I tacked it onto your comment because I was chiming in with my agreement on your disagreement, if that makes sense.
The thing about the robotaxi thing is that it only really works as metro level infrastructure. Once you start trying to do that at a level where your vehicles can traverse whole states, the costs balloon like crazy.
Sorry, you’re absolutely correct, I should have added “… or a pair of thigh highs.”
Shameful oversight on my part.
Sketch? Nah bro, that is exactly the kind of “This looked sick in the early 2000s and we haven’t bothered updating it since” level of design that I want to see from a hardware vendor. That’s a company that’s just sitting there quietly trucking along, making nerdy devices for nerdy people. That’s a website that was never intended to be viewed by anyone other than a 30+ year old sysadmin who owns at least one beard grooming product.
Yeah, I contemplated this idea, but you’d need a network of dealerships all within no more than about 450km of each other. Actually, a lot less than that if you want to deliver something like a cybertruck this way. And Tesla just doesn’t have that kind of infrastructure, especially in the Midwest and South. And that means there’s no good way to get a car from Fremont or Austin to anywhere on the East Coast either. At best you could maybe make this work in California.
But also consider the scale of what you’re talking about. Generally you’re looking at selling thousands of cars per day for a successful production model. Can their dealerships handle charging thousands of cars per day?
This is such obvious BS. Putting aside that Tesla are always making claims about self driving that they can’t deliver on, let’s just consider the basic logistics of doing this for any customer who lives more than about 300km from a Tesla factory (of which there are two IIRC, and one of those is in Austin and the other is in Fremont)…
How the fuck is the car going to recharge?
It’s not like it’s going to plug itself in, and there are no staff at Tesla supercharger stations as far as I’m aware. With the range on a typical Model S even getting to LA might be tough if it gets stuck in traffic. Fremont to LA is just under 600km if you’re lucky.
this new gadget makes it easy to take Windows system events, and feed them into Copilot, looking for potentially malicious activity. And while it’s not perfect, it did manage to detect about 40% of the malicious tests that Windows Defender missed. It seems like LLMs are going to stick around, and this might be one of the places they actually make sense.
Yes, the pattern recognition engine is good at pattern recognition.
In all seriousness, it really would be great if we’d focused development of transformer models on stuff like this instead of everyone getting caught up in the fact that they can kinda sorta pass the Turing test and deciding that the singularity had arrived and they could be the ones to sell tickets to it.
Pro-tip: If you marry said friend, they have to seat you together anyway.
Not even remotely. LLMs have failed to find any viable market fit.
The problem continues to be hallucinations and limited utility. This is compounded by the fact that LLMs are very expensive to run. The latter problem wouldn’t really be a problem if LLMs were truly capable of replacing a human employee, but they’re not. They’re just too unreliable for any serious enterprise grade application, and they’re too expensive for any low severity application.
For example, as a coding assistant, a lot of people quite like them. But as a replacement for a human coder, they’re a disaster. That means you still have to employ the expensive human, and you also have to pay an exorbitant monthly fee for what amounts to a very cool search engine.
There are tonnes of frivolous applications where they work really well. The AI girlfriend stuff, for example. A chatbot that sexts you is a very sellable product, regardless of how icky it might seem to some people. But no one is going to pay over $200 / month for it (as an example, ChatGPT still doesn’t make a profit at their $200/month tier).
LLMs are too unreliable to make anything better than toys, but too expensive to sell as toys.
Insanely bad idea. You should not be honebrewing anything with the capacity to kill people.
Not that Tesla’s solution is any safer, but that’s a separate discussion.
It really doesn’t. You’re just describing the “fancy” part of “fancy autocomplete.” No one was ever really suggesting that they only predict the next word. If that was the case they would just be autocomplete, nothing fancy about it.
What’s being conveyed by “fancy autocomplete” is that these models ultimately operate by combining the most statistically likely elements of their dataset, with some application of random noise. More noise creates more “creative” (meaning more random, less probable) outputs. They do not actually “think” as we understand thought. This can clearly be seen in the examples given in the article, especially to do with math. The model is throwing together elements that are statistically proximate to the prompt. It’s not actually applying a structured, logical method the way humans can be taught to.
I’m not sure what would make you think the “customers” for an enormous DNA database were the people providing the DNA.
Those people were just paying to be the product.
So yes, I did, and yes, their docs suck (better documentation is on their roadmap).
There’s a really good guide here on Lemmy that I recommend instead. https://lemmy.ml/post/25006407
Following this I had it up and running in no time. Check the comments as well, I added some notes on getting attachments working. If you’re still having issues shoot me a message and I’ll try to help.
If you can, take a moment to upvote Drawing Support in their suggested features section; https://notesnook.com/roadmap/
I did find that with a very large OneNote account the importer struggled, specifically because OneNote was timing out and rejecting the requests after a while.
My solution was to backup (in onenote) and then delete the notebooks that had been moved already and then run the importer again.
Not even once. The syncing has been incredibly robust for me. It also has a really nice flow for handling conflicts.
Of course, it’s worth keeping in mind that it can new self-hosted, so experiences will vary.
I’m using the self hosted version. Take from that what you will.
Yes, it’s all open source and can be self-hosted. They run a paid plan, but if you self host then you get all the paid features free.
This is a good time to switch to Notesnook, which has a OneNote importer.
Why am I about to shill so hard for this particular app? Simple, because after Evernote enshittified over a decade ago, I switched to OneNote as the least terrible alternative, and then spent the next ten years trying to find an actually good, open source notes app.
Call me Ahab because this motherfucker has been my white whale for a not-insignificant portion of my life.
Notesnook, finally, hit everything I wanted;
What it’s currently lacking is drawing support. If that’s a must have for you, check out Joplin instead (at least for now, I’ve seen some talk about Notesnook integrating Excalibur for digital canvas, which would be a superb solution).
Anyway, please check out Notesnook. It’s excellent, and I like sharing excellent things. https://notesnook.com/downloads/
Honestly, I don’t really understand how people prefer the Plex UI to Jellyfin. No shade, it just doesn’t make sense to me. Plex is incredibly cluttered and busy. Jellyfin is simple and clean. I like the latter a lot more.
This might be a good time to remind everyone that Jellyfin is open source, free (as in beer) and is, at this point, a better media streamer than Plex. No fees, no ads, no constant pushing of their streaming content, and still has the watch together feature that Plex went and removed.
Seconded.
Andor is the best piece of Star Wars media, period.
Yes, even including the original trilogy.