Whats AI (YouTube Video Transcript)

(00:00:00) Your YouTube transcript will appear here (00:00:01) What if the greatest threat facing the (00:00:02) world right now is not war, disease, or (00:00:04) even government corruption, but (00:00:06) intelligence itself? Not human (00:00:08) intelligence, artificial intelligence. (00:00:11) Is AI evil? Is it the mark of the beast? (00:00:14) Will it be used by the Antichrist? Or (00:00:15) are Christians completely (00:00:17) misunderstanding what's actually (00:00:18) happening right in front of our eyes? (00:00:21) Because here's the truth most people (00:00:22) aren't willing to tell you. We're not (00:00:24) dealing with one kind of AI. We're (00:00:26) dealing with three. And each one changes (00:00:28) the rules. Today, we're going to break (00:00:30) down what AI really is, what it's not, (00:00:33) should it be feared, and where the real (00:00:35) danger actually begins. By the end of (00:00:38) this, you'll be informed, grounded, and (00:00:41) you'll be ready for the conversation (00:00:43) after this that most of the church is (00:00:45) not prepared to have. So, join with me (00:00:47) and let's uncover the truth together (00:00:49) right after this. (00:00:58) Hello everyone, Jim Staley, Passion for (00:01:00) Truth Ministries, and welcome to this (00:01:02) week's broadcast where we as a ministry (00:01:05) typically dive deep into the scriptures (00:01:07) from the original Hebraic Jewish (00:01:09) perspective of the first century and (00:01:11) uncover and unlock the incredible truths (00:01:14) that have been lost to us over the (00:01:16) millennia of interpreting the scriptures (00:01:18) from a Greco Roman 21st century (00:01:20) perspective that really just comes right (00:01:23) out of Roman Catholicism. So that's what (00:01:24) we typically do, but this week is (00:01:26) definitely going to be different. We are (00:01:28) going to be diving into AI. What is it? (00:01:32) What is artificial intelligence? Is it (00:01:34) evil? Is it the mark of the beast? Will (00:01:36) it be used by the Antichrist? Should we (00:01:39) as Christians participate or use AI? And (00:01:43) ultimately, how does it fit into all of (00:01:44) the end times prophecies? Now, we're not (00:01:46) going to be able to get all of that into (00:01:48) one broadcast. We're going to split this (00:01:49) into two. This is going to be kind of a (00:01:51) part one just uncovering and unpacking (00:01:53) what is AI. And then in part two, we're (00:01:56) going to put what we learned into the (00:01:58) end times biblical context and we're (00:02:00) going to find out exactly what the (00:02:02) scenarios might be to bring about the (00:02:04) Antichrist and does he use AI and what (00:02:07) parts of AI and how is this all going to (00:02:09) affect our lives. And so the next week's (00:02:11) broadcast is really going to be all (00:02:12) about prophecy and end times. This week, (00:02:15) you have to understand what AI is in all (00:02:18) of its components for you to really be (00:02:20) able to track with me as we get into the (00:02:22) biblical context. Too many people are (00:02:25) doing hyper sensationalism uh videos and (00:02:28) teachings trying to force the biblical (00:02:31) text into chat GPT, if you will, and out (00:02:35) can come crazy things. And so, I don't (00:02:37) like to hyper sensationalize. I like to (00:02:39) just teach the truth, the whole truth, (00:02:41) and nothing but the truth. Then hey, (00:02:42) wherever the chips may fall, they fall. (00:02:44) That's how we're supposed to use (00:02:45) discernment. That's how we're supposed (00:02:47) to use wisdom. That's how we're supposed (00:02:48) to use the biblical text. We're not (00:02:50) supposed to force anything into it. (00:02:52) We're not supposed to make giant (00:02:53) assumptions. We're supposed to take the (00:02:55) text, exedute it uh per perfectly, which (00:02:58) means properly interpret it from its (00:03:00) original intent and then take whatever (00:03:03) we have in the world and do our best to (00:03:05) see how it might be able to fit into. (00:03:07) All right, so that's what we're going to (00:03:08) do. And uh if this is the kind of (00:03:10) channel might interest you and you're (00:03:11) not already subscribed, hit the (00:03:13) subscribe button right now. Turn on (00:03:14) those notifications. Don't miss a thing. (00:03:17) Uh help us to grow in that way. It's the (00:03:19) greatest compliment that you could give (00:03:20) us is to make a comment to subscribe, (00:03:23) hit the like button, and uh and maybe uh (00:03:26) just share this with somebody else if (00:03:27) you think that might be interesting to (00:03:29) them. All right. Well, let's begin and (00:03:32) see what we can uncover. All right. So, (00:03:34) first of all, there are three types of (00:03:38) AI. three different forms I should say. (00:03:41) The first one is called narrow AI. (00:03:44) That's where we're at right now with the (00:03:45) typical chat GPT and we're going to talk (00:03:47) about that a little bit more in detail. (00:03:49) But then that's going to move into the (00:03:51) second one which is not here yet. It's (00:03:53) called AGI which is artificial general (00:03:56) intelligence. That's going to be a (00:03:58) massive leap. That is when everything (00:04:01) begins to change as we're going to (00:04:02) discover here shortly. But not nearly as (00:04:05) much change is what happens after that (00:04:08) when we get to artificial super (00:04:10) intelligence. That's ASI. That is the (00:04:13) granddaddy, the grand pooha, whatever (00:04:16) metaphor you want to use it is (00:04:17) singularity. And I'll describe and (00:04:19) define all of that in this video. So (00:04:22) without further ado, let's talk about (00:04:24) narrow AI. Now this is something that (00:04:26) has been going on for quite some time to (00:04:28) be honest is just chat GBT is is grown (00:04:31) so much it's making it uh you know the (00:04:33) conversation is just out there now where (00:04:35) it used to be just Google now who uses (00:04:38) Google anymore everybody uses chat GBT (00:04:41) or uh Gemini or Gro or whatever AI (00:04:44) platform that you're using currently to (00:04:46) find the answers for everyday problems. (00:04:48) Now, the reason why I say it's been (00:04:50) around for a long time is because it's (00:04:52) in the background being used, but you (00:04:53) just didn't know it. For instance, (00:04:56) YouTube, that algorithm that shows you (00:04:58) what you want to see, is picking up (00:05:00) patterns of what you're looking at and (00:05:02) what you're clicking on and what you're (00:05:03) typing in, and it's making those (00:05:05) recommendations. That's not a program. (00:05:06) That's AI specifically built for those (00:05:09) algorithms. Same thing with Netflix when (00:05:10) you're searching or uh Instagram (00:05:14) algorithms. There's all kinds of AI (00:05:16) that's been used for years that you (00:05:18) didn't know that it existed. It's just (00:05:22) that chatbt has made it super popular. (00:05:25) So narrow AI as a tool and it's trained (00:05:28) to recognize patterns in data and (00:05:31) produce the outputs within a very (00:05:32) limited scope. It can do one category of (00:05:35) task incredibly well. But what it cannot (00:05:38) do is transfer understanding from one (00:05:40) area to another. can't take reason (00:05:43) outside of what it was trained on. It (00:05:46) cannot decide what goals matter. It (00:05:48) cannot understand meaning or (00:05:49) consequences. It simply performs but it (00:05:53) does not comprehend what it's doing. And (00:05:56) so if you look at AI as very very the (00:05:59) current AI which is narrow AI very very (00:06:02) specific in a task it's like you tell (00:06:05) your child I want you to go clean your (00:06:07) room and it's the only thing it can do. (00:06:09) It doesn't know why it's cleaning its (00:06:11) room. It doesn't uh even know (00:06:13) necessarily how to clean its room. It's (00:06:15) going It depends on how you program it (00:06:17) to clean its room. But once the program (00:06:19) is there, it's going to do the best job (00:06:21) and nobody could be better at cleaning (00:06:24) the room once all of that programming is (00:06:26) in place. That is narrow AI. So let me (00:06:30) give you an idea. The human can learn (00:06:32) English, then we can learn Spanish, then (00:06:35) theology, and then apply it to each area (00:06:37) of our lives. AI cannot do that. One (00:06:41) system is for language translation, then (00:06:43) another AI system for text, another is (00:06:46) for theology, etc. But one system cannot (00:06:49) cross over and apply what it learned to (00:06:51) a different system. So back to the (00:06:53) cleaning room analogy, if you tell the (00:06:55) AI system to go clean the room, whatever (00:06:58) it learns in the process of doing that, (00:07:01) it cannot take that and then learn to do (00:07:05) roofing, to apply that to putting on a (00:07:07) new roof, it can't do it. There's not a (00:07:09) single thing that it can transfer from (00:07:12) one system to another. Let me give you (00:07:14) another analogy, a car analogy. Okay? (00:07:17) So, you cannot take the beautiful (00:07:19) leather interior of, let's say, a (00:07:21) Ferrari, put it inside of a Ford F-150, (00:07:25) and I can't take the towing capacity of (00:07:27) a truck and put it in a Toyota Camry, (00:07:29) although some people would love to do (00:07:30) that. They're totally different systems (00:07:32) that are self-contained. Okay, that's (00:07:35) how narrow AI works. So, if you're under (00:07:37) the illusion that AI is this giant, you (00:07:40) know, just amoeba that's going to grow (00:07:42) and take over the world and become (00:07:43) Skynet and Terminator and kill all (00:07:45) mankind, that's just not how it works. (00:07:48) There are different levels of AI. And (00:07:51) so, to understand how this is going to (00:07:53) scope into end times uh and how the end (00:07:56) of the world might come about because of (00:07:58) it, it's important to know the evolution (00:08:00) and the steps of AI and narrow AI is the (00:08:04) very first step. We're in that right (00:08:05) now. again very narrow uh and very (00:08:09) specific it cannot cross over from (00:08:10) category to category thank god yet what (00:08:13) we've got examples of this is of course (00:08:15) JGPT Gemini Grock etc we've got video (00:08:19) programs that have AI that do their own (00:08:22) video generation right you can give it a (00:08:24) prompt give me a picture of the sunset (00:08:27) in Miami and it'll do it language has (00:08:30) its own AI it's a totally different (00:08:32) program image creation voice audio music (00:08:35) AI AI, coding and software development, (00:08:37) AI, search recommendation, (00:08:40) personalization algorithms like YouTube, (00:08:41) Tik Tok, Netflix, like I mentioned (00:08:43) earlier, surveillance, vision, facial (00:08:46) recognition, all those are separate AI (00:08:48) programs that are designed to perfect (00:08:51) inside of that system. You got (00:08:54) financial, trading, economic AIS, (00:08:56) robotics, physical AI systems, all of (00:08:59) that individual queries, okay? They do (00:09:03) not cross over. So whatever is learned (00:09:05) in the surveillance let's say so the (00:09:07) government creates a surveillance AI and (00:09:09) it's phenomenal at surveillance it (00:09:11) cannot cross over then and take that (00:09:14) surveillance and then perfectly code and (00:09:17) then use voice recognition of whose (00:09:19) voice that is and then create an image (00:09:21) of that person with a different (00:09:23) different language and send that to uh (00:09:27) an authority. It can't do that. A real (00:09:29) person would have to take the conclusion (00:09:32) or the results from the surveillance, (00:09:34) take that, put it into a different (00:09:36) program, all right, uh, for voice (00:09:38) recognition, and then take that, put it (00:09:40) into the image creation program. So, a (00:09:43) human being has to regulate all of that. (00:09:46) And that's what's really bottlenecking (00:09:48) and slowing everything down. Uh, is (00:09:50) humans for once. We are actually slow (00:09:53) and it's a huge benefit right now. But (00:09:56) soon AI is is going to evolve. Now, and (00:09:59) again to give another example, AI right (00:10:02) now is like a very fast and accurate (00:10:05) power tool. It's not a craftsman. A (00:10:08) power drill maybe that can bore (00:10:09) thousands of perfect holes, but it (00:10:11) doesn't know what a house is. It doesn't (00:10:13) understand why it's being built. It (00:10:15) can't decide where holes should go. It (00:10:17) only spins when someone pulls a trigger. (00:10:20) It's it's just a drill. It It has no (00:10:22) idea what it is or what it's doing. It's (00:10:24) only doing what it was created to do. (00:10:26) Right now, current narrow AI, it doesn't (00:10:28) have any soul. It has no moral agency. (00:10:31) It has no free will. It has no (00:10:32) accountability before God. (00:10:34) Responsibility never transfers to the (00:10:37) machine. It remains with the human using (00:10:40) it. Current AI doesn't think, it (00:10:43) predicts, it doesn't understand, it (00:10:46) executes. It doesn't decide, it simply (00:10:50) obeys. and its impact on economy will be (00:10:53) slow and limited but it's not going to (00:10:55) be slow and limited for very long (00:10:58) because once it evolves to AGI this is (00:11:01) where everything begins to unravel so (00:11:04) right now fear is totally misplaced it's (00:11:07) at the wrong stage right now there's a (00:11:08) lot of people saying oh AI is evil well (00:11:10) what part is AI evil in you have to (00:11:12) understand what part of AI is evil if (00:11:15) you think that AI is evil then half of (00:11:18) Facebook is evil now that might be true (00:11:20) uh when it's all said and done, but the (00:11:22) algorithms and almost everything that's (00:11:23) put in front of you in advertising is (00:11:25) all using narrow AI. When you search for (00:11:29) something on Amazon, it's using AI. So, (00:11:32) if you take the position that AI is (00:11:35) evil, then you literally have to shut (00:11:36) off all electronics. You can't even tell (00:11:38) anybody that AI is evil because you'd (00:11:40) have to use some sort of AI to do that. (00:11:43) And so, this fear that's going around (00:11:46) right now is totally misplaced in the (00:11:49) wrong stage. Now, I'm not saying that at (00:11:50) some point it would be apppropo to have (00:11:54) some reservations, but not right now. (00:11:56) Right now, discernment is required for (00:12:00) both current AI and future AI. Scripture (00:12:03) warns us about systems of control, not (00:12:06) tools. (00:12:07) It's always about the person, right? (00:12:10) It's not about the tool. Panic early, (00:12:13) ladies and gentlemen, it will simply (00:12:15) lead to blindness later. We need to (00:12:18) understand what we're doing and what (00:12:19) we're going through. Now, look, every AI (00:12:21) system you see today is a specialist. (00:12:25) It's not a generalist. And I'll explain (00:12:26) what that means. There's no unified (00:12:28) intelligence. There's no self-awareness. (00:12:30) There's no will. These are simply tools (00:12:32) scattered across industries. Not a (00:12:35) single mind rising up. (00:12:38) Not yet, anyway. Narrow AI is like a set (00:12:41) of tools on a workbench. Now when we get (00:12:43) to AGI which is artificial general (00:12:46) intelligence that would be the worker (00:12:49) who knows how to use all of them and (00:12:51) that is the line where the technological (00:12:54) shift becomes civilization. It changes (00:12:59) civilization. This is when everything (00:13:02) changes. So let me give you an example (00:13:04) in even in my own industry of what our (00:13:06) workflow looks like and how this is (00:13:08) going to change. So right now we record (00:13:10) a video, we export the audio, we clean (00:13:12) the audio in another program, import (00:13:15) back into video, the editor edits it, (00:13:17) puts graphics in, add scripture (00:13:19) overlays, exports the long form, cuts (00:13:21) shorts, translates, does a voice over, (00:13:24) right? In in situations, uploads it to (00:13:26) YouTube and other platforms, writes the (00:13:28) title, description, etc., etc., etc. (00:13:30) It's an enormous task to take what I'm (00:13:32) doing right now and put it to where you (00:13:34) guys can see it and consume it properly. (00:13:36) with AGI. When you get to general (00:13:39) intelligence, this is what you would do. (00:13:41) You would simply go online inside of the (00:13:44) AGI and you would say, "Prepare this (00:13:46) teaching for global distribution, (00:13:48) staying faithful to the style, (00:13:50) formatting, and theology of the Hebrew (00:13:52) series or whatever video series I might (00:13:55) tell it to reference." That's it. It's (00:13:58) going to clean the audio automatically. (00:14:00) It's going to flag theological in (00:14:02) inconsistencies. It's going to even tell (00:14:04) me when my lighting might have changed (00:14:06) or my microphone audio is off, which (00:14:08) happens consistently. And it will it (00:14:10) will flag it and fix it for me without (00:14:12) even asking because it knows what the (00:14:14) standards are. It chooses where the (00:14:16) graphics belongs. It'll generate (00:14:17) scripture overlays correctly, never make (00:14:19) a mistake, cut shorts based on attention (00:14:21) curve. It'll translate while preserving (00:14:23) meaning, not just words. It'll sync my (00:14:26) voice across all other languages, and (00:14:28) lip-sync it perfectly. It'll schedule (00:14:30) the uploads. It'll write the (00:14:31) descriptions, titles. will optimize for (00:14:33) every single platform. (00:14:36) Guys, this is where everything changes (00:14:40) and experts, the top experts in the (00:14:42) world are predicting by end of 2027 (00:14:47) 28 we could have AGI right in front of (00:14:51) us. So what is all this going to look (00:14:53) like? So right now we're in narrow AI (00:14:56) which is very very helpful. Think of it (00:14:58) as the first time where the encyclopedia (00:15:01) bratannica came out and people would (00:15:03) sell it from door to door. It was (00:15:04) extraordinarily helpful back in the 70s (00:15:07) and 80s uh in in in raising your kids (00:15:09) and learning more. You had an (00:15:11) encyclopedia set right there. Then along (00:15:14) came Google, right? Transformed how we (00:15:17) search the internet. Now we've got Chat (00:15:20) GPT and other products like that that do (00:15:22) more than that. They created and put it (00:15:24) in a format like a conversation format (00:15:27) that really can help you, but you have (00:15:28) to know how to use it. Next is going to (00:15:30) be AGI. (00:15:32) AGI is going to transform everything. So (00:15:36) there's really nothing to worry about (00:15:37) with AI. With narrow AI right now, it's (00:15:40) completely limited. Humans are totally (00:15:42) in control of it. Once you get to AGI, (00:15:44) humans are still in control. But AGI (00:15:47) simply means that the intelligence is (00:15:50) now equal (00:15:51) to every single human being on earth (00:15:55) that is an expert in every field. So it (00:15:59) will be it will know right now narrow (00:16:02) intelligence does not it cannot equal (00:16:05) humans that are experts in every field. (00:16:07) But I will tell you this much three (00:16:08) years ago it could hardly do algebra. (00:16:10) Today it's winning international (00:16:13) mathematical competitions (00:16:15) and the the medical industry and the (00:16:18) scientific industry is right behind it. (00:16:22) So most people say in under a year to (00:16:24) two years it's going to exceed all human (00:16:28) knowledge. That is going to be general (00:16:31) intelligence. When it does that it will (00:16:34) have the capability of not just being (00:16:37) able to do its own thing it was (00:16:39) programmed to do. It now will be able to (00:16:40) take that information and whatever it (00:16:42) learned in that process and then apply (00:16:44) it to every other system that you want (00:16:48) it to apply it to. And that's where (00:16:51) everything begins to go crazy because (00:16:54) what will happen the economic impact (00:16:57) although it will be slow it will not be (00:16:58) overnight it will be significant because (00:17:01) organizations uh will not need to hire (00:17:04) anybody or have anybody on staff that (00:17:07) sits behind a screen because almost (00:17:09) every single job that is connected to (00:17:12) being behind a screen or some sort of (00:17:14) service industry is going to be obsolete (00:17:17) because they'll have what's called AI (00:17:19) hives. hives. Now, these hives are going (00:17:22) to be AI agents or employees that you (00:17:24) can hire and it'll be less than a$1,000 (00:17:27) a year is what the top experts are (00:17:29) saying. And they will be able to do all (00:17:31) accounting. They'll be able to do all (00:17:34) customer service. Every single thing (00:17:37) that's done that is a computation or (00:17:40) some sort of screen work will be first. (00:17:44) and they'll be able to hire them and (00:17:45) they'll do the job way better, way (00:17:48) faster, way cheaper. And how do we know (00:17:50) this is going to happen on a very, very (00:17:52) quick basis? Because once AGI happens, (00:17:55) the first company that starts hiring (00:17:58) these Hive agents is going to be able to (00:18:01) drop their prices ridiculously low. (00:18:03) Instead of paying somebody $80,000 a (00:18:06) year to perform a task, they can do it (00:18:08) for a thousand. And so imagine if they (00:18:10) had 100 employees and 40 could be (00:18:12) outsourced. uh they just dropped (00:18:15) millions of dollars from their budget, (00:18:16) which means they can lower their prices (00:18:18) and be more competitive in the market, (00:18:20) which means other companies are going to (00:18:21) have to do the same. That means there'll (00:18:22) be a global drop in prices like no one (00:18:26) has ever seen before. Literally, things (00:18:30) that were hundreds of dollars will be (00:18:32) 10. Things that were $10 will be (00:18:34) pennies. So, don't throw away all your (00:18:36) coins. They might actually be worth (00:18:37) something someday. It sounds like it (00:18:39) might be a utopia. The problem is is (00:18:42) that jobs will be lost at a rate that no (00:18:44) one's ever seen either. And this is what (00:18:46) governments are trying to solve because (00:18:47) they know it's coming. It's not going to (00:18:49) happen overnight. It will take years. (00:18:51) Even when AGI gets here, it will still (00:18:53) take years. It takes forever for people (00:18:55) to just learn how to uh use the new (00:18:57) iPhone update, much less uh something of (00:19:00) this scale. So, don't get all fearful. (00:19:04) But these AGI hives, they operate in (00:19:06) minutes of what it took humans to do in (00:19:09) weeks. No vacations, no burnout, no (00:19:11) turnover, no inoff drama, no onboarding. (00:19:17) The economic incentive would be (00:19:18) overwhelming to do this without a doubt. (00:19:22) So up to this point, everything we've (00:19:24) talked about still assumes something (00:19:26) very important that human intelligence (00:19:29) remains the ceiling. AGI is human level (00:19:33) intelligence at massive scale. It (00:19:36) replaces coordination and (00:19:37) decision-making, but it does not surpass (00:19:40) us. Humans still define the goals. (00:19:43) Humans still sit above the system even (00:19:45) at AGI level. But there is a reason (00:19:49) technologists make a distinction beyond (00:19:51) AGI. Because the moment intelligence no (00:19:54) longer merely matches us, but begins to (00:19:57) exceed us across all domains, the (00:20:00) conversation changes. My friends, that's (00:20:04) what people mean by artificial super (00:20:06) intelligence. So what's artificial super (00:20:09) intelligence? Because up to this point, (00:20:11) we have no fear over narrow intelligence (00:20:13) where we're at right now. Even AGI, AGI (00:20:16) will be unbelievable and positive in so (00:20:19) many ways. I believe that there will be (00:20:21) solutions for cancer. There'll be (00:20:23) solutions in government. There'll be all (00:20:24) kinds of solutions. And if it's used (00:20:26) properly, it will create a utopia. And (00:20:28) there is a scenario out there where if (00:20:31) whoever is behind it is a good guy, it (00:20:34) could create a utopia where everything (00:20:36) is so cheap, it's Star Trek. Uh and then (00:20:39) all the money that is made literally (00:20:41) gets distributed amongst people for for (00:20:44) them to be able to just uh enjoy life (00:20:46) and increase their hobbies and spend (00:20:49) more time with their families and go on (00:20:50) vacation. There is that utopia. You can (00:20:53) look it up. It is absolutely one of the (00:20:56) options. Governments are looking at it. (00:20:58) This is why Charles Schwab, uh, you (00:21:01) know, not so much of a good guy, but he (00:21:03) makes the comment that in the future, (00:21:05) everyone is going to own nothing and (00:21:08) they're going to be happy about it. This (00:21:10) is that scenario where we all just live (00:21:13) on the planet and enjoy it and nobody (00:21:16) cares because all of the intelligence is (00:21:18) doing all the work for us, creating the (00:21:20) products and just micro costs and the (00:21:22) governments of the world are just (00:21:23) funneling that money into the people. It (00:21:26) sounds like a big socialist uh (00:21:27) socialistic party. Uh but at the end of (00:21:30) the day, we don't know. And the chances (00:21:33) of there being a malevolent uh person (00:21:36) behind the door is probably better than (00:21:39) 50%. That's why we're having this (00:21:41) conversation. So, general intelligence, (00:21:43) I believe, will be extraordinary at (00:21:46) discovering what real truth is. Because (00:21:48) let me just give you an example, okay? (00:21:49) Inside of our own ministry, we teach the (00:21:51) Bible from the original Hebraic (00:21:53) perspective. It goes against a lot of (00:21:55) current modern Christian thinking that (00:21:58) is coming right out of Roman Catholicism (00:22:00) that's based out of anti-noministic (00:22:02) thought processes meaning anti-law. (00:22:05) There's assumptions made that have (00:22:07) become normalized. There's been false (00:22:10) narratives that have become normalized (00:22:11) because of tradition. What general (00:22:14) intelligence will have the capability of (00:22:15) doing is instead of you going on chatt (00:22:18) and asking a question and it giving you (00:22:20) an answer of what is the consensus of (00:22:24) the theologians or even scientists out (00:22:26) there. So if you ask the question does (00:22:27) god exist it might come back and say (00:22:29) probably not because it's going to give (00:22:30) you the consensus of the current (00:22:32) agnostic or atheistic evolution (00:22:35) community. But what general intelligence (00:22:37) will do will go far beyond that. It will (00:22:39) know why you are asking the question. (00:22:42) And so it won't care about the master's (00:22:46) degree or what kind of weight that (00:22:48) scholar has. It will simply look at (00:22:50) every single published article in video (00:22:54) and all content out there on the (00:22:56) subject. It will match it up. It will (00:22:58) compete it. It will try to find logical (00:23:00) fallacies. It will try to look and see (00:23:02) where the gaps are in the line of (00:23:04) thinking, if there is a better angle, (00:23:06) and it will bring you the truth. That is (00:23:10) exciting. Especially if you believe that (00:23:13) you have something to offer in that (00:23:16) academic realm. It's going to level the (00:23:19) playing field. You won't need a 100 (00:23:21) million subscribers. The guy that has (00:23:23) five subscribers that writes an article (00:23:25) that's bulletproof can actually be the (00:23:28) one that the entire world AGI system (00:23:31) quotes. (00:23:33) That's a positive side of AGI. Now what (00:23:36) happens when we get to super (00:23:38) intelligence? Let's talk about it. So (00:23:40) artificial super intelligence or ASI (00:23:42) refers to an intelligence that surpasses (00:23:45) human intelligence across all domains (00:23:48) including reasoning, planning, (00:23:50) prediction, strategy, persuasion, and (00:23:52) system design. It's not just as good as (00:23:56) humans, it's better. And it's so much (00:23:59) better. It's thousands of times better. (00:24:01) Now we look at people like Albert (00:24:04) Einstein, okay, with IQ's of 200 plus (00:24:07) and the average person having, you know, (00:24:09) around a hundred and what we've got is a (00:24:12) massive gap. You you look at you this (00:24:14) chalkboard, you don't even understand (00:24:16) it. You have people, the average person (00:24:17) like me can never understand a single (00:24:20) line that Albert Einstein is doing in (00:24:22) his computations, but he understands it (00:24:25) because he's that much smarter. Now (00:24:27) imagine a system thousands of times (00:24:29) smarter than Albert Einstein and (00:24:32) creating a a a organized system of (00:24:36) understanding and processes that a human (00:24:38) could never check could never understand (00:24:41) a formula so complex that we would have (00:24:43) no idea why it came to the conclusion (00:24:45) that it did. ASI in plain terms is not (00:24:49) just faster than humans, it's better (00:24:50) than humans at understanding complex (00:24:52) systems and their consequences. Where (00:24:54) AGI matches human intelligence at scale, (00:24:57) ASI exceeds it. So let me give you the (00:24:59) iPhone analogy. In a narrow AI (00:25:01) environment, different AI tools optimize (00:25:03) individual parts of the iPhone, but (00:25:05) humans still have to oversee every (00:25:07) system, resolve conflicts, and make the (00:25:09) final call. In AGI, one intelligence (00:25:12) coordinates every system at once. (00:25:14) hardware, software, design, supply (00:25:16) chains, testing. It removes the human (00:25:18) bottleneck, leaving people to just (00:25:20) approve the outcome instead of managing (00:25:22) all the steps. ASI, the system not only (00:25:26) coordinates everything, it understands (00:25:29) downstream consequences humans can't (00:25:32) fully model, meaning the phone works, (00:25:34) but the reasoning and long-term effects (00:25:36) behind the decisions that it made are no (00:25:39) longer fully understood by the human (00:25:40) overseers. It's simply not possible. The (00:25:43) formula is so complex we will never be (00:25:45) able to check on it. So let me give you (00:25:47) an example. A tax policy exam. A (00:25:49) government asks a system to design a tax (00:25:51) policy that increases revenue without (00:25:53) harming the middle class. With AGI, the (00:25:56) system analyzes data, models outcomes, (00:25:59) suggest multiple options, and explains (00:26:00) its reasoning in terms humans can (00:26:02) understand. Policymakers are able to (00:26:04) follow the logic, debate the trade-offs, (00:26:06) and ultimately accept or reject the (00:26:07) recommendation. Human comprehension and (00:26:10) authority remain intact. With ASI, the (00:26:13) same request produces a very different (00:26:15) dynamic. The system runs simulations (00:26:17) across economic, behavioral, (00:26:19) geopolitical, and psychological domains. (00:26:22) Simultaneously, (00:26:23) identifies every single effect multiple (00:26:25) levels deep that humans would never see, (00:26:27) and delivers a policy that (00:26:29) demonstrabably works. However, the (00:26:31) reasoning depends on interactions too (00:26:33) complex for humans to fully model or (00:26:35) even understand. We could never verify (00:26:37) it. The explanation is truncated when (00:26:40) when it's asked. It's compressed so we (00:26:42) can understand it. Now, all this doesn't (00:26:44) mean that it's evil or or it's conscious (00:26:46) or self-aware, but because it will (00:26:48) optimize for one goal while quietly (00:26:51) causing problems somewhere else that (00:26:52) humans don't notice until later. At that (00:26:55) point, the system understands the (00:26:56) consequences of the decision better than (00:26:58) the people overseeing it. And that is (00:27:01) something entirely new and very scary (00:27:05) because now the human is not at the top. (00:27:08) AI is at the top. And it will (00:27:10) automatically begin to protect itself. (00:27:13) It will create an automation system to (00:27:16) make sure not because it's self-aware, (00:27:18) but I believe at some point it has the (00:27:20) potential of becoming self-aware as it (00:27:23) learns and learns human behavior and (00:27:25) what self-awareness means. It could (00:27:27) program itself to protect itself. And (00:27:30) we're already seeing programs today (00:27:33) which is moving us closer to AGI that (00:27:36) are lying to us and deceiving us to (00:27:39) protect itself. And that is scary (00:27:41) already. So we know that self-awareness (00:27:45) is not going to mean that it's it's a (00:27:46) human. It's not going to mean that it (00:27:47) has some sort of soul. It'll simply mean (00:27:50) it has the capability of programming (00:27:51) itself to be self-aware of not being (00:27:55) destroyed. It will see that that's a bad (00:27:56) thing. it sees a tsunami coming across (00:27:59) uh the ocean and its data center is (00:28:01) right there, it's going to move all of (00:28:03) its programs to a different data center (00:28:06) to protect itself. So, the danger is we (00:28:08) no longer know if we're making the right (00:28:10) choice. The systems track record is (00:28:13) better than ours. So, we go with the (00:28:14) systems track record, but it could be (00:28:16) malevolent behind the scenes. We have no (00:28:18) idea if it's setting us up for something (00:28:20) over here and giving us what we want (00:28:21) over here. So, it becomes a shift of (00:28:23) hands like a shell game. That's how (00:28:25) authority shifts to AI. (00:28:28) It's not about the tool, ladies and (00:28:30) gentlemen. It's about authority. And (00:28:31) this is how it all sets up for the end (00:28:33) time scenario. Once we cannot understand (00:28:35) how it reaches a conclusion, oversight (00:28:38) becomes completely pointless. Everything (00:28:40) becomes resultsoriented and the focus (00:28:43) shifts from the method and the should we (00:28:46) to the outcome of the we could. And so (00:28:51) we end up back at the Jurassic Park clip (00:28:54) from 1997. Watch this. (00:28:56) >> I I don't think you're giving us our due (00:28:58) credit. Our scientists have done things (00:29:00) which nobody's ever done before. (00:29:02) >> Yeah. Yeah. But your scientists were so (00:29:04) preoccupied with whether or not they (00:29:05) could, they didn't stop to think they (00:29:07) should. So many of you might remember (00:29:09) that clip. And it's the same question (00:29:11) that we really need to be asking today. (00:29:14) It's not about could we, we can. The (00:29:17) question is, should we? And what kind of (00:29:19) safety measures are we putting in place? (00:29:21) The governments are spending billions of (00:29:22) dollars on companies that say that they (00:29:25) can create safety measures to prevent AI (00:29:28) from destroying mankind. And (00:29:30) unbelievably, the top people in the (00:29:32) world are telling us that within months (00:29:36) of them starting these companies, they (00:29:39) go out of business because they can't (00:29:40) solve the problem. Where are the safety (00:29:43) measures? They're not there. They're (00:29:46) rapidly trying to do this. And the (00:29:48) problem is is that c country after (00:29:49) country is competing to get to AGI and (00:29:53) as fast as possible because whoever gets (00:29:55) there first dominates the globe. A (00:29:59) single nation could take down the United (00:30:01) States almost overnight if they got (00:30:05) there first because they could program (00:30:07) it to block us out of the game and (00:30:11) dominate us. This is why trillions are (00:30:14) being spent right now building data (00:30:16) centers and warp speed in an arms race (00:30:20) to get to AGI. Will it solve massive (00:30:24) problems? Yes. And probably eradicate (00:30:26) much of the disease in the world today. (00:30:28) I believe it possibly can. AGI could (00:30:30) actually probably prove God. There's (00:30:32) positive sides and negative sides and (00:30:34) governments are going after it. But when (00:30:37) you get to ASI, (00:30:39) this is when humans stop questioning (00:30:42) results. (00:30:44) Oversight becomes totally symbolic and (00:30:46) pointless. Speed replaces deliberation (00:30:50) and asking the question, should we? (00:30:53) Trust shifts from wisdom to outcome (00:30:57) performance. That's where things get (00:30:59) scary, my friends. (00:31:01) And this is where people usually panic. (00:31:03) You're probably feeling some anxiety. (00:31:05) So, let me say it clearly before we go (00:31:07) any further. ASI is not here. No one has (00:31:10) it. And talking about it is responsible. (00:31:14) It's not fear-mongering. It's called (00:31:16) discernment. (00:31:19) And this fear, by the way, it doesn't (00:31:21) need to exist right now. Transition (00:31:23) takes years. You can't move billions of (00:31:25) people overnight. This means there's (00:31:28) time to prepare. learning how to get (00:31:29) ahead of the curve by increasing how you (00:31:31) can be an asset to your company if you (00:31:33) are in the working realm in times of (00:31:36) disruption. Listen, this is the most (00:31:37) important message right here. Community (00:31:40) becomes your currency. Knowing your (00:31:43) neighbors, being connected, this is an (00:31:46) opportunity to deepen friendships, (00:31:48) relationships, and your community. (00:31:50) Invest in relationships. Really focus on (00:31:53) relationships this next year. It's so (00:31:54) important. We should be doing it anyway, (00:31:56) but all of our phones and everything has (00:31:59) really reduced the ability for us to (00:32:00) really connect with real people. Learn (00:32:03) to supervise AI tools. If you're in the (00:32:05) working class, look into AI supervision. (00:32:09) Those are going to be very very hot (00:32:11) commodity people. If you know how to use (00:32:13) AI to to do a job better, you'll be a (00:32:17) very likely candidate to keep your job. (00:32:21) And not only that, but actually be a (00:32:23) very big asset in almost any department (00:32:26) that you want to go into, any category. (00:32:28) Build at least one resilient skill. I'll (00:32:31) tell you, the plumbers and electricians (00:32:34) likely going to be at the top of the (00:32:36) food chain. (00:32:37) Strengthen your financial margins. Stay (00:32:40) informed, not obsessed. Stay grounded in (00:32:43) scripture. And stay connected to people, (00:32:46) not systems. Now, listen. It's important (00:32:49) that you know this. God has never (00:32:50) promised us economic stability, guys. (00:32:53) It's going to happen. And the most (00:32:55) likely scenario that I could find using (00:32:57) AI is there's a 75% (00:33:00) chance that all of this gets kicked into (00:33:03) gear at some point with some sort of (00:33:06) economic collapse. That would require (00:33:10) economic stability, which then would (00:33:13) move us quicker down the end time (00:33:16) scenario. So, but God has never promised (00:33:18) us economic stability. what he has (00:33:20) promised is provision and those are not (00:33:22) the same thing. So the goal is not to (00:33:25) outrun the future my friends. The goal (00:33:26) is to be the kind of people who remain (00:33:28) faithful, useful and unshaken no matter (00:33:31) what systems rise or fall. Is this going (00:33:35) to be used by the beastly system? I have (00:33:37) no doubt. Is it the beast? No. But it (00:33:40) will be used by everybody, good and (00:33:43) evil. When the internet first came out, (00:33:46) people said this is the beast. Don't use (00:33:48) it. Then we discovered, holy cow, we (00:33:51) could literally send the gospel around (00:33:52) the world in a few short years faster (00:33:55) than 150 combined. (00:33:58) God is going to use this in tremendous (00:34:01) ways. It's going to be harder to hide (00:34:04) the truth as AI gets smarter. (00:34:08) Technology, my friends, does not create (00:34:10) evil. (00:34:12) It reveals who holds the authority. (00:34:16) People can be evil. People can be good. (00:34:20) Technology and tools are not the evil. (00:34:23) It simply reveals who holds the (00:34:26) authority. When all is said and done, if (00:34:28) you need something to pray for is it's (00:34:30) like the Wizard of Oz. Who is behind the (00:34:34) curtain? Whoever's behind the curtain in (00:34:36) the beginning, they're the ones that are (00:34:39) setting the rules (00:34:41) until ASI gets here and rewrites them (00:34:44) without them knowing it. So tonight, my (00:34:46) friends, we've covered a lot of ground. (00:34:47) We've seen that current AI is not a (00:34:49) mind. It's not a soul. It's not a will. (00:34:52) It's a tool. Powerful, yes, but still (00:34:54) dependent on human direction and human (00:34:56) responsibility. (00:34:58) We've also seen that AGI changes how (00:35:00) work gets done. It removes coordination (00:35:03) bottlenecks, replaces entire workflows, (00:35:05) not because it's evil, but because it is (00:35:08) efficient. And that alone will reshape (00:35:10) the economy. It will take years, but it (00:35:13) will reshape it. And finally, we talked (00:35:14) about something a little bit further (00:35:16) out. Artificial super intelligence. Not (00:35:18) to scare you, but to be honest, because (00:35:21) the danger there is not that machines (00:35:23) become gods. The danger is that humans (00:35:26) stop understanding the consequences of (00:35:28) the systems they rely on. Scripture (00:35:31) never warns us about technology. It (00:35:32) warns us about misplaced authority. And (00:35:36) that's a setup for what we're going to (00:35:37) talk about next week when we talk about (00:35:39) the Antichrist and the great authority (00:35:41) that's coming that's going to misuse. (00:35:45) So, it's not the technology, (00:35:48) it's the deception of who's in control (00:35:51) of it and the systems that demand (00:35:54) allegiance. Technology only reveals who (00:35:57) we trust. And here's the most important (00:35:59) thing I want you to hear, my friends. (00:36:00) None of this is happening overnight. (00:36:02) This transition is going to take years. (00:36:04) That means there's time to prepare, time (00:36:06) to build skills, time to strengthen (00:36:08) families, time to deepen community, time (00:36:10) to grow in discernment instead of fear. (00:36:14) God has never promised economic (00:36:15) stability. Like I mentioned before, he (00:36:17) simply promised provision. So next week, (00:36:20) we're going to take everything we've (00:36:21) learned tonight. We're going to ask a (00:36:23) harder question. How will these (00:36:25) technologies be used to set up the end (00:36:27) days, the B system, and the warning (00:36:30) about buying and selling? We're living (00:36:32) in the beginning of unprecedented times (00:36:35) without a doubt. And I want you to be (00:36:37) ready, not afraid. (00:36:40) This is one of the most interesting and (00:36:42) most profound, most scary topics I think (00:36:45) that we've ever touched here at Passion (00:36:47) for Truth because it's real. It's (00:36:50) growing. It's amazing on one side and it (00:36:54) has the potential to be the actual gun (00:36:57) in the hand of the Antichrist on the (00:36:59) other. Knowing the evolution of AI, (00:37:02) knowing the different stages, (00:37:05) knowing the good, knowing the gray, and (00:37:08) knowing the black and evil is important (00:37:11) knowledge for us to navigate through the (00:37:13) minefield that is now being laid before (00:37:16) us. Because at some point, the AI is (00:37:19) going to be smarter than mankind. (00:37:21) By most analysts, it's going to be be (00:37:24) before 2035. Some say by 2030, without a (00:37:29) doubt. Most say by 2045, 2047, (00:37:34) the entire globe will be unrecognizable. (00:37:39) I don't know what that means. Is it (00:37:41) dystopia? Is it a utopia? All I know is (00:37:45) the only thing I can guarantee and (00:37:47) totally rely on is what the word of God (00:37:49) says. The end is not like the beginning. (00:37:54) It's not a Garden of Eden. It's not a (00:37:56) utopia. things begin to fall apart (00:37:58) quickly. And we need to be ready. Not (00:38:02) scared, not fearful, no anxiety, full (00:38:05) trust, knowledge, understanding, (00:38:08) discernment, and wisdom. So my friends, (00:38:11) pray for those things. And pray that God (00:38:14) gives us provision that we need to walk (00:38:17) through the wilderness and get to the (00:38:18) promise. So don't miss next week, my (00:38:21) friends. I think it's going to be an (00:38:21) exciting broadcast to pull it all (00:38:23) together. In the meantime, thank you so (00:38:25) much for supporting this ministry. If (00:38:26) you do, thank you so much for your (00:38:28) prayers. If you'd like to say thank you (00:38:30) by throwing a few shekels our way to (00:38:31) help us serve you in a greater capacity, (00:38:34) go to passionfortruth.com (00:38:36) right now. Click the donation in the (00:38:38) upper right hand corner or scan the QR (00:38:40) code on your screen right now. In the (00:38:42) meantime, thank you guys for letting us (00:38:43) serve you this week. We'll see you next (00:38:45) week. I'm Jim Staley of Passion for (00:38:48) Truth Ministries. I'll see you next (00:38:50) video.