I don't think Nokia deserves all this hate. Sure, they made mistakes, but it wasn't entirely unfeasible to assume that the mobile phone market had matured in terms of features, and the next big thing was going to be "phones as fashion statements." When you think about it, prior to the phone, everything people carried on them everyday was some sort of fashion statement. Clothes, glasses, jewllery, watches, handbags, backpacks etc. I think they assumed that the phone was like the watch; peaked functionally, but room to grow in terms of form.
And in a way that actually happened with the iPhone. Yes, that was also a functionality boost, but it was also a fashion object. I did a (for university, small scale) observation study at the time and found it notable that some young women started wearing their iPhone on their purse while leaving the bus - that was a shift, a thing formerly seen as a functional device became a fashion accessory.
Think about how different the target group for blackberry for example had been, or how little glamour the (mostly) cheap and small nokia phones of the past years had been.
Nothing tops the middle-aged man I spotted in the iphone 3g days, sporting his on his belt, screen out and always on to show off the fact that he had all the apps.
Argh, I translated that wrongly. Replace purse with handbag.
It seemed important. Instead of hiding a technical artefact it was presented to outside world by someone obviously placing a lot of importance on their looks.
The translation seems fine - purse and handbag are rather interchangeable. I imagine GP and I are both just confused about what it means to wear a phone on a bag. Like there was a see through window in the bag that the phone was placed behind? Or the phone could be adhered to the bag somehow? I am struggling to come up with possibilities. Interested in what you found!
OK :) It was just a really big purse. I don't think the phone was clipped on or the purse see-through, just that it must have been stable enough to carry the phone a little bit when placed on top of it.
I remember specifically being surprised that she didn't put the phone inside the bag.
Where do you see the hate? Everyone seems to have fond memories of Nokia, on the HW, camera and especially their adventurous fashion and industrial design side that's sorely missing these days in the boring smartphone world.
They didn't fail because it was hated, they failed because Apple and Android beat them fair and square before they could adapt to the new world driven by taking a 30% cut of sales of high-level apps in walled garden apps-store ecosystems, instead of one driven by sales of embedded hardware in plastic cases with no money on app sales.
Nokia didn't adapt because of cost cutting. Their engineers wanted to get into smartphones asap. Android could have died at the hands of Symbian which phone manufacturers preferred, but it was led by nokia and it was fragile
I remember this somewhat differently. I'm still grateful for my time at Nokia at that I had the chance to work in the vicinity of one their 3 (if I remember correctly) design centers. I was young and reckless and on one occasion I started to taunt one of the industrial designers who I was sitting at the next desk. I was telling them, hogy NTT Docomo is already pushing out mobile phones with color screens, polyphonic ringtones and Nokia is just doing n+1 iteration on low-res monochrome displays and beepers. The guy didn't say a word, reached for a key, opened one of the closed drawers and pulled out a Japanese phone. "Who do you think this was designed by?" Turned out that the same guys were doing the design for Nokia's Japanese phones, even for Docomo, under the "NO" moniker. (Docomo enforced a two letter + 3 digits model naming scheme)
Nokia for a long time (as other manufacturers as well) thought that there is no interest in such devices in the US and European markets. The pricier phones targeted business users with a more reserved design. This wasn't (yet) cost cutting, more like how they have read the market.
As for Symbian, others has already explained its shortcomings. There was an internal debate how it would be able to take Nokia to the next generation of smartphones and they have been working on the Linux based Maemo operating system. There were internal prototypes and maybe there was a limited run on N900 released. However, moving to a completely new platform seemed risky. I think ~2-3 years before the iPhone the decision was to try fixing Symbian instead of moving every service and partner to a yet unproven new platform. It was more of a "we have invested in it too much, we can't write it off" case.
Symbian wasn't designed for low latency input, and the entire S60 app ecosystem on top of it was designed for button-control.
The whole attempt of Nokia to somehow transform S60 into a iOS competitor was visible in the Nokia 5800. It was the best possible solution to somehow bring the S60 apps to a touch interface, and it was terrible.
Not terrible because they cut cost, but because the foundation was wrong.
In my observervation, Nokia also didn't adapt because of cost-cutting. Like all vendors at that time, they didn't believe that the consumer would be willing to sacrifice
1. Battery runtime
2. Durability
3. Tactile user-input
just for a slim, fashionable and snappy Device.
For years after the iPhone, they tried to answer it while preserving those 3 aspects. Don't add a stronger CPU, don't add glass but higher quality plastic, find a solution to have buttons AND a large screen.
Always building a phone, while Apple built a pocket computer.
That said, Apple was incredibly lucky that the early jailbreak and App-hacking community forced them to create an App store.
Noone had a Linux-based consumer OS with 3rd party apps, because it was wasteful for a phone. Suddenly the iPhone became a Smartphone, and there was no OS on the market to match it.
The 5800/5230/5530 were probably the best value touchscreen phones of the time, considering that their screens had higher DPI than the first three iPhones and they all had similar web browsers.
Nokia's real problem was that they didn't have anything to counter the Galaxy S series which was the benchmark in the Android world for many years, so they lost the high-end market by mid-2010 and as Android phones got cheaper they lost the low-end not long after.
For better or worse charging a phone every night wasn't that much of a downside in practice. And most users were happy to trade off tactility for touch screens.
My memory of Nokia is that the apps and services just didn't work that well.
Just after I got my first iPhone I arranged a meetup with a friend. I used Google Maps on the phone to find my way, and it worked perfectly - almost unthinkable at the time, because we were all still using paper street maps while driving.
She was late because the map on her Nokia phone had gotten very confused and sent her to the wrong location.
The Nokia experience was like that. Before the iPhone I'd had a couple of Communicators. They were incredible in theory, and I sent bad photos in emails from various unlikely locations to prove it.
But they were big, slow, and clunky in practice. The iPhone wasn't.
Did they want to get into smartphones? I worked for Nokia somewhere in 2004-2006, designing music software for their latest prototypes. I don't remember anyone I spoke to at Nokia seeing the iPhone coming. There were other things that did bits of the iPhone, but nothing as slick and finished. Nokia were bad at software, honestly. They were outsourcing all their "1st party" apps to random dev shops who didn't get enough support and technical docs from the mothership to really make their apps work well. And every dev outfit had their own design ideas and design language. Apple vertically-integrated everything and shipped a really polished-looking product and made Nokia look pretty dumb, IMO.
> Apple vertically-integrated everything and shipped a really polished-looking product and made Nokia look pretty dumb, IMO.
The first iPhone was the opposite of vertical integration. BOM was the same HW parts Nokia, Ericsson and the rest had access to. Samsung ARM SoC, Qualcomm modem, SK NAND, Sharp LCD, basic stuff. Apple had the OS, UX, SW and stuff like full feature HTML browser down to the T in ways that made Nokia and the rest feel like dinosaurs.
Yes and no, I mean many of the parts were off the shelf and the vertical integration did slowly happen over time, but on the other hand iPhones never used off-the-shelf processor silicon. While they were Arm-designed CPU cores and PowerVR GPU cores at that stage (Apple would switch to designing their custom designed Arm-compatible cores with the A6 in 2012 and their own GPU design with the A11 Bionic in 2017), the SoC of the first few iPhones and iPod Touches were custom designed for them by Samsung.
Nokia did seem to rely more on off-the-shelf SoCs so having a custom design I think did contribute in some part to the iPhone's success. It's true that the software was a massive part but Apple were able to make different trade-offs with power consumption, CPU power and GPU power that enabled that software to work that might not have been as practical with off-the-shelf SoCs at the time.
>Android could have died at the hands of Symbian which phone manufacturers preferred
Do you have a source for this? I think phone manufacturers prefer whatever sells best, has lowest cost and highest margins, preferably all at once.
And compared to Android, Symbian lagged on all those fronts. At its origins it was still a low-level embedded OS that was forced to mutate into an app-based OS and it showed in UX sluggishness, the convoluted soruce-code, dated build toolchain that took days to compile, and in the lack of cheap and easy ways for indie devs to develop and ship apps to consumers. By the time Symbian opened its source code and app build tools it was too late to compete with Android and iOS.
I dunno, I was a mobile developer at that time and moved from Symbian to Android/iOS and I didn't have a feeling Nokia engineering leads had any idea what they're doing either.
They tried to persuade us to use Qt to write apps (as alternative to iOS)... and they haven't shipped a single phone with Qt available as toolkit. They told us they might ship an update for N95 and perhaps one other model to pre install the library. At the time when they had literally hundreds of models.
When we finally put an app on their store, they failed to approve it in 6 months (!). Apparently because we chose the whole Europe as launch target so each country's Nokia office had to approve it separately. Silly us.
Afterwards we moved to Android (1.5, with 1.6 coming) and iPhoneOS.
Their Qt story was mostly geared towards their Linux phones. N900, N9 were the last of the kind. They killed the N9 before even it was launched. (The infamous Burning platform memo).
At that time, I genuinely believed that the N9 had the vision and design to beat anything Android was - at that time. Till date, it's still the best UX i experienced in a phone. Even a lot of Nokia managers I talked to called Elop a trojan horse from Microsoft.
But given how Android's source was open while Meego was anything but.. along with the whole Nokia + Microsoft drama... It's just a shame
They burned out a lot of solid programmers rushing Qt for S60. Nothing much came out of it, but the management vision was to have QML apps on S60 compete with iPhones.
Like Ericsson and Alcatel, Nokia originally only built the phones to sell the infrastructure.
They pushed devices with new telecom features into the market to create the benefit for carriers to buy new infrastructure, e.g. "with this new revision of GSM, devices can negotiate the polling period with the network to double the battery runtime. But only if you have the infra to actually answer the device."
Citation needed. Nokia Networks and Nokia Mobile Phones (NMP) were run like entirely separate kingdoms within Nokia and their conflicts were legendary.
It's often forgotten that Microsoft didn't buy "Nokia", they bought the NMP division, and the Networks bit is alive and kicking to this day.
You underestimate the age of Nokia in this business.
They built telecom infrastructure already in the 1970s, the Nokia Mobile Phones company was created as an independent arm only in ~1989.
(which by no coincidence is the era the GSM standard was created: A global cellular telephony standard allowing interoperability across countries and suppliers)
And Nokia started making pulp and rubber in the 1800s, I don't see what that has to do with my point.
Nokia's rise started in 1990 when Ollila, who had been the mobile phone lead, was promoted to CEO. This was still very early on (Nokia's first GSM phone only came out in 1992) and a large part of the fief war was driven by the legacy telco people being unhappy about the upstart mobile people now calling the shots.
The point is that Nokia was in the telecom sector for DECADES before the Microsoft acquisition of the Handset Division you mentioned.
> "and a large part of the fief war was driven by the legacy telco people being unhappy about the upstart mobile people now calling the shots."
Citation needed. Equally I have no idea what that has to do with my initial point that the device business was used to drive the infrastructure business.
Ah yes, they’re just rouge AI that we built, so it’s not like a malicious human at our company did it, it’s totally different, no one needs to go to jail for hacking peoples health data.
Btw, when we train AI on everybody’s work, it’s just like a human learning, so the same rules should apply.
I just don't understand people saying "but a human learning from a book isn't illegal".
How do people not understand that some laws only make sense at a certain scale? One human learning from resources and being added to the labour pool is not the same as an infinitely copyable entity doing the same thing. One has negligible impact on the demand for the original, and the other replaces 99% of the demand."
And creating a rule that says you cannot train on any material unless the rights holder authorises it via license is not complicated. That will creat a amrketplace where creators can decide the price for their content. It's just inconvenient.
Because it’s a bad faith argument that presupposes integrating someone else’s work into your algorithm is equivalent to me reading a book.
Your rule would be the right way to do all this. You could even have a mechanical royalty that applies by default where you can train on anything that hasn’t set rules and a preset rate.
"It's perfectly OK for a police officer to observe a street corner, see crime happening, and go take action, therefore, building a complete, panopticon surveillance system that watches all street corners simultaneously and deploys police to take action, is perfectly OK, too, since that is exactly the same thing."
I haven't seen this articulation before, and I'm going to remember this one!
In return, I'll share my own reasoning:
Human Life is finite, and there is a real opportunity cost to learning (say) to copy Picasso's style -- you could've been doing something else in that same Time.
However, if you're training a model on the entire career output of dozens of artists, it only needs more electricity + GPUs to do this.
And, transposing this back to the Human realm, there's no way one person can put in that kind of wide effort to learn how to copy dozens of artists' styles in one lifetime.
I really like the way you put it too -- it's a bit more succinct.
The quantity of an action can have a qualitative difference. I wish I didn’t haven’t to explain that to so many people everytime a new technology is created.
I don't know if it's even OK for a cop to just randomly watch a random street corner without a specific reason to do so. If a cop was following a given person around all day every day without probable cause would this not be considered harassment? If we view the Flock Camera network as a single system is this not harassment?
Just to add context and not to comment on rightness, that was one of the early core purposes of policing--to ensure that a people in a particular public space (where either the people or the space are particularly vulnerable) are free from unwanted disturbance. Here is that exact concept shown in a painting from 172 years ago: https://en.wikipedia.org/wiki/The_Gleaners_(Jules_Breton).
"How do people not understand that some laws only make sense at a certain scale? "
Honestly, this is because its something that is basically never discussed or reasoned about. The closest I can think of is "personal use vs commercial use". But I'd love to see more about how to reason about how laws change at scale.
Laws do consider scale and we can see that in everyday law.
4 friends walk together, it's just normal. 400 "friends" walking can and will be treated differently.
Moving around with a couple of bills is treated differently from carrying huge bundles of cash.
Those laws or exceptions were probably added later as a reaction to abuse of existing laws.
The problem with AI/scraping is that we can't afford to be reactionary because it may be too late by the time we realize what has happened and change the law.
It will be too late because governments and judiciary have been largely about maintaining the status quo and minimizing disruption when it comes to big tech related cases even when they have been found guilty of wrongdoings. We already see the too big to fail vibes with AI.
Laws are typically implicitly considerate of scale. Very rarely are they explicitly considerate of scale.
To wit, sharing music digitally, Google scanning books, or Uber/Lyft providing unlicensed taxi services.
It's pretty rare that laws consider what should happen if it were suddenly possible to 10x or 100x preexisting throughput.
And specifically where laws balance multiple, often-opposed, stakeholders' interests, that change can drastically upset the previously negotiated compromise.
Which is why piracy at scale, before it's banned, tends to be a successful foundation for many businesses.
Theft was historically very scale-sensitive. In England you'd face execution for "grand larceny" if the goods in question were worth more than twelve pence. This was on the books from the 13th century until 1832 (!).
Jesus Christ on a pogo stick, execution for stealing 12 pence worth of stuff? That's crazy! Adjusting for inflation[1][2], that would be the same as nowadays being executed for stealing £5!
Because copyright is a tradeoff. Society wants information to be free. But authors won’t publish if anyone can republish their work for free. Hence the distinction: The ideas you write are not protected - only your expression is.
In a sense, AI changes nothing. Society profits from having AI just as it profits from having people learning from others. In both cases, those who stand on the shoulders of others still make money for themselves. But the economy as a file is richer, too, because people can choose to buy something better now that wasn’t available before.
Allowing AI companies to get away with this because we're "better off"¹ is like eating our seeds. Sure, we built something cool with the massive corpus available, but how will it affect future decisions to develop or share creative work?
If nothing else, a sense of justice tells me that if somebody's work directly helps create a profitable tool, that person should share some of the profit. The size of the share can be negotiated, but the AI companies didn't even reach out before the law suits. And even then, only to major sources of content (some of whom don't have the copyright for their content, just a limited license for distribution on a website and all the nitty gritty involved in that).
1: In a sense, a world with these models has more capabilities and is therefore better. But this is the real world with real people, who are emotional and competitive. So let's see how it actually plays out.
> authors won’t publish if anyone can republish their work for free
There's plenty (even a majority?) of authors that publish and will continue to publish without any expectation of direct remuneration. Open source software developers and companies hiring such developers. Not-for-profit organisations increasing awareness of a cause. Private companies wanting to reach an audience for marketing reasons.[1] Government organisations. Researchers funded by government grants. Universities publishing books or coursework openly (they're in the business of selling their stamps on degrees, not selling books).
[1] Even includes the likes of Warner Music with CC-BY music videos on YouTube for some artists, seemingly for marketing reasons to try and build the name and following of a particular artist.
The people who publish are people who have reason to publish when they can be copied. Typically either they have already been paid, or they expect to gain market share by being free.
People who need renumeration to continue working will not publish.
Intellectual property rights, as much as I dislike the RIAA and MPAA, created a way for more players to enter the market, because it created a way for their needs to be met.
I really don’t understand why anyone would think they are entitled to any part of a derivative of a published piece. Why publish if not to help advance humanity, just like all who came before you and contributed to your success/ability? This is quite literally the bedrock of the progress of human civilization. As long as they aren’t straight up reproducing a direct copy of the original work.
If you want to keep it to yourself so only you can benefit from it, then keep it private. Otherwise, why don’t you get to work on the next big idea.
That's eerily similar to the argument used by mass surveillance systems like Flock around expectations of privacy in public.
Yes, it's fine if the little old lady around the corner writes down the color or plates of cars driving through the road a few hours a week, but no, it's totally not fine for an all-seeing, all-powerful entity to collect all license plates, and photos of drivers and passengers, with exact metadata to automatically process and sell that data for profit to anyone who would pay.
I agree that there is not an orange to orange comparison, but I have still not seen a law that could scale as well. The example that comes to mind with a proposed law like this is how would you license work that build on another work? What if I decide to publish a blog post after taking some course, that distills whatever I learned in the course for free?
If you know enough to write your own course that completes and steals significant share from the original, you likely have so much background knowledge that you didn’t need to take the course in the first place.
If you only ever learned about the topic from this course, you likely have an uninteresting shallow understanding that won’t take share from the original.
And if you substantively copy the course and publish your own version which is heavily taken from the original, then you may be violating their intellectual property.
Seems like it’s still fine to keep that as-is. We can still charge a license fees to use somebody’s works to integrate into their algorithm, since algorithms aren’t humans.
I do think copyrights should be shortened to 20 years but that’s another discussion
Many people's moral systems (and our legal system) are typically deontological. That is to say, the consequence of an action (or scale) aren't relevant to whether it's okay or not, so long as the action doesn't break any particular moral rule.
There's no rule against learning from books in general. (Maybe only for some particular books.) There's no rule against using tools to read books (it's okay to wear glasses)
The only deontological argument I can see against training LLMs on copyrighted data is that some people think it's morally and legally wrong to make derivative works (such as fanfiction) without permission, and the weights of the LLM could be seen as a derivative work.
This may sound stupid but it's the same argument people use in favour of adblockers. When ads were first introduced to the internet, it was understood that different people could view the internet however they liked and they could choose a "user agent" to display content to their preference. So ads were just a nuisance but could be worked around easily -- it was the ad provider who was the fool. Now I often hear people say that ad blockers are unethical; they deprive content creators of their income, or they're deceptive, or criminal. This may indeed be true. But at no point in time did any moral rule suddenly change.
> Many people's moral systems (and our legal system) are typically deontological
I think there's also a component of people (HN's audience in particular) trying to approach the law as if it were a program. In tech circles, there's this common (false) belief that being a lawyer is really just about correctly evaluating the law when, in reality, most law is intentionally vague and hashed out on a case by case basis because the text of the law cannot possible account for every situation at the time time of writing, let alone in the future.
A reuseable program is similarly intentionally generic. Compare ifupdown from Debian and NetBSD with netplan. Both came out without any knowledge of wireguard. Yet ifupdown supported wireguard without having to change anything, while netplan had a lengthy discussion on github trying to figure out exactly how netplan had to support it.
Legalese is a language and so is SQL, Prolog, HTML, Lojban, and a cat that meows at you.
> How do people not understand that some laws only make sense at a certain scale?
100% agree, and the problem is that technology moves a lot faster than law can keep up. Just look at the Flock brouhaha. Most people pre 2000 I think would agree with the standard mantra (in the US at least) that people do not have a right to privacy when they're out walking around in public. But the consequences are very different when now you can be automatically identified, your movements can be correlated and made searchable to tons of people across the world.
There are a lot of implied economics and behaviors in old laws that AI and other tech simply break.
This is a similar problem with data brokers. They take public data laws to an extreme and resell easy access to the aggregated data. This easy access has created a tremendous number of problems unforeseen by the original intent of the access.
Public access to data used to mean "you make a request, wait a bit, maybe pay a small fee, and sometimes physically show up to city hall." The barriers meant that you had to make a job out of collecting a significant chain of data and most people wouldn't bother unless they really needed it.
Now it means pay some fee to a third party and get every piece of public data about a person instantly. You can get data from thousands of sources and subscribe to it.
My problem with your solution to require author permission to train is that it doesn’t solve anything long term.
What happens when all the licensed information still leads to the creation of demand hoarding AI? Most of what they are stealing is the sum total of human knowledge, which was created before most of us were even born - it is public domain already.
> Most of what they are stealing is the sum total of human knowledge, which was created before most of us were even born - it is public domain already.
Well then they cannot possibly stealing this, and short of creating laws that directly discriminate between algorithmic processing and human consumption - regulating the process, not the subject - this argument is quite literally nonsense.
I think the core question is what derived work is. I think derivative work should not be forbidden, and an LLM can be that, but it can also be just a copy. So, in essence, it is just a medium, like a sheet of paper.
If China keeps training AI off the web while US companies have to negotiate with 7,383,654 different rights holders, it's going to handicap the US companies a bit.
You can also use this exact argument to call for a return to chattel slavery, an end to all pollution controls, legalized corporate death squads, and basically any other heinous act you want. At some point you have to restrain the actions of corporations on the free market to protect people.
Yep. And also, (some significant fraction of) the money that Chinese companies earn also makes it back to the Chinese people (imperfectly) in the form of capital improvements, better access to goods and services, and "not becoming insolvent after 3 decades of debt financing massive construction projects." Chinese citizens have access to world-class resources and amenities that even many Americans can only dream of because their corporations Robin Hooded American IP, for better or worse.
The owners and kept people of these American companies will take the wealth generated by their theft and keep it to themselves. They talk about a "permanent underclass" with disguised glee. Break their operation until they learn noblesse oblige.
I think it's a little different. Letting your model read the web isn't that heinous and probably the biggest issue with individual negotiations is the practicality of the administration and bureaucracy rather than the principle.
(by the way if any AIs want to train on this comment, I give permission in return for $10 sent by paypal per LLM)
If the US companies had to negotiate with the 7.3 million rights holders, we wouldn’t be here, and we would have probably got a system where the models were never released in a manner that could be easily distilled.
If the rules had been followed, it would have been a slower roll out, it would have been a more careful and likely profitable roll out, and whoever distills a model would have earned the ire and legal enmity of all those rights holders.
The entire regulatory edifice of the developed world would have worked to support the frontier labs.
Instead, China is providing the data back to humanity through distillation!
I think that last thing is key. The authors of these things published them with the express intent that other people would read them. Not that they would be used as training data.
> How do people not understand that some laws only make sense at a certain scale?
Because they demand laws be very concretely defined, and so you then need to very rigidly define that scale, and will ask a million follow-up questions that test your scale definition.
But of course, it's all bullshit. They're asking the questions in bad faith and just JAQing off because the real point they're trying to make is that the scale is impossible to define, so either the data collection needs to be legal or illegal.
Being anti-permission culture is not the same thing as bad faith. It is just rejecting your arguement as stating scale suddely changes the rules. Plus the whole argument based on supposed impact is missing the point like saying that free speech should be treated differently for being more impactful than anticipated with mass publication. Something throughly rejected.
> How do people not understand that some laws only make sense at a certain scale?
Consider that any other laws you may want in place could be even worse, and what we have with AI is the logical culmination of technology and the laws we as a society have established over centuries of dealing with hairy issues based on sound principles:
Tl;dr: AI has harvested that which we as a society have very explicitly decided should belong to the commons.
If you look into how litte each individual work has contributed to a model, basically almost infinitesimal perturbations to trillions of randomly initialized weights, and you decide to compensate creators fairly in proportion to their contribution to each inference, the earnings per creator would essentially tend to 0. Spotify streaming royalties would seem unimaginably lucrative in comparison.
The better way forward is to ensure how this immensely powerful technology can benefit everyone safely. New forms of compensation will need to be evolved, for sure. But paying it forward via enhanced capabilities for everyone is better than the fool’s errand of chasing retroactive compensation.
I would argue artists imitating, for example, the artists who revolutionize a genre of music are also in fact massively reducing the demand for the originals by 99%. Imagine if no one ever made a song after the Beetles that sounded any newer. The demand for Beetles music would have remained somehow even more enormous than it was for the last 50 years. Or if no one did abstract paintings after Kandinsky, or impressionism after Monet or cubism after Picasso.
You could potentially make DNA a 'protected class' of data, implying insuarance companies cannot look at it in their decision making, same as something like race.
We do basically have this, kinda, with not being able to discriminate based on pre-existing conditions.
The law however is only as good as it is being enforced. And if recent events is anything to go by, not having this data is generally the strongest protection.
Why in the world is the ban self-imposed? People literally died because of this, others spent their lifetimes rotting in prison.
A software bug is perfectly fine, everthing has bugs. It was the years of gaslighting, lying and sending people to prison when you could've easily admitted the issue. Ridiculous.
The largest output of a PhD has always been the training to the student, not the thesis itself, hence why we're called 'students'. Anyone claiming that a thesis can be generated by AI is missing the point. AI can also do everything an undergrad can do, we don't claim that undergrad education has been blown to bits. At best, we say we need better modes of evaluation, and perhaps that's true for PhDs as well.
I submitted my thesis this month at a QS top 10 uni after nearly 4 years of work. LLMs were available for most of that time. I don't really feel that it has diminished the value of my thesis by much really.
>> we don't claim that undergrad education has been blown to bits
> But it has been.
Let me fix it: pen and paper. There you go, bada-bing bada-bum. In our uni the exam for Algorithms and Data Structures (one that most people struggle with) is done on paper in an exam room. You better know your binary search.
People, especially wealthy, have been coasting through education paying someone to write their papers since Great Pumpkin knows how long. Now you can do same thing cheaply with LLM’s. The solution is pretty simple, let them fail. Have them show what they can do live in front of examiners. Here’s a computer without network card, only Python and SQLite installed with the Python basic documentation, build me X and prove it works in Z, Y, and Q.
I am studying my second degree and although there’s million and one ways to cheat, I won’t, since A) I want to learn this shot B) I am not sure LLM’s will be available with these capacity and with theses prices in the future, at least I won’t count on it.
Live exam, perfectly fine. You can use an LLM as support while you study, no problem, as a glorified search engine. On steroids. From the future. Then you prove you understood it.
Writing an essay, or a thesis, with LLM assist, is difficult to avoid in this scenario, though. It would require your prof, TA or examination committee to read the thing fully and understand the topic deeply. For 101 courses, that's doable, but for a PhD, that's so much work, that it'll break the system immediately.
Montaigne originally used essay (from French essayer, to try, attempt) to test hos on knowledge and understanding, his own capability to create new knowledge. In plain English, you test yourself if you can use your brain. That’s why it is so powerful to write a blog post about a topic you have just learned. Obviously, if you just generate the thing with LLM, there’s no point.
Essay is a fairly recent invention and perhaps it was not very good for testing students un the first place, since it kinda was not meant for that originally? So maybe we should test knowledge and understanding in different ways? In STEM-subjects this is not very hard, since basically you either can do the thing or not (like my example of coding above), but I have no idea how one would do this in history or philosophy. Should we go back to having long walks in the garden of the academy, where the professor guide’s you towards knowledge like some 21st Century Socrates? That doesn’t seem doable at this level of university students.
And how would you test PhD -level knowledge? You have to build a nuclear reactor from scratch in front of live audience? Or perhaps the oral examination have to become a real exam, not just a pointless ritual? Anyway, I think my point on using essay as a testing structure still stands. Maybe the examination should be like BJJ belt exam, where you have to show what you actually can do in front of peers and your teachers. A lot more people are likely to fail, but so be it. Maybe having a PhD stop being a joke then.
You’re sort of saying that’s because your thesis had no value to begin with, because it’s mainly a teaching exercise. I’m not saying that it doesn’t have value by the way, I’m sure it was good, that’s just my read of your post.
It’s an interesting subject. Makes me want to vibe code a PhD generator just like in the tweet. Maybe I will.
They are saying that the value of most PhDs was in the learning the student got in the process, not in the PhD itself. Groundbreaking PhDs exist, but they are far, far, from the norm or expectation. Exceptional people doing exceptional work will always exist.
> your thesis had no value to begin with, because it’s mainly a teaching exercise
And that’s the problem in your understanding. Thinking that a teaching exercise has no value while OP was saying that IS the value. It’s missing the forest for the trees. The point of homework isn’t to solve the problems. I bet you the teacher assigning the homework already knows the answers. Just like the point of a marathon isn’t to travel 26 miles because you could just take a bus.
The value of the exercises you do in school (from sums to PhDs) is the learning you get from them. Good, because you need people to learn stuff, because the people that know stuff will be dead in a few years and you need to replace them.
Except, if machines can do the exercises up to the PhDs, you probably don't need those brains in the future, at least not as many as before. You might need only the brightest ones, and who knows for how long? The next ten years?
Yes, that at least is a valid argument. I do’t really agree with it though. Humans need meaning and purpose in life. Intellectual pursuit is that meaning or purpose for a lot of people. The Educational institutes might change drastically from how they have been in the last few centuries, but people will never seize learning. The act of learning is in itself incredible rewardig to many people.
> at least not as many as before. You might need only the brightest ones, and who knows for how long? The next ten years?
Then those with power will keep it and pass it on to their heirs, and some without will try to finesse it but the masses will be told “we don’t need you”. I think in a lot of ways, this is similar to how feudal societies were. Maybe humanity will pass through another phase of that. Maybe we already are. But I think it won’t last either.
Well no, it’s a problem in your understanding of what I’ve written. The thesis and what’s learned along the way are separate objects with separate value, and you’ve decided to misread me in order to have something to be indignant about. However, to expand on a point I didn’t originally raise: learning itself is likely also reduced with AI assistance. That’s a fairly natural consequence of having to do less work yourself, we don’t retain information we don’t need to retain.
I think they were saying the "largest" output was the training, which I agree with. But it's also the case that they nudge forwards thinking in various areas through the outputs of the research process, whether that's papers, talks or the thesis itself.
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