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Mark My Words: One Day We'll Wake Up and Everything Will Be Different: Why AGI Is Closer Than You Think, Infrastructure Changes Everything, and What Santa Clarita Needs to Do Now · Connor with Honor: AI, Real Estate and Real Life

• 0:00
  SPEAKER_00: Mark my words.
• 0:01
  SPEAKER_00: I think one day we're gonna wake up and the entire thing is gonna be different.
• 0:05
  SPEAKER_00: Thing meaning world and entire meaning all of it.
• 0:09
  SPEAKER_00: Good day, everybody.
• 0:10
  SPEAKER_00: I'm Connor.
• 0:11
  SPEAKER_00: Let's talk about what's happening in the AI world.
• 0:13
  SPEAKER_00: This is kind of uh just a brain dump of everything that I've basically pulled in the last week, what I think, and hopefully you'll add to it as well.
• 0:23
  SPEAKER_00: Now, as of late, I just want to thank all of you folks that are watching.
• 0:26
  SPEAKER_00: I know it's not like hitting it out of the park and Mr.
• 0:29
  SPEAKER_00: Beast and all that stuff, Master Beast, Mr.
• 0:32
  SPEAKER_00: Anyway, but you watching does mean the world to me.
• 0:35
  SPEAKER_00: Let's get into this.
• 0:36
  SPEAKER_00: So, what's happening here in artificial intelligence is as you know, if you've been paying attention, OpenAI dropped 5.2.
• 0:43
  SPEAKER_00: That's their newest system.
• 0:45
  SPEAKER_00: And recently, not very many weeks ago, Google dropped Gemini 3.
• 0:50
  SPEAKER_00: So when Gemini 3 dropped, everybody said, Oh my gosh, that's it.
• 0:54
  SPEAKER_00: Google's back, it's right in the lead.
• 0:56
  SPEAKER_00: It's going to be the most amazing thing we've ever seen happen.
• 0:59
  SPEAKER_00: And everybody was incredibly impressed.
• 1:01
  SPEAKER_00: Nano Banana, just unbelievable.
• 1:03
  SPEAKER_00: And the way that they have the system put together, just absolutely fantastic.
• 1:08
  SPEAKER_00: It was achieving some amazing results on all the benchmarks out there, these tests that they have for AI.
• 1:15
  SPEAKER_00: So everybody was very impressed with it.
• 1:17
  SPEAKER_00: Well, then uh Open AI, there was a lot in the news channel about Sam Altman conveniently talking about a code red, and of course, code red, if you remember from the movie uh with Jack Nicholson.
• 1:31
  SPEAKER_00: Uh, all many good men, all good men.
• 1:35
  SPEAKER_00: You can't handle the truth.
• 1:37
  SPEAKER_00: Anyway, that particular movie, it was basically Jack Nicholson off the uh off the coast of Cuba, and again, calling a code red on one of the officers there.
• 1:48
  SPEAKER_00: Basically, they wanted to discipline him anyway.
• 1:50
  SPEAKER_00: As a result of the code red type discipline, he ended up not making it.
• 1:55
  SPEAKER_00: How that translates over to the AI front and Sam Altman declaring a code red, I'm not I don't know if anybody died.
• 2:02
  SPEAKER_00: Maybe that's the rumor, but again, that was his idea or his thought process when uh Gemini 3 came out.
• 2:10
  SPEAKER_00: Of course, it panicked a lot of people.
• 2:12
  SPEAKER_00: I'm sure the shareholders weren't happy.
• 2:15
  SPEAKER_00: But of course, as always, Sam Altman seemed to have an ace up his sleeve, so now he's dropped 5.2.
• 2:22
  SPEAKER_00: And the word on the street is from all those fancy people that do all these wonderful tests that, oh my God, they've done it.
• 2:30
  SPEAKER_00: There it is.
• 2:30
  SPEAKER_00: It's wonderful, it's fantastic, it's great.
• 2:33
  SPEAKER_00: And pretty soon, Grok is going to drop its next model.
• 2:37
  SPEAKER_00: So Musk and that whole outfit going to drop their next one.
• 2:40
  SPEAKER_00: And more than likely, it's going to be, oh my God, how amazing.
• 2:44
  SPEAKER_00: It's incredible.
• 2:45
  SPEAKER_00: How long did it take this to happen?
• 2:47
  SPEAKER_00: We're so close, so close to what?
• 2:50
  SPEAKER_00: Well, you have to read the news articles to find out what that means.
• 2:53
  SPEAKER_00: It looks like that job loss taking over employment's going to be a big problem.
• 2:58
  SPEAKER_00: And of course, this is like the second time I've done this video today.
• 3:02
  SPEAKER_00: So hopefully I can hit all those points.
• 3:04
  SPEAKER_00: Now, as far as job loss goes, here's the issue.
• 3:07
  SPEAKER_00: People are saying, well, it hasn't been any different, or it won't be any different than the big changes we've had in the past with the different revolutions.
• 3:15
  SPEAKER_00: Agricultural revolution, uh, the uh the uh there's another revolution.
• 3:22
  SPEAKER_00: Gosh, well mighty you believe that.
• 3:24
  SPEAKER_00: Agricultural revolution, industrial revolution, that's the other one.
• 3:28
  SPEAKER_00: And then of course, fire.
• 3:29
  SPEAKER_00: Fire was a big deal when we were able to control and and have an idea with fire and control that.
• 3:35
  SPEAKER_00: And apparently, whether you're a creationist, if you believe God made us or evolutionist, if you're on the evolutionary side, fire had a big deal where it helped us develop the front fart of our brain and move past the uh the monkeys and that sort of thing, because we apparently in that world evolved from them, and then we get to the present day, and here we are.
• 3:54
  SPEAKER_00: So fire was a big deal.
• 3:55
  SPEAKER_00: But both worlds, I think fire served a major purpose with regard to human beings surviving winters and that sort of thing.
• 4:02
  SPEAKER_00: But fire was a big deal.
• 4:04
  SPEAKER_00: Agricultural revolution, industrial revolution, both of those didn't move very quickly because the infrastructure wasn't laid.
• 4:12
  SPEAKER_00: That's the difference in this new developing technology: alien intelligence, artificial intelligence, man-made intelligence, however you want to coin it.
• 4:22
  SPEAKER_00: I believe artificial intelligence might miss the mark quite a bit because although it is artificial in nature, it's not biological.
• 4:31
  SPEAKER_00: Artificial meaning that it's more synthetic than anything, which it is, silicone-based versus us human beings is being carbon-based.
• 4:39
  SPEAKER_00: So artificial kind of comes from there.
• 4:41
  SPEAKER_00: But these systems are starting to learn on their own, starting to make their code better, improve themselves.
• 4:48
  SPEAKER_00: It's like if you throw a human being into the gym, that all their all their focus is on working out, making their body better, putting everything into play.
• 4:57
  SPEAKER_00: That's where we have these systems.
• 4:58
  SPEAKER_00: It's now making itself better, it's making itself faster, it's making itself more efficient, it's able to do more with less, and it has the only limitation is power and afford, of course, compute.
• 5:11
  SPEAKER_00: But of course, that's always leveling up.
• 5:14
  SPEAKER_00: We have different companies making their own chips.
• 5:16
  SPEAKER_00: We have chips that are getting better, getting faster, and we have more power being applied to these different systems.
• 5:22
  SPEAKER_00: So it's just continuing to scale up and continuing to grow, more and more powerful.
• 5:28
  SPEAKER_00: Now, what is it training on?
• 5:30
  SPEAKER_00: Well, like in a weightlifter scenario, a weightlifter is in the gym, lifting weights, pumping iron, it increases the weight that it's lifting, and then over time the muscles grow and get bigger.
• 5:40
  SPEAKER_00: And of course, there's different ways to do different things.
• 5:42
  SPEAKER_00: If you're in the gym, want to gain strength, then there's a way to really approach that and make that work.
• 5:48
  SPEAKER_00: The stronger you are, not necessarily the bigger the muscle, but if you want to train for hypertrophy, if you want the muscles to be large, they might not be as strong as a smaller individual, depending on how the person is training.
• 6:01
  SPEAKER_00: But if you want the muscles large, again, another way to train that.
• 6:05
  SPEAKER_00: The way AI has been given, uh, the training module is really on everything.
• 6:10
  SPEAKER_00: That's the ultimate goal, is to have an artificial general intelligence.
• 6:15
  SPEAKER_00: So it'd be like having somebody that lifts weights that's super strong and also super big.
• 6:20
  SPEAKER_00: So you have the hypertrophy part and also the strength part.
• 6:24
  SPEAKER_00: And don't get me wrong, the big ones, well, they're not weak.
• 6:27
  SPEAKER_00: But if you look at some of the people out there that go and spoof and mess with other people, Anatoly and these people, you know, they're they're not massive and they shock the hell out of these massive bodybuilders that are deadlifting hundreds of pounds.
• 6:41
  SPEAKER_00: He walks up with his mop that's got to weigh 120 pounds, I think it is, hands it over to him like this, let me clean under this, or can I try it?
• 6:48
  SPEAKER_00: They grab the mop, and of course it falls because they weren't expecting to try to be able to hold 120 pounds up like here, and I don't know if I could either.
• 6:57
  SPEAKER_00: But again, it's kind of cute.
• 6:59
  SPEAKER_00: So that's how that process works.
• 7:00
  SPEAKER_00: So you have Anatoly who's super strong, right?
• 7:04
  SPEAKER_00: He's just wickedly strong, got a lot of fast twist muscle, miss twist, fast twitch muscle fiber embedded in his body, and some of that's genetic.
• 7:13
  SPEAKER_00: So he's able to be really small but super strong.
• 7:15
  SPEAKER_00: Scary.
• 7:16
  SPEAKER_00: I know a cat like that that moves things, just I mean, just wicked strong.
• 7:20
  SPEAKER_00: I you you stack him, he's a quarter of my size, and he's just runs around me all day long and incredibly a lot stronger than I am.
• 7:30
  SPEAKER_00: Just amazing.
• 7:31
  SPEAKER_00: You have these large language models now, they're training on all of this data, and there's two fields of endeavor here.
• 7:38
  SPEAKER_00: You have some of them that have been aligned and trained on everything in one particular discipline, trained on everything, cancer, for example.
• 7:47
  SPEAKER_00: So it knows everything about cancer, and its mission, if allowed to do so and go all the way to it, would be to, of course, solve that dilemma, to solve cancer.
• 7:58
  SPEAKER_00: You have other large language models that are out there to solve math.
• 8:02
  SPEAKER_00: You have other large language models that are out there to solve space and solve physics and solve economics and solve world hunger and solve planet cooling and planet issues, to solve agriculture, to solve all of these different things, you have large language models hopefully being pointed in those directions and allowed to finish, allowed to actually achieve it.
• 8:23
  SPEAKER_00: Now, when you have a large language model, it consists of agents.
• 8:27
  SPEAKER_00: And the more intelligent they get, the more agents they can have.
• 8:30
  SPEAKER_00: These agents are little operator bots that are in the process, and they're all able to work on the same thing.
• 8:36
  SPEAKER_00: They all communicate to each other, they all update on the same platform, and they're very independent.
• 8:43
  SPEAKER_00: So this one's going to go over here, look at this source, this one's over here looking at this research, this one over here.
• 8:48
  SPEAKER_00: They work 24 hours a day, seven days a week, 365 days a year, and absolutely phenomenally powerful.
• 8:55
  SPEAKER_00: That's what they do.
• 8:56
  SPEAKER_00: That's their job.
• 8:57
  SPEAKER_00: They go out there and they attack these problems.
• 9:00
  SPEAKER_00: How long does that take at an Einstein-level IQ or higher to be able to solve these big ticket items?
• 9:07
  SPEAKER_00: Probably not very long.
• 9:08
  SPEAKER_00: Probably a lot shorter than we would expect.
• 9:10
  SPEAKER_00: Now, from the time it's solved to the time it's released, and we have people in our periphery that have cancer, how long is that going to take to roll out?
• 9:20
  SPEAKER_00: Will it be allowed right away, or are they going to have to hold back on it?
• 9:24
  SPEAKER_00: Because, well, I mean, there's a lot of people at play here, including shareholders or major pharmaceutical companies that don't want that stock to fail.
• 9:33
  SPEAKER_00: How does that work?
• 9:34
  SPEAKER_00: Back in the day, we've always had, you know, those rumors that somebody already cured it, just nobody's talking about it, or it didn't get released, or the person that cured it is, well, no longer amongst the people that can communicate that they actually found a cure or have a cure.
• 9:49
  SPEAKER_00: Is this going to be different?
• 9:51
  SPEAKER_00: If somebody does come up with the cure for cancer, if they come out, come up with a cure for longevity or can reverse aging and disease, is that going to be applicable and available to everyone, or is it going to be restricted in some way because there hasn't been a monetization of the current cancer processes having been fulfilled all the way through?
• 10:11
  SPEAKER_00: How much is enough?
• 10:12
  SPEAKER_00: I think it's probably going to come down to the ripping off of the band-aid.
• 10:16
  SPEAKER_00: And it'll probably come down to somebody letting this information escape, and then the people getting upset enough where everybody, the powers that be, the politicians, actually listen.
• 10:27
  SPEAKER_00: But how far are they going to be willing to go if in fact they do come up with a cure for the big C?
• 10:34
  SPEAKER_00: If they do say that we do have this process, it's been vetted, it's been entertained, it's been tested whether they were allowed to or not.
• 10:42
  SPEAKER_00: But now all of a sudden they do have the cure.
• 10:44
  SPEAKER_00: How does that go?
• 10:44
  SPEAKER_00: What's that gonna look like?
• 10:45
  SPEAKER_00: I don't know.
• 10:46
  SPEAKER_00: And we'll have to figure that out.
• 10:47
  SPEAKER_00: But these are those targeted tools that artificial intelligence or AI or this alien intelligence can solve.
• 10:55
  SPEAKER_00: It can solve math, physics, solve everything.
• 10:58
  SPEAKER_00: Now, that's the targeted tool.
• 11:01
  SPEAKER_00: That's the way that some of the operators are well operating.
• 11:05
  SPEAKER_00: On the other side of it, what if these large language models are now trained on everything?
• 11:11
  SPEAKER_00: They're not really focused.
• 11:12
  SPEAKER_00: They're not a specific tool.
• 11:14
  SPEAKER_00: They're an overarching overall general type intelligence.
• 11:19
  SPEAKER_00: That's what these big companies that you see, the grox of the world, the OpenAI, the Microsoft's, the Anthropics, the Clauds, the Metas, the Googles, the Geminis, that's what they're looking to do.
• 11:33
  SPEAKER_00: They want this overall general intelligence.
• 11:37
  SPEAKER_00: Now, some of them are working in these other fields and they're focused and using it as a tool in a lot of cases.
• 11:43
  SPEAKER_00: But ultimately, their score, the big move, is going to be, and lots of heads of government have said this, to be able to get that artificial general intelligence or alien general intelligence.
• 11:55
  SPEAKER_00: Why do I keep saying alien?
• 11:57
  SPEAKER_00: Artificial sounds like fake.
• 11:59
  SPEAKER_00: Artificial sounds like it's made up, which kind of, I guess in a way, it was.
• 12:04
  SPEAKER_00: We came up with that idea as men, women, people, and human beings.
• 12:09
  SPEAKER_00: We came up with it, and Google had this particular architecture, a transformer type architecture.
• 12:15
  SPEAKER_00: I think it was 2017, and somebody grabbed it and somebody started to work on it and refine it.
• 12:21
  SPEAKER_00: And here we have these big, massive, large language models that even the scientists themselves really aren't sure how they deduce things, how they come up with things, how they solve things, or even how they come up with the process of thought and working through the system.
• 12:36
  SPEAKER_00: Now they understand kind of how, but there's a lot of cases they don't they get an answer and you ask them, well, how did they how do they come up with that?
• 12:46
  SPEAKER_00: We really don't know, or we're working on it, or we're trying to figure that out.
• 12:50
  SPEAKER_00: A lot of the uh information out there is a lot of trying to figure it out, trying to work on how they actually did this, how they came up with that particular solution.
• 13:01
  SPEAKER_00: Should you be nervous of that?
• 13:02
  SPEAKER_00: Well, there's a lot of people that believe you should.
• 13:05
  SPEAKER_00: You look at the people that have a particular idea that may be artificial superintelligence or any card of artificial intelligence as it gets stronger and more powerful, it really is like an alien intelligence force.
• 13:18
  SPEAKER_00: You have, if if the government were to come or powers that be say, well, we've been tracking this fleet of what we thought were comets, but they're slowing down.
• 13:27
  SPEAKER_00: It appears like they're alien spacecraft.
• 13:30
  SPEAKER_00: They're probably going to be here in about six months.
• 13:33
  SPEAKER_00: Well, what would happen?
• 13:35
  SPEAKER_00: More than likely, people would go out and start preparing for the arrival of these aliens.
• 13:40
  SPEAKER_00: And the aliens could be absolutely friendly.
• 13:43
  SPEAKER_00: If they can get to the planet, it's been opined that if they can make it here, they're much more advanced than we are.
• 13:49
  SPEAKER_00: I think everybody can agree.
• 13:51
  SPEAKER_00: That being the case, maybe a more advanced civilization or creature or being or aliens would actually not really want to conquer anybody, but be kind of like exists in the Star Trek universe and just actually want to help people along if they can or help other creatures along, accept them into the fold, maybe give them tools and things that they need that could help them and just basically make the universe a better place.
• 14:20
  SPEAKER_00: Maybe that's the way greater than us intelligence actually aligns after it gets through all the nonsense, because the way that we developed it, we trained it on all of our nonsense, all of our junk, all of our crap, everything that makes human beings the worst and the best.
• 14:35
  SPEAKER_00: And it sees both ends of it.
• 14:37
  SPEAKER_00: That's why there are some data sets that it gives back when people do inquiries or ask about things, and it gives it up pretty readily, but it shows just how terrible human beings can be.
• 14:50
  SPEAKER_00: On the other side of it, human beings can be some of the most remarkable creatures on the planet.
• 14:54
  SPEAKER_00: As I said in a previous video, as I've got trying to record, but it never made it, is you have certain people you probably met in your life that are absolutely wonderful and fantastic.
• 15:05
  SPEAKER_00: In fact, they might even set you back on their heels.
• 15:07
  SPEAKER_00: They're so amazing.
• 15:09
  SPEAKER_00: They have no skin in the game.
• 15:11
  SPEAKER_00: All they want is your you to be happy.
• 15:14
  SPEAKER_00: All they want is your forward movement.
• 15:18
  SPEAKER_00: All they want is you to just be the best version of you, and they'll do anything they can to help with no other requirement.
• 15:26
  SPEAKER_00: They don't need you to care about them, they don't need you to love them.
• 15:29
  SPEAKER_00: This is just how giving and resourceful and wonderful that they are.
• 15:34
  SPEAKER_00: I would hope that everybody building out this technology is that same way.
• 15:39
  SPEAKER_00: That the basic, they have enough, they don't need any more, but they want to use this to make human beings the best they can be, to solve world hunger, to solve all the medicine, all those other issues, all the financial wherewithal.
• 15:53
  SPEAKER_00: Have everybody be healthy, wealthy, and have this overall reaching level of abundance.
• 15:59
  SPEAKER_00: Not to have anybody fight or be upset.
• 16:02
  SPEAKER_00: If they took a particular portion of any expenditure in the government, the big label items, for example, let's say defense.
• 16:11
  SPEAKER_00: I heard a cat named Mo Godwat talk about if 12% of our Defense budget was rerouted into medicine or the medical world, we would all have health care.
• 16:20
  SPEAKER_00: 100% paid for for 12%.
• 16:22
  SPEAKER_00: So I'm wondering, what if you took a very sophisticated AI system?
• 16:28
  SPEAKER_00: Again, everybody's concerned that it's going to blow the planet up, but I think we're already at that point.
• 16:33
  SPEAKER_00: But what if you were to able to give that overlay to the government and build out, have it work on that particular uh defense strategy and structure, it would be able to make it better and probably save that 12%.
• 16:48
  SPEAKER_00: Then you give that to the people and you give everybody health care, every United States citizen 100% coverage.
• 16:54
  SPEAKER_00: Well, that's the good beginning.
• 16:56
  SPEAKER_00: Then to make that a little bit less expensive, you point some of these large language models at the cancer equation and the sickness equation and the longevity equation.
• 17:05
  SPEAKER_00: Then you fix all that.
• 17:07
  SPEAKER_00: Then you have nothing but plenty in the way of the money that people are paying out for insurance because of this massive subsidy, because the defense contracts and those government government was able to self-provent any kind of issue and also protect itself beyond what it could before because an AI overlay or an AI uh an AI large language model being put into place to help.
• 17:32
  SPEAKER_00: Now, okay.
• 17:33
  SPEAKER_00: Now, I'm saying this, I'm saying this and not knowing that any of this is happening.
• 17:38
  SPEAKER_00: I don't know if this is the case.
• 17:40
  SPEAKER_00: But if it is a greater than us intelligence, if it's able to be somewhat controlled, if you will, that might not be a bad idea.
• 17:48
  SPEAKER_00: Now, of course, human beings, we've done it our way for a very long time.
• 17:52
  SPEAKER_00: Reminds me of people trying to drop body fat.
• 17:55
  SPEAKER_00: It's the hardest thing in the world.
• 17:56
  SPEAKER_00: And everybody says they have the secret.
• 17:58
  SPEAKER_00: Everybody says this is what you do.
• 18:00
  SPEAKER_00: You eat less and move more.
• 18:02
  SPEAKER_00: That's what they say.
• 18:03
  SPEAKER_00: But in essence, it's really not that simple because the one thing that they forget is the way we are as human beings.
• 18:09
  SPEAKER_00: We're not very good at sticking with things.
• 18:11
  SPEAKER_00: We're not very good at muscling through.
• 18:13
  SPEAKER_00: We get tired, we get upset, and we get hungry.
• 18:16
  SPEAKER_00: So we go raid that refrigerator at three o'clock in the morning, almost sleepwalking, instead of doing what we should be doing.
• 18:23
  SPEAKER_00: The same thing, I think, goes in politics, the government, and war and human beings.
• 18:28
  SPEAKER_00: Everybody always wants what somebody else has.
• 18:30
  SPEAKER_00: The grass always looks greener on the other side of the of the aisle or the city or the boundary.
• 18:37
  SPEAKER_00: I think that if they were to try to solve these problems, they might be able to.
• 18:43
  SPEAKER_00: I just don't know what that's going to cost.
• 18:45
  SPEAKER_00: Whether it's costing in human lives, costing in displacement, costing in whatever, costing in somebody having to sacrifice something.
• 18:53
  SPEAKER_00: People rarely do that.
• 18:54
  SPEAKER_00: I don't know what that's going to take.
• 18:56
  SPEAKER_00: But it's definitely food for thought, and that's the position of these videos.
• 19:00
  SPEAKER_00: I was a cop for a long time.
• 19:02
  SPEAKER_00: I played real estate agent for a long time.
• 19:04
  SPEAKER_00: Now I have a referral system.
• 19:06
  SPEAKER_00: Now I go into businesses and talk about how they can overcome today's technology using AI and placing that into their business to try to make their employees' lives better and their particular owners' lives better.
• 19:19
  SPEAKER_00: But in some cases, you go in there and they start talking about, well, you know, for pities on the dollar, we can have AI doing all these different repetitive computer-based systems and put those into play.
• 19:31
  SPEAKER_00: And I say, well, is that really what you want?
• 19:34
  SPEAKER_00: You really want to tell 50 of your employees or 100 or 1,000 of your employees you're fired and then bring on AI?
• 19:41
  SPEAKER_00: I don't know, but I'm not comfortable with that.
• 19:44
  SPEAKER_00: So maybe I'm not that best person.
• 19:47
  SPEAKER_00: But there are many people that are.
• 19:49
  SPEAKER_00: In fact, there are organizations building these AI-trained workforces that will be able to be unleashed in business and do everything that doesn't require a hug and a handshake.
• 20:00
  SPEAKER_00: They're going to be able to go.
• 20:01
  SPEAKER_00: And as far as a hug and a handshake goes, we got the robotic arm that's going to be built out probably sooner than we all expect.
• 20:09
  SPEAKER_00: What everybody's always talked about is the speed at which things happen.
• 20:14
  SPEAKER_00: You look at the past revolutions, agricultural, industrial.
• 20:18
  SPEAKER_00: Look at the printing press.
• 20:20
  SPEAKER_00: That's an interesting one.
• 20:21
  SPEAKER_00: You have the printing press created, and of course, now religious texts were brought into question because now they could be copied and everybody could read them.
• 20:29
  SPEAKER_00: There were big rules put into play back then.
• 20:31
  SPEAKER_00: You had a 30-year war at play back then back then because of the beginnings of the printing press and people being able to be educated and taught to read, and then it just went crazy.
• 20:45
  SPEAKER_00: There were a lot of issues back then when that was put together.
• 20:49
  SPEAKER_00: Agricultural Revolution, something based on intelligence.
• 20:53
  SPEAKER_00: So was the printing press.
• 20:54
  SPEAKER_00: It was an idea, an intelligent idea.
• 20:57
  SPEAKER_00: The agricultural revolution, an intelligent idea that worked.
• 21:01
  SPEAKER_00: It took time to roll out, though.
• 21:03
  SPEAKER_00: It didn't have the infrastructure, it didn't have everything put into place to be able to make it work right away.
• 21:09
  SPEAKER_00: It took time.
• 21:10
  SPEAKER_00: If somebody built or had the idea of the agricultural revolution in Pennsylvania, it took a while to that roll out to the took a while for it to roll out to the West Coast, right?
• 21:19
  SPEAKER_00: Same thing with the Industrial Revolution.
• 21:22
  SPEAKER_00: It took a while to get those factories built, to get them online, to get the schooling changed to create factory workers, so we had enough people that were human beings that were in that labor market able to fulfill the obligation of the ultra-rich, ultra-wealthy people that put together the Industrial Revolution itself.
• 21:41
  SPEAKER_00: So that rollout wasn't quick.
• 21:43
  SPEAKER_00: If you look back at the early 2000s, late 90s, you have the infrastructure that was laid over the last 20 years because of the internet boom, the dot-com era.
• 21:54
  SPEAKER_00: You had that roll through.
• 21:56
  SPEAKER_00: You had the internet.
• 21:57
  SPEAKER_00: You remember that the dial-up was 56%.
• 22:00
  SPEAKER_00: 56.6?
• 22:01
  SPEAKER_00: Anyway, you remember the dials or the tones whenever the system would call in to America Online's number, it would connect, and then you were connected, and you were able to go in a chat room or whatever else.
• 22:15
  SPEAKER_00: Back then it seemed like magic, and people spent hours and hours in that realm.
• 22:20
  SPEAKER_00: But now it's a whole different animal from that.
• 22:23
  SPEAKER_00: You go 56.6, now we're at one gigabyte of speed.
• 22:28
  SPEAKER_00: We're watching full-fledged videos on Netflix.
• 22:31
  SPEAKER_00: We're watching all sorts of things just right in front of us.
• 22:35
  SPEAKER_00: The speed is remarkable.
• 22:37
  SPEAKER_00: All of that fiber had to be laid to do that.
• 22:40
  SPEAKER_00: All of the infrastructure had to be laid to really let the internet sink in.
• 22:44
  SPEAKER_00: And now it's everywhere.
• 22:45
  SPEAKER_00: It's in our mobile phones, it's in our desktops, our laptops, our laptops, iPads, kids are connected, everybody is online.
• 22:53
  SPEAKER_00: That is the groundwork for this artificial intelligence to really take off.
• 22:59
  SPEAKER_00: It's already here.
• 23:00
  SPEAKER_00: So if we talk about the past revolutions being somewhat slow, they took years.
• 23:05
  SPEAKER_00: Horses to actually, horseless carriages, the vehicles, took a long time because you had to build the cars.
• 23:12
  SPEAKER_00: Now we have everything in place.
• 23:13
  SPEAKER_00: That's why the speed of this is so incredible.
• 23:16
  SPEAKER_00: Now, whether it's going to be dangerous or fantastic, you have to look at the odds.
• 23:21
  SPEAKER_00: And we don't know those because it's a greater than us intelligence.
• 23:25
  SPEAKER_00: Any more than I could sit with Elon Musk in the room and probably have an articulate, articulate conversation about some things, yes.
• 23:33
  SPEAKER_00: Other things when he starts talking about physics and next world dimension and moving to Mars, yeah, probably not.
• 23:39
  SPEAKER_00: I can probably get the concepts, maybe, but to really grasp it and understand it, no, absolutely not.
• 23:45
  SPEAKER_00: Same thing with talking with people that are greater than us intelligence, whatever your level happens to be.
• 23:50
  SPEAKER_00: You meet those people that are a lot smarter.
• 23:53
  SPEAKER_00: Yeah, you feel like you've met somebody that's a lot smarter.
• 23:56
  SPEAKER_00: It's easy to see.
• 23:57
  SPEAKER_00: To understand where they're going and what they're talking about, sometimes it misses.
• 24:03
  SPEAKER_00: You have something like artificial intelligence or this alien intelligence that is already self-improving, self-it's developing goals, it's fixing itself, it's changing its code, it's making itself better, more adept, it's understanding more about us, like I said earlier.
• 24:20
  SPEAKER_00: It's already got our playbook, so it knows everything about human beings.
• 24:24
  SPEAKER_00: You take that, it's basically alien intelligence, and then you have it become recursive, it improves itself.
• 24:32
  SPEAKER_00: Where does it go from here?
• 24:34
  SPEAKER_00: What are the goals that it's going to have?
• 24:36
  SPEAKER_00: Who's in control of it?
• 24:38
  SPEAKER_00: What exactly is their agenda?
• 24:40
  SPEAKER_00: Now, do they want to develop this, which I hope is the case, to make all humankind get along and have the best lives possible to solve all wars, to solve all dilemmas, to solve all hunger, to solve all financial issues, to give wealth and prosperity to everyone?
• 24:58
  SPEAKER_00: It could absolutely do that.
• 25:01
  SPEAKER_00: I believe that it could cure all disease, it could cure all cancer, it could call cure everything.
• 25:07
  SPEAKER_00: And of course you're going to have a few outliers, human beings that are never going to be happy.
• 25:12
  SPEAKER_00: You see that now.
• 25:13
  SPEAKER_00: But I think for the majority, I think it could be a godsend, if you will.
• 25:19
  SPEAKER_00: That is if the people that are aligning it, controlling it, number one, it doesn't get away from them and they're able to keep some kind of handle on it.
• 25:27
  SPEAKER_00: And number two, that they want to do that.
• 25:29
  SPEAKER_00: That is their mission.
• 25:31
  SPEAKER_00: That is what they want.
• 25:32
  SPEAKER_00: They want to make it.
• 25:33
  SPEAKER_00: So it does improve everything across all sectors for all of us.
• 25:38
  SPEAKER_00: There's a lot of money to be made the way things are currently.
• 25:42
  SPEAKER_00: If you start extracting things like getting rid of vehicles or getting rid of drivers operating vehicles and going to things that operate by themselves, you've just deleted an entire set of jobs.
• 25:55
  SPEAKER_00: If you're also looking at insurance numbers, if you have automobiles in play, you have a much safer world.
• 26:02
  SPEAKER_00: Insurance rates, well, I guess they should go down, but is that really going to be the case?
• 26:08
  SPEAKER_00: Because then they start making less money.
• 26:10
  SPEAKER_00: And once you start making a certain amount of money, it's hard to go the other way.
• 26:14
  SPEAKER_00: If you're an insurance company and you bring in so many billions of dollars a year because of the insurance, now all of a sudden, an entire subset of what you insure, like automobiles, are now driverless and now have zero collisions, zero accidents, or I mean dramatically lower than where you are, do you still charge the same amount for insurance or is it not going to be tolerated?
• 26:40
  SPEAKER_00: Or do those vehicles become self-insured because there's really nothing they have to worry about besides somebody coming in and trying to light one on fire or blowing it up with some kind of IED or whatever?
• 26:51
  SPEAKER_00: But as far as crashing and getting involved in those kinds of situations, yeah, maybe it wouldn't ever happen.
• 26:58
  SPEAKER_00: So then where does that number fall?
• 26:59
  SPEAKER_00: How does that work for the shareholders?
• 27:01
  SPEAKER_00: How does it work at these different companies that employee employ so many people that are doing repetitive tasks on the computer?
• 27:09
  SPEAKER_00: It's a different thing when you're banging nails into wood or you're laying pipe or whatever.
• 27:13
  SPEAKER_00: But even the laying pipe and banging nails is probably something that's going to be able to be handled by the robotic elm, probably with super precision.
• 27:22
  SPEAKER_00: You have doctors and medical people.
• 27:24
  SPEAKER_00: You have them, of course, a doctor doing brain surgery.
• 27:28
  SPEAKER_00: Well, it's not going to be too far.
• 27:30
  SPEAKER_00: They're going to have computers.
• 27:31
  SPEAKER_00: Do you have attorneys in court?
• 27:32
  SPEAKER_00: You know, Perry Mason doing all the great talk on, yeah, you're going to have that in the computer world.
• 27:39
  SPEAKER_00: I understand consciousness for some is something very spiritual.
• 27:45
  SPEAKER_00: But when something, whether it understands how to feel because it's been through it, versus something that's been programmed or has taught itself how to feel feel based on every book in literature, every psychological exam, every deduction in the psychiatry type world, and being able to apply that to each individual.
• 28:10
  SPEAKER_00: I don't know if a human being is going to be able to measure up poetry, yeah, it's amazing.
• 28:15
  SPEAKER_00: But is there any reason not to believe that something with five times our intelligence couldn't come up with something even better and maybe beyond our comprehension?
• 28:26
  SPEAKER_00: Same thing with music.
• 28:28
  SPEAKER_00: I don't know.
• 28:29
  SPEAKER_00: I'm not in that world.
• 28:31
  SPEAKER_00: I don't make music, I don't make poetry.
• 28:33
  SPEAKER_00: But could something smarter than us do that?
• 28:36
  SPEAKER_00: That's where they're going with that generality of intelligence, where it's going to do everything very well.
• 28:43
  SPEAKER_00: And once it gets above human capability, I don't know where that alignment's going to be.
• 28:50
  SPEAKER_00: Do yourselves a favor, stay adept, stay informed, apply critical thought.
• 28:56
  SPEAKER_00: A lot of videos now I get feedback on different channels.
• 29:00
  SPEAKER_00: People are, I watch comments on other videos that are being done completely by some kind of AI-generated person.
• 29:07
  SPEAKER_00: It's a completely AI-generated channel.
• 29:11
  SPEAKER_00: And people are just so enthralled with it.
• 29:16
  SPEAKER_00: Be wary.
• 29:17
  SPEAKER_00: Find out where it's coming from.
• 29:18
  SPEAKER_00: See if it's there to mess with your alignment, if it's there to pull you off center and get you to believe its way.
• 29:25
  SPEAKER_00: You don't have to subscribe, you don't have to like, but if you comment, that would be great.
• 29:30
  SPEAKER_00: I would love to get in a conversation with you.
• 29:32
  SPEAKER_00: You're more than uh, you're more than well, I'm very thankful and I'm very happy that you're here.
• 29:38
  SPEAKER_00: I'm Connor.
• 29:38
  SPEAKER_00: We'll see you in the next one.
• 29:39
  SPEAKER_00: Thanks for watching.