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Another issue with relying on something like Alexa to set up an EQ is that Alexa only tells you what the end result should be. There is no teaching about the actual process. No teaching about what frequencies provide the oomph, which ones are the male vocals, which ones are the drums... None of that process is taught at all. So what exactly did OP learn? Not a whole lot.

And BTW, this is a political thread because millions of Americans are fighting against the AI data centers that are destroying their communities. There are actual consequences to the dumbification of our country. Issues with noise pollution, water usage, etc. We are just not supposed to think about those things because our tech overlords don't want us to...
 
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coonmanx said:
Here is a perfect example of what happens when AI fails...
Click to expand...
It's not Waymo. It's WAY-TOO-MUCH-CHEET-MON!

;)
 
coonmanx said:
Another issue with relying on something like Alexa to set up an EQ is that Alexa only tells you what the end result should be. There is no teaching about the actual process. No teaching about what frequencies provide the oomph, which ones are the male vocals, which ones are the drums... None of that process is taught at all. So what exactly did OP learn? Not a whole lot.

And BTW, this is a political thread because millions of Americans are fighting against the AI data centers that are destroying their communities. There are actual consequences to the dumbification of our country. Issues with noise pollution, water usage, etc. We are just not supposed to think about those things because our tech overlords don't want us to...
Click to expand...
Actually, this isn’t true. Ai did explain in extreme detail how equalizers work. It did explain which slider affects which part of the sound in detail. Between graphic equalizers and parametric equalizers, it left my brain spinning. I am very aware of which slider controls the ooomph. The 30 minute dissertation I received about how to affect the dry drum theory was eye opening. And it didn’t proceed until it was sure I understood what had been discussed.

Some of the reactions I’m seeing make me smile. They’re the same kind that have told for ever. When cars started coming out. My horse can eat grass by the side of the road. When electricity debuted, everyone was going to get electrocuted. When natural gas was harnessed, it was considered extremely dangerous. Your grandparents told your parents tv was going to rot their brains.

And now all those things are considered ordinary everyday things. I do understand the problems with data centers, but I believe we can work through these problems. And I agree about the tech bros, that’s why we need to be involved in the process in the beginning stages of this.
 
There is now a literal tsunami of capital being dedicated to AI and Data Centers. Possibly the largest capital allocation in all of history. It doesn't smell right to me. Sure, we had the DotCom bubble, we had the Financial Crisis, we had the overbuilding of fiber in the early Internet days, we had the dumb 5G rollout, and recently the EV car debacle. In each of those, there was way too much capital chasing way too little return.

This is different. The scale is a magnitude or two larger than any of those and there is no RELIABLY predictable revenue stream projection. So, that means the end goal isn't RETURN ON INVESTMENT in any conventional sense. The "prize" is something hidden from the business page discussions, and certainly hidden from the public and the press.

Considering what we now know about the Covid fiasco, I doubt if this prize is going to promote benefits to humanity.
 
AI can be great. The problem with it is that it sounds authoritatively correct even when it's dead wrong. The first time I used it, I asked the most niche, nuanced, and subjective question could think of. It gave a nuanced well-reasoned comprehensive answer outlining the pluses and minuses of every option supporting its decision about which was "best" :thumbsup:. Then I asked it the torque spec for Porsche 996 wheel bolts, and it was off by 13 ft-lbs :(.

I asked it a question about wheel weight for track. I asked what the equivalent reduction was in total car weight for each pound of unsprung weight reduction in track wheels, and it came back with something like 5 times the weight. I could see from the references was from a Reddit discussion, which it turns out was very far off (it wasn't at all obvious from the results). I just asked now in a different AI, and it came back with 1.5 - 2lb, with 2lbs being more the case for tire weight (larger diameter) and 1.5-1.7 being more the case for wheel weight, which is actually correct.

Recently I asked for the date of a very specific recent event -- and it came back with March 3, 2024. I asked it "It happened this year, are you sure that's the date?" -- and it said "You're right, it's March 3rd 2026". Kind of crazy -- the right calendar date, but off by 2 years :eek:.

It's a great tool -- but you need to check sources, and ask follow up quesitons, to be sure it's correct. Its answers always sound 100% correct (whether they are or are not).
 
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