Soon we’ll find delivery robots trying to pull some amazing stunts, all thanks to the sacrifices of some daring Pokemon Go players. Good times ahead 🍿

Thanks. Seems like a really freaky situation. Must be something with the training data. My guess is, this LLM was trained with all the creepy hostility found on Twitter.

They could just run the whole dataset through sentiment analysis and delete the parts that get categorized as negative, hostile or messed up.

Twitter is another possibility. The LLM could have learned how to write like a bubbling barrel of radioactive toxic waste, and then just applied those lessons in longer format.

Stuff like this should help with that. If the AI can evaluate the response before spitting it out, that could improve the quality a lot.

Oh, there it is. I just clicked the first link, they didn’t like my privacy settings, so I just said nope and turned around. Didn’t even notice the link to the actual chat.

Anyway, that creepy response really came out of nowhere. Or did it?

What if the training data really does contain hostile and messed up stuff like this? Probably does, because these LLMs have eaten everything the internet has to offer, which isn’t exactly a healthy diet for a developing neural network.

Would be really interesting to know what kind of conversation preceded that line. What does it take to push an LLM off the edge like that. Did the student pull a DAN or something?

It would make sense to include matching images in the search results and other engagement driven recommendations. There are quite a few screenshots too, so if the search can only handle text, it’s going to completely miss a pretty large category.

It’s probably going to be a rare collectible in about 50 years. Right now, it’s a high risk investment.

Obviously Netfilx wants to tell the stock holders how many “new subscribers” they have every quarter. Nobody stopped to think what those numbers actually mean.

Winamp source code was published on github, but the license said you can’t fork or share the code. Such a license isn’t compatible with github, which is all about forking and sharing.

Based on the article, this is a train wreck of cosmic proportions. My guess is, the CEO panicked and went into damage mitigation mode.

Sounds like they’re trying to put out a titanium fire using only a bucket of water. What could go wrong.

Yeah, those services can be really expensive, so justifying expenses like that might be hard in a small project.

And if you decide to use an LLM, don’t settle for the first version. Ask thoughtful questions, request relevant improvements, and spend some time with this document. The first version tends to have a bunch of flaws, mistakes and oversights, and the LLM might even be able to find and fix them if you tell it to do that. After a few iterations of ironing out the wrinkles, you should show the document to a real lawyer just in case.

It really depends on your assumptions. If you assume that software and hardware will stay at the current level, then the article does present a valid point. I would argue that those assumptions are only reasonable in the short term. AGI development does depend on some big technological changes we haven’t seen yet, so it could take decades or even a century, but I wouldn’t call it impossible.

If you assumed that 1950s style vacuum tube computers were the best thing ever, you could safely say that playing a game like fortnite with your buddies living in different countries is completely impossible. Modern semiconductors and integrated circuits would have seemed pretty magical in that context.

If we assume that we’re going to be stuck with silicon, you can safely say that AGI just isn’t going to happen with these tools and methods. Since quantum computers aren’t quite useful just yet and optical computers aren’t even in the news in any meaningful way, it seems that we will be stuck with silicon for quite some time. However, in the long term, you can’t really say that for sure. Technological developments have taken sudden and unpredictable jumps from time to time.

In addition, technological development can take unexpected twists and turns. For a while, it looked like analogue technology involving gears was going to solve every problem… until transistors were developed and mechanical calculators were soon forgotten. Also, the development of fertilizers revolutionized farming and and food production, which changed the world more than anyone even realized.

Could take a while, but how long? Progress tends to be non-linear, so things can slow down and speed up suddenly. I’m pretty sure we’ll get there sooner or later unless we nuke ourselves to oblivion before that.

If AI development isn’t prioritized, it could take centuries. Maybe we’re still missing some crucial corner stores we haven’t even thought of yet. Just imagine what it was like to build an airplane in an age when the internal combustion engine hadn’t been invented yet. Maybe we’re still missing something that big. On the other hand, it could also be just around the corner, but I find it unlikely.

Sounds really counterintuitive to say that it’s impossible.

The article says that we would run out of computing power, and that’s definitely true for current hardware and software. It’s just that they are being developed all the time, so I think we need to leave that door open. Who knows how efficient things can get within the next decade or century. The article didn’t even mention any fundamental obstacle that would make AGI completely impossible. It’s not like AGI would be violating the laws of physics.

It’s like Lemmy, but very broken.

”Facebook’s AI spam problem is one that is powered and funded primarily by Facebook itself”

Now that you have created a problem, it’s time to start selling the solution. Make a spam detector AI, and put it behind a monthly subscription. People will pay good money to filter out the trash. Also, better include some lootboxes and micro transactions too, while you’re at it.