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.

AI needs to be regulated with an energy cap. If you need more capacity, optimise your AI. Don't just throw more electricity at it.

I admire your positivity. I do not share it though, because from what I have seen, because even if there are open weights, the one with the biggest datacenter will in the future hold the most intelligent and performance model. Very similar to how even if storage space is very cheap today, large companies are holding all the data anyway. AI will go the same way, and thus the megacorps will and in some extent already are owning not only our data, but our thoughts and the ability to modify them. I mean, sponsored prompt injection is just the first thought modifying thing, imagine Google search sponsored hits, but instead it's a hyperconvincing AI response that subtly nudges you to a certain brand or way of thinking. Absolutely terrifies me, especially with all the research Meta has done on how to manipulate people's mood and behaviour through which social media posts they are presented with

I often wonder if yours is an automated account, but did you read the comments?

I know there decent alternatives to SalesForce, but I’m not sure what you’d replace Slack with. Teams is far worse in every conceivable way and I’m not sure if there’s anything else out there that isn’t already speeding down the enshittification highway.

A fairer comparison would be Eliza vs ChatGPT.

It’s funny how the article asks the question, but completely fails to answer it. About 15 years ago, Nvidia discovered there was a demand for compute in datacenters that could be met with powerful GPU’s, and they were quick to respond to it, and they had the resources to focus on it strongly, because of their huge success and high profitability in the GPU market. AMD also saw the market, and wanted to pursue it, but just over a decade ago where it began to clearly show the high potential for profitability, AMD was near bankrupt, and was very hard pressed to finance developments on GPU and compute in datacenters. AMD really tried the best they could, and was moderately successful from a technology perspective, but Nvidia already had a head start, and the proprietary development system CUDA was already an established standard that was very hard to penetrate. Intel simply fumbled the ball from start to finish. After a decade of trying to push ARM down from having the mobile crown by far, investing billions or actually the equivalent of ARM’s total revenue. They never managed to catch up to ARM despite they had the better production process at the time. This was the main focus of Intel, and Intel believed that GPU would never be more than a niche product. So when intel tried to compete on compute for datacenters, they tried to do it with X86 chips, One of their most bold efforts was to build a monstrosity of a cluster of Celeron chips, which of course performed laughably bad compared to Nvidia! Because as it turns out, the way forward at least for now, is indeed the massively parralel compute capability of a GPU, which Nvidia has refined for decades, only with (inferior) competition from AMD. But despite the lack of competition, Nvidia did not slow down, in fact with increased profits, they only grew bolder in their efforts. Making it even harder to catch up. Now AMD has had more money to compete for a while, and they do have some decent compute units, but Nvidia remains ahead and the CUDA problem is still there, so for AMD to really compete with Nvidia, they have to be better to attract customers. That’s a very tall order against Nvidia that simply seems to never stop progressing. So the only other option for AMD is to sell a bit cheaper. Which I suppose they have to. AMD and Intel were the obvious competitors, everybody else is coming from even further behind. But if I had to make a bet, it would be on Huawei. Huawei has some crazy good developers, and Trump is basically forcing them to figure it out themselves, because he is blocking Huawei and China in general from using both AMD and Nvidia AI chips. And the chips will probably be made by Chinese SMIC, because they are also prevented from using advanced production in the west, most notably TSMC. China will prevail, because it’s become a national project, of both prestige and necessity, and they have a massive talent mass and resources, so nothing can stop it now. IMO USA would clearly have been better off allowing China to use American chips. Now China will soon compete directly on both production and design too.