The main findings from the Economic Index’s first paper are:
- Today, usage is concentrated in software development and technical writing tasks. Over one-third of occupations (roughly 36%) see AI use in at least a quarter of their associated tasks, while approximately 4% of occupations use it across three-quarters of their associated tasks.
- AI use leans more toward augmentation (57%), where AI collaborates with and enhances human capabilities, compared to automation (43%), where AI directly performs tasks.
- AI use is more prevalent for tasks associated with mid-to-high wage occupations like computer programmers and data scientists, but is lower for both the lowest- and highest-paid roles. This likely reflects both the limits of current AI capabilities, as well as practical barriers to using the technology.
Interesting, not really surprising, and nowhere near as entertaining as when Pornhub does it’s annual introspection.
The “innovation” in the article is passive tech for fiber to the room (FTTR), specifically made to be low cost and easier to implement. It’s also how your computer might get that 50Gbit - it’ll have to be wired in with a fiber connection. It’s not happening over WiFi (or even Ethernet)
Kinda funny how when mega corps can benefit from the millions upon millions of developer hours that they’re not paying for they’re all for open source. But when the mega corps have to ante up (with massive hardware purchases out of reach of any of said developers) they’re suddenly less excited about sharing their work.
No need to limit it to only people on social media…
😂
Yeah in that context I guess it makes sense.
I never understood people posting porn to microblogging sites. What’s the point of this? There are literally millions of other places to get porn already, it’s like what the Internet was invented for.
Yeah, the company that made the article is plugging their own AI-detection service, which I’m sure needs a couple of paragraphs to be at all accurate. For something in the range of just a sentence or two it’s usually not going to be possible to detect an LLM.
I have a hard time understanding facebook’s end game plan here - if they just have a bunch of AI readers reading AI posts, how do they monetize that? Why on earth is the stock market so bullish on them?
The original gpt4 is just an LLM though, not multimodal, and the training cost for that is still estimated to be over 10x R1’s if you believe the numbers. I think where R 1 is compared to 4o is in so-called reasoning, where you can see the chain of though or internal prompt paths that the model uses to (expensively) produce an output.
The thing is that R1 is being compared to gpt4 or in some cases gpt4o. That model cost OpenAI something like $80M to train, so saying it has roughly equivalent performance for an order of magnitude less cost is not for nothing. DeepSeek also says the model is much cheaper to run for inferencing as well, though I can’t find any figures on that.
Correct but there are really only 2 parts (3 if you’re adding a front-facing proxy which it sounds like you know how to do). If you’re using something like truenas or proxmox there are prebuilt containers for both iCloudpd and immich/photoprosm/whatever and even if not both have generic Docker containers or can be run out of their own repo checkout. So you just need:
Good luck!
Right, this is for the “hard” part of getting your content out of iCloud in an automated fashion. You’d then put the content in storage locally and use photoprism or immich or a similar self hosted gallery to be able to access them
icloudpd can be run in a container or just your host machine. It’s a little finnicky to get logins set up (and honestly I haven’t done it in a few months), but once that is working you can automate a job to pull down a backup every day/week/month and delete files from icloud.
It’s more like “I don’t have any money for you. What? This? Oh, this hoard technically belongs to the dragon that I have subjugated and keep in my dungeon. He lends me coin as I need it, and I will pay him back when I’m dead”
Algorithm is just a fancy word for rules to sort by. “New” is an algorithm that says “sort by the timestamp of the submissions”. That one is pretty innocuous, I think. Likewise “Active” which just says “sort by the last time someone commented” (or whatever). “Hot” and “Scaled”, though, involve business logic – rules that don’t have one technically correct solution, but involve decisions and preferences made by people to accomplish a certain aim. Again in Lemmy’s case I don’t think either the “Hot” or “Scaled” algorithms should be too controversial – and if they are, you can review the source code, make comments or a PR for changes, or stand up your own Lemmy instance that does it the way you want to. For walled-garden SM sites like TikTok, Facebook and Twitter/X, though, we don’t know what the logic behind the algorithm says. We can speculate that it’s optimized to keep people using the service for longer, or encouraging them to come back more frequently, but for all intents and purposes those algorithms are black boxes and we have to assume that they’re working only for the benefits of the companies, and not the users.
Algorithms can be useful - and at a certain scale they’re necessary. Just look at Lemmy - even as small as it is there’s already some utility in algorithms like “Active”, “Hot” and “Scaled”, and as the number of communities and instances grows they’ll be even more useful. The trouble starts when there are perverse incentives to drive users toward one type of content or another, which I think is one of the fediverse’s key strengths.
Even modest hardware can run a decent LLM. Maybe someone will open source a project to let people make their own avatars explicitly to poison the social media sites.
Yes! Slip the sound board guy your discman and $20 and get a perfect recording. I remember a few times where there were a stack of discmans and walkmans (Walkman?) recording.