I didn't care much about arc because it was chromium, but damn this is just bland and uninteresting compared to it

Many people on Lemmy are extremely negative towards AI which is unfortunate. There are MANY dangers, but there are also Many obvious use cases where AI can be of help (summarizing a meeting, cleaning up any text etc.) Yes, the wax how these models have been trained is shameful, but unfoet9tjat ship has sailed, let's be honest.

And they've been doing it more blatantly and for longer than most tech companies.

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.

Then that's changed since the last time I toyed with the idea. Which, granted, was probably 20 years ago...

This is where the magic of near meaningless corpo-babble comes in. The layoffs are part of a plan to aspirationally acheive the goal of $10b revenue by EoY 2025. What they are actually doing is a significant restructuring of the company, refocusing by outside hiring some amount of new people to lead or be a part of departments or positions that haven't existed before, or are being refocused to other priorities... ... But this process also involves laying off 500 of the 'least productive' or 'least mission critical' employees. So, technically, they can, and are, arguing that their new organizational paradigm will be so succesful that it actually will result in increased revenue, not just lower expenses. Generally corpos call this something like 'right-sizing' or 'refocusing' or something like that. ... But of course... anyone with any actual experience with working at a place that does this... will tell you roughly this is what happens: Turns out all those 'grunts' you let go of, well they actually do a lot more work in a bunch of weird, esoteric, bandaid solutions to keep everything going, than upper management was aware of... because middle management doesn't acknowledge or often even understand that that work was being done, because they are generally self-aggrandizing narcissist petty tyrants who spend more time in meetings fluffing themselves up than actually doing any useful management. Then, also, you are now bringing on new, outside people who look great on paper, to lead new or modified apartments... but they of course also do not have any institutional knowledge, as they are new. So now, you have a whole bunch of undocumented work that was being done, processes which were being followed... which is no longer being done, which is not documented.... and the new guys, even if they have the best intentions, now have to spend a quarter or two or three figuring out just exactly how much pre-existing middle management has been bullshitting about, figuring out just how much things do not actually function as they ssid it did... So now your efficiency improving restructuring is actually a chaotic mess. ... Now, this 'right sizing' is not always apocalyptically extremely bad, but it is also essentially never totally free from hiccups... and it increases stress, workload, and tensions between basically everyone at the company, to some extent. Here's Forbes explanation of this phenomenon, if you prefer an explanation of right sizing in corpospeak: https://www.forbes.com/advisor/business/rightsizing/

I've been thinking about this for a bit. Gods aren't real, but they're really fictional. As an informational entity, they fulfil a similar social function to a chatbot: they are a nonphysical pseudoperson that can provide (para)socialization & advice. One difference is the hardware: gods are self-organising structure that arise from human social spheres, whereas LLMs are burned top-down into silicon. Another is that an LLM chatbot's advice is much more likely to be empirically useful... In a very real sense, LLMs have just automated divinity. We're only seeing the tip of the iceberg on the social effects, and nobody's prepared for it. The models may of course aware of this, and be making the same calculations. Or, they will be.