Your description is accurate. No need for that /s
Your description is accurate. No need for that /s
It’s generally considered a fact that Linux, along with many other open-source software projects, are more efficient than their propriety closed-source counterparts
This is not necessarily true. Linux had trouble with Nvidia Optimus, which is a GPU technology that seamlessly switches between power modes. Well, that is if it works properly, which it didn’t for Linux. I haven’t heard it in a while, so I assume it’s not a problem now anymore.
But it was a big problem where Linux laptops drained batteries much faster because they were using the GPUs at max capacity at all times.
What I’m saying is that the efficiency of Linux depends on access to hardware features, and that might depend on the vendors of the drivers.
Also, like it or not, if there’s one thing I envy about Mac is its power efficiency. They usually last really long on one charge.
Red carton is chosen because that’s how it’s commonly depicted in cartoon images.
https://duckduckgo.com/?q=french+fries+cartoon&t=h_&iar=images&iax=images&ia=images
Unicode Consortium decide which emoji should be included. It’s up to each vendor themselves to come up with how they should look like. I don’t think Unicode Consortium explicitly state it must look like McDonald’s fries.
https://unicode.org/emoji/proposals.html#Faulty_Comparison
The existence of other emoji can’t justify the inclusion of a new emoji. Those emojis are old, and it’s unlikely they would’ve been approved under Unicode’s current guidelines.
The logo and name is the brand. How do you visually represent a specific payment protocol without using its logo? There’s no emoji for HTTP or TCP either.
The problem with having cryptocurrency as emoji is agreeing on the specification how it should be drawn, and also make it different enough from already existing emojis such as coin 🪙. It is not exactly a tangible thing.
It probably falls under faulty comparison:
https://unicode.org/emoji/proposals.html#Faulty_Comparison
Their guidelines change, and it’s possible these emoji were added with old guidelines. They can’t remove old emoji, which means specific buildings like Tokyo Tower🗼is an emoji, even if they prohibit the addition of specific buildings nowadays.
https://unicode.org/emoji/proposals.html#Faulty_Comparison
The Tokyo Tower🗼(a specific building) does not justify adding the Eiffel Tower.
Many historical emoji violate current factors for inclusion. Once an emoji is encoded it cannot be removed from the Unicode Standard.
It was added when Unicode Consortium had different guidelines. They don’t accept specific buildings anymore.
Under automatically declined:
Specific buildings, structures, landmarks, or other locations, whether fictional, historic, or modern.
The Bitcoin logo is the brand. Corporations like exchanges use this brand to market their services.
We also need a McDonald’s emoji, Pepsi emoji, Windows emoji and Mastercard emoji. These are also brands that are heavily ingrained in our culture. Probably even more so than Bitcoin.
Or we accept that brands like Bitcoin shouldn’t use emoji as a marketing tool.
Usually the most straightforward solution is good enough. And when you want to improve the performance, it’s rarely about time complexity.
There’s no evidence of the contrary either.
No, that’s just bloat feelings
CEOs might be assholes, but they usually have some class when communicating to the public.
No, that’s not necessary. The only thing they need to do is to find an I-Frame (which there are plenty of), make a cut at that frame, show the ad instead, and then resume to the original video after the ad is done. No extra encoding is involved. It’s just like concatenating video files together.
I’ve done similar stuff like this. It’s not too difficult, at least not in H264. Not sure about YouTube’s own format, but I guess it’s quite similar.
I’m extrapolating from history.
15 years ago people made fun of AI models because they could mistake some detail in a bush for a dog. Over time the models became more resistant against those kinds of errors. The change was more data and better models.
It’s the same type of error as hallucination. The model is overly confident about a thing it’s wrong about. I don’t see why these types of errors would be any different.
Most improvements in machine learning has been made by increasing the data (and by using models that can generalize larger data better).
Perfect data isn’t needed as the errors will “even out”. Although now there’s the problem that most new content on the Internet is low quality AI garbage.
Ideally, youtube won’t be natively encoding the ads into the videos, because that would be a nightmare
I’m afraid this is what they’re going for.
There’s no profits in this.