People who do so aren't smart enough to use internet anyway. With or without AI it wouldn't change anything for them, they stay stupid and will continue acting stupidly
I don't expect it to be 100% correct. I have realistic expectations built on experience. Any source isn't 100% reliable. A friend is 50% reliable, an expert maybe 95. A random web page probably 40... I don't know.
I built up my strategies to address uncertainty by applying critical thinking. It is not much different than in the past. By experience, chatgpt 4 is currently more reliable than a random web page that comes in the first page of a Google search. Unless I exactly search for a trustworthy source, such as nhs or guardian.
The main problem is the drop in quality of search engines. For instance, I often start with chatgpt 4 without plugins to focus my research. Once I understand what I should look for, I use search engines for focused searches on official websites or documentation pages.
I don't really understand what it means. If the product is unreliable people won't use it, and everything will stay as it is now. It's not a big issue. But It is already pretty reliable for many use cases.
Realistically the real future problem will be monetization (which is causing the issues of Google), not features
If you try "copilot" option, you get the full experience. It's pretty neat because it allows for brainstorming.
It is still a very "preliminary version" experience (it often gets stuck in a small bunch of websites), because the whole thing is just few months old. But it has a lot of potential
If you aren't paying for chatgpt, give a look to perplexity.ai, it is free.
You'll see that sources are references and linked
Don't judge on the free version of chatgpt
Edit. Why the hell are you guys downvoting a legit suggestion of a new technology in the technology community? What do you expect to find here? Comments on steam engines?
Because international agencies and governments recognize those settlements as violations of international laws https://press.un.org/en/2016/sc12657.doc.htm . To create those settlements, most often, people previously living there were forced to move somewhere else, often by using army.
That's the reason. Whatever is someone's side on the conflicts, those settlements are simply widely recognized as illegal
It's clear that the reason the robot in the article doesn't shoot autonomously is because developers couldn't implement directive 4... It's an alpha version
In the easiest example of a neuron in a artificial neural network, you take an image, you multiply every pixel by some weight, and you apply a very simple non linear transformation at the end. Any transformation is fine, but usually they are pretty trivial. Then you mix and match these neurons to create a neural network. The more complex the task, the more additional operations are added.
In our brain, a neuron binds some neurotransmitters that trigger a electrical signal, this electrical signal is modulated and finally triggers the release of a certain quantity of certain neurotransmitters on the other extreme of the neuron. Detailed, quantitative mechanisms are still not known. These neurons are put together in an extremely complex neural network, details of which are still unknown.
Artificial neural network started as an extremely coarse simulation of real neural networks. Just toy models to explain the concept. Since then, they diverged, evolving in a direction completely unrelated to real neural network, becoming their own thing.
No, what you describe is a basic decision tree. Let's say the simplest possible ML algorithm, but it is not used as is in practice anywhere. Usually you find "forests" of more complex trees, and they cannot be used for generation, but are very powerful for labeling or regression (eli5 predict some number).
Generative models are based on multiple transformations of images or sentences in extremely complex, nested chains of vector functions, that can extract relevant information (such as concepts, conceptual similarities, and so on).
In practice (eli5), input is transformed in a vector and passed to a complex chain of vector multiplications and simple mathematical transformations until you get an output that in the vast majority of cases is original, i.e. not present in the training data. Non original outputs are possible in case of few "issues" in the training dataset or training process (unless explicitly asked).
In our brain there are no if/else, but electrical signals modulated and transformed, which is conceptually more similar to the generative models than to a decision tree.
In practice however our brain works very differently than generative models
Problem of science is corrupted funding, toxic environment, mafia-like organizations and practices, exploitation, widespread corruption.
The current amount of bad science is due only to that. Even before reaching mainstream media, of which I don't care. Unmanageable excess of meaningless published work is just a side effect of all above. Clearly it cannot change from inside, as current system selects only those who agree or compromise.
A revolution must come from outside. Tools and platforms like arxiv, github, hugging face are already demonstrating that alternative way of working exists, better ways to spread science and facilitate collaboration, increasing quality. Unfortunately they do not currently represent a real alternative outside niche fields, were quality, reproducibility and speed of evolution are critical. But also alternative tools such these can alleviate a minimal part of the huge problems.
I am honestly curious too see how "scientific" system will evolve, because it will. Because as it is now it is doomed to miserably continue falling down even further...
People who do so aren't smart enough to use internet anyway. With or without AI it wouldn't change anything for them, they stay stupid and will continue acting stupidly