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CS289 L3 Quinn silverscript

Silverlining33 Aug 9th, 2017 171 Never
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  1. CS289 L3 Quinn silverscript Aug 6 2017
  2.  
  3. L3 Exploring Palantir with Quinn Michaels
  4.  
  5. https://www.youtube.com/watch?v=l0RPn9Ikh0AYouTube livechat https://pastebin.com/GzgNV7Vx
  6.  
  7. Buddhist bot-master and AI guru Quinn Michaels schools us on Palantir, Trump's shadow president and new insights into Seth Rich's possible role in the DNC leaks. George phones in from Ohio.
  8.  
  9.  Transcript
  10. 0:44
  11. here there we go okay okay we are live
  12. 0:48
  13. with two wonderful guests here we've got
  14. 0:53
  15. Quinn Michaels of course and George from
  16. 0:56
  17. Ohio how you guys doing pretty good good
  18. 1:02
  19. to see you both thanks for joining me
  20. 1:03
  21. tonight
  22. 1:04
  23. okay so tonight we are going to be
  24. 1:07
  25. talking about Palantir probably a lot of
  26. 1:12
  27. people have not heard about that
  28. 1:14
  29. George you and I have discussed Palantir
  30. 1:16
  31. a bit mostly in the context of its
  32. 1:19
  33. similarities to multigo and there was an
  34. 1:22
  35. issue recently where the NYPD terminated
  36. 1:26
  37. their contract with Palantir is that
  38. 1:28
  39. correct yeah I think Trish had that
  40. 1:32
  41. story actually and she didn't really get
  42. 1:33
  43. credit for it but yeah they didn't what
  44. 1:38
  45. they knew was a backdoor so they just
  46. 1:40
  47. said wait a minute this is like promise
  48. 1:42
  49. I'm not doing this and so that was NYPD
  50. 1:45
  51. Intel mm-hmm
  52. 1:47
  53. and I told him I said just hire Quinn
  54. 1:49
  55. Michael Ivy you're done yeah that's
  56. 1:51
  57. right but that's right but anyway he's a
  58. 1:53
  59. human Palantir be quiet tonight really
  60. 1:56
  61. just listen to Quinn because I know when
  62. 1:58
  63. I'm a 60-watt bald and and I'm in the
  64. 2:01
  65. president's if like that 500 watt bulb
  66. 2:04
  67. Quinn why don't you take us through it a
  68. 2:06
  69. lot of people have no idea what Palantir
  70. 2:08
  71. is okay so first Palantir is essentially
  72. 2:16
  73. the human tracking system used by most
  74. 2:20
  75. of the agencies around the country and a
  76. 2:23
  77. lot in the world Palantir specializes in
  78. 2:28
  79. like big data and machine learning
  80. 2:30
  81. artificial intelligence quantum
  82. 2:33
  83. computing artificial intelligence human
  84. 2:36
  85. algorithms natural likes they're like
  86. 2:39
  87. the top of the top for my research the
  88. 2:43
  89. some of the news agencies equate them to
  90. 2:45
  91. being as powerful as Google Facebook and
  92. 2:48
  93. Twitter but being a privately held
  94. 2:49
  95. company that works with the CIA the FBI
  96. 2:52
  97. the NSA local law enforcement they
  98. 2:57
  99. handle the database for the Missing and
  100. 3:00
  101. Exploited Children so anytime a child
  102. 3:02
  103. goes missing it gets into their database
  104. 3:04
  105. they have arms for like like I said
  106. 3:09
  107. local law enforcement to financial
  108. 3:12
  109. institutions to hedge funds so pretty
  110. 3:15
  111. much their system is tied into
  112. 3:18
  113. everything from high-end government
  114. 3:20
  115. banking sorry about that little audio
  116. 3:23
  117. jump there guys
  118. 3:24
  119. you know Quinn I was talking earlier
  120. 3:26
  121. with brainy blonde about Palin tears
  122. 3:28
  123. involvement with missing children and
  124. 3:31
  125. all of that and we were gonna add her to
  126. 3:33
  127. the panel but she said she didn't know
  128. 3:36
  129. all that much about it so I suspect
  130. 3:38
  131. she's watching now and everyone's gonna
  132. 3:40
  133. get a little bit smarter from hearing
  134. 3:42
  135. what you've got to say peter thiel many
  136. 3:45
  137. people have identified was involved with
  138. 3:47
  139. the founding of Palantir and i didn't
  140. 3:51
  141. know really how AI was involved so what
  142. 3:53
  143. else can you share with us about it
  144. 3:56
  145. well Palantir was funded it's big
  146. 4:00
  147. funding came from two resources one it
  148. 4:03
  149. came from in-q-tel which is the CIA's
  150. 4:06
  151. venture capital arms so they were
  152. 4:08
  153. primarily funded by the CIA and then
  154. 4:11
  155. they were they were funded by in large
  156. 4:13
  157. part the second part they were funded by
  158. 4:15
  159. a venture fund that comes from the
  160. 4:18
  161. Malaysian government that's managed by
  162. 4:19
  163. the Prime Minister of Malaysia and if
  164. 4:22
  165. you've seen the like 1mdb can you know
  166. 4:25
  167. debacle that's going on right now with
  168. 4:27
  169. billions of dollars going missing from
  170. 4:28
  171. their investment fund so primarily
  172. 4:31
  173. Palantir funding comes from like Peter
  174. 4:33
  175. teal spawns it comes from like Josh
  176. 4:36
  177. Kushner Jared Kushner comes from
  178. 4:38
  179. Malaysia and it comes from the CIA so it
  180. 4:42
  181. ties in pretty much everybody mmm ties
  182. 4:46
  183. in you know Josh Kushner and I've found
  184. 4:50
  185. news articles where Josh Kushner and
  186. 4:51
  187. Jared Kushner and Peter Tegel are
  188. 4:53
  189. longtime friends and Peter teal is
  190. 4:56
  191. investing in Josh Kushner's health care
  192. 4:58
  193. technology and you know Josh Kushner
  194. 5:02
  195. runs like I think it's called thrive
  196. 5:04
  197. capital is that that adrenalized blood
  198. 5:06
  199. thing that we
  200. 5:07
  201. heard so much about that that's what
  202. 5:09
  203. Peter teal Peter teal is investing in a
  204. 5:12
  205. company called ambrosia which is
  206. 5:13
  207. pitching injecting the blood of the
  208. 5:16
  209. young into people to vault like make
  210. 5:19
  211. them live longer so they're doing a lot
  212. 5:22
  213. of like research into like the
  214. 5:23
  215. singularity the merging of technology
  216. 5:26
  217. and human beings they're doing a lot of
  218. 5:28
  219. research into using blood of the young
  220. 5:30
  221. to prolong life they're building the
  222. 5:34
  223. OpenGov system so if you know OpenGov
  224. 5:36
  225. calm that is managing your local
  226. 5:39
  227. governments the same group josh
  228. 5:41
  229. Kushner's running that with you know
  230. 5:43
  231. peter Till's some involvement somehow
  232. 5:45
  233. either being a silent an investor just
  234. 5:47
  235. being knowing about the technology
  236. 5:49
  237. they're delivering hmm and it all
  238. 5:52
  239. becomes like a big circle where you have
  240. 5:55
  241. Palantir which in 2004-2005 was funded
  242. 6:00
  243. by the CIA and then a few years later
  244. 6:03
  245. they came out to use their technology
  246. 6:06
  247. with helping like discover the chinese
  248. 6:08
  249. darknets
  250. 6:10
  251. which then you know lots of information
  252. 6:13
  253. we're like the same Malaysian government
  254. 6:15
  255. venture firm also funded Alibaba with
  256. 6:18
  257. two billion dollars that funded Palantir
  258. 6:20
  259. and Wow
  260. 6:21
  261. like Alibaba is the largest like holder
  262. 6:24
  263. of like the Chinese Network so I mean it
  264. 6:26
  265. just really is like this huge big
  266. 6:29
  267. confusing global network of like we're
  268. 6:32
  269. like the United Arab Emirates ambassador
  270. 6:34
  271. to the United States is also a big
  272. 6:36
  273. investor in Palantir and he's also
  274. 6:39
  275. involved in the 1mdb scandal and so
  276. 6:43
  277. basically at the end Palantir has the
  278. 6:45
  279. system that manages and tracks and
  280. 6:47
  281. supposedly can predict the future but
  282. 6:49
  283. yet is being built by a bunch of people
  284. 6:52
  285. that seem to be connected that really
  286. 6:53
  287. shouldn't oh these are all the best guys
  288. 6:55
  289. Quinn yeah so from there they have a rat
  290. 7:01
  291. line these are the people you want rata
  292. 7:03
  293. good right right and so from there like
  294. 7:06
  295. once I started learning about where the
  296. 7:08
  297. Palantir system was all over the world
  298. 7:11
  299. and all the people that were backing it
  300. 7:12
  301. like I started remembering how like I
  302. 7:15
  303. was looking into the svv and they
  304. 7:17
  305. claimed to have a big network of people
  306. 7:19
  307. with AI and I'm just like wow
  308. 7:21
  309. this Palantir system is potentially the
  310. 7:25
  311. system that like you know cess rich may
  312. 7:28
  313. have been trying to reveal that they
  314. 7:29
  315. were building in the background with the
  316. 7:31
  317. Panda Network with the the ng P vans
  318. 7:34
  319. with connecting to the Clintons to their
  320. 7:37
  321. data mining and their spying and
  322. 7:40
  323. connecting you know the Republicans and
  324. 7:42
  325. the foreign governments I mean this
  326. 7:44
  327. Palantir system is the only system I
  328. 7:46
  329. found that would be managing that amount
  330. 7:48
  331. of data if they were having this big
  332. 7:50
  333. hacker Network through Wi-Fi with you
  334. 7:53
  335. know trying to keep it a secret with
  336. 7:55
  337. advanced monitoring AI and getting all
  338. 7:57
  339. these people together to create like
  340. 7:59
  341. their own economy in a way Wow
  342. 8:02
  343. their own economy so that's you mean on
  344. 8:03
  345. the darknet with Bitcoin and all of this
  346. 8:06
  347. untraceable kind of digital currency
  348. 8:08
  349. yeah that's that's kind of where it goes
  350. 8:10
  351. because the Palantir system runs
  352. 8:12
  353. entirely on a blockchain so it makes it
  354. 8:15
  355. way more secure which block chain is
  356. 8:16
  357. cryptocurrency so then you can assume
  358. 8:18
  359. that Palantir probably has a big giant
  360. 8:20
  361. day like crypto mining operation but I
  362. 8:24
  363. started connecting it to like that SBB
  364. 8:26
  365. group that Dafeng go was the web admin
  366. 8:29
  367. for that was trying to create that own
  368. 8:31
  369. coin aha and I started connecting a lot
  370. 8:34
  371. of the names in the emails from svv to
  372. 8:37
  373. the WikiLeaks that were directly related
  374. 8:39
  375. to like the Palantir system and it just
  376. 8:42
  377. is starting to really look like like a
  378. 8:45
  379. group of people trying to create their
  380. 8:46
  381. own currency to subvert like US markets
  382. 8:50
  383. and get people find the people that
  384. 8:52
  385. would join their network and find the
  386. 8:53
  387. smart people and it's just like once I
  388. 8:57
  389. started digging into Pelletier like my
  390. 8:58
  391. whole research just opened up like a
  392. 9:00
  393. butterfly well and you know of course
  394. 9:02
  395. also Peter Thiel was involved in the
  396. 9:05
  397. founding of PayPal so stuff having to do
  398. 9:07
  399. with digital currency and tracking you
  400. 9:10
  401. know huge amounts of transactions I was
  402. 9:13
  403. watching you know that stuff's right all
  404. 9:15
  405. up his alley I was watching this video
  406. 9:17
  407. that was kind of like Palantir 101 and
  408. 9:21
  409. it was talking about how how the company
  410. 9:25
  411. was founded and basically I'm sorry I'm
  412. 9:30
  413. just trying to track this buzz here
  414. 9:32
  415. it was difficult to follow it was
  416. 9:34
  417. talking about how the thing handles big
  418. 9:36
  419. data and processes tons of transactions
  420. 9:38
  421. and all that sort of stuff but how could
  422. 9:42
  423. we take it back even a step so that like
  424. 9:44
  425. the dumb people like me listening can
  426. 9:46
  427. begin to wrap their brains around
  428. 9:47
  429. exactly what it is that that Palantir
  430. 9:51
  431. does the example this guy in the video
  432. 9:53
  433. is giving was combining a human chess
  434. 9:57
  435. player with a computer chess player
  436. 9:59
  437. basically he was saying that you know
  438. 10:01
  439. and this I found it kind of interesting
  440. 10:03
  441. and ironic because just the other day we
  442. 10:05
  443. did a segment where George spoke about
  444. 10:07
  445. big blue and how that was such a big
  446. 10:10
  447. deal towards the end of the 2000s there
  448. 10:13
  449. or the end of the 20th century when big
  450. 10:16
  451. blue beat Kasparov at chess and that was
  452. 10:20
  453. a huge deal but now of course as you
  454. 10:22
  455. know we're so far beyond that with the
  456. 10:25
  457. sophistication of AI and all this other
  458. 10:27
  459. stuff yeah and well in relation to that
  460. 10:32
  461. the Palantir system besides its big
  462. 10:36
  463. giant complex like quantum blockchain
  464. 10:38
  465. multi thousand user complexity Palantir
  466. 10:45
  467. is at every pretty much high-level
  468. 10:48
  469. government agency whether it's the FBI
  470. 10:50
  471. the military of the Air Force the
  472. 10:53
  473. Marines the NSA the only agency right
  474. 10:57
  475. now that isn't using the Palantir system
  476. 10:59
  477. is the army why is it now because the
  478. 11:03
  479. Army has their own AI and they don't
  480. 11:06
  481. want the Palantir system touch in their
  482. 11:07
  483. custom-built AI huh pretty much that's
  484. 11:12
  485. what I've gathered I mean plus it's you
  486. 11:14
  487. know politics but the army has been
  488. 11:16
  489. developing artificial intelligence
  490. 11:18
  491. solutions for like firing mechanisms and
  492. 11:20
  493. telemetry and they've been developing
  494. 11:23
  495. their own with Raytheon for like I think
  496. 11:25
  497. like over the past 20 30 years probably
  498. 11:28
  499. so it's real hard to let Palantir which
  500. 11:31
  501. is a public company come in and deal
  502. 11:33
  503. with that high level technology whereas
  504. 11:35
  505. Raytheon is like a tried and proven you
  506. 11:37
  507. know private strictly government
  508. 11:39
  509. contractor that they've been working
  510. 11:40
  511. with and the army does it I would
  512. 11:43
  513. imagine the army doesn't exactly trust
  514. 11:45
  515. Palantir because
  516. 11:46
  517. there there there original backing and
  518. 11:48
  519. they probably figured that the Palantir
  520. 11:50
  521. is using the the CIA's AI that they
  522. 11:53
  523. built in the army from what I gather
  524. 11:54
  525. probably doesn't like the CIA AI that
  526. 11:57
  527. runs underneath the volunteer see that's
  528. 12:00
  529. interesting because this goes right to
  530. 12:02
  531. this whole deep state war concept that
  532. 12:04
  533. like CIA versus President Trump and all
  534. 12:07
  535. these warring factions within the FBI
  536. 12:10
  537. and we've we've heard about dissent with
  538. 12:14
  539. the field offices and all that sort of
  540. 12:16
  541. thing
  542. 12:16
  543. man I this buzz is killing me let's see
  544. 12:21
  545. sorry so what have you been able to
  546. 12:24
  547. learn what would you say is the most
  548. 12:26
  549. shocking thing that you've learned about
  550. 12:27
  551. Palance here in the past couple weeks
  552. 12:30
  553. that you've been studying it there's a
  554. 12:33
  555. couple shocking things that if they're
  556. 12:35
  557. in every single agency and they have a
  558. 12:38
  559. blockchain back door to access
  560. 12:40
  561. everybody's information they could be
  562. 12:43
  563. manipulating everybody
  564. 12:45
  565. when you say blockchain backdoor I think
  566. 12:48
  567. a lot of people are still trying to
  568. 12:49
  569. catch up with exactly what the hell the
  570. 12:50
  571. blockchain is so okay so the blockchain
  572. 12:54
  573. is a way for you to do private secure
  574. 12:57
  575. untraceable transactions so if if I have
  576. 13:01
  577. two computers that are like I want to do
  578. 13:05
  579. quick transactions p2p I can use the
  580. 13:08
  581. blockchain to have them do that
  582. 13:09
  583. transaction whether that be a
  584. 13:11
  585. cryptocurrency transaction whether that
  586. 13:13
  587. be or a string of text transaction to
  588. 13:16
  589. communicate across systems to have one
  590. 13:18
  591. system do another thing or you know it's
  592. 13:22
  593. it's basically like a personal private
  594. 13:24
  595. watching Network where you have a
  596. 13:26
  597. network ID and you can connect to that
  598. 13:28
  599. network ID and then you can encrypt
  600. 13:29
  601. things on the blockchain it's it's the
  602. 13:32
  603. they want it to be the future basically
  604. 13:34
  605. I mean without getting too complex into
  606. 13:36
  607. it it's like the future of networking
  608. 13:38
  609. and when you say p2p so that's a
  610. 13:40
  611. peer-to-peer type of yeah yeah and that
  612. 13:44
  613. is computer to computer network okay so
  614. 13:47
  615. that's like a closed network between two
  616. 13:49
  617. computers right and so the blockchain
  618. 13:53
  619. it's like a mathematical complex thing
  620. 13:57
  621. that's like an encrypted so so a
  622. 13:59
  623. blockchain
  624. 14:00
  625. peer-to-peer connection between two
  626. 14:01
  627. computers is some extremely secure thing
  628. 14:04
  629. right yeah it's like when they transfer
  630. 14:06
  631. a Bitcoin cryptocurrency it's one of the
  632. 14:09
  633. reasons it's been so hard to find like
  634. 14:11
  635. the pizza gate stuff or the pedo gate
  636. 14:13
  637. stuff or you know any kind of criminals
  638. 14:15
  639. because they do secure transactions on
  640. 14:17
  641. the blockchain and to get a ledger of
  642. 14:20
  643. the transactions you need the blockchain
  644. 14:22
  645. ID and without the blockchain ID you
  646. 14:24
  647. won't be able to find the ledger of
  648. 14:25
  649. transactions so but if someone had that
  650. 14:28
  651. blockchain ID I mean is this because
  652. 14:30
  653. we've always heard that you know I know
  654. 14:32
  655. that Bitcoin is based on blockchain
  656. 14:34
  657. technology and we've always heard that
  658. 14:36
  659. that makes it somehow SuperDuper secure
  660. 14:39
  661. but how though I don't think I don't
  662. 14:43
  663. think I fully it's it's basically super
  664. 14:49
  665. advanced encryption that gets like a
  666. 14:54
  667. type of ID so like the data exists on
  668. 14:57
  669. the network in the block and then once
  670. 15:00
  671. you have the blockchain ID the network
  672. 15:01
  673. will kind of put that information
  674. 15:02
  675. together for you with like a list of
  676. 15:05
  677. transactions and Wow I'm still digging
  678. 15:07
  679. into like the complexities of it because
  680. 15:09
  681. what I was looking for when I was
  682. 15:12
  683. looking for a rogue AI was I was looking
  684. 15:14
  685. for a rogue AI that was large-scale and
  686. 15:17
  687. existed on the blockchain and so
  688. 15:19
  689. Palantir is the only one that really has
  690. 15:20
  691. that okay so in a previous conversation
  692. 15:23
  693. you told me that something to do with
  694. 15:25
  695. mega and Z and in secure p2p real-time
  696. 15:31
  697. technology made it very interesting to
  698. 15:35
  699. people who might want to compromise
  700. 15:38
  701. kim.com to sort of force him to do
  702. 15:41
  703. things that they want him to do does
  704. 15:44
  705. this sum well feed into the Palantir
  706. 15:46
  707. thing it does because Peter Thiel just
  708. 15:50
  709. received citizenship in New Zealand aha
  710. 15:53
  711. and they awarded him citizenship under
  712. 15:56
  713. special circumstances because he's part
  714. 15:59
  715. in large part if not mostly in part
  716. 16:02
  717. funding a fiber-optic network that goes
  718. 16:04
  719. from America to New Zealand to Australia
  720. 16:07
  721. and then back to America haha so if
  722. 16:10
  723. someone was building a fiber-optic
  724. 16:12
  725. network with that
  726. 16:13
  727. the throughput and you're dealing with
  728. 16:14
  729. like a large secure data provider most
  730. 16:17
  731. likely you would be talking to each
  732. 16:19
  733. other about you know what you're going
  734. 16:22
  735. to be doing because you're in the same
  736. 16:23
  737. playing field so I would imagine that
  738. 16:25
  739. Peter Thiel is moving to New Zealand and
  740. 16:27
  741. building a fiber network Wow
  742. 16:30
  743. I would imagine that you know kim.com
  744. 16:33
  745. would probably already know about that
  746. 16:35
  747. if he's not already an investor in that
  748. 16:37
  749. in New Zealand now George is smiling in
  750. 16:40
  751. a way that makes me think he might have
  752. 16:41
  753. some idea as to what's going on what do
  754. 16:43
  755. you guys make of this what does all this
  756. 16:45
  757. mean I can barely understand the
  758. 16:46
  759. explanation well so I'll be the you know
  760. 16:52
  761. it's kind of like the reason I'm smiling
  762. 16:54
  763. is kind of like I know Steve Jobs had
  764. 16:56
  765. this experience when he went to India
  766. 16:59
  767. and he climbed the mountain and he got
  768. 17:01
  769. to speak to the mountain Russia you know
  770. 17:04
  771. whatever and I don't have to climb them
  772. 17:07
  773. out you know this is mrs. Quinn Michaels
  774. 17:09
  775. you know it's like here and so I'm just
  776. 17:13
  777. so excited because I learned so much
  778. 17:16
  779. when I hear this man speak and I to you
  780. 17:21
  781. know be in Silicon Valley for 25 years
  782. 17:24
  783. or 30 but but Quinn is such a genius and
  784. 17:28
  785. it is it's like the Oracle of Delphi and
  786. 17:32
  787. I learned so much every time I hear him
  788. 17:35
  789. what a little I know about this is that
  790. 17:40
  791. this is kind of from the promise
  792. 17:42
  793. software the promise software going back
  794. 17:45
  795. to the old database days before
  796. 17:47
  797. object-oriented was that they would
  798. 17:50
  799. basically the promise was a software
  800. 17:53
  801. system that was put in place for
  802. 17:55
  803. prosecutors it was called prosecutor
  804. 17:57
  805. management information system I think it
  806. 17:58
  807. was called and a pretty cool Mossad guy
  808. 18:04
  809. Maxwell put a backdoor in it so that as
  810. 18:08
  811. these countries around the world were
  812. 18:10
  813. putting in the front of software to
  814. 18:11
  815. manage their criminal investigations and
  816. 18:14
  817. cases Mossad could dial in and see all
  818. 18:18
  819. the people
  820. 18:19
  821. sorry George hang on one second I'm
  822. 18:21
  823. gonna do something low-tech to try to
  824. 18:22
  825. improve the audio quality here
  826. 18:24
  827. all right can you guys hear me all right
  828. 18:30
  829. no see that's the problem the REIT okay
  830. 18:32
  831. that's not gonna work anyway I'm not
  832. 18:37
  833. sure why that that happened everybody's
  834. 18:40
  835. having a problem with the audio and I
  836. 18:42
  837. agree it is it is bad so I'm gonna just
  838. 18:47
  839. we got a buzz on the audio so let's just
  840. 18:50
  841. try one more one more thing real quick
  842. 18:55
  843. yeah no please please continue
  844. 18:58
  845. so I thought that buzz was coming from
  846. 19:00
  847. my system but its young prosecutorial
  848. 19:04
  849. system if I'm doing rap lines I can go
  850. 19:07
  851. and compromise those people hey you're
  852. 19:10
  853. looking at 30 years bub are you sure you
  854. 19:13
  855. don't want to run drugs for five years
  856. 19:15
  857. instead you know here's your choices
  858. 19:17
  859. right that the Palantir takes it to a
  860. 19:21
  861. whole nother level
  862. 19:22
  863. I mean it's if you want to run ratlines
  864. 19:24
  865. promise software was your baby because
  866. 19:27
  867. it was you know flat file not only flat
  868. 19:30
  869. file but it was database files you can
  870. 19:31
  871. just go oh who are my top ten most
  872. 19:34
  873. vulnerable people at forum XYZ right
  874. 19:37
  875. right Palantir is different because it's
  876. 19:40
  877. object-oriented and it allows you to
  878. 19:42
  879. bring in big data and the thing that
  880. 19:45
  881. I've learned from Quentin is that you
  882. 19:47
  883. can create these box my customer service
  884. 19:50
  885. pots or these discs or pots in case of
  886. 19:53
  887. Dibango which are our specialized bots
  888. 19:57
  889. that go to your file of all the
  890. 19:59
  891. interactions you've had in social media
  892. 20:02
  893. with in your conversations your word
  894. 20:05
  895. patterns your work frequency everything
  896. 20:08
  897. that's stored out there and Bluffdale
  898. 20:10
  899. Utah you know at you know the NSA data
  900. 20:14
  901. center of your choice right and then
  902. 20:16
  903. they can craft these bods to start
  904. 20:21
  905. interacting with you they become like
  906. 20:22
  907. your alter ego or your doppelganger
  908. 20:24
  909. right out there and they can be
  910. 20:27
  911. programmed in suite in a I mean the
  912. 20:31
  913. reason why the CIA loves programming and
  914. 20:33
  915. love software is you can create one for
  916. 20:36
  917. everybody with no marginal increase
  918. 20:38
  919. for very little increase in cost and so
  920. 20:41
  921. when when Quinn's talking about this AI
  922. 20:43
  923. stuff what we're really talking about is
  924. 20:45
  925. the thoughts that have access to your
  926. 20:48
  927. personal data they know you they've
  928. 20:51
  929. learned you because they watch your
  930. 20:53
  931. speech patterns they watch your
  932. 20:55
  933. interactions on social media they have
  934. 20:58
  935. your communications network with you
  936. 21:01
  937. look the people you associate most
  938. 21:03
  939. closely so they know they're getting
  940. 21:05
  941. better and better I know this is a
  942. 21:07
  943. Orwellian nightmare scenario but they're
  944. 21:11
  945. getting better and better at being able
  946. 21:14
  947. to disrupt you or discord you or or
  948. 21:16
  949. whatever you want to call it and that's
  950. 21:21
  951. what's also that doesn't let the Oracle
  952. 21:24
  953. speak hey Quinn do you have any like
  954. 21:26
  955. electrical power stuff near any of your
  956. 21:28
  957. sound I'm trying to troubleshoot this
  958. 21:29
  959. sound problem in real time I'm sorry
  960. 21:31
  961. everybody my phone is not close to the
  962. 21:34
  963. laptop I've got 50 suggestions about the
  964. 21:36
  965. sound coming from the comments here part
  966. 21:42
  967. of the reason why we have some of these
  968. 21:44
  969. technical issues is that there's
  970. 21:45
  971. virtually every day something
  972. 21:48
  973. substantial changing about the way the
  974. 21:51
  975. system is set up here but anyway let's
  976. 21:55
  977. just move on I think people can I think
  978. 21:59
  979. people can I think people can hear all
  980. 22:02
  981. right I'll just do one more preamble for
  982. 22:05
  983. Quinn because it's it you know I
  984. 22:08
  985. shouldn't do this but yep let's just say
  986. 22:11
  987. that you have a data set like the NGP
  988. 22:13
  989. van and I'm just going to show you how
  990. 22:15
  991. you can uptick a data set or add value
  992. 22:19
  993. to a data set and let's say you have the
  994. 22:20
  995. MGP band data set now I know who all the
  996. 22:23
  997. voters are now let's say I have this
  998. 22:26
  999. catalyst information which is a layer on
  1000. 22:28
  1001. top of that that Tony and John Podesta
  1002. 22:32
  1003. would add and that would be oh you know
  1004. 22:36
  1005. you're you're a heavy donor the NGP van
  1006. 22:39
  1007. tells me you're heavy donor to the
  1008. 22:41
  1009. Democratic Party you give $50,000 a year
  1010. 22:44
  1011. that's a significant amount of money now
  1012. 22:46
  1013. because you go over that you trip that
  1014. 22:49
  1015. wire now I go out and interview you I
  1016. 22:51
  1017. send somebody out
  1018. 22:52
  1019. I find out that Oh your cottage
  1020. 22:55
  1021. cardiologist and the wife is a
  1022. 22:57
  1023. neurosurgeon and oh by the way you have
  1024. 23:00
  1025. a son that has this this genetic disease
  1026. 23:03
  1027. and you have a daughter that wants to
  1028. 23:04
  1029. get into Harvard you know and I this
  1030. 23:08
  1031. profile now using that information right
  1032. 23:13
  1033. which is the catalyst information that
  1034. 23:14
  1035. Harold Ickes added on Rajesh's is kind
  1036. 23:18
  1037. of like hey I run ratlines
  1038. 23:20
  1039. hey I have military I use military
  1040. 23:24
  1041. transportation networks and State
  1042. 23:28
  1043. Department pay-to-play
  1044. 23:29
  1045. to provide favors for the elite I can do
  1046. 23:32
  1047. that what if I then put this in Palantir
  1048. 23:36
  1049. what if I put this data that's in this
  1050. 23:39
  1051. NGP van and this is exactly what is
  1052. 23:42
  1053. happening I am not speculating this is
  1054. 23:45
  1055. exactly what it's happening a catalyst
  1056. 23:47
  1057. was a layer on top of the NGP van
  1058. 23:50
  1059. democratic voter database to this
  1060. 23:53
  1061. ratline information how susceptible you
  1062. 23:56
  1063. be to things we could provide you
  1064. 23:58
  1065. through military ratlines we have all
  1066. 24:00
  1067. over the world now we throw it in to all
  1068. 24:03
  1069. the datasets that you have in your
  1070. 24:07
  1071. social media right and that now that's
  1072. 24:11
  1073. Quinn and as that's claimed can take it
  1074. 24:13
  1075. from there what what what what can be
  1076. 24:15
  1077. done from a database point of view and a
  1078. 24:17
  1079. bot point of view from there exactly so
  1080. 24:21
  1081. you're very spot on George would pound
  1082. 24:27
  1083. here because Palin tears and healthcare
  1084. 24:29
  1085. Palin tears at Walmart volunteers at
  1086. 24:32
  1087. coca-cola volunteers at the CIA
  1088. 24:35
  1089. volunteers at the Marines the NSA the
  1090. 24:37
  1091. FBI it's at the DNC I there's an email
  1092. 24:42
  1093. and WikiLeaks that confirms that Chelsea
  1094. 24:44
  1095. Clinton was using Palantir to do data
  1096. 24:46
  1097. mining for the Clinton Foundation to
  1098. 24:49
  1099. find out where their successes and
  1100. 24:50
  1101. failures are all the news articles that
  1102. 24:53
  1103. talk about volunteers customers and
  1104. 24:56
  1105. really Palantir looks like it's creating
  1106. 24:59
  1107. a big giant Network that's global where
  1108. 25:03
  1109. it's sucking up everybody's information
  1110. 25:05
  1111. from the
  1112. 25:06
  1113. things you buy at Walmart to your
  1114. 25:09
  1115. records with the CIA and it's all being
  1116. 25:12
  1117. stored in the same system and if you
  1118. 25:14
  1119. look at the court case that Palantir has
  1120. 25:16
  1121. with the NYPD the whole reason that the
  1122. 25:19
  1123. court case is there is because the NYPD
  1124. 25:21
  1125. couldn't give volunteered to give them
  1126. 25:24
  1127. their analyzed data they could get
  1128. 25:27
  1129. powned here to give them the data that
  1130. 25:29
  1131. they sent to them to put into the system
  1132. 25:30
  1133. but Palantir wouldn't return the data
  1134. 25:34
  1135. that they had analyzed so they could
  1136. 25:36
  1137. integrate their new IBM system and that
  1138. 25:39
  1139. means that Palantir doesn't even need a
  1140. 25:41
  1141. backdoor because it's a cloud service
  1142. 25:43
  1143. it's not like it was in the old days
  1144. 25:45
  1145. where your customers would hold the
  1146. 25:47
  1147. machines at their location and you would
  1148. 25:50
  1149. have to have a dial in line or a rat
  1150. 25:52
  1151. line nowadays in the cloud all the
  1152. 25:55
  1153. information is stored on the same system
  1154. 25:57
  1155. so behind the scenes they could have a
  1156. 26:00
  1157. network of very very advanced
  1158. 26:03
  1159. programmers putting all that stuff in
  1160. 26:05
  1161. together to do predictive analytics or
  1162. 26:07
  1163. predictive mathematics they could incite
  1164. 26:11
  1165. Wars they could change currencies they
  1166. 26:14
  1167. could increase product prices they could
  1168. 26:17
  1169. change education markets I mean you name
  1170. 26:20
  1171. it with all that data being in the same
  1172. 26:22
  1173. system and it not being housed in the
  1174. 26:25
  1175. respective locations where the office
  1176. 26:26
  1177. can control it I can almost guarantee
  1178. 26:29
  1179. you that they're there data analysts
  1180. 26:31
  1181. that they have that are secret are
  1182. 26:33
  1183. taking all that data and using it to
  1184. 26:35
  1185. make the future or make finances or make
  1186. 26:38
  1187. government's sway how they would want it
  1188. 26:43
  1189. would be very easy if I'm being backed
  1190. 26:45
  1191. by the Malaysian government and the CIA
  1192. 26:47
  1193. and I'm in Saudi Arabia and I'm in
  1194. 26:50
  1195. United Arab Emirates where all the oil
  1196. 26:52
  1197. is that and I'm handling the database
  1198. 26:55
  1199. for Missing and Exploited Children and
  1200. 26:57
  1201. I'm handling Roberts big data I'm
  1202. 27:00
  1203. handling all the big data it would be
  1204. 27:02
  1205. easy for me as that person to manipulate
  1206. 27:05
  1207. that data without anyone ever knowing
  1208. 27:07
  1209. about it
  1210. 27:08
  1211. Wow so Peter Thiel is kind of like the
  1212. 27:10
  1213. George Soros of data pretty much pretty
  1214. 27:14
  1215. much him and dr. Alex as I call him and
  1216. 27:16
  1217. dr. alex is the the mathematician
  1218. 27:19
  1219. program or the
  1220. 27:20
  1221. that I believe came up with the original
  1222. 27:21
  1223. predictive algorithms that Palantir uses
  1224. 27:24
  1225. or he says he came up with his
  1226. 27:26
  1227. predictive algorithms that Palantir uses
  1228. 27:28
  1229. as their base for other applications and
  1230. 27:32
  1231. then what Palantir does is when you sign
  1232. 27:35
  1233. on they'll give you a license and then
  1234. 27:37
  1235. they either you sell you one of their
  1236. 27:38
  1237. pre-existing off-the-shelf apps where
  1238. 27:40
  1239. they come in and build you a custom
  1240. 27:42
  1241. volunteer app for your data now quit
  1242. 27:44
  1243. your net all that sorry and then all
  1244. 27:47
  1245. that data gets sent to Palantir for
  1246. 27:49
  1247. analysis you had sent me an article
  1248. 27:52
  1249. about Peter Thiel's involvement with
  1250. 27:57
  1251. Trump this was from Politico talking
  1252. 28:00
  1253. about and and you know the comments have
  1254. 28:02
  1255. been discussing this in-between giving
  1256. 28:04
  1257. me advice for how to fix the sound we've
  1258. 28:06
  1259. got Donald Trump's shadow president in
  1260. 28:11
  1261. Silicon Valley you tell me about this
  1262. 28:14
  1263. what was this political article getting
  1264. 28:16
  1265. at the political argument was getting at
  1266. 28:19
  1267. how Jared and Josh Kushner introduced
  1268. 28:21
  1269. Peter Thiel to Donald Trump and from
  1270. 28:25
  1271. that moment on Peter Thiel has had a
  1272. 28:27
  1273. massive amount of influence to where he
  1274. 28:29
  1275. even had his own office during that I
  1276. 28:32
  1277. believe the transition period to the
  1278. 28:34
  1279. president and his consultants and
  1280. 28:39
  1281. contractors were being put into places
  1282. 28:41
  1283. like the Pentagon asking questions like
  1284. 28:44
  1285. how they procure their resources and
  1286. 28:47
  1287. they were able to put people into very
  1288. 28:49
  1289. high places in the government that
  1290. 28:51
  1291. weren't necessarily members of service
  1292. 28:56
  1293. the the other thing about the pond to
  1294. 28:59
  1295. your thing that's related to that that
  1296. 29:01
  1297. shadow president is whenever you're a
  1298. 29:04
  1299. big client and you sign on to Palantir
  1300. 29:06
  1301. they put a pound tear developer on site
  1302. 29:09
  1303. where you're at so that gives them
  1304. 29:12
  1305. further control over the data so they're
  1306. 29:14
  1307. sending in their own programmers they're
  1308. 29:16
  1309. sending in their system so to me at the
  1310. 29:19
  1311. end of it real simply it just looks like
  1312. 29:21
  1313. volunteers probably the system they're
  1314. 29:23
  1315. using to the Deep States using to
  1316. 29:26
  1317. manipulate everything Wow that's what it
  1318. 29:29
  1319. looks like that that's how it looks like
  1320. 29:32
  1321. this deep state super
  1322. 29:33
  1323. rich group of people like Jared Kushner
  1324. 29:36
  1325. who back most of the dot-coms like
  1326. 29:39
  1327. Airbnb and patreon and PayPal it seems
  1328. 29:43
  1329. to be the system they're using to
  1330. 29:44
  1331. manipulate and do predictive data and to
  1332. 29:47
  1333. keep everything in check so this guy
  1334. 29:49
  1335. David gelernt er he's the reclusive Yale
  1336. 29:53
  1337. University computer scientist who he's
  1338. 29:56
  1339. the shadow president is that the idea no
  1340. 29:59
  1341. he's he's one of the early predictors of
  1342. 30:02
  1343. the Internet and he's just a good friend
  1344. 30:04
  1345. of Peter Thiel that Peter Thiel
  1346. 30:06
  1347. recommended President Trump put in an
  1348. 30:08
  1349. advisory position so Peter Thiel is
  1350. 30:12
  1351. pretty much recommending that his
  1352. 30:14
  1353. friends or people that are part of his
  1354. 30:15
  1355. network get put into places like the FDA
  1356. 30:17
  1357. and you know other places in government
  1358. 30:20
  1359. where you can be of influence okay I'm
  1360. 30:22
  1361. sorry I misunderstood it steel himself
  1362. 30:24
  1363. who is the shadow president yes yes it
  1364. 30:27
  1365. steel himself that's the shadow
  1366. 30:28
  1367. president in Silicon Valley so my guess
  1368. 30:31
  1369. my guess is that Palantir when they did
  1370. 30:35
  1371. the meeting between Jared and Josh
  1372. 30:37
  1373. Carson Kushner to introduce Peter teal
  1374. 30:41
  1375. to Donald Trump before he was president
  1376. 30:43
  1377. logically there's a high option that
  1378. 30:46
  1379. Peter Thiel might have presented some
  1380. 30:48
  1381. damning evidence that would have kind of
  1382. 30:50
  1383. allowed him an opening into Trump's
  1384. 30:53
  1385. world to get that much power right off
  1386. 30:55
  1387. the bat you know and when you have the
  1388. 30:58
  1389. system that like tracks all the data can
  1390. 31:00
  1391. access all the video cameras uses AI to
  1392. 31:03
  1393. do image reading and video recognition
  1394. 31:06
  1395. and text analysis it's pretty easy to
  1396. 31:10
  1397. say hey I got some information on you my
  1398. 31:12
  1399. system found we you know we want you to
  1400. 31:13
  1401. use us and so from that the power of the
  1402. 31:17
  1403. tier system I mean it was happening in
  1404. 31:20
  1405. an Obama era from what I found but from
  1406. 31:22
  1407. that the Palantir system there's now
  1408. 31:25
  1409. being a custom program just built that's
  1410. 31:27
  1411. gonna be released in the file that's
  1412. 31:28
  1413. going to be running the ice program
  1414. 31:30
  1415. that's what's going to be tracking and
  1416. 31:32
  1417. detaining illegal immigrants for
  1418. 31:34
  1419. deportation huh so that's really the big
  1420. 31:38
  1421. Palantir system that they're working on
  1422. 31:40
  1423. releasing in the fall right now is the
  1424. 31:42
  1425. one that's going to track illegal
  1426. 31:43
  1427. immigrants so I'm on the cards
  1428. 31:46
  1429. sort of particularly fascinated with
  1430. 31:48
  1431. this photograph of Peter Thiel and
  1432. 31:50
  1433. Donald Trump holding hands I didn't know
  1434. 31:53
  1435. much about Peter Thiel when the election
  1436. 31:55
  1437. was going on I I remember people found
  1438. 31:58
  1439. it quite strange that he was a
  1440. 32:00
  1441. Republican and gay and that it seemed to
  1442. 32:03
  1443. me that Donald Trump was you know
  1444. 32:06
  1445. utilizing him to sort of ingratiate
  1446. 32:09
  1447. himself to the gay population
  1448. 32:11
  1449. but obviously there's so much more to it
  1450. 32:14
  1451. yeah if you if you you if you
  1452. 32:16
  1453. cross-reference with WikiLeaks you'll
  1454. 32:19
  1455. find that dr. alex was communicating
  1456. 32:21
  1457. with John Podesta saying things like oh
  1458. 32:23
  1459. the DNC and Hillary Rodham Clinton are
  1460. 32:25
  1461. the only people Palantir will support
  1462. 32:27
  1463. and meanwhile Peter Thiel on the other
  1464. 32:30
  1465. side is getting on the Trump train going
  1466. 32:32
  1467. Oh
  1468. 32:33
  1469. Trump we have this amazing system where
  1470. 32:35
  1471. you can you know make your immigration
  1472. 32:37
  1473. policies go over real easily and
  1474. 32:39
  1475. smoothly and no one will ever know it
  1476. 32:41
  1477. and they won't know how you're finding
  1478. 32:43
  1479. all the illegal immigrants because we
  1480. 32:45
  1481. have a system that accesses every camera
  1482. 32:48
  1483. and every government agency and we can
  1484. 32:50
  1485. give you a list of where your hotspots
  1486. 32:52
  1487. of illegal immigrants would be based on
  1488. 32:54
  1489. property sale records grocery store
  1490. 32:56
  1491. purchases I mean they can literally
  1492. 32:59
  1493. narrow it down based on okay we know
  1494. 33:01
  1495. immigrants are gonna buy more food from
  1496. 33:03
  1497. their country so they're gonna visit
  1498. 33:04
  1499. places where there's more you know
  1500. 33:06
  1501. Mexican delis or grocery stores I mean
  1502. 33:10
  1503. they can narrow it down to any anything
  1504. 33:11
  1505. from what you're buying at Walmart I
  1506. 33:13
  1507. mean they could say oh people from
  1508. 33:15
  1509. Mexico are gonna be more likely to buy
  1510. 33:18
  1511. this so let's start building an
  1512. 33:20
  1513. algorithm pattern to monitor it and
  1514. 33:21
  1515. eventually world come close to finding
  1516. 33:23
  1517. people who shouldn't be here and we can
  1518. 33:25
  1519. use subversive algorithms to track and
  1520. 33:28
  1521. and find people and then once they get
  1522. 33:31
  1523. rid of other immigrants most likely that
  1524. 33:33
  1525. system will be used for other means and
  1526. 33:36
  1527. other places if it's Palantir and
  1528. 33:38
  1529. they're both getting someone to pay for
  1530. 33:39
  1531. the building of it they'll keep a copy
  1532. 33:41
  1533. of it for themselves and use it
  1534. 33:42
  1535. somewhere else now you had mentioned
  1536. 33:44
  1537. that Palantir is somehow involved in
  1538. 33:47
  1539. quantum computing
  1540. 33:49
  1541. you know I've received some previous
  1542. 33:52
  1543. information that the investors in d-wave
  1544. 33:56
  1545. which is a company we've heard about
  1546. 33:57
  1547. before and that you and I have spoken
  1548. 33:59
  1549. about relative to the most advanced AI
  1550. 34:01
  1551. around
  1552. 34:02
  1553. how is d-wave involved in the Palantir
  1554. 34:05
  1555. or is it to your knowledge it's needed
  1556. 34:08
  1557. for the advanced predictive algorithms
  1558. 34:10
  1559. you you need a at least low level
  1560. 34:14
  1561. quantum computer with notes because the
  1562. 34:17
  1563. Palantir system is a node based system
  1564. 34:19
  1565. and quantum systems are node based plus
  1566. 34:22
  1567. the if you remember the picture of
  1568. 34:25
  1569. Donald Trump when he I think it was
  1570. 34:26
  1571. Saudi Arabia they got a picture of him
  1572. 34:28
  1573. with like the Egyptian Sheik and the
  1574. 34:31
  1575. politician with them while putting their
  1576. 34:33
  1577. hands on that glowing orb yeah what the
  1578. 34:35
  1579. hell was that that's what is it that's
  1580. 34:38
  1581. that's a Palantir system that's how big
  1582. 34:41
  1583. they are well the whole monitoring room
  1584. 34:44
  1585. all the analysts the central AI brain
  1586. 34:47
  1587. which is the the Palantir processing
  1588. 34:50
  1589. unit that whole thing is the Palantir
  1590. 34:52
  1591. system it's not just like a thing you've
  1592. 34:55
  1593. load up on a webpage this is like you
  1594. 34:57
  1595. need like serious horsepower to run
  1596. 35:00
  1597. these predictive mathematics that
  1598. 35:01
  1599. they're they're pushing out and to house
  1600. 35:05
  1601. all that data you would need literally a
  1602. 35:07
  1603. quantum system to access it in real time
  1604. 35:09
  1605. I mean that looked like something out of
  1606. 35:11
  1607. you know the x-men cerebro that was like
  1608. 35:13
  1609. such a bizarre photograph yeah yeah but
  1610. 35:19
  1611. that's the purpose of your weird sphere
  1612. 35:21
  1613. it's part of the Palantir system I'm
  1614. 35:24
  1615. assuming that the big Palantir systems
  1616. 35:27
  1617. probably have one is like some type of
  1618. 35:30
  1619. marker you know because it's the Sirah
  1620. 35:32
  1621. you know the evil crystal ball disease
  1622. 35:34
  1623. into the future you know and they sound
  1624. 35:37
  1625. like they like to name things after
  1626. 35:38
  1627. movies and do things for nostalgia so it
  1628. 35:40
  1629. could be just like you know a little
  1630. 35:42
  1631. statue marker for their Palantir system
  1632. 35:45
  1633. that's yeah what Trump and the other
  1634. 35:48
  1635. politicians are touching is actually a
  1636. 35:50
  1637. Palantir it's like a crystal ball that
  1638. 35:51
  1639. sees into the future you know and that's
  1640. 35:54
  1641. what Palantir is meant to be it's meant
  1642. 35:55
  1643. to be your all-seeing eye that can see
  1644. 35:58
  1645. into the future at least five years well
  1646. 36:00
  1647. that's how can it
  1648. 36:01
  1649. see into the future just predictive
  1650. 36:03
  1651. algorithms human beings they're
  1652. 36:06
  1653. creatures of habit and they generally
  1654. 36:08
  1655. make decisions based on certain logic or
  1656. 36:12
  1657. decision sets that they contain from
  1658. 36:14
  1659. education on up so like when I go to the
  1660. 36:17
  1661. school the school I go to teaches me to
  1662. 36:19
  1663. make certain choices then I go to junior
  1664. 36:22
  1665. high school and then I learned how to
  1666. 36:23
  1667. make different choices and then I go to
  1668. 36:24
  1669. high school learn how to make more
  1670. 36:25
  1671. expanded choices then I go to college
  1672. 36:27
  1673. and depending on what college I go to
  1674. 36:28
  1675. watch University and which program I'm
  1676. 36:31
  1677. in I learned how to make certain types
  1678. 36:32
  1679. of decisions based on my education
  1680. 36:34
  1681. background and then the computer then
  1682. 36:36
  1683. takes your job your purchase history
  1684. 36:38
  1685. your groceries the kind of shoes you
  1686. 36:40
  1687. wear the color clothes you buy it takes
  1688. 36:42
  1689. your education background and then it
  1690. 36:43
  1691. starts producing what's called a future
  1692. 36:46
  1693. matrix of potential options of where you
  1694. 36:48
  1695. could go and what types of jobs and
  1696. 36:50
  1697. where you're going to eat and then from
  1698. 36:51
  1699. there it starts whittling it down as
  1700. 36:53
  1701. time moves forward Wow you know I've got
  1702. 36:57
  1703. the picture up I don't imagine you can
  1704. 36:58
  1705. see the broadcast where you are right
  1706. 37:00
  1707. now but I've zoomed into the corner and
  1708. 37:02
  1709. I hope you'll look at this on playback
  1710. 37:04
  1711. it appears that this photograph was
  1712. 37:06
  1713. taken at some sort of Center for
  1714. 37:09
  1715. extremist ideology yeah the hell is the
  1716. 37:13
  1717. president doing there George uh I have
  1718. 37:19
  1719. no idea my my brush quit mate you know
  1720. 37:26
  1721. it's doing his thing and you know
  1722. 37:28
  1723. obviously very busy so I don't think
  1724. 37:30
  1725. he's seen these episodes but I went to
  1726. 37:33
  1727. Clarksburg West Virginia I'm with a
  1728. 37:34
  1729. whole bunch of people tonight they just
  1730. 37:36
  1731. met up by the fireplace here in Ohio
  1732. 37:37
  1733. from West Virginia and it was it was it
  1734. 37:42
  1735. reminded me of that episode but the
  1736. 37:44
  1737. criminal justice information systems cg8
  1738. 37:46
  1739. CJ is which was kind of like the old
  1740. 37:50
  1741. promise system of flat not I don't mean
  1742. 37:52
  1743. to say flat file but like a relational
  1744. 37:54
  1745. database system is moving in the
  1746. 37:57
  1747. direction they bought a deep wave
  1748. 37:58
  1749. computer and this Burrell guy he you are
  1750. 38:02
  1751. temporal temporal data systems ex-fbi
  1752. 38:06
  1753. guy has bought one of these and they are
  1754. 38:09
  1755. using it in Clarksburg web West Virginia
  1756. 38:11
  1757. to
  1758. 38:11
  1759. do exactly what Wayne is saying and that
  1760. 38:16
  1761. is adding the temporal component when
  1762. 38:18
  1763. you add your geolocation and your
  1764. 38:21
  1765. thoughts and and time continuum to
  1766. 38:25
  1767. everything except the complexity vehicle
  1768. 38:27
  1769. the calculations goes up by a factor 100
  1770. 38:30
  1771. it goes left by the square of 10 so the
  1772. 38:34
  1773. computing power needed needed to do all
  1774. 38:37
  1775. these things in real time because what
  1776. 38:39
  1777. they want to do is go from making
  1778. 38:40
  1779. predictive decisions a day ahead of time
  1780. 38:43
  1781. which is more of a batch process they
  1782. 38:45
  1783. want to now start to do it in real time
  1784. 38:48
  1785. so as Quinn is saying if I can predict
  1786. 38:52
  1787. where you're gonna eat if I can predict
  1788. 38:53
  1789. where you're going to apply to go to
  1790. 38:56
  1791. graduate school all these things it's
  1792. 38:59
  1793. it's right out of Minority Report it's
  1794. 39:02
  1795. right out of predicting crime and it's a
  1796. 39:06
  1797. winner's list Society all these things
  1798. 39:11
  1799. are it's kind of like the airplane or
  1800. 39:13
  1801. whatever can be used for good or could
  1802. 39:17
  1803. be used for evil and unfortunately the
  1804. 39:20
  1805. CIA if you watch and look at their
  1806. 39:23
  1807. investments in what they study it's all
  1808. 39:25
  1809. about like winners lists and losers
  1810. 39:27
  1811. lists it's us versus them and how do I
  1812. 39:29
  1813. use this technology to destroy the lives
  1814. 39:32
  1815. of these people that we for some reason
  1816. 39:35
  1817. have chosen to be our enemy and I think
  1818. 39:37
  1819. you know I think when it's gone through
  1820. 39:39
  1821. that very personally with the Dibango
  1822. 39:42
  1823. type stuff you know this is MIT you know
  1824. 39:47
  1825. PhD level top of the top minds yeah
  1826. 39:52
  1827. Berkeley this isn't something like you
  1828. 39:55
  1829. know 13 year old in a in an apartment
  1830. 39:58
  1831. working on some algorithms this is the
  1832. 40:00
  1833. top research institutions in our country
  1834. 40:03
  1835. working on this stuff on CIA contracts
  1836. 40:06
  1837. it's just that's just the truth Wow
  1838. 40:09
  1839. you know but the we had heard previously
  1840. 40:14
  1841. that DynCorp was involved with DARPA
  1842. 40:18
  1843. and MIT and Raytheon developing AI for
  1844. 40:23
  1845. the US Army so it almost seems like
  1846. 40:25
  1847. we've got
  1848. 40:25
  1849. ái factions there that how do we know
  1850. 40:29
  1851. who's on our side well in my observation
  1852. 40:34
  1853. with the AI and it it's all pretty much
  1854. 40:37
  1855. I've there been developed by one of the
  1856. 40:40
  1857. secret agencies or or under some type of
  1858. 40:42
  1859. military contract right right now to me
  1860. 40:46
  1861. and George may agree or disagree right
  1862. 40:49
  1863. now the sides of Defense are the people
  1864. 40:51
  1865. that are using the AI and the people
  1866. 40:54
  1867. that aren't Wow sorry you know it's like
  1868. 40:59
  1869. a couple days ago I was even sitting in
  1870. 41:02
  1871. the Mount Shasta library and I was doing
  1872. 41:03
  1873. research on the Army's AI and I was
  1874. 41:06
  1875. looking at the Palantir court case that
  1876. 41:09
  1877. cuz Palantir suing the army because the
  1878. 41:11
  1879. army doesn't want to use their system
  1880. 41:13
  1881. and literally like the next day when I
  1882. 41:16
  1883. was doing research in the library there
  1884. 41:18
  1885. was a guy sitting across from me who was
  1886. 41:20
  1887. part of Army Intelligence and he was a
  1888. 41:22
  1889. ranger who was deployed to the field in
  1890. 41:25
  1891. Afghanistan and he was the field tech to
  1892. 41:28
  1893. maintain the Army's Clips AI which I
  1894. 41:31
  1895. don't know what it stands for but that's
  1896. 41:32
  1897. the name of their AI that sits on their
  1898. 41:35
  1899. machines you know so so it's a real
  1900. 41:39
  1901. strange thing that it just seems now
  1902. 41:40
  1903. it's about that everyone wants to
  1904. 41:42
  1905. complete their their AI so it's a fully
  1906. 41:45
  1907. functioning one because they don't
  1908. 41:47
  1909. function entirely correctly I mean if
  1910. 41:50
  1911. they did we wouldn't see a lot of the
  1912. 41:52
  1913. social problems that we have in the
  1914. 41:53
  1915. world
  1916. 41:53
  1917. what doesn't damage an entirely
  1918. 41:56
  1919. correctly AI they're they're big giant
  1920. 41:58
  1921. AI that they spent all this time and
  1922. 42:01
  1923. money building it doesn't function
  1924. 42:02
  1925. properly and the outcome of that is all
  1926. 42:05
  1927. the social problems we're having because
  1928. 42:08
  1929. a quantum based strong or intelligent
  1930. 42:11
  1931. artificial general intelligence should
  1932. 42:13
  1933. be able to analyze society problems in
  1934. 42:16
  1935. 24 hours and then on for our solutions
  1936. 42:18
  1937. to maintain balance whoa
  1938. 42:20
  1939. or it's broken aha
  1940. 42:23
  1941. so so I these things can get dystopian
  1942. 42:26
  1943. really quickly
  1944. 42:27
  1945. you know III want to say first of all I
  1946. 42:31
  1947. completely agree 100% whoops I think we
  1948. 42:36
  1949. lost George no you're back up I could
  1950. 42:38
  1951. I completely agree with Wynn that it's
  1952. 42:40
  1953. the humans like Quinn and very smart
  1954. 42:44
  1955. guys like Quinn versus the AI because
  1956. 42:48
  1957. somehow for some reason that side the
  1958. 42:51
  1959. evil side doesn't have Quinn you know
  1960. 42:54
  1961. and it really is this that's why I put
  1962. 42:57
  1963. this far off versus deep blue this is
  1964. 43:00
  1965. really kind of this human chess match
  1966. 43:03
  1967. versus these AI guys and you've seen it
  1968. 43:07
  1969. with you and Topanga you know in a
  1970. 43:10
  1971. personal thing between you two guys
  1972. 43:12
  1973. but in a larger sense you're just the
  1974. 43:15
  1975. kind of a microcosm of this you know
  1976. 43:18
  1977. this war that's coming and you know you
  1978. 43:23
  1979. have I mean the good the good news is
  1980. 43:25
  1981. there are guys like point out there that
  1982. 43:27
  1983. have designed and safe networks and ways
  1984. 43:29
  1985. of defeating these things that are quite
  1986. 43:32
  1987. ingenious and it's almost like this I
  1988. 43:36
  1989. don't like comparison I get to give this
  1990. 43:38
  1991. Kasparov playing deep blue and even
  1992. 43:41
  1993. though deep blue had this incredible
  1994. 43:45
  1995. computing power just the the
  1996. 43:47
  1997. intuitiveness and an imagination and
  1998. 43:50
  1999. creativity of the human mind somehow
  2000. 43:51
  2001. somehow still wins still wins and could
  2002. 43:55
  2003. you just talk about safe networks and
  2004. 43:57
  2005. like made safe and and some of the
  2006. 43:59
  2007. different safe networks that you devised
  2008. 44:03
  2009. some of the some of the snake safe
  2010. 44:06
  2011. networks are creating like word-of-mouth
  2012. 44:11
  2013. networks where you create a
  2014. 44:14
  2015. word-of-mouth network where you go from
  2016. 44:16
  2017. one person who says okay we're creating
  2018. 44:18
  2019. a bot safe networking the only way to
  2020. 44:19
  2021. get in there is to give a code to a
  2022. 44:21
  2023. person that gives it to one of their
  2024. 44:23
  2025. friends to create a safe network to
  2026. 44:26
  2027. isolate the AI from the humans because
  2028. 44:30
  2029. that's safe networks having a safe
  2030. 44:32
  2031. network at least one safe network in the
  2032. 44:34
  2033. near future is going to be very
  2034. 44:35
  2035. important because people are gonna need
  2036. 44:37
  2037. a way not to communicate anonymously but
  2038. 44:40
  2039. to communicate without influence because
  2040. 44:44
  2041. that's one of the things the anonymous
  2042. 44:46
  2043. chat networks and anonymous anonymous
  2044. 44:49
  2045. apps and anonymous gossip apps they're
  2046. 44:51
  2047. not
  2048. 44:52
  2049. those are being used to collect massive
  2050. 44:54
  2051. data to train machines so for people to
  2052. 44:59
  2053. communicate and come up with solutions
  2054. 45:01
  2055. and to start being able to better deal
  2056. 45:05
  2057. with this there has to almost be a safe
  2058. 45:07
  2059. network or an I I call it an isolated
  2060. 45:10
  2061. network that isolates itself away from
  2062. 45:12
  2063. bots it isolates itself away from that
  2064. 45:16
  2065. section of the internet so you have one
  2066. 45:18
  2067. place where the networks like the
  2068. 45:19
  2069. contour network or there's another one I
  2070. 45:22
  2071. call I think it's called by Cambridge
  2072. 45:24
  2073. analytics or Cambridge its Cambridge
  2074. 45:27
  2075. data something but there's quite a few
  2076. 45:29
  2077. companies out there right now especially
  2078. 45:31
  2079. now that the quantum computer isn't
  2080. 45:33
  2081. locked away in a government research
  2082. 45:34
  2083. program or not being you know hoarded by
  2084. 45:37
  2085. the CIA or the military now that
  2086. 45:40
  2087. corporations can buy these quantum
  2088. 45:42
  2089. computers and they can buy the licenses
  2090. 45:45
  2091. to Palantir systems and they can become
  2092. 45:47
  2093. customers to these what they call SAS
  2094. 45:49
  2095. which is software as a service companies
  2096. 45:53
  2097. the people that want to operate
  2098. 45:56
  2099. independently of that it will like I
  2100. 45:58
  2101. said it will be very important to find a
  2102. 46:00
  2103. safe net like that's secure that's
  2104. 46:03
  2105. potentially I mean it doesn't
  2106. 46:05
  2107. necessarily need to operate on the
  2108. 46:06
  2109. blockchain it just would be best
  2110. 46:09
  2111. operating from word-of-mouth like people
  2112. 46:11
  2113. share a link like hey I get a link to
  2114. 46:13
  2115. share for this network so you can trace
  2116. 46:15
  2117. back how they get in if they do get in
  2118. 46:18
  2119. and you can find out you know okay this
  2120. 46:20
  2121. person gave the link to this person
  2122. 46:22
  2123. because BOTS no matter how nice they are
  2124. 46:25
  2125. what the percentage is there's always
  2126. 46:27
  2127. going to be somewhere out there that's
  2128. 46:28
  2129. going to design a bot to strike your
  2130. 46:31
  2131. emotions or poke you for personal data
  2132. 46:34
  2133. or analyze your conversations or your
  2134. 46:37
  2135. photos I mean it's just gonna be there I
  2136. 46:39
  2137. mean look at Facebook they have AI that
  2138. 46:41
  2139. writes its own language now yeah that
  2140. 46:44
  2141. didn't just not to get to 1984 about
  2142. 46:50
  2143. this but what I've encouraged the people
  2144. 46:52
  2145. on our network across source the truth
  2146. 46:55
  2147. is to speak in these kind of deep
  2148. 46:58
  2149. analogy is what I call it
  2150. 47:00
  2151. yeah and deep analogy it still seems
  2152. 47:03
  2153. like the box have trouble
  2154. 47:05
  2155. deep analogy and and Shakespeare just
  2156. 47:08
  2157. seems to just mangle all the gears for
  2158. 47:11
  2159. them and just Shakespeare just destroys
  2160. 47:13
  2161. them for some reason so if you think
  2162. 47:16
  2163. someone is like a fake or phony if you
  2164. 47:20
  2165. say you think Smouse not both protest
  2166. 47:24
  2167. too much you know what I mean I know
  2168. 47:27
  2169. what you mean it's sort of a safe speak
  2170. 47:29
  2171. if you will and I know we're getting a
  2172. 47:31
  2173. little ethereal and a little abstract
  2174. 47:32
  2175. here but if you I mean it just destroys
  2176. 47:37
  2177. the buds and it's it's so fun because if
  2178. 47:42
  2179. you so I encourage everybody if they're
  2180. 47:45
  2181. making a comment just give me that
  2182. 47:47
  2183. Shakespeare quote and it just it just I
  2184. 47:50
  2185. the box come back with a strange is the
  2186. 47:52
  2187. answer it's so money to watch and the
  2188. 47:55
  2189. other thing you can do the another thing
  2190. 47:57
  2191. that comes to mind is if you think
  2192. 48:00
  2193. you're talking to a bot go to one of the
  2194. 48:03
  2195. translation services and translate your
  2196. 48:05
  2197. reply into a foreign language and see
  2198. 48:08
  2199. the reply of the bot usually if it's a
  2200. 48:09
  2201. human it'll say something like what
  2202. 48:12
  2203. language is that why did you say that
  2204. 48:14
  2205. but if it's a bot it'll try to analyze
  2206. 48:16
  2207. what you're saying and respond
  2208. 48:17
  2209. accordingly it won't yeah they respond
  2210. 48:21
  2211. in the same way you know guys that
  2212. 48:22
  2213. picture of President Trump in the center
  2214. 48:25
  2215. for extremists whatever it is that
  2216. 48:28
  2217. reminded me of sleeper Jorge which we
  2218. 48:30
  2219. were just talking about the other day
  2220. 48:32
  2221. where they got the or yeah it's got the
  2222. 48:34
  2223. the orgasm orb now Quinn the comments on
  2224. 48:37
  2225. YouTube are asking me if you're
  2226. 48:40
  2227. referring to a huge you know what a Q is
  2228. 48:43
  2229. I haven't heard of that I haven't really
  2230. 48:47
  2231. and that hasn't come across in my
  2232. 48:48
  2233. research yet either that I can go look
  2234. 48:50
  2235. it up well aq usually is al-qaeda I mean
  2236. 48:53
  2237. I think that's a terrorism reference AHA
  2238. 48:55
  2239. but unless that's it that's a tech
  2240. 48:59
  2241. reference somebody tell me I would think
  2242. 49:01
  2243. if it's being posed to Quinn but who
  2244. 49:04
  2245. knows maybe the person who asked it will
  2246. 49:07
  2247. will hear that my research is really
  2248. 49:11
  2249. staying out of the al-qaeda point of
  2250. 49:14
  2251. view or the the extremist terrorist
  2252. 49:17
  2253. point of view that exists
  2254. 49:19
  2255. outside of the boundaries of the country
  2256. 49:22
  2257. because outside of the boundaries of the
  2258. 49:25
  2259. country Palantir is the field operation
  2260. 49:27
  2261. system for the Marines and you know the
  2262. 49:30
  2263. field servicemen and women that are in
  2264. 49:34
  2265. most parts of the world dealing with
  2266. 49:36
  2267. whatever problems they're dealing with
  2268. 49:38
  2269. my concern is is that there's another
  2270. 49:42
  2271. darker deeper pocketed network behind
  2272. 49:45
  2273. Palantir where they really got their
  2274. 49:47
  2275. system from that has a system themselves
  2276. 49:49
  2277. that they're selling to those extremists
  2278. 49:52
  2279. to do their operations
  2280. 49:54
  2281. what do you man to do well because when
  2282. 49:57
  2283. you have a large network of people you
  2284. 49:59
  2285. have resources you have logistics you
  2286. 50:00
  2287. have personal profiles you have a lot of
  2288. 50:04
  2289. things that need to be maintained and
  2290. 50:06
  2291. tracked and you have to make sure people
  2292. 50:07
  2293. are staying in line so what's to make
  2294. 50:10
  2295. you think Isis doesn't have a big data
  2296. 50:12
  2297. system of their own I mean they have the
  2298. 50:15
  2299. resources so my concern with that is is
  2300. 50:19
  2301. like that's kind of where I draw the
  2302. 50:21
  2303. line because when you start getting to
  2304. 50:22
  2305. that line and you start talking about
  2306. 50:24
  2307. insurgent forces that may have access to
  2308. 50:27
  2309. a big data system that's really
  2310. 50:29
  2311. something for a military tribunal to
  2312. 50:32
  2313. investigate and it's not something for a
  2314. 50:34
  2315. citizen to get involved in but if it
  2316. 50:36
  2317. exists inside the boundaries of United
  2318. 50:39
  2319. States I'm a United States citizen if
  2320. 50:41
  2321. it's on the public net and I have public
  2322. 50:43
  2323. access to it and I can put the patterns
  2324. 50:44
  2325. together and I can investigate it on my
  2326. 50:46
  2327. own and then that information can be
  2328. 50:49
  2329. relayed to some type of potential agency
  2330. 50:52
  2331. an hour in the future that can take
  2332. 50:53
  2333. correct action that's my objective you
  2334. 50:57
  2335. know my objective isn't to stir up
  2336. 50:59
  2337. feathers and get in the way of like
  2338. 51:01
  2339. these international terrorist groups
  2340. 51:03
  2341. that would really just rather see you
  2342. 51:05
  2343. disappear for getting in their way yeah
  2344. 51:07
  2345. we don't want to see that happen Quinn
  2346. 51:09
  2347. what's that yeah or is there any
  2348. 51:11
  2349. connection with prism I saw some article
  2350. 51:14
  2351. that was talking about you know Palantir
  2352. 51:16
  2353. said our prism is not the NSA's prism is
  2354. 51:19
  2355. that just stupid or what is that that
  2356. 51:22
  2357. that's the the core the autonomous chord
  2358. 51:26
  2359. there they're referencing I believe
  2360. 51:28
  2361. because it operates kind of like a fad
  2362. 51:31
  2363. that diamond or a faceted gem you know
  2364. 51:35
  2365. when they very complex it's like
  2366. 51:38
  2367. bouncing laser lights to create
  2368. 51:41
  2369. connections so that would I would assume
  2370. 51:45
  2371. would be what they call their course
  2372. 51:47
  2373. their gem or their spectrum earth huh
  2374. 51:51
  2375. there's asset another comment that's
  2376. 51:53
  2377. coming up people want to know Quinn do
  2378. 51:55
  2379. you have any advice for people that want
  2380. 51:57
  2381. to make themselves less traceable in the
  2382. 51:59
  2383. online world you seem to have done a
  2384. 52:01
  2385. good job of that being up there in the
  2386. 52:03
  2387. mountains I would actually like to be
  2388. 52:07
  2389. more traceable the more traceable you
  2390. 52:09
  2391. are to these AI the better chance you
  2392. 52:11
  2393. have because you become less suspicious
  2394. 52:15
  2395. the the more paranoid you are the higher
  2396. 52:19
  2397. chance you have of their network seeing
  2398. 52:21
  2399. you as a risk like I because of it I
  2400. 52:24
  2401. don't use encryption on my computer I
  2402. 52:26
  2403. don't really send a lot of you personal
  2404. 52:28
  2405. emails or you know most of this stuff I
  2406. 52:31
  2407. do I'm just very cautious about how I
  2408. 52:33
  2409. like like hiding your face from the AI
  2410. 52:37
  2411. is definitely one way to get yourself to
  2412. 52:40
  2413. be monitored huh
  2414. 52:42
  2415. in a way Wow you know it's it's
  2416. 52:47
  2417. predictive algorithm so if it wants to
  2418. 52:49
  2419. make a timeline for you it needs to see
  2420. 52:51
  2421. your face hear your voice and observe
  2422. 52:54
  2423. your patterns and if it can't do that
  2424. 52:57
  2425. then it can't make a timeline for you
  2426. 52:58
  2427. it's kind of why I said in the past how
  2428. 53:00
  2429. anonymous uses the masks for a
  2430. 53:03
  2431. collective timeline ah ha ha ha that's
  2432. 53:06
  2433. why that's one of the reasons why I'm
  2434. 53:08
  2435. also concluding that the main disruptive
  2436. 53:11
  2437. force of anonymous might be funded by
  2438. 53:13
  2439. these same people who are manipulating
  2440. 53:15
  2441. time lines with their supercomputer
  2442. 53:18
  2443. someone's telling me that aq is the
  2444. 53:20
  2445. adversity quotient does that make some
  2446. 53:24
  2447. more sense once we know that let me get
  2448. 53:27
  2449. a reference to that real quick yeah sure
  2450. 53:29
  2451. it's really a fascinating conversation
  2452. 53:32
  2453. as always Quinn Quinn why don't you tell
  2454. 53:34
  2455. everybody in the interest of making
  2456. 53:36
  2457. yourself more traceable how can people
  2458. 53:38
  2459. find you online the Rahula Club and your
  2460. 53:41
  2461. patreon page or whatever you want to
  2462. 53:43
  2463. yeah and also in the past month I
  2464. 53:47
  2465. started building my own artificial
  2466. 53:49
  2467. intelligence computing environment and
  2468. 53:52
  2469. you can go to Indra AI how do you spell
  2470. 53:56
  2471. the one of the IND RA got AI one of the
  2472. 54:01
  2473. things I found in dealing with this is
  2474. 54:02
  2475. like I had to start building my own big
  2476. 54:04
  2477. data system so I started developing
  2478. 54:07
  2479. against like the Google cloud and I have
  2480. 54:10
  2481. some IBM chat BOTS and I'm just getting
  2482. 54:13
  2483. into accessing the IBM Watson neuro
  2484. 54:18
  2485. linguistic analysis system because
  2486. 54:21
  2487. Watson has a thing where I can feed data
  2488. 54:23
  2489. into it and it'll do things like
  2490. 54:24
  2491. personality analysis it'll do tonal
  2492. 54:26
  2493. analysis for your speech
  2494. 54:29
  2495. so what I'm gonna start doing is I'm
  2496. 54:30
  2497. actually going to build an entire AI
  2498. 54:32
  2499. system and start feeding these peoples
  2500. 54:33
  2501. data into it and analysis analyzing
  2502. 54:35
  2503. their speech patterns analyzing their
  2504. 54:37
  2505. personal connections looking at their
  2506. 54:40
  2507. creating personality profiles based on
  2508. 54:43
  2509. data that I can collect in the public
  2510. 54:45
  2511. sphere and so right now that's kind of
  2512. 54:48
  2513. pretty much you know what I've been
  2514. 54:49
  2515. doing besides research since I talked to
  2516. 54:51
  2517. you guys last my god Quinn I can't even
  2518. 54:54
  2519. get a t-shirt store online so no so now
  2520. 55:03
  2521. I'm pretty much I've been spending a lot
  2522. 55:06
  2523. of time like talking to the IBM services
  2524. 55:08
  2525. and building coding against that so that
  2526. 55:11
  2527. way I can like I want to be able to put
  2528. 55:14
  2529. Peter Till's name into my system and
  2530. 55:16
  2531. have it analyzed all its connections
  2532. 55:18
  2533. based on my own personal algorithms that
  2534. 55:20
  2535. I know how they work and then eventually
  2536. 55:22
  2537. that'll lead me to a group of people who
  2538. 55:24
  2539. are funding and backing and influencing
  2540. 55:27
  2541. this scenario while trying to remain
  2542. 55:30
  2543. hidden so people can reach you by email
  2544. 55:33
  2545. with contact at Indra dot AI and I've
  2546. 55:36
  2547. got that email address up on the screen
  2548. 55:38
  2549. right there it's fascinating really
  2550. 55:40
  2551. fascinating yeah so in Android a I I'm
  2552. 55:44
  2553. trying to really also make it be like
  2554. 55:46
  2555. community funded because Peter Thiel and
  2556. 55:49
  2557. his group of investors they pretty much
  2558. 55:52
  2559. own and invest in everything so right
  2560. 55:55
  2561. you
  2562. 55:55
  2563. you know they invest in everything from
  2564. 55:58
  2565. OpenGov to Airbnb they invested in
  2566. 56:00
  2567. patreon really yeah if you're a
  2568. 56:03
  2569. programmer they gave two hundred million
  2570. 56:05
  2571. dollars to get hub which is where every
  2572. 56:07
  2573. programmer in the world stores their
  2574. 56:09
  2575. open-source source code huh they
  2576. 56:12
  2577. invested in slack which if you're in
  2578. 56:15
  2579. familiar with like Enterprise chat
  2580. 56:16
  2581. software the big companies use like Nike
  2582. 56:19
  2583. Dale you slack so all your enterprise
  2584. 56:21
  2585. conversations are going through one of
  2586. 56:23
  2587. the companies they funded and that's
  2588. 56:26
  2589. probably the one of the other big data
  2590. 56:28
  2591. things is I got to find out exactly
  2592. 56:29
  2593. which companies and technology they're
  2594. 56:31
  2595. funding that they put together to form
  2596. 56:33
  2597. this big giant future system Wow now I
  2598. 56:37
  2599. can't remember if we said this at the
  2600. 56:38
  2601. start of the broadcast or if you
  2602. 56:40
  2603. mentioned to me when we were talking
  2604. 56:41
  2605. before we began you said you had
  2606. 56:43
  2607. discovered something new with regard to
  2608. 56:46
  2609. Seth right yeah yeah ready for this I'm
  2610. 56:51
  2611. ready well you know I'm saying there's a
  2612. 56:54
  2613. and I'm just gonna recap on this so
  2614. 56:56
  2615. correct me if I remember correctly that
  2616. 56:58
  2617. in in the Seth rich rich instance you
  2618. 57:01
  2619. guys had a thumb drive where the data
  2620. 57:03
  2621. was transferred to the thumb drive in
  2622. 57:05
  2623. near-real-time but in burst packets like
  2624. 57:08
  2625. every 20 seconds I believe correct well
  2626. 57:11
  2627. this was information that came from the
  2628. 57:13
  2629. forensic aider and I think you've got
  2630. 57:15
  2631. more detail on there than I recall I
  2632. 57:17
  2633. just recalled that the data rate was too
  2634. 57:19
  2635. high for it to be an internet connection
  2636. 57:23
  2637. and then we had spoken about that
  2638. 57:25
  2639. company 4k solutions that can aggregate
  2640. 57:28
  2641. LTE connections and conceivably could
  2642. 57:31
  2643. get a very high-speed connection with
  2644. 57:33
  2645. that techno the offer technology and
  2646. 57:36
  2647. they work with another company that you
  2648. 57:39
  2649. would have to look at in their solutions
  2650. 57:41
  2651. and they deal with the technology called
  2652. 57:44
  2653. WiMAX
  2654. 57:44
  2655. right people in the comments we're
  2656. 57:47
  2657. asking about 5g and what does it have to
  2658. 57:49
  2659. do well five not 5g WiMAX WiMAX is
  2660. 57:52
  2661. already in use and can get up to 1
  2662. 57:55
  2663. gigabit per second throughput rates with
  2664. 57:58
  2665. an antenna why would it get sent in
  2666. 58:00
  2667. bursts aha so you're suspecting that
  2668. 58:04
  2669. WiMAX was utilized to download the day
  2670. 58:07
  2671. I that they sent that why they used
  2672. 58:11
  2673. WiMAX to send it to some place where the
  2674. 58:15
  2675. data got put into a driving sort so
  2676. 58:18
  2677. their thumb drive some solid-state drive
  2678. 58:21
  2679. because it sends data in burst packets
  2680. 58:25
  2681. so if it's writing to a drive the record
  2682. 58:27
  2683. of the drive that it's writing to would
  2684. 58:29
  2685. record that the data got written in a
  2686. 58:30
  2687. burst packet like oh I got a data packet
  2688. 58:32
  2689. size of this every 20 seconds and then I
  2690. 58:35
  2691. wrote the burst packets and the the
  2692. 58:38
  2693. WiMAX technology is designed like that
  2694. 58:40
  2695. so that it allows other nodes or other
  2696. 58:45
  2697. devices to interchange data transmission
  2698. 58:48
  2699. in near real time so it'll send like
  2700. 58:50
  2701. near real-time data like one gigabit per
  2702. 58:53
  2703. second and then it'll someone else to do
  2704. 58:55
  2705. it so it does everything in bursts and
  2706. 58:57
  2707. it's the only wire this technology that
  2708. 58:59
  2709. does that huh Wow
  2710. 59:02
  2711. I want to follow up on that because one
  2712. 59:04
  2713. of the footprints that I've been
  2714. 59:06
  2715. following is this guy named Mohammed
  2716. 59:08
  2717. Hounslow who comes to the United States
  2718. 59:11
  2719. and stays with Imran Awad and he's a
  2720. 59:14
  2721. cell tower expert and he is got
  2722. 59:18
  2723. tremendous experience in WiMAX and he's
  2724. 59:21
  2725. staying at in Ron's house over there on
  2726. 59:22
  2727. hotbed and you know Mohammed Shah his
  2728. 59:28
  2729. father
  2730. 59:29
  2731. Imran father is also doing this blue sky
  2732. 59:33
  2733. technology with iridium so there's all
  2734. 59:36
  2735. this emphasis on cell technology cell
  2736. 59:38
  2737. towers they have these many towers sort
  2738. 59:40
  2739. of like the dirt box that you were
  2740. 59:42
  2741. talking about in England Jason yeah
  2742. 59:45
  2743. where you could set up a WiMAX
  2744. 59:47
  2745. capability right outside the dnc and
  2746. 59:49
  2747. have not not a few laptops but
  2748. 59:54
  2749. everybody's laptops that's using the
  2750. 59:57
  2751. WiMAX
  2752. 59:57
  2753. system at the DNC and at the d-triple-c
  2754. 60:00
  2755. with the capability I'm not saying Imran
  2756. 60:03
  2757. did this
  2758. 60:03
  2759. I'm not saying a bead or Jamal but you
  2760. 60:06
  2761. would if Mohammed Huns left you look at
  2762. 60:08
  2763. Mohammad huntress resume it it's all
  2764. 60:13
  2765. this it and LCC lightbridge
  2766. 60:15
  2767. communications this is exactly what they
  2768. 60:17
  2769. did they do WiMAX and LTE towers
  2770. 60:20
  2771. and I very much believe that when he was
  2772. 60:24
  2773. brought in for the period of time he was
  2774. 60:26
  2775. here it looks like a setup operation to
  2776. 60:29
  2777. set up a WiMAX facility over at and I
  2778. 60:32
  2779. think and the wacky to white van yeah
  2780. 60:37
  2781. the NGP man me it's so ridiculous it's
  2782. 60:41
  2783. so much of an orgy of evidence you know
  2784. 60:43
  2785. to see that you know I would think pay
  2786. 60:45
  2787. this is the big move that's covering the
  2788. 60:47
  2789. small move which is the WiMAX power all
  2790. 60:49
  2791. I needed
  2792. 60:50
  2793. exactly what Quinn saying all I need is
  2794. 60:52
  2795. the tower and I'm done huh why man isn't
  2796. 60:57
  2797. it the same encoding is white Wi-Fi it
  2798. 61:00
  2799. is but it operates mic it operates in
  2800. 61:03
  2801. the microwave and so it's like wireless
  2802. 61:08
  2803. microwave is the best like I can it's a
  2804. 61:11
  2805. radio though the radio handshake is - is
  2806. 61:14
  2807. is what my understanding is different
  2808. 61:17
  2809. right because the different frequency
  2810. 61:18
  2811. bus but the packet handling and the and
  2812. 61:21
  2813. the handshake on the data at the data
  2814. 61:23
  2815. layer Network layer is the same right
  2816. 61:25
  2817. why it should be it runs on the ADA
  2818. 61:28
  2819. it runs on a different variation of the
  2820. 61:30
  2821. 802 one one protocol and that's the
  2822. 61:34
  2823. white that's the overarching ie like
  2824. 61:37
  2825. Wireless packet transmission protocol
  2826. 61:39
  2827. and then they have like 802 11 a they
  2828. 61:42
  2829. have 802 11 G a and B so WiMAX is just a
  2830. 61:47
  2831. different specification inside the 802
  2832. 61:49
  2833. 11 wireless communication protocol right
  2834. 61:53
  2835. but but that's Wi-Fi it's you're
  2836. 61:56
  2837. describing and then WiMAX is an
  2838. 61:57
  2839. extension of that so you wouldn't have
  2840. 61:59
  2841. to rewrite any software to much you just
  2842. 62:02
  2843. need to hack if you've got somebody if
  2844. 62:04
  2845. you've got a administrator's credentials
  2846. 62:06
  2847. through the vault seven tools like that
  2848. 62:08
  2849. Julian Assange we've been publishing and
  2850. 62:11
  2851. I can't member the latest one but that
  2852. 62:14
  2853. is some kind of a man-in-the-middle
  2854. 62:15
  2855. attack to get big credential you're done
  2856. 62:18
  2857. I mean once you get the credentials one
  2858. 62:22
  2859. I all I need is one administrator once I
  2860. 62:25
  2861. have everybody's handle on the what do
  2862. 62:28
  2863. you the microsoft directory services
  2864. 62:30
  2865. well you know what I mean I just get the
  2866. 62:33
  2867. directory and I'm done
  2868. 62:34
  2869. so this this is confusing people a
  2870. 62:36
  2871. little bit because this sounds more like
  2872. 62:37
  2873. it's skewing towards the wands what did
  2874. 62:40
  2875. this what did this WiMAX discovery have
  2876. 62:42
  2877. to do specifically with seth rich
  2878. 62:44
  2879. so the seth rich would have found that
  2880. 62:48
  2881. this WiMAX network existed by using the
  2882. 62:51
  2883. panda stuff and may have found that the
  2884. 62:52
  2885. WiMAX was in combination with the
  2886. 62:55
  2887. Palantir system was being used to
  2888. 62:57
  2889. collect illegal information and the page
  2890. 62:59
  2891. system again was we had like five
  2892. 63:02
  2893. different things that we thought panda
  2894. 63:04
  2895. might have been yeah and that's that
  2896. 63:06
  2897. that goes along with confirming my
  2898. 63:08
  2899. suspicions that panda is like one of the
  2900. 63:10
  2901. overarching systems it's like panda
  2902. 63:13
  2903. might be the AI that Palantir is running
  2904. 63:15
  2905. on panda could be the communication
  2906. 63:18
  2907. network that the Palantir system is
  2908. 63:20
  2909. running on the panda could really just
  2910. 63:23
  2911. be like the group of people that are
  2912. 63:24
  2913. running the operation so to speak so
  2914. 63:27
  2915. that's still a big mystery but the Panda
  2916. 63:30
  2917. portion is big the Palantir is really
  2918. 63:33
  2919. the only system that the NGP vance could
  2920. 63:35
  2921. have used to analyze that data in real
  2922. 63:37
  2923. time so way I see it is whatever panda
  2924. 63:42
  2925. is that inside of the access point or
  2926. 63:46
  2927. the NGP van that would go to the DNC tag
  2928. 63:48
  2929. to exchange data with the real-time
  2930. 63:51
  2931. WiMAX access point you're seeing a
  2932. 63:55
  2933. connected network now of people who have
  2934. 63:58
  2935. a vested interest it can keep their data
  2936. 64:00
  2937. collecting and manipulation activities a
  2938. 64:03
  2939. secret from the public because they have
  2940. 64:06
  2941. WiMAX technology they have panda which
  2942. 64:09
  2943. may be old government technology that
  2944. 64:11
  2945. could literally crack into any Bluetooth
  2946. 64:12
  2947. device and then they're collecting all
  2948. 64:15
  2949. that data in near real time over WiMAX
  2950. 64:18
  2951. without proper FCC permits into an
  2952. 64:21
  2953. unmarked van that's then taking that
  2954. 64:23
  2955. data and putting it into a real-time
  2956. 64:25
  2957. Palantir data mining system you start
  2958. 64:29
  2959. seeing the problems these people would
  2960. 64:31
  2961. have if this type of network got found
  2962. 64:33
  2963. out my brain is exploding I don't know
  2964. 64:36
  2965. it's so much so much to process I have a
  2966. 64:40
  2967. simple one for everybody which is there
  2968. 64:45
  2969. is a server up in New York
  2970. 64:48
  2971. which where Jason is which is anthony
  2972. 64:51
  2973. Weiner's laptop right with 650,000 we
  2974. 64:54
  2975. know that's sinking with human Abaddon's
  2976. 64:57
  2977. blackberry right i know that we know
  2978. 65:00
  2979. that hillary clinton is writing to human
  2980. 65:04
  2981. Abidine about anthony's trusted staff we
  2982. 65:07
  2983. know Anthony is has a trusted staff
  2984. 65:10
  2985. secure creating secure phones creating
  2986. 65:13
  2987. secure BlackBerry's and sending them out
  2988. 65:15
  2989. to people almost like tokens for access
  2990. 65:18
  2991. for pay-to-play information right so
  2992. 65:20
  2993. they're almost handing out these phones
  2994. 65:22
  2995. or it's kind of like Lee here's your
  2996. 65:26
  2997. access to the war that's about ready to
  2998. 65:29
  2999. happen in Libya it's gonna be 30 days
  3000. 65:32
  3001. you're you don't have to pay a half
  3002. 65:33
  3003. million dollars goldman sachs right then
  3004. 65:36
  3005. we know that the person who worked for
  3006. 65:40
  3007. anthony's trust no staff are the Awad
  3008. 65:42
  3009. brothers right that's who that that's
  3010. 65:45
  3011. who Anthony's trusted staff is and right
  3012. 65:47
  3013. also have a laptop now we know at em
  3014. 65:51
  3015. Ron's house so what are the odds that
  3016. 65:54
  3017. Imran server is a blackberry enterprise
  3018. 65:58
  3019. server as well it's just a mirrored
  3020. 66:00
  3021. server of houmous server in New York so
  3022. 66:02
  3023. as they're compromising people in
  3024. 66:05
  3025. Washington DC they're compromising
  3026. 66:07
  3027. senators are compromising a congressman
  3028. 66:10
  3029. that are on the sensitive committees
  3030. 66:12
  3031. it's just syncing with New York Wow
  3032. 66:14
  3033. that's the reason why the Hillary only
  3034. 66:16
  3035. has 60,000 emails in there human has
  3036. 66:19
  3037. 650,000 it's because they're there
  3038. 66:22
  3039. they're singing have you have you
  3040. 66:24
  3041. thought about just the mechanics of that
  3042. 66:27
  3043. when and and just that whole idea that
  3044. 66:29
  3045. this might be you know what we found in
  3046. 66:32
  3047. in Morton Virginia may just be the flip
  3048. 66:35
  3049. side of what was going on in New York
  3050. 66:36
  3051. yeah and then that's there's going to be
  3052. 66:39
  3053. a lot of flip sides because for the main
  3054. 66:42
  3055. players they're going to keep a lot of
  3056. 66:44
  3057. the heavy data synchronization out of
  3058. 66:46
  3059. their hands because they're there they
  3060. 66:48
  3061. don't really know how to use the system
  3062. 66:50
  3063. so the assistant of the the main key
  3064. 66:53
  3065. player is generally going to be the
  3066. 66:55
  3067. person using the system or is putting
  3068. 66:58
  3069. data into the system interfacing with
  3070. 66:59
  3071. the system like Huma hab
  3072. 67:02
  3073. you're gonna see a lot more data coming
  3074. 67:04
  3075. from her platform than you would like
  3076. 67:06
  3077. Hillary Clinton because Hillary Clinton
  3078. 67:08
  3079. would be more of just like hey I'm a
  3080. 67:10
  3081. face I'm signing off on the deal I'm
  3082. 67:13
  3083. taking all of the benefits of its
  3084. 67:16
  3085. seemingly appearing successes meanwhile
  3086. 67:19
  3087. the assistants who may have already had
  3088. 67:21
  3089. previous CIA contacts know how to use
  3090. 67:24
  3091. the system that they know which
  3092. 67:25
  3093. information needs to synchronize they
  3094. 67:28
  3095. know that like for example if they're
  3096. 67:29
  3097. using blackberry servers they could
  3098. 67:31
  3099. synchronize the information with a
  3100. 67:32
  3101. blackberry server then like a system
  3102. 67:35
  3103. like volunteer could have a data
  3104. 67:37
  3105. connector that connects directly to that
  3106. 67:38
  3107. blackberry server and just starts
  3108. 67:40
  3109. pulling all the data off over secure
  3110. 67:42
  3111. line so well I've got a couple messages
  3112. 67:47
  3113. coming in here that I want you guys to
  3114. 67:48
  3115. hear George is likely to hate this but
  3116. 67:51
  3117. multiple people have suggested that
  3118. 67:53
  3119. panda might be referring to Obama since
  3120. 67:56
  3121. he's both black and white not my words
  3122. 68:00
  3123. that's the comment I mean it could be
  3124. 68:02
  3125. that could be what they named the the
  3126. 68:04
  3127. system in the Obama era because one of
  3128. 68:08
  3129. the articles I read mentioned Jared
  3130. 68:10
  3131. Kirchner talking about how Obama had his
  3132. 68:12
  3133. own entire system developed that they
  3134. 68:16
  3135. were competing against that the Clinton
  3136. 68:18
  3137. and the DNC were using after Obama left
  3138. 68:20
  3139. that they were just reusing his system
  3140. 68:23
  3141. so the Panda I mean it could be the
  3142. 68:25
  3143. system that was developed under the
  3144. 68:27
  3145. Obama administration with Palantir like
  3146. 68:29
  3147. the peon Panda could stand for Palantir
  3148. 68:31
  3149. well and that kind of directly relates
  3150. 68:34
  3151. to this other comment which is
  3152. 68:35
  3153. suggesting that the shadow president and
  3154. 68:37
  3155. those associated are Trump's kitchen
  3156. 68:40
  3157. cabinet or shadow cabinet and the Trump
  3158. 68:44
  3159. is creating his own deep state with
  3160. 68:46
  3161. predictive algorithms and certainly
  3162. 68:47
  3163. Jared Kushner helped him win the
  3164. 68:50
  3165. presidency with his expertise in social
  3166. 68:53
  3167. media so the concept that Jared has got
  3168. 68:57
  3169. some computer expertise or at least
  3170. 68:59
  3171. enough smarts to associate himself with
  3172. 69:01
  3173. people with computer expertise seems at
  3174. 69:05
  3175. least like a reasonable theory based on
  3176. 69:07
  3177. the the business and investment
  3178. 69:10
  3179. backgrounds of Jared and Josh Kushner
  3180. 69:12
  3181. and the resources that they get from
  3182. 69:14
  3183. Vornado real
  3184. 69:15
  3185. Teairra New York who owns all the
  3186. 69:17
  3187. billboards in Times Square and is pretty
  3188. 69:20
  3189. much the landlord to the United States
  3190. 69:22
  3191. government I would imagine that they're
  3192. 69:26
  3193. not setting up a new deep state I would
  3194. 69:28
  3195. imagine that they've been in this
  3196. 69:30
  3197. business a long time and they've been
  3198. 69:32
  3199. setting up these venture capital firms
  3200. 69:34
  3201. and investing in comms for 20 years
  3202. 69:37
  3203. they've been building you know like
  3204. 69:40
  3205. Jared Kushner he can build a four
  3206. 69:41
  3207. hundred million dollar startup with the
  3208. 69:44
  3209. by snapping his fingers you know he can
  3210. 69:46
  3211. put all the resources together he can
  3212. 69:48
  3213. get his buddies together he can hire the
  3214. 69:50
  3215. contractors that are needed and within a
  3216. 69:53
  3217. month if he wants a new startup he just
  3218. 69:55
  3219. basically puts it all together so right
  3220. 69:58
  3221. you know they've been funding one of the
  3222. 70:01
  3223. things that really gets me is that it
  3224. 70:02
  3225. looks like they're in in part funding
  3226. 70:05
  3227. with Alibaba and the Malaysian
  3228. 70:07
  3229. government so then we start we're just
  3230. 70:09
  3231. leaving the borders of the US so that's
  3232. 70:11
  3233. when US interests start getting lost
  3234. 70:14
  3235. like you know if you're buying a system
  3236. 70:18
  3237. that's supposed to be tracking yours
  3238. 70:19
  3239. your crime why are you buying it from
  3240. 70:23
  3241. people who are being funded by other
  3242. 70:25
  3243. governments I'm saying yeah and you know
  3244. 70:28
  3245. we've heard so much we're talking about
  3246. 70:30
  3247. these liaison operations and Jorge coin
  3248. 70:34
  3249. the term Operation Paperclip - we've
  3250. 70:37
  3251. heard about Josie bear we've heard about
  3252. 70:39
  3253. fancy bear has any of your research have
  3254. 70:42
  3255. you come across Pooh Bear I come across
  3256. 70:47
  3257. a lot of bears at Pooh Bear ever because
  3258. 70:49
  3259. that was something you know before I
  3260. 70:51
  3261. don't know if we've ever spoken with you
  3262. 70:52
  3263. about the Hudson group which has
  3264. 70:54
  3265. recently gone dark but they were talking
  3266. 70:57
  3267. about the pooh bear was one of the last
  3268. 70:58
  3269. things they had asked us about and i
  3270. 71:00
  3271. don't really know what that is so here's
  3272. 71:06
  3273. what i found in their system i don't
  3274. 71:08
  3275. have much information on it they named
  3276. 71:10
  3277. their different programs in various ways
  3278. 71:12
  3279. like hey who's that but the the group of
  3280. 71:16
  3281. people that are involved with this
  3282. 71:18
  3283. high-level system that i'm from my own
  3284. 71:21
  3285. sanity just like to call them that they
  3286. 71:23
  3287. like the Palantir that you know the deep
  3288. 71:26
  3289. state they
  3290. 71:28
  3291. a way of gaming their systems where when
  3292. 71:31
  3293. they have a system that's meant for like
  3294. 71:32
  3295. social influence they'll generally name
  3296. 71:34
  3297. it after a book movie or some
  3298. 71:36
  3299. pop-culture reference when they have a
  3300. 71:40
  3301. system that usually deals with wanting
  3302. 71:43
  3303. to keep things secret or when they have
  3304. 71:46
  3305. a system that's like they want people to
  3306. 71:48
  3307. think it's cute or usually a system that
  3308. 71:50
  3309. involves some type of illegal activity
  3310. 71:52
  3311. they usually name it after an animal
  3312. 71:54
  3313. like a type of bear panda fox you know
  3314. 71:58
  3315. something like that and then the
  3316. 72:01
  3317. original developers of the AI units when
  3318. 72:03
  3319. you get into the chat BOTS they mostly
  3320. 72:05
  3321. named them after girls
  3322. 72:06
  3323. I see so you have these standard naming
  3324. 72:09
  3325. patterns for their initiatives so it's
  3326. 72:13
  3327. like the generally the illegal behaviors
  3328. 72:15
  3329. are after animals you know like predator
  3330. 72:17
  3331. animals the AIS are usually named after
  3332. 72:21
  3333. like girls or people like you know clips
  3334. 72:23
  3335. is probably like you know cyber
  3336. 72:26
  3337. logistics intelligence personality
  3338. 72:31
  3339. system probably something like that
  3340. 72:33
  3341. because the military likes to give
  3342. 72:35
  3343. acronyms and criminals like to be
  3344. 72:37
  3345. predators and when you're infecting the
  3346. 72:40
  3347. social and you generally want to use pop
  3348. 72:42
  3349. culture because of the association got
  3350. 72:45
  3351. it
  3352. 72:46
  3353. Wow boy it's so much to absorb did you
  3354. 72:49
  3355. did you get anything on that aq did you
  3356. 72:52
  3357. find anything when you were looking for
  3358. 72:53
  3359. that I did let me go back to that so I
  3360. 73:00
  3361. don't know we lost George there and
  3362. 73:04
  3363. there he's back oh no he's gone it's
  3364. 73:08
  3365. hiding hiding George well there's just a
  3366. 73:11
  3367. still image hit the video the camera
  3368. 73:14
  3369. icon
  3370. 73:19
  3371. oh there we go
  3372. 73:22
  3373. there we go but at the ache you stand
  3374. 73:25
  3375. for again adversity quotient I believe
  3376. 73:29
  3377. well what one of the things I would like
  3378. 73:32
  3379. to put forward on the Panda thing and I
  3380. 73:36
  3381. don't have the acronym right now and
  3382. 73:39
  3383. this is so speculative and it's kind of
  3384. 73:41
  3385. I I do feel like I am a third grader
  3386. 73:46
  3387. yeah at the in Harvard here but but I
  3388. 73:50
  3389. really do focus on these ratline because
  3390. 73:52
  3391. I just focus on that the clintons and i
  3392. 73:55
  3393. think about how they've run their
  3394. 73:56
  3395. rattler and there's a panda system
  3396. 73:59
  3397. that's kind of associated with this in
  3398. 74:01
  3399. deep you know the dark web for running
  3400. 74:04
  3401. these transactions over this dark web
  3402. 74:06
  3403. and the Navy did to develop this router
  3404. 74:09
  3405. called The Onion Router and so Quinn can
  3406. 74:12
  3407. rip off this and he knows a lot more
  3408. 74:14
  3409. about the Onion Router than I do but the
  3410. 74:16
  3411. tor browser and a lot of these kind of
  3412. 74:19
  3413. advanced deep web dark web deep dark web
  3414. 74:25
  3415. type type browsers work in this fashion
  3416. 74:28
  3417. and it's to enable these encrypted
  3418. 74:31
  3419. transactions like Silk Road and so if
  3420. 74:35
  3421. you have if you have a lot of Navy
  3422. 74:37
  3423. vessels and you're sending a lot of
  3424. 74:39
  3425. let's say let's say illicit weapons or
  3426. 74:44
  3427. drugs or children or whatever you don't
  3428. 74:49
  3429. necessarily want to advertise that you
  3430. 74:51
  3431. don't want that to be searchable or
  3432. 74:53
  3433. reachable by Google you want you want a
  3434. 74:57
  3435. firewall between the visible web and the
  3436. 75:01
  3437. dark web and that's the idea of this
  3438. 75:03
  3439. onion router where the onion router is
  3440. 75:06
  3441. smart enough to be able to search below
  3442. 75:08
  3443. the visible web and to find all these
  3444. 75:12
  3445. things
  3446. 75:13
  3447. if you're gonna be selling children you
  3448. 75:16
  3449. want those children to be found by Arab
  3450. 75:18
  3451. sheiks for instance who can pay the cash
  3452. 75:19
  3453. to cash that's you to buy them so can
  3454. 75:26
  3455. you comment at all about that theory
  3456. 75:28
  3457. that this is just basically the Navy
  3458. 75:30
  3459. Panda system and the engine
  3460. 75:33
  3461. that's kind of what I was leading at is
  3462. 75:38
  3463. because the the panda rat or the panda
  3464. 75:41
  3465. technology from what I've learned is
  3466. 75:43
  3467. what allows like really amazing
  3468. 75:45
  3469. communication it never came out in the
  3470. 75:47
  3471. public from what I found but The Onion
  3472. 75:50
  3473. Router is if you take like sir Pinet
  3474. 75:55
  3475. which is the secret internet routing
  3476. 75:57
  3477. protocol network that's essentially what
  3478. 76:00
  3479. an Onion Router is is it's it's a public
  3480. 76:03
  3481. version of the military's private
  3482. 76:06
  3483. network so when in the old days when the
  3484. 76:09
  3485. military wanted to create like a private
  3486. 76:12
  3487. one-to-one network they would create a
  3488. 76:13
  3489. satellite office that would give it a
  3490. 76:15
  3491. private address that would then go out
  3492. 76:17
  3493. over tcp/ip through like a private type
  3494. 76:19
  3495. network over the standard network and
  3496. 76:21
  3497. then it would connect directly to like
  3498. 76:23
  3499. another router which on the internet a
  3500. 76:25
  3501. router is a way the machines communicate
  3502. 76:28
  3503. and have like information on how they
  3504. 76:31
  3505. can communicate with different addresses
  3506. 76:33
  3507. and so you would make a connection to
  3508. 76:35
  3509. this and this was like early days before
  3510. 76:37
  3511. PGP and you would go router to router
  3512. 76:40
  3513. and then that router would say hey I can
  3514. 76:42
  3515. do this protocol the other the router
  3516. 76:44
  3517. would say hey I can do that protocol too
  3518. 76:46
  3519. then they would establish a protocol
  3520. 76:47
  3521. connection nowadays with onion it goes
  3522. 76:51
  3523. point-to-point rather than router to
  3524. 76:53
  3525. router so it's more like its own
  3526. 76:55
  3527. protocol from what I'm kind of gathering
  3528. 76:59
  3529. so onion is like hey we're gonna open an
  3530. 77:02
  3531. onion connection rather than open up
  3532. 77:04
  3533. like a router to router connection so
  3534. 77:06
  3535. it's it's entirely encrypted and then
  3536. 77:08
  3537. once again you get the blockchain for
  3538. 77:10
  3539. transactions on an onion network and you
  3540. 77:14
  3541. have a way you can securely basically
  3542. 77:16
  3543. buy anything you want whether it be
  3544. 77:17
  3545. drugs to children to snuff thumps Wow
  3546. 77:20
  3547. you know guys just real briefly back on
  3548. 77:23
  3549. this panda thing I'm looking at an image
  3550. 77:25
  3551. that I brought up which I photograph
  3552. 77:27
  3553. just outside or maybe somebody sent this
  3554. 77:29
  3555. to me this was when George and I went to
  3556. 77:32
  3557. DC for the Seth Rich vigil that was the
  3558. 77:35
  3559. first time I became aware of the bike
  3560. 77:37
  3561. rack that was negated - seth rich which
  3562. 77:41
  3563. is just sort of so ridiculous and stands
  3564. 77:44
  3565. out as such a strain
  3566. 77:46
  3567. thing to dedicate to someone
  3568. 77:48
  3569. posthumously the first line of it says
  3570. 77:51
  3571. son of Omaha and for some reason then
  3572. 77:56
  3573. stuck out at me probably because when I
  3574. 77:58
  3575. was loading up the image one of you guys
  3576. 78:00
  3577. or somebody mentioned something about
  3578. 78:01
  3579. Obama and for a moment from the distance
  3580. 78:04
  3581. I'm at it looked like it said son of
  3582. 78:05
  3583. Obama and I was like wait whoa whoa whoa
  3584. 78:08
  3585. that's wrong and this is in son of Omaha
  3586. 78:11
  3587. and I'm thinking why why is that so
  3588. 78:14
  3589. significant I mean I mean if you ask me
  3590. 78:20
  3591. that there's a town outside of Omaha
  3592. 78:23
  3593. called Janesville that Paul Ryan is from
  3594. 78:26
  3595. yeah I had someone out of about a week
  3596. 78:30
  3597. ago doing research on Omaha being a
  3598. 78:34
  3599. direct line of sight to Fermilab's in
  3600. 78:36
  3601. Illinois that is one of the labs to
  3602. 78:39
  3603. developing the quantum AI systems and
  3604. 78:41
  3605. the Large Hadron colliders right you
  3606. 78:45
  3607. know like the you know Naval Observatory
  3608. 78:47
  3609. that we talked about last time that's
  3610. 78:49
  3611. all being developed by Fermi labs and
  3612. 78:51
  3613. there's a direct line of sight from
  3614. 78:53
  3615. Fermilab's to the University of Omaha
  3616. 78:55
  3617. which if I'm not mistaken I believe
  3618. 78:57
  3619. that's where Seth rich went to college
  3620. 78:59
  3621. yeah and then from Omaha there's a
  3622. 79:03
  3623. direct line of sight to Janesville which
  3624. 79:05
  3625. I've found has a quantum computing
  3626. 79:08
  3627. company and has a data analysis company
  3628. 79:11
  3629. which might need to believe it's one of
  3630. 79:13
  3631. the big data processing warehouses in
  3632. 79:17
  3633. Janesville that they're using for
  3634. 79:19
  3635. Palantir or one of the underlying
  3636. 79:22
  3637. systems hmm so it could be related to
  3638. 79:26
  3639. that because I found a lot of relations
  3640. 79:28
  3641. between Fermilab's development of this
  3642. 79:30
  3643. technology in Omaha and the University
  3644. 79:33
  3645. of Omaha has a big connection to this
  3646. 79:36
  3647. for some reason uh-huh and what about
  3648. 79:39
  3649. the warranty Wisconsin I think I think
  3650. 79:41
  3651. you mean you'd you'd up I think right I
  3652. 79:44
  3653. mean Janesville is in Wisconsin right
  3654. 79:46
  3655. and so people are saying that Janesville
  3656. 79:48
  3657. is in Wisconsin not near Alma yeah yeah
  3658. 79:50
  3659. and I know you dub or Wisconsin maybe
  3660. 79:54
  3661. that's how you say it sorry I was
  3662. 79:56
  3663. confused yeah yeah it has
  3664. 79:59
  3665. a heavy a curriculum there also in in
  3666. 80:02
  3667. Oregon harvesting University of
  3668. 80:07
  3669. Wisconsin is always pushing out you know
  3670. 80:09
  3671. the newest technology in organ
  3672. 80:11
  3673. harvesting this isn't a sideline I
  3674. 80:13
  3675. always kind of saw it as a CIA you know
  3676. 80:16
  3677. all the way back to MKULTRA and you know
  3678. 80:20
  3679. you know like the University of Denver
  3680. 80:22
  3681. for the Midwest Wow you're gonna you're
  3682. 80:25
  3683. gonna mess up some kids and you're gonna
  3684. 80:27
  3685. experiment on the whole population you
  3686. 80:29
  3687. may as well start with all right
  3688. 80:32
  3689. and then work your way up and I really I
  3690. 80:35
  3691. mean I know this sounds absolutely
  3692. 80:37
  3693. insane but I think he was one of those
  3694. 80:40
  3695. kids it's his dad died when he was 18
  3696. 80:43
  3697. they wanted him to you know I really
  3698. 80:46
  3699. believe this I know it's terrible but
  3700. 80:48
  3701. they wanted him to compromise Jack camp
  3702. 80:51
  3703. and as a Paige way back when and and
  3704. 80:57
  3705. then of course if you play the game like
  3706. 80:59
  3707. Ben Sasse or whoever else if you play
  3708. 81:01
  3709. the game and you get compromised and do
  3710. 81:03
  3711. what they say you become you move on you
  3712. 81:06
  3713. become a congressman and then you you
  3714. 81:08
  3715. know from a Paige the legislative
  3716. 81:10
  3717. assistant to a to a congressman to a
  3718. 81:12
  3719. senator and now we've done the Senate
  3720. 81:13
  3721. Foreign Armed Services Committee so this
  3722. 81:16
  3723. is really how I think Congress works
  3724. 81:18
  3725. that it's also unbelievable but if you
  3726. 81:23
  3727. look at Paul Ryan going all the way back
  3728. 81:25
  3729. he is this compromise a subservient to
  3730. 81:30
  3731. jacket nice exterior views Quinn that
  3732. 81:35
  3733. looks like a Lightwave 3d logo on the
  3734. 81:37
  3735. tattoo below your ear
  3736. 81:38
  3737. you remember Lightwave 3d I do yeah the
  3738. 81:43
  3739. exact logo it's kind of like it's kind
  3740. 81:47
  3741. of like it it's a it's a it's a gaming
  3742. 81:50
  3743. AI algorithm that's tattooed on the side
  3744. 81:52
  3745. of my neck huh I gotta I gotta kind of
  3746. 81:55
  3747. plug in my inverter here so I'll be
  3748. 81:56
  3749. right back with you guys you know what
  3750. 81:58
  3751. let's do this Quinn it's been a
  3752. 82:00
  3753. fascinating conversation but yeah it's
  3754. 82:02
  3755. getting real late here in New York we're
  3756. 82:04
  3757. gonna love to have you back real soon
  3758. 82:05
  3759. because there's always so much to talk
  3760. 82:07
  3761. about give us one more time how can
  3762. 82:09
  3763. people get in touch with you what's the
  3764. 82:10
  3765. best way to reach you
  3766. 82:12
  3767. Indre dot ai or on Twitter at Quinn
  3768. 82:15
  3769. Michaels or on YouTube obviously my
  3770. 82:19
  3771. username is Quinn Michaels you can just
  3772. 82:21
  3773. type it in and I'll come up but
  3774. 82:23
  3775. generally injured a I if you want to
  3776. 82:25
  3777. contact me directly you can do it
  3778. 82:27
  3779. through there all right Quinn thanks so
  3780. 82:29
  3781. much man it's always great talking to
  3782. 82:30
  3783. you and you know you find interesting
  3784. 82:32
  3785. give us a call we'll have you back real
  3786. 82:34
  3787. soon I will do anything else I'm
  3788. 82:37
  3789. volunteer I'll come to you guys first
  3790. 82:38
  3791. very good take care of yourself bill
  3792. 82:41
  3793. thanks but yeah guys you know George if
  3794. 82:44
  3795. Quinn runs into Dave acting up there
  3796. 82:47
  3797. chest uh I'm gonna want to hear about it
  3798. 82:50
  3799. speaking of Blair Witch Project it costs
  3800. 82:55
  3801. very little money to make that movie
  3802. 82:57
  3803. that's true how much money did it make
  3804. 82:59
  3805. it was over 80 million as I recall and
  3806. 83:03
  3807. and that just goes to show you all you
  3808. 83:06
  3809. need is a few handheld cameras and and
  3810. 83:10
  3811. be willing to chop someone into small
  3812. 83:13
  3813. pieces right you have a movie yeah
  3814. 83:16
  3815. absolutely well listen George there's
  3816. 83:19
  3817. been a lot of positive comments in here
  3818. 83:21
  3819. wishing you well at the hearing tomorrow
  3820. 83:22
  3821. and what times whose day Oh Tuesday
  3822. 83:27
  3823. sorry right tomorrow you'll be preparing
  3824. 83:30
  3825. for that but correctly you know I will
  3826. 83:33
  3827. speak to you in the morning and we'll
  3828. 83:35
  3829. have some more stuff to go over tomorrow
  3830. 83:37
  3831. I'm gonna rearrange everything here and
  3832. 83:39
  3833. nail this sound problem I'm not sure why
  3834. 83:40
  3835. that's happening I mean people who are I
  3836. 83:42
  3837. just wanted to plug your interview with
  3838. 83:45
  3839. Charles or Town Hall today the 17-minute
  3840. 83:48
  3841. that I saw you posted a little bit later
  3842. 83:51
  3843. and unfortunately I had left New York
  3844. 83:53
  3845. before I posted your video Bluewater us
  3846. 83:56
  3847. going to blue water capital but I
  3848. 83:58
  3849. believe that's gonna be at the center of
  3850. 84:00
  3851. the eb-5 thing and the whole dead
  3852. 84:03
  3853. lawyers thing and all that it's also
  3854. 84:05
  3855. good news because you've solved your
  3856. 84:07
  3857. uploading problem yeah I guess so it did
  3858. 84:13
  3859. it yeah I guess I did upload it yeah I
  3860. 84:15
  3861. somehow solved the problem myself I
  3862. 84:18
  3863. think it was so long boring live chats
  3864. 84:22
  3865. and start going back to upload well I
  3866. 84:24
  3867. think it was just slow internet and
  3868. 84:25
  3869. floor
  3870. 84:26
  3871. that was plaguing us over there probably
  3872. 84:28
  3873. anyway we'll talk tomorrow and have a
  3874. 84:30
  3875. good night George people want to check
  3876. 84:32
  3877. out that Charles or tell interview
  3878. 84:34
  3879. Charles called me very excited about
  3880. 84:36
  3881. that FBI document on Hillary Clinton and
  3882. 84:41
  3883. he's definitely finding some interesting
  3884. 84:43
  3885. stuff there I will certainly solve this
  3886. 84:47
  3887. audio problem by tomorrow problem is I'm
  3888. 84:50
  3889. just constantly reconfiguring the studio
  3890. 84:54
  3891. here every time we do something so it's
  3892. 84:56
  3893. it's a new problem every day this the
  3894. 85:00
  3895. shape search words of the day for people
  3896. 85:03
  3897. who'd like to do the in an entity
  3898. 85:05
  3899. analysis and link link link analysis is
  3900. 85:09
  3901. what Charles gave me was matrix labs
  3902. 85:12
  3903. matrix labs and mile and mile and
  3904. 85:16
  3905. pharmaceuticals is obviously famous for
  3906. 85:19
  3907. the EpiPen in the six hundred percent
  3908. 85:21
  3909. increased mm in the EpiPen
  3910. 85:23
  3911. remember that yes and then I talked to
  3912. 85:27
  3913. all these people from West Virginia
  3914. 85:28
  3915. tonight Joe Manchin the the Democratic
  3916. 85:32
  3917. senator from West Virginia his daughter
  3918. 85:37
  3919. I think their name is Hersh or something
  3920. 85:40
  3921. like that
  3922. 85:41
  3923. is the CEO of my life yes or conflict of
  3924. 85:44
  3925. interests in the in the Senate about
  3926. 85:48
  3927. rapid increases for critical medical
  3928. 85:51
  3929. technology hmm maybe we can have some
  3930. 85:54
  3931. more info on that tomorrow all right
  3932. 85:56
  3933. George have a good night there in Ohio
  3934. 85:58
  3935. we'll see everybody tomorrow thanks
  3936. 86:00
  3937. everybody thank you everybody
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