Reminds me of a display at Chabot in the bay area. A bubbling volcano covered by a stable mass stays bubbling underneath, but shaking up the mass gives little bubbles a bath up and they break way for the big bubbles leading to a volcanic eruption. If you fragment a he soil at some point in the mantle of earth and there is pressure anywhere below, you could get yourself a new volcano.
You are a photographer from the olden age. Taking a photo back then took forever. You are standing on a hill trying to get the perfect picture of a sunset. You measure and sort and calculate angles and light. A tourist stands next to you with an high-speed iphone auto-settings camera. They spin around and get thousands of photos from different angles while you are thinking and measuring your one shot. That’s what AI does. It gives you many shots at the same problem. The thinking guy with the one approach will likely lose a photo competition to one of the accidentally better shots of the person who tried a lot more. Make and filter now may be a better approach than overthink and try only once.
I don't buy this analogy and I think it takes a depressingly reductive view of creativity. In both cases, the photographers had to take the time to go to a place, see a view they thought was worth capturing, operated their equipment to get a shot, and then had enough discernment to recognize which of their final products were worth something. Both the traditional photographer and the modern photographer can create images of value in different ways.
If you want to shoehorn AI into this analogy at all then no one is even bothering going hiking at this point, let alone seeing anything worth capturing. It would just vomit up endless permutations of statistically average images that look like the kind of pictures people take of landscapes.
However, for writing software with AI the analogy still works. Just as the photographer needs to pick a shot worth capturing, you have to figure out software worth building. That often also involves some leg work: you need to understand the problem and user needs. Then you need discernment to figure out where the software works well, and which parts need improvements
Well yeah and then you can be liberated by the fact that maybe getting to the landscape and experiencing it and not taking the photo was the goal all along.
You can be creative and take the photo for your sake but at the same time accept that you can generate 1000s of them and many of the generated ones will be more liked by the general public than your creative one.
There used to be no such thing as a woodworker. It used to be a number of different professions, such as the jointer, the cabinet maker, the planer, etc. now with modern tools it’s merged into one job
In the past few could afford to be photographers due to time and money. Many were not the most artistic or talented minds in the universe on the subject (you can’t find those until you give everyone a camera) but just people who enjoyed it and could make money off of it. Those who gained experience with the old tech were essentially AI models trained on statistically good probabilities of getting good shot. You had smaller selection and the model / brain quality determined what % of
the best that photo was between 0 and 100% for any sunset. In modern days more people get a camera - more people with bad taste and more people with good taste. You also get more attempts at the shot - more photos taken, more tries. More tries means you are now preserving more of that moment from more angles and extending the time your taste people have to pick the best shot of all possible.
Your plethora of statistically average photos happen if you don’t have anyone filtering the ginormously increased output. If the problem is really valuable, someone will filter it. Possibly a model.
The real filter is value, not capability anymore. Do you have the empathy and taste to know what matters? The AI tokens/cost lets everyone make and become interested in making of someone hasn’t solved their problem. And then if search isn’t improved - everyone will just repeat the making of the same thing over and over. So if you don’t want repeated slop. fix search.
Or do you copy everything and everyone into making more of nothing.
Once upon a time, in Switzerland, there was a "chronometry contest" putting the best watchmakers of Switzerland against each other to make the most accurate mechanical watch and have it certified by the observatory of Neuchâtel (observatories were at the time the entities in charge of giving the most accurate time, based on reference star observations).
It worked for a time, and manufactures employed experienced, legendary even, watchmakers and specialized "watch setters" to create and tune to the best possible extent a few experimental watch movements. They would be sold as collection pieces, the firm would gain boasting rights in its advertising, and the experience informed the design and tuning of more mainline movements.
By the end of the history of (the revival* of) this concours, the winner was always Tissot, a second-rate company. What hides behind Tissot is ETA, a huge watch movement manufacturer for all of the Swatch group (dozens of brands, from Omega to the worst no-name stuff you can find).
What they were doing to win was just to pick the best watch movements out of the millions of basic, bland, uninteresting "workhorse" ones they were producing each year. Just by chance, there was always one combination of the hundreds of components, each with their manufacturing tolerances and variations, that would fit all together to make an exceptionally accurate movement.
In the end, yes, Tissot won repeatedly. But the concours is dead. And Tissot is still a second-rate brand making second rate watches. Nobody is interested by their watch movements, no collector, no historian, no customer.
The credulous LLM users Dan Luu is complaining about don't take the equivalent of thousands of photos of the same sunset. They take a couple photos at most, say "LGTM", and move on to taking a photo of something else, even if their couple of photos of the sunset aren't great.
As someone who will often compare different things, I think doing that usually takes time. I think LLMs can help reduce the time (especially if it's programming, not necessarily so much in other areas), but I'm not seeing many people use LLMs to try a large number of independent approaches and compare them.
The tourist has another advantage over your photographer: experience. They have thousands of photographs to look at and thus get a better scene of what makes things good. That is if you took both to the same spot and gave them one photograph (the phone's memory is almost full) the tourist is likely to get the better shot because they have a better idea of when to pull the trigger having seen all the possibilities.
I am sure the tourist can take hundreds or thousands of photos, and have every single one of them turn out wrong.
It's not as if he was covering every combination possible of exposition, composition, depth of field, shutter speed etc. The tourist doesn't even know the existence of those settings.
I mean there are some obvious examples of a photo just being all black or all white. There are things so blurry that you can't identify the subject matter. But in between these extremes exist matters of preference and taste and everything goes subjective as hell. There are very few rights and wrongs here.
> someone clueless about photography just shooting hundreds of photos?
That doesn't exist. The very act of taking hundreds of photos will give anybody a clue. They won't be able to pass a written test - they will have no clue what terms like "depth of field" mean - but they will start to apply the concepts in their photos without knowing the terms.
I suppose there is someone who takes hundreds of photos without ever looking at them and thus never starts to develop any sense of what is good. Likewise some people just have more taste than others and so will get better. However in the real world people are taking lots of photos and they are on the way becoming reasonably good.
Training alone will not make you a good photographer. Someone already skilled at this can help you look at your photos and understand why it "looks bad". However it takes hundreds - perhaps thousands of photos before you become an award winning photographer in the best case. While someone without training will need thousands of even tens of thousands - but these days a photo on an iphone is cheap enough that getting a thousand photos is not hard.
What is more interesting to me, the most beautiful photo of a sunset taken by an iPhone ever, or a mundane quality photo of my daughter taking her first steps?
I really don't think so. A pro that knows all the ins and outs of working their camera for the perfect shot in the given conditions will do better than a one-off hope that the camera auto settings nail it. A professional literally spends their life framing shots, a tourist spams the shutter hoping one turns out and crops/filters/AI enhances their way from the best of the bunch to whatever will get likes from their family. No contest for a single exposure: the pro knows what they're doing, the tourist doesn't.
Really? The one who canonically doesn't consider lighting, depth of field, composition, etc... I can only speak from my own experience, but on average a typical person who doesn't consider themselves a photographer isn't going through the old photos on their phone and analyzing the quality and technique for future endeavors. They just want to send a fun picture to their friends and family. Nothing wrong with that, but it won't cultivate skill or lead to award-winning photography.
They don't think of those terms. However they generally are looking at their photos and so get a sense of what "looks nice" - which is what those terms are all getting at.
Now if you know and analyze your photos in those terms you can get good faster. There is no shortcut to the value of quantity.
What we have never done here is define how much effort the "professional" has put into getting better. I've known a lot over the years that know the terms and have the "best" equipment, but they just take a measurement and put it into the tools without understanding the whole and so take really bad pictures. They consider composition as a checklist - which works okay (only okay) in a studio when it means put the chair here - but they can't handle a sunset where they can't control the scene.
Award winning photography means get those details perfect. If you have the details right a phone is often more than good enough to take the right shot - and if it can take more photos faster than is worth a lot more than the best equipment limited to one shot (or a few) and hope that you get hit the shutter at the right moment. If you can get the right moment the better equipment is better, but that is one of the least important parts of the shot.
> The thinking guy with the one approach will likely lose a photo competition to one of the accidentally better shots of the person who tried a lot more.
If that were the case then photo competitions would have been upended by now by tourists who accidentally took masterpieces with their phones.
I can take as many thousands of pictures as I want but, without taking the time to critically review them to see what works and what doesn't, I will rarely produce a prize-worthy picture. And then there's the risk that I'll discard it anyway because I don't have the eye to separate the prize-winning picture from the Instagram shot all my contacts are publishing.
And how do you get a person able to nail "that one shot" when the moment is fleeting? Your "tourist" is unable to do it, because he never put any deliberate practice in photography.
Incidentally, analog film photography is having a huge revival, and Instax is still Fujifilm's best seller. Maybe there is something missing from "I did an award-winning photo but I have have no clue how, lol".
Is there anybody here who wants to have their portrait taken by the "tourist"? Is there anyone here who would prompt an AI to generate their portrait, apart from Ghibli-style remixes (which are funny five minutes, and stale a month later)?
Have even more fun with the instax UP!™ app.
With the introduction of AI, you can now scan an instax™ photo regardless of the background or angle, or even in your hand.
Incidentally, the memory price increase is going to hit hard the "hybrid" cameras - the ones who take a digital picture and then print it out. So the pure analog one may increase its predominance over the "hybrid" one.
Well now the phones actually take a video over a period of time so you can pick the best shot.
But a better analogy is how we hired a guy to take photos of us in front of the Eiffel tower on Christmas day. He came with a DSLR, directed the different poses, then sent us the photos later that day. Whole thing took less than 20 minutes.
It's the fact that the floor has been lowered so substantially.
Of course every modernized, automated craft ends up having its hobbyist revival. Whether it's analog photography, hand tool woodworking, knitting, assembly programming, or whatever. And that's lovely, but it doesn't mean much for economic trends.
I think this analogy works with respect to stuff like coding, engineering, etc, where the AI is capable of validating the success of its own efforts and where the result just has to "work", regardless of its elegance or aesthetic quality.
I also think the analogy works if we're talking about average photographs, or even very good photographs, that are conventionally well-composed, balanced, etc, but lack the special spark that we associate with true art.
But if the photographer on the hill is a real artist, it's hard for me to imagine a current frontier LLM winning the contest. I suppose it may stumble upon a winning photo sooner than a roomful of monkeys would, but I believe the number of attempts would still be so vast that it would be more efficient for the human to make one single attempt at taking a photo, rather than dealing with prompts and sorting through the millions of AI-generated options.
EDIT: I also think it's very easy to underestimate the size of the nearly limitless set of possible "solutions" to the photograph, and also easy to overlook the constant feedback loop in the artist's mind as he considers each option and looks through the viewfinder, while the LLM is shooting blind the entire time.
That's an interesting analogy, because there's still a spectrum. Photography's big advancement was the move to digital. Prior to that, you had to know what an F stop is, different developer chemicals, manual focus. These days, yes, an iPhone is actually quite good at taking pictures. Apple invested billions for that to happen, it wasn't an accident. SLR cameras are still there though, you still have wedding photographers. You don't have the mall photographer for once a year photoshoots so much anymore, however. Everyone just takes pictures everywhere as they need. Software is the same now. I need a program to do a thing, I'll just have AI whip one up instead of looking for software that does something that but has 100 more features I don't need. Gone are the days where customers would come to the mall to get photos done and buy software. (Though that world's been gone for a while.) Software is now only a means to an end, so better find the customers that have needs and embed with them instead of having them look for Photoshop.
Even in the late 19th century "bracketing" was already a photographic technique where a photographer would take several shots of the same subject from various angles and with various settings. Digital cameras may make this faster and cheaper, but the one who employs thoughtful practices in their photography is far more likely to win that competition than the one who just (to paraphrase your example) spins to win.
Maybe so, but for the good shots by the thinking guy, I suspect he would derive longer term emotional gratification from how well they came out. Effort and investment adds to the experience.
Making things easy is good as long as it is not too easy, then it's Spotify muzak.
Except it sometimes shows you a photo of something completely different than what you're looking at for or alters the landscape to "improve" it. Maybe that's not a good analogy.
Who is this "we're" you're talking about, because I see shitloads of powerseeking people that would build a god in a heartbeat if they could stand on its right-hand side.
This ignores the reality that many people are, unfortunately, taking that one iPhone picture, sending it to everyone in their contacts list as if it’s art, and then moving on to the next slop shoot.
Are we considering what is the shelf life of information?
If you build a building, the expense on materials determines longevity. If you build a city. The robustness of government and the economy in it determines the property taxes and value of property over time.
If you make or cook food. The majority of the nutritional value of it goes to the initial consumption. Once the food has stayed out without refrigeration it is taken over by bacteria and fungi. Refrigeration seems to be paywalls. Once the information is out it accumulates at exponential rates - the amount of text on the internet does not diminish but increases. Some people may “prune” old content away, but that is rare. Human attention is somewhat a fixed number. Thus text left out is not consumed, but sits idle and decays in accuracy and value over time. The fresh content of valuable should be in a fridge. If not valuable it is released - thus scavengers and those hungry and motivated to dig can consume it. If spammy and sales-y / propaganda-y which a lot of content farms are doing, the goal is for it to be consumed by the masses and push the zeitgeist to buy its premise. That’s Sugar or addictive shelf-stable junk foods. AI model companies are the bacteria / fungus/cockroaches/rats of the information dumpster. They sneak out any remaining energy from content that would otherwise be buried by other content and try to give it a second shelf life - one reachable and accessible and consumable by humans. They make alcohol. Alcohol is addictive. Ir may mess with your brain - it may make you lazy. It will sneak in bad decisions because it lowers your judgement. It is repurposed food, not the one you are used to injesting. It may even have its own agenda - depending on how the information is reprocessed. And it also has a shelf life since humanity continues to have new insights and people keep getting new alcohol brands to try.
“A government audit of family registries in Japan in 2010 uncovered more than 230,000 people listed as being aged 100 or older who were unaccounted for, some having died decades previously.
The miscounting was attributed to patchy record-keeping and suspicions that some families may have tried to hide the deaths of elderly relatives in order to claim their pensions“ Thus they need to redo the audit in 2026.
I head similar stories. Also from Italy. Another aspect is that many 100+ year old have questionable birth certificates, as in the record of the birthday might be guessed. Different times back then.
That’s all true, but if you walk around “old people neighbourhoods” even within Tokyo, you’ll realize there are A LOT OF old people. Maybe it’s much more urbanized, and older people are more likely to still go out for groceries and stuff here. But even on the ground it feels like “yeah story tracks”.
Of course the Japanese government hasn't been sitting idle for 16 years.
https://www.demographic-research.org/articles/volume/26/11
"In Japan 234,354 people registered before 1910 remained on the family registers in 2010, without being crossed out. They would have been 100 years old at least and represent 0.5% of the births recorded between 1872 and 1910. The impact of this group on life expectancy statistics, however, is effectively nil. "
I was also thinking about that, but that miscounting story is so old, notable, and well-known by now, that it's basically popular knowledge around the world. So I hope that the BBC, but especially also the Japanese government that the BBC was reporting on, are aware of that issue and have, by now, accounted for it.
Unlikely, as the quote about >230k misattributed people comes from the article itself. So even without taking into account that I generally expect more from the BBC, the author of this article seems to be at least aware of the fact.
Be it as it may, and even if that's an AI-generated article (which I don't think so), the point is that the article is reporting on the Japanese government:
Japanese authorities have called the trend an "existential crisis" with Prime Minister Sanae Takichi describing the decline as a "quiet emergency".
And my hope that they have taken that past mistake into account seems to have some ground, given that the 100k total number that the current figures cite is by itself well below the then-figure of 230k misattributions.
Looks useful, but the Mac download shows "“Capsule” is damaged and can’t be opened. You should eject the disk image." and then you realize it could be ripe for malicious payloads as well.
Preparing https://www.dreamlist.com for the holidays. It's a private wish list and registry site that enables you to also group lists of friends and family into one page to share with grandparents or social media. So you can run family holiday giving + gift drives / toy drives / disaster recovery with no ads or spam or any other badness.
When I first launched it was the only wish list that didn't list your name and registry on search engines. It is has grown a lot since then, and added a lot more privacy features, and the best marketing has always been doing right by users (extremely rare these days). You can see by looking up any name + the name of a wishlist/registry site and see what shows up to check at any time.
I'm working on more products following the same rule - serve users as you would your own family.
When a person spends time with other people, they outsource some of their thinking organically. That’s the efficiency gain in teams. Marriage leads to couples becoming two halves of a shared brain - one person takes on some cognitive load (finances, kids education, etc), while the other takes on another (maybe house issues, taxes, you name it). The load that can be carried with one brain is limited, so merging with others and outsourcing to others feels organic to the brain. LLM create the impression they have the cognitive ability to carry the load, but they don’t have the consistency of memory. You gladly assume you can finally get rid of a task and the model you trusted it to gets swapped under the curtain, or doesn’t train and improve on the task you outsourced, or the inference provider just quantizes it stupid. In the mean time you’ve lost your skill and your task has failed. Yes they feel good on some tasks some of the time, but still very much variably good (even same models different days of week or times of day). That’s closer to gambling and variable rewards than a spouse.
So if your code is spaghetti and that makes it impossible to add new features (happens easy, especially if you let an LLM loose on it), the refactoring to fix it would never happen and the engineers who stay or are willing to be hired will just be those clueless enough not to know they won’t be able to achieve anything.
That certainly happens. On the other hand, engineers are typically way too eager to claim a spaghetti code. We need to rewrite the whole thing. After long experience, I've concluded most cases of people complaining that something needs to be written because of spaghetti code are really just somebody other than me wrote it and I disagree with some design decisions without understanding why those decisions were made in the first place and I think I can do better. I was involved with the very large rewrite some years ago. The code is now in production for 10 years, and so we call it successful. On the other hand, most of what we learned along the way of doing the rewrite was why the original code was designed that way in the first place, and so a lot of design decisions that we thought we were going to be able to rethink were designed that way for good reason in the first place. Even the places where we did make a big improvement because of what we still believe was a bad design decision in the first place. Not only could we have refactored in place to the new design but also the new design I can now say in hindsight was also a terrible idea. We're now trying to figure how to refactor in place to a third option which only time will tell if this is a good idea but we know for a fact two different ways to design this part that are not a good idea.
I'm skeptical of your claim that an LLM is really going to add more Spaghetti for Code. Now, certainly, especially the LLMs of last year did a terrible job of designing code. However, they have gotten much better just in the course of one year. But even at that, most of the problem, I think, is you are not taking the time to understand what the LLM is doing in the first place. An LLM is by definition code that was not written by you and therefore it is a lot of boring and tedious effort to understand it. However, if you take the time to actually read the code, it often is perfectly understandable and just as good as code any other human right. But that other human is also not you and so if another human wrote it you would also call it spaghetti code.
Good part of LMS is they are very good at refactoring code. Whether they wrote it or a human wrote it, they can do a lot of changes for you that would be tedious or take a long time to do by hand.
Part 1: Everything was turned into social User Generated Content to reduce editorial costs. Part 2: Predatory third parties ranging from nation states to SEO agencies started mass filling UGC with anxiety inducing brain rot. Part 3: the brainrot generation is automated by AI and it silences any real people or voices. Part 4: People go outside to touch grass and Part 5: That leaves opportunities for platforms for real people with good culture
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