>However, like many models in this leaderboard - I can’t use it - since it doesn’t support voice cloning.
That's such a strange requirement. A TTS is just that. It takes a text and speaks it out loud. The user generally doesn't care whose voice it is, and personally I think TTS's sharing the same voice is a good thing for authenticity since it lets users know that it's a TTS reading the script and not a real person.
You want your voice to be reading the script, but you don't want to personally record yourself reading the text? As far as I'm concerned that's an edge case. No wonder that TTS's can't do that properly since most people don't need that in first place.
It makes me really sad how Google pushes this technology that is simply flat out wrong sometimes. I forgot what exactly I searched for, but I searched for a color model that Krita supports hoping to get the online documentation as the first result and the under several Youtube thumbnails the AI overview was telling me that Krita doesn't support that color model and you need a plugin for that. Under the AI overview was the search result I was looking for about that color model in Krita.
And worse of all is that it's not even consistent, because I tried the same searches again and I couldn't get the same answer, so it just randomly decides to assert complete nonsense sometimes while other times it gives the right answer or says something completely unrelated.
It's really been a major negative in my search experience. Every time I search for something I can't be sure that it's actually quoting anything verbatim, so I need to check the sources anyway. Except it's much harder to find the link to the source with these AI's than it is to just browse the verbatim snippets in a simple list of search results. So it's just occupying space with something that is simply less convenient.
The AI is also indiscriminate with what "sources" it chooses. Even deep research mode in gemini.
You can go through and look at the websites it checked, and it's 80% blogspam with no other sources cited on said blog.
When I'm manually doing a Google search, I'm not just randomly picking the first few links I'm deliberately filtering for credible domains or articles, not just picking whatever random marketing blog SEO'd their way to the top.
Sorry Gemini, an Advertorial from Times of India is not a reliable source for what I'm looking for. Nor is this xyz affiliate marketing blog stuffed to the brim with ads and product placement.
Some of that is due to that's probably 90% of the internet, but weren't these things trained on huge amounts of books, and published peer-reviewed works? Where are those in the sources?
It's trained on them, yes. But is it trained to prefer them as sources when doing web search?
The distinction is rather important.
We have a lot of data that teaches LLMs useful knowledge, but data that teaches LLMs complex and useful behaviors? Far less represented in the natural datasets.
It's why we have to do SFT, RLHF and RLVR. It's why AI contamination in real world text datasets, counterintuitively, improves downstream AI performance.
The next time you're working on your car google bolt torque specs and cross reference the shit their "AI" says with the factory shop manual. Hilarity ensues.
Spaces are skewing the numbers lower. Remove them from any of those and see the number increase at least an order of magnitude. That “let me login” goes from 0 to 4,714 just by removing spaces (“letmelogin”).
HTMLTableElement.prototype.rows actually just returns a HTMLCollection, so same as document.forms, or document.getElementsByClassName. HTMLCollection implements Symbol.iterator as you would expect.
This is very disappointing. I bought Affinity because I thought a "pay once, own the software" was a business model worth supporting. In fact, people loved to point to Affinity's transactional model to contrast it with Adobe's subscription model.
Now it will become freeware, and by "freeware" I mean "nagware" because it will keep telling you about pro/AI features that you don't have access to.
Just like on Windows you don't own the system, on this "freeware" you don't own the software. You're a renter, a freeloader. So you can't complain about the ads. But you WANTED to just buy the thing so you wouldn't have to deal with ads. That option is now off the table.
Imagine if you bought a boat and you can't just enter every room of the boat, because the boat comes with a bouncer that stands in front of a certain door and he won't let you enter. That's what it feels like. Not only the boat isn't yours, it is also not a welcoming place to be. It will always feel like you're an outsider being conditionally allowed on someone's software instead of just being a guy using a thing you own.
I don't know. On some days I feel I just don't like software anymore.
Imagine that you have an a spreadsheet that dates from the beginning of the universe to its end. It contains two columns: the date, and how many days it has been since the universe was born. That's very big spreadsheet with lots of data in it. If you plot it, it creates a seemingly infinite diagonal line.
But it can be "abstracted" as Y=X. And that's what ML does.
I don't think it's the same thing because an abstraction is still tangible. For example, "rectangle" is an abstraction for all sorts of actual rectangular shapes you can find in practice. We have a way to define what a rectangle is and to identify one.
A neural network doesn't have any actual conceptual backing for what it is doing. It's pure math. There are no abstracted properties beyond the fact that by coincidence the weights make a curve fit certain points of data.
If there was truly a conceptual backing for these "abstractions" then multiple models trained on the same data should have very similar weights as there aren't multiple ways to define the same concepts, but I doubt that this happens in practice. Instead the weights are just randomly adjusted until they fit the points of data without any respect given to whether there is any sort of cohesion. It's just math.
That's like saying multiple programs compiled by different compilers from the same sources should have very similar binaries. You're looking in the wrong place! Similarities are to be expected in the structure of the latent space, not in model weights.
Well, the comment I was replying to cited ease of installation, so I did, too.
> Linux shoots itself in the foot just because Windows has two feet
This is exactly the opinion that everyone who is not accustomed to all of the GNOME nonsense gets after using GNOME. And GNOME fans are far too used to things to even hear that it is imperfect.
To me it's sad that Linux never became a good desktop OS, Windows just became worse and worse until it became worse than Linux :(
When I upgraded to 7 I tried Linux and I simply hated that I had to deal with the terminal and install strange third-party programs from strange forums to get anything working. Then I had to upgrade to 11 and I had to run strange terminal programs to install it without without creating a Microsoft account, and everyone recommends using some third-party Windows power tools to fix what Microsoft did to Windows. I could not believe it. IT IS THE SAME THING!
Now I'm using Linux, and I don't like it, but least it isn't spyware.
That's such a strange requirement. A TTS is just that. It takes a text and speaks it out loud. The user generally doesn't care whose voice it is, and personally I think TTS's sharing the same voice is a good thing for authenticity since it lets users know that it's a TTS reading the script and not a real person.
You want your voice to be reading the script, but you don't want to personally record yourself reading the text? As far as I'm concerned that's an edge case. No wonder that TTS's can't do that properly since most people don't need that in first place.