My personal experience is that the increase in ads has encouraged me to subscribe to creators I like via Patreon and view content on there. If many people are doing this, I wonder if it skews the view statistics and, therefore, lowers the number of recommendations for the best channels. In turn, this makes it less likely for good channels to be discovered. The increase in YouTube ads also makes me much less interested in browsing there, and I am finding other things to do instead.
You just don't make enough money from ads anyway, a lot of creators now see YT as more of top of funnel advertising leading you to a patreon or even more common livestream format where they make the real money from superchats.
I opted for sorting by project. We live in a world where you can get most things the next day. Then, I keep a few part-sample books for common components like capacitors and resistors for modding. Even if I need a specialist component, I know what projects I have used it in before
My take is that it means founders are sharing the risk by investing in the company and by taking a smaller salary than they could otherwise. This means there is a clear motivation to get a successful exit for them as well as the VC's
Because often, the tokens are broken up as random groups of numbers. For example, let's say 1984 appears quite a few times in the source text, this will become a single token. Given that these many different, semi-random groups of digits it is hard for the LLM to learn any consistent rules. I believe there are papers showing that if you structure numbers more consistently LLMs have no problem with this kind of arithmetic.
I have a question which I don't know the answer to:
With those structured numbers will the LLMs be 100% accurate on new prompts or will they just be better than chance (even significantly better than chance)?
Because this is one thing, it has to learn the structure and then create probabilities based on the data, but does that mean it's actually learning the underlying algorithm for addition for example or is it just getting better probabilities because of a narrowing of them? If it can indeed learn underlying algorithms like this that's super interesting. The reason also this is in an issue if it _can't_ learn those, you can never trust the answer unless you check it, but that's sort of a sidepoint.
From what I understand, it can learn and execute the algorithm fairly reliably, though it won't be 100%. When the LLM generates text, it is randomised a little, as well as some tricks that prevent repetition, which would likely cause problems with numbers containing all the same digit.
From what I've seen in the art world it is common practice to build on the work of others without attribution. Is this really all that different? That said, I think these tools still implicitly depend on people to pick out good images that resonate with people, as if people don't like the image it creates it won't get shared.
1) When artists 'steal' from others, they generally build something 'new'. AI can't really create anything 'new'. Case in point: Umberto Eco's The Name Of The Rose steals the plot and outline from crime stories, steals the library idea from Borges, and steals the murderer's motive from Eco's medieval manuscript (forgot which one). Yet the outcome is something completely new. Same goes for hip-hop music; sampling is at its core, but the final music that comes out is nothing like what it samples, the samples are just a part of something new.
2) when artists steal from each other, it's generally poor artists ripping off other poor artists. No money can flow. When a million/billion-dollar company rips off poor artists to make more money via generative AI it's a different story. Money could flow but it doesn't.
a_bonobo.... I think you're digging in the right vein here, but to perhaps to make the point clearer we could separate the discussion into two:
In an AI laden world
1) How are artists relevant
2) How are artists fairly compensated
I believe the answer to 1) is as you say, simply in the word 'new'. AI functionally remixes toward a mean. You can improve the impression of this with exquisite sources or more nuanced algorithms, but the result is always, literally, average.
I believe that an artist works out of an authentic story that is much more than the sum of their influences, and is uniquely their own. This story is the value proposition that is offered to an appreciant - it is an expression of identity that rises above the noise, and that can be joined. Mechanisms of payment have changed with the gyrations of technology, culture, and power since the concept of 'art' was birthed. But as long as there is a distinctive story in an artist's work, I believe there will always be a path to compensation.
Too your first point, I am not sure what constitutes new or novel here. I've seen the AI do exactly the type of borrowing from different sources you describe and producing something that seems very new to me. Though I admit, often these are under human direction with some carefully chosen sentences. Is that enough to generate something really new?
To your second point, most of the work I've seen generated from these models were done for free. It could be argued that these tools add to an artists toolbox rather than take something away. I can see for example where one poor artist could create a computer game of the same quality that it takes a triple-AAA game company to do today. Is that good or bad?
Why would you say AI can't create something new? It should be abler to merge ideas from its training data and create something like "The Name Of The Rose".
ChatGPT is able to write lyrics about a topic of my or its choice in the style of an unrelated philosopher for example. It creates something new by mixing ideas from different modalities.
Why is it some of the worlds greatest achievers say something like: "everything I've done was built on those who came before, I'm standing on the shoulders of giants", and others say: "I and I alone made the entirety of this"?
We're all standing on the shoulders of giants, dwarves, and everything in between. That's not really arguable. Even if you create something "entirely unique" (yeah right), that somehow doesn't draw on any work done before (ha!), you can only communicate it because people made language.
You can only share it because people fed you, clothed you, educated you. Countless squintillions of interactions and evolutions, in nature, in humanity, in culture and science and art and language, in the very cosmos, went into putting you in the position you were when you created the "completely new" thing.
However, one of the things that people do is go into bubbles - religious bubbles, ego bubbles, psychotic delusions, etc. It can be powerful to give yourself all the credit for your work. It can be motivating, comforting, and generally advantageous sometimes to think that God has your back, that your tribe is chosen above others.
Think of all the performers with diva complexes - those complexes serve a role in helping them. It's absurd and kind of sad from the outside, but it works for those people to believe that they're the greatest.
But the truth that they're all forgetting is that they had teachers, helpers, warriors, workers, people of all kinds supporting them to get to the position they're in. They all had ancestors who broke their backs to bring them into the world and protect them. They've all eaten thousands of pounds of food grown with exploited labour. They've all benefited from countless artists and creators enriching the local and global culture.
So, I can see why someone might believe, or even choose to believe that they "made the entirety" of a thing... But it's not the truth - not even close. A wider and less egoistic perspective might not help them create or believe in themselves, but if we're talking about a broader truth than one person's viewpoint, it's utterly absurd, wholly delusional, to give yourself that much credit. I think it's a sign of sickness in our culture that any of this is news to people.
When I first stumbled on a senior engineer browsing HN at my very first internship, I assumed it was a hut for developers. However, the more I've browsed this place over the years, the more I realize the community is much, much larger than that. There are some very insightful people from many industries contributing to this site.
As someone who’s changed careers, I value HN for the wide variety of intellectual topics and often insightful commentary. I think in recent years it’s actually moved further away from the ‘$N raised by $X from $Y to build A for B’ headlines that I used to hate. It still takes some digging to find stuff I like, but not long. The classic web1 design helps.
Every community on the internet has its problems. Every community has its own circlejerk customs. And n-gate.com is all that needs to be said about HN’s problems (hope he comes back).
I’d be curious to hear from people here about other communities or news aggregators of the same quality or better
I find picking one calorific food and cutting it out, but otherwise eating the same works really well. For example I used to have small bottle of orange juice with lunch, which I cut out and it put my weight on a downward path. It is easier than worrying about the whole of your diet.
