That has always been the two big problems with AI. Biases in the training, intentional or not, will always bias the output. And AI is incapable of saying "I do not have suffient training on this subject or reliable sources for it to give you a confident answer". It will always give you its best guess, even if it is completely hallucinating much of the data. The only way to identify the hallucinations if it isn't just saying absurd stuff on the face of it, it to do independent research to verify it, at which point you may as well have just researched it yourself in the first place. AI is a tool, and it can be a very powerful tool with the right training and use cases. For example, I use it at a software engineer to help me parse error codes when googling working or to give me code examples for modules I've never used. There is no small number of times it has been completely wrong, but in my particular use case, that is pretty easy to confirm very quickly. The code either works as expected or it doesn't, and code is always tested before releasing it anyway. In research, it is great at helping you find a relevant source for your research across the internet or in a specific database. It is usually very good at summarizing a source for you to get a quick idea about it before diving into dozens of pages. It CAN be good at helping you write your own papers in a LIMITED capacity, such as cleaning up your writing in your writing to make it clearer, correctly formatting your bibliography (with actual sources you provide or at least verify), etc. But you have to remember that it doesn't "know" anything at all. It isn't sentient, intelligent, thoughtful, or any other personification placed on AI. None of the information it gives you is trustworthy without verification. It can and will fabricate entire studies that do not exist even while attributed to real researcher. It can mix in unreliable information with reliable information becuase there is no difference to it. Put simply, it is not a reliable source of information... ever. Make sure you understand that.

Large language models and "generative AI" such as Stable Diffusion, Midjourney, and DALL-E are all just machine learning models. We do not currently have a real "AI branch" of computer science, we have a branch of machine learning that poses as AI. No matter how good a machine gets at recognizing and predicting patterns, it will not constitute AI, as intelligence is different from pattern recognition and prediction. Even if LLMs can sometimes appear to be reasoning, they importantly are not.

Gobble that AI slop NPR. Reads like sponsored content.

"I hate it when misandry pops up on my feed" Word for word. I posted that 5 weeks ago and I'm still getting hate for it.

Cool. Well, the feedback until now was rather lukewarm. But that's fine, I'm now going more in a P2P-direction. It would be cool to have a way for everybody to participate in the training of big AI models in case HuggingFace enshittifies

By giving us the choice of whether someone else should profit by our data. Same as I don't want someone looking over my shoulder and copying off my test answers.

If only they didn’t fake it to get their desired result, then maybe it could have been useful. I agree that LiDAR and other technologies should be used in conjunction with regular cameras. I don’t know why anyone would be against that unless they have vested interests. For various reasons though I understand that it isn’t always possible - price being a big one.