Maybe eventually, it has to do with market share and if the service is a “core platform”. Signal doesn’t have enough market share to warrant it yet, even iMessage wasn’t forced to since it’s not that popular in EU. The law was mainly targeted at WhatsApp as that’s THE messenger in the EU.
I get paying a decent wage but why ban tipping. Here in California there is no tipped wage difference and min wage is pretty high but I still tip whenever I get the chance because I earn a lot more than service workers and that $5 is worth more to them than me. I also appreciate that it goes directly to the workers instead of through the boss who will take god knows off the top. It should definitely not be required and discrete enough so that those who don’t can’t be shamed but banning it just hurts workers.
I think you misunderstand what apples value proposition is, at least nowadays. The app store and not being able to use other app stores is not a reason people get iPhones. Maybe back when app stores were first created and the threat of malware was greater people might have considered it but nowadays no one cares. Even the idea of a unified ecosystem isn’t as much a selling point any more because Google and Samsung offer similar seamless integrations with their accessories. You can see this in their marketing, they aren’t focused on how all the apple products work together easily any more. In their marketing you can see what they think their value proposition is, and what was their big Superbowl ad this year, longer battery life …
Apple at this point knows it doesn’t have much of a value proposition for switching from android. So the only way they’re gonna sell new phones is to get the kids who don’t have a phone and convince the people who do have an iPhone to get a new one.
They convince the kids through their tried and true aesthetics and lifestyle marketing, this is about half there marketing these days. This along with iMessage in the U.S. and the general fear of being in the out group and obsession with brands that younger people have moved them towards iPhones.
They convince the current users with incremental upgrades, eg. Better battery life, better camera; and maintaining the walled garden and keeping exit costs high so they don’t turn to androids for those incremental updates.
All this is to say that apple having a single app store isn’t a sign of consumer sentiment, but a sign of apples desire to milk as much profits out of their current users as they can. Other app stores can only benefit the consumers, either they do get them for lower fees or don’t because they put some value on the “ecosystem”. From a company’s perspective yes your right that they want to be able to do anything to their product they want, but the goal of regulation is to step in when the companies desires are at odds with the people or the consumers desire, this is one of those cases.
If anything this was worse under the old system. Making art previously costed a lot of money, you had to pay the artists for their time and money, and better artists cost more. So in the past that oil company could commission 100 top quality artists to make corporate propaganda while a person who cares for the environment but has no money could only make a drawing limited by their own personal technical artistic ability, which could be just stick figures.
This is why “high quality” consumerist and capitalist “art” and branding in the form of advertising is so abundant meanwhile anti-consumerist, anti-capitalist art is rarer, no one’s paying to get it made.
Now any cause, regardless of money, can create at least mid art to get there message across. Those causes can also have way more people behind them then an oil company can reasonably hire
It’s sort of like how the gun changed how power worked. Previously a king could use there resources to pay for a smaller army of well equipped highly trained knights to subjugate a group of people. Then when the gun came training and equipment didn’t matter nearly as much and it became more of a numbers game, and to get those numbers rulers needed to give more power to the masses in order to be able to marshall them for their cause. Those rulers who didn’t got overthrown in revolutions.
Why would real meaning and messages be harder to find, does AI generated art inherently have less meaning?
Let’s say I wanted to convey the message that oil companies are destroying the environment so , throwing subtlety out the window, come up with an idea of “a vampiric oil baron draining mother nature of oil”, does the picture that is generated from me putting that prompt into an AI generator have any less meaning then if I actually drew it myself?
For all the advances in AI it still lacks intentionality, and always will under these current models, that has to be supplied by the person in the form of a prompt. I’d say that intention is the source of messages and meaning in art. AI just allows people without technical abilities in art to express those intentions, feelings and messages.
The u.s. also still holds all their foreign currency reserves, so they’re kinda forced to be friendly if they want to keep their economy a float.
Oh definitely, I don’t see it getting to SF before the bright line opens and I don’t see it getting to la in the next decade. But the bright line is using more tried and tested technology and methods in a significantly less populated area on an established corridor, while hsr is building from scratch through the heartland of California.
It’ll take a long time but it will eventually get done, because there is still a will, not a strong one, to get it done. Most Californians recognize the immense value it will bring and will keep pushing for it.
Oh definitely, I don’t see it getting to SF before the bright line opens and I don’t see it getting to la in the next decade. But the bright line is using tried and tested technology and methods, while hsr is building from scratch.
It’ll take a long time but it will eventually get done, because there is still a will, not a strong one, to get it done. Most Californians recognize the immense value it will bring and will keep pushing for it.
Hsr isn’t dead, it’s still being actively built, employing thousands of people, still has broad public support and just got a shit ton of funding from the feds. It’s over budget and delayed yes but so was the original shinkansen because bootstrapping that kind of project and industrial knowledge is hard.
That study is like giving a written test to an illiterate adult, seeing them do worse than a child and saying they aren’t intelligent or innovative. Like I said earlier intelligence is multi-faceted, and chatgpt excels at rhetorical, conversational and other types of written intelligence. It does not, as that study shows, do well in spatial manipulation, that doesn’t mean it’s not intelligent. If you gave that same test to a paralyzed blind person with little to no concept of spatial reality they’d probably do just as bad. If you asked them to compose a short story or an essay they might be good at it because that’s where they’re capabilities lye. That short story could still be innovative in its composition and characters, and could be way better than anything a child wrote.
You have to measure different types of intelligence with different tests. If you asked chatgpt and a set of adults and children to write a short story about a wholey new subject chatgpt would beat most of the children and probably some of the adults.
And if that short story is about a new subject matter completey out of its training set what/who is it plagiarizing from? You could say it’s taking common tropes, themes and story elements from other stories, but that’s fundamentally what a lot of writing and culture is. If that’s plagiarism then you should be more worried about the marvel franchise as it’s a plagiarism machine that has way more cultural impact.
It can answer questions as well as any person. Just because you may need to check with another source doesn’t mean it didn’t answer the question it just means you can’t fully trust it. If I ask someone who’s the fourth u.s. president and they say Jefferson they still answered the question, they just answered it wrong. You also don’t have to check with another source in the same way you do with asking a person a question, if it sounds right. If that person answered Madison and I faintly recall it and think it sounds right I will probably not check their answer and take it as fact.
For example I asked chatgpt for a chocolate chip cookie recipe once. I make cookies pretty often so would know if the recipe seemed off but the one it provided seemed good, I followed it and made some pretty good cookies. It answered the question correctly as shown by the cookies. You could argue it plagiarized but while the ingredients and steps were pretty close to some I found later none were a perfect match which is about as good as you can get with recipes which tend to converge in the same thing. The only real difference between most of them is the dumb story they give at the beginning which thankfully chatgpt doesn’t do.
The 7th grader and plagiarism comment make me think you haven’t played with them much or really tested them. I have had it write contracts, one of which I had reviewed by a lawyer who only had some small comments, as well as other letters and documents I needed for my mortgage and buying a home. All of these were looked over by proffesionals and none of them realized it was a bot. None of them were plagiarized too because the parameters I gave it and the output it created were way too unique to be in its training set.
I’m not saying it doesn’t encode some of its training data, I’m saying it’s not just encoding its training data. It probably does “memorize” a bunch of trivial facts from its training data and regurgitate them when asked. I’m saying that’s not all they are and that’s not what makes the intelligent, their ability to also answer questions outside their training data is.
Auto complete is not a lossy encoding of a database either, it’s a product of a dataset, just like you are a product of your experiences, but it is not wholly representative of that dataset.
A wind tunnel is not intelligent because it doesn’t answer questions or process knowledge/data it just creates data. A wind tunnel will not answer the question “is this aerodynamic” but you can observe a wind tunnel and use your intelligence to process that and answer the question.
Temperature and randomness don’t explain hallucinations, they are a product of inference. If you turned the temperature down to 0 and asked it the question " what happened in the great Christmas fire of 1934" it will give it’s best guess of what happened then even though that question is not in it’s dataset and it can’t look up the answer. The temperature would just mean that between runs it would consistently give the same story, the one that is most statistically probable, as opposed to another one that may be less probable but was pushed up due to randomness. Hallucinations are a product of inference, of taking something at face value then trying to explain it. People will do this too, if you tell someone a lie confidently then ask them about it they will use there intelligence to rationalize a story about what happened.
If LLMs were just lossy encodings of their database they wouldn’t be able to answer any questions outside of there training set. They can though, and quite well as shown by the fact you can give it completely made up information that it can’t possibly have “seen” and it will go along with it and give plausible answers. That is where it’s intelligence lyes and what separates it from older chatbots like Siri that cannot infer and are bound by the database they pull from.
How do you explain the hallucinations if the llm is just a complex lookup engine? You can’t lookup something you’ve never seen.
All inference is just statistical probability. Every answer you give outside of your direct experience is just you infering what might be the answer. Even things we hold as verifiable truth that we haven’t experienced is just a guess that the person who told it to us isn’t lying or has some sort of proof to there statement.
Take some piece of knowledge like “Biden won the 2020 election” me and you would probably agree this is the truth, but we can’t possibly “know” it’s the truth or connect it to some verifiable experience, we never counted every ballot or were at every polling station. We “know” it’s the truth because more people, and more respectable people, told us it was and our brain makes a statistical guess that their answer is right based on their weight. Just like an LLM other people will hallucinate or bullshit and come on the other side of that guess and assert the opposite and even make up stuff to go along with that story.
This in essence is what reasoning is, you weigh the possibilities of either side being correct, and pick the one that has more weight. That’s why science, an epistemological application of reason, is so heavily reliant on statistics…
This is not how LLMs work, they are not a database nor do they have access to one. They are a trained neural net with a set of weights on matrices that we don’t fully understand. We do know that it can’t possibly have all the information from its training set since the training sets (measured in tb or pb) are orders of magnitude bigger than the models (measured in gb). The llm itself is just what it learned from reading all the training data, just like how you don’t memorize every passage in a book you read, just core concepts, relationships and lessons. So if I ask you " who was gatsbys love interest?" You don’t remember the line and page of the text that says he loves Daisy, your brain just has a strong connection of neurons between Gatsby, Daisy , love, longing etc. that produces the response “Daisy”. The same is true in an LLM, it doesn’t have the whole of the great Gatsby in its model but it too would have a strong connection somewhere between Gatsby, Daisy, love etc. to answer the question.
What your thinking of are older chatbots like Siri or Google assistant which do have a set of preset responses mixed in with some information from a structured database.
computer scientists, neurologists, and philosophers can’t answer that either, or else we’d already have the algorithms we’d need to build human equivalent A.I.
I think your mixing up sentience / consciousness with intelligence. What is consciousness doesn’t have a good answer right now and like you said philosophers, computer scientists and neurologist can’t come to a clear answer but most think llms aren’t conscious.
Intelligence on the other hand does have more concrete definitions that at least computer scientists use that usually revolve around the ability to solve diverse problems and answer questions outside of the entities original training set / database. Yes doing an SAT test with the answer key isn’t intelligent because that’s in your “database” and is just a matter of copying over the answers. LLMs don’t do this though, it doesn’t do a lookup of past SAT questions it’s seen and answer it, it uses some process of “reasoning” to do it. If you gave an LLM an SAT question that was not in it’s original training set it would probably still answer it correctly.
That isn’t to say that LLMs are the be all and end all of intelligence, there are different types of intelligence corresponding to the set of problems that intelligence is solving. A plant identification A.I. is intelligent for being able to identify various plants in different scenarios but it completely lacks any emotional, conversational intelligence, etc. The same can be said of a botanist who also may be able to identify plants but may lack some artistic intelligence to depict them. Intelligence comes in many forms.
Different tests can measure different forms of intelligence. The SAT measures a couple like reasoning, rhetoric, scientific etc. The turing test measures conversational intelligence , and the article you showed doesn’t seem to show a quote from him saying that it doesn’t measure intelligence, but turing would probably agree it doesn’t measure some sort of general intelligence, just one facet.
This is just like Canada banning foreign investment in real estate. It admits there’s a problem, data harvesting , homes as investments, but just solves a small part of the problem pertaining to “foreign bad guys” while ignoring the larger domestic issue.
All it does is make the government look like they did something without actually confronting the powerful interests that are causing the problem.