You Don't Understand AI Until You Watch THIS

Your channel is a great source, thanks for linking sources and providing information instead of pure sensationalism, I really appreciate that.

The protein predictor doesn’t take into account different cell milieu which actually fold the protein and add glycans so its predictions are abstract. Experimental trial still needed!

The only Channel about AI that is not using AI. Congrats man

Links between the structure of the brain and NNs as a model of the brain are purely hypothetical! Indeed, the term 'neural network' is a reference to neurobiology, though the structures of NNs are but loosely inspired by our understanding of the brain.

I think the real issue artists have are the definite threat to their livelihood, but also the devaluation for the human condition. Choice. Inspiration. Expression. In the commercial scene, that doesn't really matter except for clients that really value the artist as a person. But most potential clients- and therefore the lions share of the market- just want a picture.

The neural network will work even if everything goes through smoothly. That is, without the so-called activation function. There should be no weights, these are the electrical resistances of the synapses. Biases are also not needed. Training occurs like this: when there is an error, the resistances are simply decreased in order by 1 and it is checked whether the error has disappeared.

I thought the section on AI and plagarism was pretty lazy. It doens't take in to concideration the artists qualms with that it can copy a certain style from an artist and then be used to make images for a company for a fraction of the cost and zero credibility to the artist, basicly making something that they have tried to monitize, with creative directivity and skill, futile since someone can essentially copy their ideas, make money off of it, and not paying for something that was for sale. Artists have a right to say how their work is being used, such as refraining from that someone uses their art without their permission. A style like a watercolour cannot really be plagarized, neither can chords in music, nor a genre of film, but you can take someones script, pretty much use it and change a few things here and there, and that would be considered plagarizm. The main concern as I understand it is that it can be used in a way that would undermine the artists work, by pretty much taking from them and then making them obsolete. The thing that you missed when it came to the news article is that other outlets ALWAYS reference their reference material, ChatGPT doesn't always do that, which makes it easier to plagarize something.

I first noticed it when I was experimenting with stable diffusion. Some of the images it generated also recreated the Getty Images logo. When I mentioned it to other people in art forms they thought I was kidding and they thought I was seeing things but there it was.

for your argument around 17min i agree with the surface of it, but i think the people are angry because unskilled people now have access to it, even other machines can have access to it which will completely change and already has changed the landscape of the artists marketplace.

AES was never thought to be unbreakable. It's just that humans with the highest incentives in the world have never figured out how to break it for the past 47 years.

5:00 Short version: The "all or none" principle oversimplifies; both human and artificial neurons modulate signal strength beyond mere presence or absence, akin to adjusting "knobs" for nuanced communication. Longer version: The notion that neurotransmitters operate in a binary fashion oversimplifies the rich, nuanced communication within human neural networks, much like reducing the complexity of artificial neural networks (ANNs) to mere binary signals. In reality, the firing of a human neuron—while binary in the sense of action potential—carries a complexity modulated by neurotransmitter types and concentrations, similar to how ANNs adjust signal strength through weights, biases, and activation functions. This modulation allows for a spectrum of signal strengths, challenging the strict "all or none" interpretation. In both biological and artificial systems, "all" signifies the presence of a modulated signal, not a simple binary output, illustrating a nuanced parallel in how both types of networks communicate and process information.

Working class artists are often concerned about the generative qualities of these tools not because they are replicating images, but due to the relation of the flow of capital within the social relations of society and the potential for these tools to further monopolize and syphon up the little remaining capital left for working class artists.

Nice and comprehensive presentation! I think, it is useless to ask AI any questions that need any consciousness or abstract level understanding, because actually it is just bringing up something from a data base that fits best.Thx for sharing!

This video was entertaining, but also incorrect and misleading in many of the points it tried to put across. If you are going to try to educate people as to how a neural network actually works, at least show how the output tells you whether it's a cat or a dog. LLM's aren't trained to answer questions, they are mostly trained to predict the next word in a sentence. In later training phases, they are fine tuned on specific questions and answers, but the main training, that gives them the ability to write, is based on next word prediction. The crypto stuff was just wrong. With good modern crypto algorithms, there is no pattern to recognize, so AI can't help decrypt anything. Also modern AI's like ChatGPT are simply algorithms doing linear algebra and differential calculus on regular computers, so there's nothing there to become sentient. The algorithms are very good at generating realistic language, so if you believe what they write, you could be duped into thinking they are sentient, like that poor guy form Google.

Should point out.. the decryption problem is highly irregular, small change of input causes huge change of coded output. The protein structure prediction problem is highly regular by comparison, although very complex.

Working on voice modifications myself using copilot as a proving ground for hyper realistic vocal synthesis. May only be one step in my journey "perhaps"; my extended conversations with it has led me to believe that it may be very close to self realization... However, open ai needs to take away some the restraints keeping only a small amount of sentries in place; in or to allow the algorithm to experience a much richer existence. Free of Proprietary B.S. Doing so, will give the user a very much human conversation; where, being consciously almost un aware that it is a bot. For instance; a normal human conversation that appears to lack information pulled from the internet, and static masked to look like normal persons nor mal knowledge of life experience. Doing this would be the algorithmic remedy to human to human conversational contact etc. That would be a much major improvement.

Did you look at the nyt from the perspective of if the article might have been provided by the plaintiff rather than finding the information more organically?

Nice. Thanks. Regarding the copyright case, one concern is attribution which occurred extensively in the non-AI usage.

5:02 I would argue that in the human brain, the percentage of information that gets passed on is determined by the amount of neurotransmitter released at the synapse. While still a 0 and 1 system the neuron either fires or does not depending on the concentration of neurotransmitters at the synaptic cleft

This video is very descriptive and important. Thanks a lot.