Dasnap*LLMs and AI art stepping over the corpse of NFTs*
KantiberlCalling AI a fad is like calling electricity a fad.
kitonthenetYou lot would’ve said the same thing about self driving cars, crypto, NFTs, solar-freaking-roadways etc
AI is literally going to change everything. It's already started, don't you feel it?
No, and that’s exactly what the crypto, NFT, metaverse, self driving cars, solar roadways guys said. Show me
I’m not buying Sam Altmans fucking crypto coin
Yea, if only there were real world applications for AI. Like image/video generation and editing, text generation including code, audio processing and generation, object recognition and image classification, fraud detection, medical diagnosis, predictions in general, protein folding, or even just general data analysis. Then it might actually take off.
OpenGPT is just an LLM but that's only one small facet of AI. When people talk about AI and only mean LLMs or even one specific guy/company, it's a clear sign they don't know any more about AI than that one Vox article they read 2 months ago.
Go on then, write me an app, AI boy
Jesus you are dense. AI is already the most advanced and versatile tool we've ever made and it's only the beginning. They've already used LLMs to decode the brain waves of people looking at an image and were able to replicate the image JUST from brain waves and LLM algorithms. You seem like you don't want to understand just how huge AI is so I guess all I can say is wait and see. It's going to change every single thing about human society while you're blabbering on about crypto and NFTs. The ignorance of people is astounding sometimes.
Jesus you are dense
Why not get an AI to explain it to me then
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features, DOI 10.1109/TPAMI.2020.2995909
Published in 2020 by the IEEE. ieeexplore.ieee.org/document/9097411
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features
This work presents a novel method of exploring human brain-visual representations, with a view towards replicating these processes in machines. The core idea is to learn plausible computational and biological representations by correlating human neural activity and natural images. Thus, we first propose a model, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EEG-ChannelNet</i> , to learn a brain manifold for EEG classification. After verifying that visual information can be extracted from EEG data, we introduce a multimodal approach that uses deep image and EEG encoders, trained in a siamese configuration, for learning a joint manifold that maximizes a compatibility measure between visual features and brain representations. We then carry out image classification and saliency detection on the learned manifold. Performance analyses show that our approach satisfactorily decodes visual information from neural signals. This, in turn, can be used to effectively supervise the training of deep learning models, as demonstrated by the high performance of image classification and saliency detection on out-of-training classes. The obtained results show that the learned brain-visual features lead to improved performance and simultaneously bring deep models more in line with cognitive neuroscience work related to visual perception and attention.
So wait a minute, this 3 year old paper that isn’t related to the current crop of AI fad hype at all, and that’s supposed to sell me on das future? Also just going back to your original post I really appreciate “prediction in general” you can keep your AI astrologers lol
I’m not the original person you replied to, bud. I just wanted to find something peer reviewed for you on getting images from brain scans, since you doubted that’s a thing.
But like, you could also just look at the scene in the computer science field overall, if you’d like something more recent. Like the full journal from the IEEE, or maybe that little journal called Nature.
What do you think computer science departments at universities even do??
IEEE Transactions on Artificial Intelligence - IEEE Computational Intelligence Society
From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. The Society offers leading research in nature-inspired problem solving, including neural networks, evolutionary algorithms, fuzzy systems, and hybrid intelligent systems. Members contribute to the theory, design, application, and development of biologically and linguistically motivated computational paradigms, emphasizing neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained.
You wouldn’t need an AI to predict this low effort response from you after getting exactly what you asked for. What’d you do, look at the date and instantly form an opinion? Do you scoff at textbooks because they were written years prior to your birth?
Them Wright Brothers will never change anything! Airplanes are obviously a scam. Snake oil salesmen I tells ya!
NFT and Crypto are not in the same realm as AI other than to people who have no foresight.
The NFT people said the exact same thing. The wright brothers did not sell people on the dream of the Boeing 707, they sold the wright model A, an actual product to an actual customer. You are not selling me the wright model A
Fried_out_KombiYeah, I’m working at a company that traditionally makes digital signal processors for telecommunications, and even we’re using AI for actual practical applications. The current project I’m working on is applying an object detection model to detect different signal types in 2D spectrograms. The old way takes like 15 minutes to scan and detect across a wide band. This technique is likely going to be an order of magnitude faster (at least based on preliminary results) and lower-power, as you only need to capture one set of samples, then let the computer vision do most of the rest. The old way to scan for signals required taking a bunch of RF samples, which was very wasteful of time and energy, but there wasn’t really an alternative until now.
Having actual uses doesn’t make it not a fad. Like in the 50’s where even your mom’s toaster has to be atomic.
Look mom, our toast glow in the dark. Yes honey. Now eat it. Mmmm. It tastes really good mom. Thanks.
No ! It’s thanks to our radium toaster, (look at the camera) you can too brighten the days (and night) of your children with atomic-toaster™ by the everything radioactive corp Now, only 5.99$
Coal fire powered electricity is a fad.
Default_DefectFor most of the techbros using it, all it’s gonna take is a new get rich quick scheme for them to jump ship.