed "Centaur Chess"[1] where teams of humans and computers would complete with each other. For about a decade a team like that was superior to either an unaided computer or an unaided AI. These days pure AI teams tend to be much stronger.
How would pure ai ever be "much stronger" in this scenario?
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
You can be so far ahead of someone, their input (if you act on it) can only make things worse. That's it. If a human 'teams up' with chess AI today and does anything other than agree with its moves, it will just drag things down.
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
>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 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.
If you had a setup where the computer just did its thing and never waited for the human to provide input but the human still had an unused button they could press to get a chance to say something that might technically count as "centaur", but that isn't really what people mean by the term. It's the delay in waiting for human input that's the big disadvantage centaur setups have when the human isn't really providing any value these days.
But why would that be a disadvantage large enough to cause the player to lose, which would be necessary for
> 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?
Why? If the human has final say on which play to make I can certainly see them thinking they are proposing a better strategy when they are actually hurting their chances.
With intelligence of models seeming spikey/lumpy I suspect we'll see tasks and domains fall to AI one at a time. Some will happen quickly and others may take far longer than we expect.
More than pooping a lot, they literally cannot hold it. Humans don't poop that much, but imagine if everyone just did it on the floor at a moment's notice regardless of where they are
Maybe from the client's point of view, although it's more likely a Tamagotchi. But from the server side, it’s more like a whole hippodrome where you need to support horse racing 24/7
This metaphor really captures the current state well. As someone building products with LLMs, the "you have to tell it where to turn" part resonates deeply.
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.
I see AI as an awesome technology, but also a like programming roulette.
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.
I wrote this a long time ago, but I think the metaphor was about generative AI applications vs. traditional software applications, not about AI coding agents vs. writing code yourself.
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.
Except when you want it to improve something in a particular way you already know about. Then god forbid it understands what you have asked and makes only that change :/
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.
Hi, that's my website and my wisecrack article. It was a while ago, but I think the metaphor was that a train is traditional deterministic-ish software, whose behavior is quite regular and predictable, compared to something generative which is much less predictable.
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).
Through many attempts to make ingesting the ponyium more bearable, I’ve found that taking it with more intense flavors (wintergreen mint, hoppy hops, crushed soul, dark roast coffee, etc) improves its comestabilty. Can’t let it pile up. We’ve always eaten ponyium right, and we all like it, right, guys, folks?
Horses have some semblance of self preservation and awareness of danger - see: jumping. LLMs do not have that at all so the analogy fails.
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.
>LLMs do not have that at all so the analogy fails.
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.
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"?
I've always said that driving a car with modern driver assist features (lane centering / adaptive cruise / 'autopilot' style self-ish driving-ish) is like riding a horse. The early ones were like riding a short sighted, narcoleptic horse. Newer ones are improving but it's still like riding a horse, in that you give it high level instructions about where to go, rather than directly energising its muscles.
This micro blog meta is fascinating. I've seen small micro blog content like this popping up on the HN home page almost daily now.
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.
"It is not possible to do the work of science without using a language that is filled with metaphors. Virtually the entire body of modern science is an attempt to explain phenomena that cannot be experienced directly by human beings, by reference to forces and processes that we can experience directly...
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.
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.
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