We didn’t call them AI because they weren’t (and aren’t) intelligent, but marketing companies eventually realized there were trillions of dollars to be made convincing people they were intelligent and created models explicitly designed to convince people of things like the idea that they are intelligent and can have genuine conversations like a real human and create real art like a real human and totally aren’t just empty-headedly mimicking thousands of years of human conversation and art, and immediately used them to convince people that the models themselves were intelligent (and many other things besides). Given that marketing and advertising literally exist to convince people of various things and have become exceedingly good at it, it’s really a brilliant business move and seems to be working great for them.
Nemo@slrpnk.net 1 day ago
They had the AI models of those days.
cecilkorik@lemmy.ca 1 day ago
bathing_in_bismuth@sh.itjust.works 1 day ago
That’s cool, didn’t know AI models where a thing in those days. Are they comparable (maybe more crude?) to nowadays tech? Like, did they use machineearning? As far as I remember there were not much dedicated AI accelerating hardware pieces. Maybe a beefy GPU for neural network purposes? Interesting though
Zwuzelmaus@feddit.org 1 day ago
Models were a thing even some 30 or 40 years ago. Processing power makes most of the difference today: it allows larger models and quicker results.
bathing_in_bismuth@sh.itjust.works 1 day ago
I didn’t know. Are you somewhat informed about the history of models? I’d love to hear it from you instead of a random crypto bros’ LLM summary. Thanks!
brucethemoose@lemmy.world 1 day ago
Machine learning has been a field for years, as others said, yeah, but Wikipedia would be a better expansion of the topic. In a nutshell, it’s largely about predicting outputs based on trained input examples.
It doesn’t have to be text. For example, astronmers use it to find certain kinds of objects in raw data feeds. Object recognition (identifying things in pictures with little bounding boxes) is an old art at this point. And yes, image similarity is another, though not entirely machine learning based. IDK what Tineye does in their backend, but there are some more “oldschool” approaches using more traditional programming techniques, generating signatures for images.
Seperately, image similarity metrics (like lpips or SSIM), that measure the difference between two images as a number (where, say, 1 would be a perfect mach and 0 totally unrelated) are common components in machine learning pipelines. So are text embedding models, which do the same with text.
Zwuzelmaus@feddit.org 1 day ago
I don’t remember too much tbh, just that we heard about the theory at university and tried out some of the mathematical methods. They were tiresome ;)
Today I would recommend to start your studies on the wikipedia pages about Markov models and about machine learning.
howrar@lemmy.ca 23 hours ago
Yann Lecun gave us convolutional neural networks (CNNs) in 1998. These are the models that are used for pretty much all specialized computer vision tasks even today. TinyEye came into existence ten years later in 2008. I can’t tell you if they used CNNs, but they were certainly available.
cecilkorik@lemmy.ca 1 day ago
We didn’t call them AI because they weren’t (and aren’t) intelligent, but marketing companies eventually realized there were trillions of dollars to be made convincing people they were intelligent and created models explicitly designed to convince people of things like the idea that they are intelligent and can have genuine conversations like a real human and create real art like a real human and totally aren’t just empty-headedly mimicking thousands of years of human conversation and art, and immediately used them to convince people that the models themselves were intelligent (and many other things besides). Given that marketing and advertising literally exist to convince people of various things and have become exceedingly good at it, it’s really a brilliant business move and seems to be working great for them.
brucethemoose@lemmy.world 1 day ago
Oh and to answer this, specifically, Nvidia has been used in ML research forever. It goes back to 2008 and stuff like the GTX 280. Maybe earlier.
So have CPUs. In fact, Intel made specific server SKUs for giant AI users like Facebook. See: servethehome.com/facebook-introduces-next-gen-coo…