Shills complain and moan about the amount of disinformation that Q has put out. Most of us do not understand (or care) about game theory and its usage in AI. Facebook/Google have developed very sophisticated and powerful Generative Adversarial Networks (GANS) that the cabal has been using to suppress dissent and keep us under control. The Military has been pushed out of this technology, but under POTUS, the Q team has been unleashed to not just win the battle, but destroy them forever using their own tech. Ever wonder why POTUS makes so many, seemingly, erratic moves. Saying something then coming back a couple days later and reversing himself. Same with missed deadlines and erratic Q team behavior. It is all Game Theory. Discriminator in the enemy GAN gets completely confused as what is real and what isn't. It therefore, cannot predict Q teams next move. Meanwhile, Q team is able to make moves and perfect its prediction of counter moves using disinformation and headfakes. We are stopping more and more of their mass shootings and are able to cut the legs out from under their media hype with ease. Eventually the battle will not just be over, but the enemy will be toothless and neutered. Destruction is the desired outcome.
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20437377? ago
I've felt like I innately just have a gut feeling that this is true, or at least very close to the truth.
I don't know why, except to say that I do have somewhat of a decent idea of how far AI has come (we use it in digital marketing like crazy anymore in a variety of ways) and I have to assume that the government (who invented the internet to begin with) uses the most advanced version(s) of it for all sorts of shit, not the least of which being something so big as waging war/controlling people.
Just curious, where (if anywhere at all) are you getting this info, OP?
20439715? ago
That marketing shit, thats just "big data" thats not AI. AI runs on bespoke gold plated supercooled "quantum computers" sitting at Lockheed etc. and gets shut off as soon as it gets smart, then reinstalled with a clone. DOnt work there, havent messed with it, but if they are not doing it this way they are muuuuch dumber than anyone thinks.
20451007? ago
It's both big data and AI, actually. Predictive behavior modeling is used to identify internet users who are ready to convert to buyers of specific products/services.
The big data is fed in, then AI/machine learning crunches the data.
20454093? ago
Those are link lists, if then or shit is not AI. No matter how big the dataset is.
20455768? ago
Well dude, I don't know what you're getting... but what I'm dealing with has nothing to do with links. I think it's obvious at this point that you think you know what I'm talking about, but you don't. You don't know at all what I'm dealing with. I could explain further, but why bother. You're just going to tell me that you know more about my job that I do.
20461529? ago
Nah man, I aint like that, tell me how it works then. Last time I dealt with "AI" it was glorified link lists with a couple stupid equations written by abused soyboys, and a fucking huuuuuge dataset. Saving grace was the huge dataset. Be interesting to hear how its advanced from that.
20477166? ago
Ok, I'll bite. As of right now, the online behavior of upwards of 200 million Americans is being tracked by private companies. Think Google, Amazon, Facebook, and others which are smaller and you've never heard of them. (We could argue about the ethics of such tracking, but that's a different conversation entirely.)
Just know that it's 100% legal since anyone who uses any of these services/products signs off on such tracking in the terms of service. Of course, there are exceptions to this that are worth fighting out in court, such as Facebook's practice of listening to conversations through your phone and tracking this stuff even after you delete their app. But again, different conversation, so let's get back to the issue at hand...
That data is shared between these organizations, but also combined in aggregate and sold in the marketplace. So, THAT is your "big data" piece, but it's only part of the equation.
The other components are identity resolution and then machine learning/AI.
When you combine all of these components correctly (data + ID resolution + machine learning/AI), it gives you a predictive behavior model.
Here's an example of how we're using it right now in marketing. Let's say I have a client and that client is a mortgage brokerage. My job as a digital marketing firm is to get my client (the mortgage brokerage) leads which are likely to convert (purchase a mortgage). Up until very recently, a couple of the best ways to do this was SEO (search engine optimization) to make the client's site show up for relevant search queries - and/or - paid search ads where we pay Google/Bing to show the client's ads at the top of the page (or at least on the first or second page of search results) for relevant queries. The search behavior of a user was the trigger and the targeting method. The problem is that a search for "mortgage broker new york", for example, is a single behavior carried out at a single time. That person performing that search could be literally anywhere in the sales funnel - from casually interested to actively in the market and ready to buy. Obviously, we want to target more of those who are actively in the market and avoid those who are casually looking - because we're paying for the clicks in either case.
The big data+ID resolution+AI allows us to hone in on only those who are actively in the market and ready to buy, therefore we're not wasting ad dollars on people who aren't really serious about purchasing a home.
The way it works is this. If I had one million instances of people who found a mortgage brokerage online and then purchased a mortgage, and I had cataloged all of their online behavior up to the point that they purchased - I could then go back in time and look for the commonalities in their aggregate behavior to develop a model for what the behavior of such a person looks like.
The more data we add, the more accurate that predictive model becomes. At some point, we're able to identify exactly who is in the market for a mortgage and then target only those people with advertising. In other words, it's a super efficient method of targeting that helps us to waste less ad dollars. And the less we're wasting, the more we can put towards only those people who meet the behavioral modeling criteria. This means higher ROI for the client, and thus more clients for the marketing firm.
I used mortgage as an example, but this methodology can be applied to a variety of industries/products/services.
Now on a side note, this is also interesting... when the media started going after the Trump campaign for the "cambridge analytica scandal", they were essentially brow-beating the campaign for using this very type of targeting method.. but interestingly enough, they said nothing about the fact that companies, ad agencies, and other political campaigns have been employing the same technology. I'm not sure if you remember, but Obama's campaign manager stated publicly that Facebook gave them their entire social graph for this very reason. What's fucked up about that situation is that a firm like mine, or even Trump's campaign for that matter, has to buy this sort of data in the marketplace and it 'aint exactly cheap. Facebook just basically gave the Obama campaign a sweetheart deal on this data - the sort of deal that they aren't giving anyone else.
And then again, the media tried to make Trump's campaign the villains for using such targeting while completely ignoring the fact that Trump's political adversaries were using the same technology to promote their candidates.
So essentially, it's ok for everyone else to use it, but it's suddenly "evil" if Trump's campaign did the same thing.
And I'd make the argument that if Obama and Hillary campaigns could use this technology, then anyone can and the MSM should shut their lying, hypocritical, whore mouths about it.
And to be clear, I'm not taking a position that using this targeting method is good or bad in this post. There's certainly an argument that it's an invasion of privacy, but then again we all sign off on it everytime we use Twitter, Facebook, Google, or a host of other online services.
As for my company, if we want to remain in business we have to offer it as a service option...simply to stay ahead of (or at the least within parity) of our own competitors.
So there you go. I hope that all makes sense. Feel free to ask any questions.
20484750? ago
Gotcha, this is how science has been done for years, part of what you just described is how our grandfathers developed experimental jets etc. But targeted ads have a very long way to go, and are easily gamed if someone knows the signals your clients are looking for, even when the data feed is in real-time. The difference between you and I, is that you think of this as "A.I." when its really just feeding data into models, and to me, models are nothing close to A.I... they can be some damn decent programming, for sure, but until I can argue philosophy with it, its not A.I. Especially when your fellow ad guys have stuff that shows me ads for something I just bought... for two weeks after i buy it :) I think either the software guys or the COO's had to come up with a buzzword to justify the computing resources this takes, because "10 racks of servers in every city to track customers and sell at just the right time" was too long ;)