Scammers already are using AI. In every awful way. Like using real-time face changers in video calls in pig butchering scams.

I would have mentioned their terrible dev practices like letting their site cert expire… Five times…

Hello “Zero”!

Basically nothing is ever truly zero

Hey, don’t you know you need to become a Microsoft Certified Solutions Expert to do business properly?

Check out Blender. It’s primarily a 3D modeling software like Maya or Houdini, but it has an incredibly powerful video editor built into it.

That’s why you need to pay for premium so you can get the 1080p premium bitrate.

flat earth society scientific newsletter

Such a contradictory sentence. Can’t wait for The Final Experiment to be done with, so we can eject any remaining flerfs from society.

I think the best bet is an entirely new system from the ground up that has an open architecture that every company can equally implement that from the ground up and is as simple as possible.

This keeps getting said by people who don’t understand operating systems. Even if you build something from the ground up, you still end up with an operating system very much like Linux and Windows. The choices that were made for each OS were not random. The principles of I/O, user input, graphics display, filesystems, etc, are more or less universal concepts across all OSes.

What you will accomplish is making an OS that no one will use. Linux, Windows, and macOS already fill every market that can be filled. Microsoft tried to become a third player in the mobile market and their product died pretty quickly.

Google has been trying to build Fuschia into a new OS and they’ve asked back their ambitions (from what I recall reading).

I’m getting non-stop Samsung, insurance, food, and other kinds of ads in the middle of shows.

It makes me not want to use Prime. And in fact, I don’t anymore.

I have my money on Tesla being the first cloud-connected car (that phrase shouldn’t exist) to be hacked and push a malicious firmware that will cause all cars to simultaneously activate self driving and to pull a hard left at a specific time (time bomb).

It was a joke

wooosh

Couldn’t even use a 16 Pro?

/s

You live in a fantasy world if you think it’s possible to catch 100% of mistakes internally.

Nice strawman. No one said anything about catching 100% of mistakes internally. But outsourcing that work to unpaid volunteers with zero verification of qualifications is the definition of “passing the buck”.

The correct answer is to hire and train up a QA team.

Not many.

Yes, literally every single person on this planet can recite a song or poem.

But there are naturally massive differences between a human brain and an LLM. The point I was making is that an LLM doesn’t copy and store books and articles wholesale. The ability to reproduce samples from the dataset is more of a quirk than a feature, in the same way that a person can memorize things.

You’re right, I’ve responded to a few comments here and I thought it was another comment thread I was replying to.

I don’t get why people who don’t like their content bother hating them.

Because for good or bad, they have a significant influence in the tech world. And since they are more bad, people don’t like them.

Take the Linux challenge, for example. They massively misrepresented the usability of Linux for the average person and for gamers. They even concluded at the end of their challenge that Linux was unsuitable for most gamers. And the release and success of the Steam Deck shortly afterwards was quite delicious.

Then there was the bit where Linus didn’t read the warning about the package manager removing the desktop environment and just hit yes, then complained that it wasn’t his fault and that the system was poorly designed.

The guy literally has an issue with accountability.

You’re upset they aren’t more knowledgeable as if everyone making tech content needs to know everything.

A better statement is that I’m upset because they preach their deep and unchallengeable knowledge and act as a be-all end-all authority in tech.

But really I’m not “upset” by them. I just really dislike them and think they’re insufferable.

And I don’t watch LTT. And there are plenty of other, and objectively better, channels about tech. And I watch those better channels, including GamersNexus.

All I’ll say is I’m willing to wait and see if they improve or if they make similar mistakes.

Their entire channel is a giant mistake. All of their content is garbage by virtue of their proven flawed and subpar provides. A process they admitted was flawed, and from what I’ve seen is still flawed with the garbage corrections in the comments nonsense they promised to fix.

They’re just going to go about business as usual and just be a little more careful with their public image. They don’t deserve the views they get.

And? No one said otherwise. The comment I was responding to made the argument that LLMs merely memorize content, which isn’t true.

Fine, you win, I misunderstood.

It’s not a competition, but I genuinely respect you for saying you misunderstood.

Once an LLM is trained, it is static and unchanging until you re-train it with new data and update the model.

Absolutely! I honestly think this is the main thing (or at least one of the main things) that prevent human-level intelligence or even sentience in LLM’s.

Think about how our minds work. From the moment we’re born (really, it’s way before that) our brains are bombarded with input and feedback from every sense. It takes a person many months of that to start recognizing things. That’s also why babies sleep so much, their brains are kinda “training” and growing fast. Organizing all the data into memories.

Side bar: this is actually what dreams are. Dreams are emotions, thoughts, ideas, or whatever concept a neuron or group of neurons are associated with getting triggered. When we dream it’s our brain taking the days inputs and building new connections. The neural connections in our brains are very much like weights and feed-forward process of neural activation is near identical to how artificial neural networks function. They aren’t called “artificial neural networks” for no reason.

Here’s a useful graphic that shows things that make up “intelligence”

A very basic definition of intelligence is “the ability to solve problems or make decisions”.

I think the term is just often misused in common parlance so often that people start applying in a scientific setting incorrectly. Kinda how people used to call an entire computer the CPU, which like the word intelligence everyone understands what’s being said, but it’s factually wrong.

Same thing today when people say “I bought a new GPU” when they should say “I bought a new video card” as the GPU is just a component.