AI Leaps Forward: Robot Butlers & Nvidia's Super Brain Chip

Ep8 AI Leaps Forward_ Robot Butlers & Nvidia_s Superbrain Chip

Timestamped transcript

1 00:00:01,838 --> 00:00:06,378 Welcome to VentureStep podcasts where we discuss entrepreneurship, industry trends,

2 00:00:06,378 --> 00:00:08,078 and the occasional book view.

3 00:00:08,238 --> 00:00:12,748 If you think AI is moving fast before buckle up from robots doing household

4 00:00:12,748 --> 00:00:16,178 chores to a chip so powerful, it's scary.

5 00:00:16,178 --> 00:00:20,218 And Google teaching AI to navigate like us in the virtual world.

6 00:00:20,258 --> 00:00:22,738 This episode covers the latest breakthroughs that could change

7 00:00:22,738 --> 00:00:23,718 everything.

8 00:00:24,078 --> 00:00:27,918 Of course, before we dive in, sorry, I don't understand.

9 00:00:28,758 --> 00:00:30,138 Talk about AI.

10 00:00:30,398 --> 00:00:32,054 My Google home just.

11 00:00:32,238 --> 00:00:36,438 blurted out and we knew that we were talking about him or her or whoever.

12 00:00:38,098 --> 00:00:40,408 But before we dive in, my name is Dalton.

13 00:00:40,408 --> 00:00:46,558 I have a bit of a mix of programming experience and also work in insurance.

14 00:00:47,158 --> 00:00:49,658 Offline you can find me exercising.

15 00:00:49,658 --> 00:00:56,078 I like to go runs, work out, do calisthenics, build a side business, or

16 00:00:56,078 --> 00:00:57,698 you can find me in a good book.

17 00:00:57,858 --> 00:00:58,882 If you...

18 00:00:58,882 --> 00:01:02,012 Prefer to view this podcast in a video format.

19 00:01:02,012 --> 00:01:06,442 You can see this video on YouTube or Spotify.

20 00:01:06,802 --> 00:01:12,752 If audio is kind of your jam, you can watch this wherever, or I guess listen to

21 00:01:12,752 --> 00:01:19,982 it, wherever you get your podcasts, Apple podcasts, YouTube, Spotify, et cetera, and

22 00:01:19,982 --> 00:01:20,272 YouTube.

23 00:01:20,272 --> 00:01:22,122 YouTube does podcasts now.

24 00:01:22,582 --> 00:01:26,902 Today's agenda, we'll be talking about Nvidia's announcements that they made

25 00:01:26,902 --> 00:01:28,942 during their, I guess,

26 00:01:28,942 --> 00:01:31,262 their AI day is what they call it.

27 00:01:31,262 --> 00:01:38,552 They announced the Blackwell chip and it's a new chip that is promised to do quite a

28 00:01:38,552 --> 00:01:40,162 bit and it's a bit crazy.

29 00:01:40,162 --> 00:01:42,882 So I want to talk about that.

30 00:01:42,882 --> 00:01:48,922 And then also there was a demo with a robot called Figure01.

31 00:01:48,922 --> 00:01:57,902 Figure01 is a product designed by Figure AI and it was in conjunction with a

32 00:01:57,902 --> 00:01:58,720 partnership with

33 00:01:58,720 --> 00:02:08,770 open AI and the demo was quite interesting because the robot was able to communicate

34 00:02:08,770 --> 00:02:16,250 information from another human on the fly and do certain tasks that were instructed

35 00:02:16,250 --> 00:02:20,950 by said human, which is not something you've seen before.

36 00:02:21,730 --> 00:02:28,362 Google's deep mind, their S I M a agent is their general.

37 00:02:28,362 --> 00:02:35,302 agent model made some breakthroughs and they've moved forward with their

38 00:02:35,302 --> 00:02:38,382 generalist AI where they're changing.

39 00:02:38,382 --> 00:02:43,742 They're taking a different approach where they're training their AI in the virtual

40 00:02:43,742 --> 00:02:44,022 world.

41 00:02:44,022 --> 00:02:51,932 So they're using games like Minecraft or no man's land to train the AI on like real

42 00:02:51,932 --> 00:02:57,446 data, maybe like say YouTube data, and then take that information.

43 00:02:58,348 --> 00:03:01,040 and train the AI, we go into more detail after.

44 00:03:02,990 --> 00:03:08,770 So Blackwell B200 GPU.

45 00:03:09,350 --> 00:03:11,110 Why is it such a big deal?

46 00:03:11,110 --> 00:03:20,750 Well, to put it in perspective, they are saying, and it's more of an architecture.

47 00:03:20,750 --> 00:03:24,010 They're calling it chip, but people are calling it chip on the internet, but it's

48 00:03:24,010 --> 00:03:29,910 more of an architecture because multiple chips, but regardless, it's a big deal

49 00:03:29,910 --> 00:03:32,782 because they're saying that they're going to be able to train

50 00:03:32,782 --> 00:03:35,142 one trillion parameter AI.

51 00:03:35,142 --> 00:03:44,602 Currently for a chat GPT -3, they were at 175 billion parameters.

52 00:03:44,962 --> 00:03:53,882 Not confirmed, but a theory is that the GPT -4 is eight models, 250 billion

53 00:03:53,882 --> 00:03:57,182 parameters each that run simultaneously.

54 00:03:58,442 --> 00:04:02,126 So that being said, one trillion is quite a bit

55 00:04:02,126 --> 00:04:04,864 bigger than 250 billion?

56 00:04:06,464 --> 00:04:12,484 But, you know, additional parameters doesn't mean that the model is better per

57 00:04:12,484 --> 00:04:13,284 se.

58 00:04:13,724 --> 00:04:21,824 A lot of the open source models typically run around 60 to 70 billion parameters.

59 00:04:23,404 --> 00:04:34,822 But, so this Blackwell super architecture chip, et cetera, is promised to do...

60 00:04:34,934 --> 00:04:36,154 one trillion parameters.

61 00:04:36,154 --> 00:04:41,314 And then not only are they doing it able to accomplish this one trillion parameter

62 00:04:41,314 --> 00:04:50,944 chip as much architecture, they're also able to do it 35 or sorry, 25 % reduced

63 00:04:50,944 --> 00:04:58,404 energy consumption and 30 % faster or sorry, 30 times faster.

64 00:04:58,404 --> 00:05:01,384 I'm mixing these up, 30 times faster.

65 00:05:01,384 --> 00:05:04,578 So 30 times faster and 25 %

66 00:05:04,814 --> 00:05:06,014 more efficient.

67 00:05:06,294 --> 00:05:13,234 And I think that's important because these chips take up a lot of energy.

68 00:05:13,294 --> 00:05:19,964 I think that the blackwell chip takes up and I'm reading it up right now because I

69 00:05:19,964 --> 00:05:21,094 don't have it.

70 00:05:21,094 --> 00:05:22,342 I it takes up.

71 00:05:27,150 --> 00:05:32,750 like eight gigawatts of power, the previous one, the H100.

72 00:05:33,670 --> 00:05:36,998 And then the...

73 00:05:39,598 --> 00:05:43,218 new chip takes up, you know, obviously less.

74 00:05:43,638 --> 00:05:48,952 But it's not like we're talking about like a home.

75 00:05:50,414 --> 00:05:54,764 of you know, you know, it's like, oh, well, it takes, you know, it's like

76 00:05:54,764 --> 00:06:00,594 leaving the light on for your fan, like a gigawatt is quite a bit of power.

77 00:06:01,414 --> 00:06:02,182 And...

78 00:06:03,950 --> 00:06:05,450 Man, let me just look up.

79 00:06:05,450 --> 00:06:06,966 How much is a gigawatt?

80 00:06:09,422 --> 00:06:11,662 A gigawatt is 1 billion watts.

81 00:06:13,162 --> 00:06:20,838 So it could power 1 .2 gigawatts could power more than 10 million light bulbs or.

82 00:06:23,246 --> 00:06:24,086 What?

83 00:06:24,446 --> 00:06:29,626 Or one fictional flux capacitor in a time traveling DeLorean.

84 00:06:29,626 --> 00:06:30,686 What?

85 00:06:31,546 --> 00:06:39,006 Anyways, so basically it saves, yeah, it saves a lot of power, which saves a lot of

86 00:06:39,006 --> 00:06:39,826 money.

87 00:06:39,826 --> 00:06:44,326 Because it's one of the key expenses is not only getting the capacity to train the

88 00:06:44,326 --> 00:06:50,362 data, but also paying to train the data because it takes up a lot of electricity.

89 00:06:50,542 --> 00:06:55,462 And that's one of the key complaints with cryptocurrencies is like, okay,

90 00:06:55,462 --> 00:06:56,682 cryptocurrency is good.

91 00:06:56,682 --> 00:06:58,962 It's decentralized, blah, blah, blah.

92 00:06:58,962 --> 00:07:08,882 But the mining of crypto is taking the power of like industrialized countries.

93 00:07:08,882 --> 00:07:15,872 I think one of the claims was Bitcoin and Ethereum combined were using more power

94 00:07:15,872 --> 00:07:19,270 than Japan or some crazy like that.

95 00:07:20,046 --> 00:07:24,492 So if you use less, then it makes sense.

96 00:07:26,702 --> 00:07:33,094 I think that the new chip is going to obviously power.

97 00:07:36,014 --> 00:07:45,274 you know, the next AGI, or the, you know, the has the potential to do things that we

98 00:07:45,274 --> 00:07:51,394 have never seen because of the, just the difference in improvement and the

99 00:07:51,394 --> 00:07:55,514 improvement of speed, the improvement of the amount of parameters it could take,

100 00:07:55,514 --> 00:08:04,812 the reduced energy consumption, all those things combined can really affect

101 00:08:04,846 --> 00:08:12,636 the intensity of simulations, scientific simulations, or these power hungry AAM

102 00:08:12,636 --> 00:08:17,976 models that we would talk about, the LLMs or large language models, self -driving

103 00:08:17,976 --> 00:08:19,146 cars.

104 00:08:19,146 --> 00:08:21,166 I mean, it's endless.

105 00:08:21,166 --> 00:08:24,816 It was one of the Tesla, I mean, I talked about it with Nvidia with their supply

106 00:08:24,816 --> 00:08:26,926 chain issues in the last episode.

107 00:08:27,006 --> 00:08:30,286 What was the issue with their supply chain?

108 00:08:30,286 --> 00:08:33,318 Tesla has had to start building their own chips because...

109 00:08:33,582 --> 00:08:37,622 they couldn't get enough Nvidia chips to keep producing their Teslas because Tesla

110 00:08:37,622 --> 00:08:46,142 uses or used to use Nvidia chips to GPUs for their autonomous driving in their

111 00:08:46,142 --> 00:08:47,010 cars.

112 00:08:49,582 --> 00:08:59,802 Okay, so these chips could potentially train or be used for this Figma or not

113 00:08:59,802 --> 00:09:05,902 Figma, Figma is a coding language, but figure one, oh one robot.

114 00:09:06,022 --> 00:09:11,842 So figure oh one was a robot that was demoed recently.

115 00:09:12,222 --> 00:09:17,594 And basically the, I could see if I could share my screen here.

116 00:09:18,286 --> 00:09:20,866 If you're watching the video, I'm gonna share my screen, but I'm not gonna talk

117 00:09:20,866 --> 00:09:30,966 about it as much as I did on the open eye video that we talked about with the Soma

118 00:09:31,106 --> 00:09:32,706 video generation.

119 00:09:32,846 --> 00:09:34,206 So, let me share.

120 00:09:34,706 --> 00:09:38,666 But I will narrate for maybe 20 seconds about what's going on.

121 00:09:39,206 --> 00:09:40,746 So, let me mute this.

122 00:09:40,746 --> 00:09:47,406 Okay, so the robot is standing at a table in front of dishware and Apple and.

123 00:09:47,406 --> 00:09:52,146 some cups, some of which are put away, some are out on the table.

124 00:09:52,246 --> 00:09:57,266 The guy asked the robot, hey, can I have something to eat?

125 00:09:57,286 --> 00:10:02,126 The robot hands the human an apple.

126 00:10:02,206 --> 00:10:06,506 And then the human asks, okay, why did you give me this apple?

127 00:10:06,506 --> 00:10:08,306 Like what's going on?

128 00:10:08,446 --> 00:10:10,186 While he's putting away trash.

129 00:10:10,186 --> 00:10:12,186 So he's like, he throws trash on the table.

130 00:10:12,186 --> 00:10:13,646 He's like, can you put this away?

131 00:10:13,646 --> 00:10:16,294 And then can you explain why you gave me the apple?

132 00:10:16,622 --> 00:10:23,352 he's putting away the trash or I can't say he but you know it's a robot so the robot

133 00:10:23,352 --> 00:10:26,936 the robot is putting away the trash and

134 00:10:28,718 --> 00:10:37,158 He says, I said he again, the robot says that I gave you the apple because that is

135 00:10:37,158 --> 00:10:39,298 the only edible thing in front of me.

136 00:10:39,298 --> 00:10:41,238 And he's like, okay, cool.

137 00:10:41,258 --> 00:10:48,318 And then he asked, okay, can you put away the dishes?

138 00:10:48,398 --> 00:10:51,246 And then the robot puts away the dishes.

139 00:10:53,646 --> 00:10:54,916 in the proper order.

140 00:10:54,916 --> 00:10:56,436 Like there's a slot for the cups.

141 00:10:56,436 --> 00:10:59,206 There's a slot for the plates.

142 00:10:59,206 --> 00:11:04,776 And the robot delicately picks up the cup, the plastic cup, the plastic plates and

143 00:11:04,776 --> 00:11:10,286 slots them in to the drying area.

144 00:11:10,766 --> 00:11:15,946 And then the human asks the robot, how do you think you did?

145 00:11:16,146 --> 00:11:19,046 And the robot says, I think I did pretty well.

146 00:11:19,326 --> 00:11:23,726 I gave you your apple that you wanted.

147 00:11:23,726 --> 00:11:28,446 You and Apple found a new home for someone who was hungry.

148 00:11:28,446 --> 00:11:35,086 I put away the trash, cleaned up the area and I put away the dishes.

149 00:11:36,386 --> 00:11:42,506 But he said he because I keep saying he because the person in the video is a he

150 00:11:42,506 --> 00:11:43,946 talking to the robot.

151 00:11:44,626 --> 00:11:49,466 But the robot did everything pretty much on the fly.

152 00:11:49,466 --> 00:11:52,486 They stated, I mean, you can't really believe demos.

153 00:11:52,558 --> 00:11:57,668 at face value, but to be able to do those things like pick up an apple, pick up the

154 00:11:57,668 --> 00:12:02,818 cups, know where to put them, hand the apple delicately to the human is all

155 00:12:02,818 --> 00:12:06,318 pretty impressive and not something that we've seen.

156 00:12:06,318 --> 00:12:18,648 But this AI chip Blackwell, this is something that could be used to train this

157 00:12:18,648 --> 00:12:20,952 figure 01 robot.

158 00:12:22,894 --> 00:12:25,694 Overall, very crazy.

159 00:12:26,214 --> 00:12:34,194 And the next crazy thing was DeepMind's release of their general agent.

160 00:12:35,334 --> 00:12:45,024 So a general agent is basically you have and they're doing it in the virtual

161 00:12:45,024 --> 00:12:49,294 environment because it's less dangerous, but basically it doesn't have a purpose

162 00:12:49,294 --> 00:12:50,374 like it.

163 00:12:50,374 --> 00:12:52,394 It learns as it goes.

164 00:12:53,614 --> 00:12:58,086 So they have the...

165 00:12:59,778 --> 00:13:02,418 human play games.

166 00:13:02,418 --> 00:13:09,478 So they take the data from humans playing games and then they feed it to the AI and

167 00:13:09,478 --> 00:13:12,658 then it goes into the AI.

168 00:13:13,398 --> 00:13:18,598 And then from there they train it, have it learn.

169 00:13:19,338 --> 00:13:22,046 And then they at a certain point,

170 00:13:23,534 --> 00:13:25,446 They just...

171 00:13:27,246 --> 00:13:31,066 like basically compare it against normal humans.

172 00:13:31,066 --> 00:13:33,966 How would a normal human execute these tasks?

173 00:13:33,966 --> 00:13:40,466 And the way that they're doing it is with text.

174 00:13:40,466 --> 00:13:42,706 So they'll use natural language.

175 00:13:42,706 --> 00:13:48,846 So basically text, they send in send in text to the AI, like drive this car or

176 00:13:48,846 --> 00:13:53,766 chop down this wood or craft, you know, a pickaxe or something.

177 00:13:53,766 --> 00:13:56,736 And then the AI would do those things.

178 00:13:57,486 --> 00:14:04,236 by learning all the inputs in the game, knowing where stuff is, and just doing

179 00:14:04,236 --> 00:14:05,426 whatever.

180 00:14:05,606 --> 00:14:09,936 And what they're doing is they're training in their virtual environment to just learn

181 00:14:09,936 --> 00:14:19,642 how to live in these games and progress basically.

182 00:14:21,806 --> 00:14:25,636 in a way that isn't with a purpose.

183 00:14:25,636 --> 00:14:30,366 Like there is no reward of forgetting the right answer.

184 00:14:30,526 --> 00:14:37,446 There is no rhyme or reason for what it's doing besides just playing the game.

185 00:14:38,366 --> 00:14:48,056 They give it instructions, right, with natural language, but also at the same

186 00:14:48,056 --> 00:14:51,566 time, the AI agent just plays

187 00:14:51,566 --> 00:15:01,646 by itself doesn't have like, it doesn't have an exact purpose for what it's doing.

188 00:15:01,646 --> 00:15:08,106 So it just does whatever besides when it's given instructions.

189 00:15:08,766 --> 00:15:13,626 And so they have like a gift of, okay, you know, drive a car.

190 00:15:13,626 --> 00:15:20,032 This is successful, successful simulation or

191 00:15:21,326 --> 00:15:27,586 Satisfactory results, okay, pick up iron ore, chop down a tree, things I said

192 00:15:27,586 --> 00:15:32,986 earlier, but then they wanna generalize it across more games and more stuff.

193 00:15:32,986 --> 00:15:36,032 The idea is to take it out of the virtual world, but.

194 00:15:37,550 --> 00:15:44,490 the agent that, you know, if it's trained off of mini games, it can learn how to

195 00:15:44,490 --> 00:15:48,500 play a game without any instructions.

196 00:15:48,500 --> 00:15:52,030 Basically that's what the goal is.

197 00:15:53,110 --> 00:15:57,718 Right now they have,

198 00:15:59,662 --> 00:16:02,724 a pretty good percentage of.

199 00:16:08,238 --> 00:16:14,118 know relative performance is what they're calling it for the agent the AI agent

200 00:16:14,118 --> 00:16:18,638 playing a game that's never played before slash like being in an environment that

201 00:16:18,638 --> 00:16:25,778 it's never used or has no information on in following the instructions and then

202 00:16:25,778 --> 00:16:32,166 they have maybe a 25 % relative performance for things that

203 00:16:33,742 --> 00:16:39,882 looks more like 35 for when the AI agent isn't given any instruction.

204 00:16:40,542 --> 00:16:48,702 So this is pretty cool because you could use it for a more flexible AI assistance.

205 00:16:48,702 --> 00:16:52,502 You could use this for video game development.

206 00:16:52,502 --> 00:16:57,692 Like imagine video games that have no

207 00:16:59,566 --> 00:17:00,546 ending, right?

208 00:17:00,546 --> 00:17:08,796 Or that constantly evolves ongoingly and the characters are always dynamic and have

209 00:17:08,796 --> 00:17:15,536 their own personalities and quirks that the user or the gamer can't predict

210 00:17:15,536 --> 00:17:19,646 because it is all original every time.

211 00:17:20,086 --> 00:17:26,886 And so you have this endless playability, which also is kind of dangerous because

212 00:17:26,886 --> 00:17:28,686 what about

213 00:17:28,686 --> 00:17:38,226 you know, things like deep fakes or these other nefarious activities.

214 00:17:38,226 --> 00:17:45,546 I know that there are a couple of these like well -known kind of not well -known,

215 00:17:45,546 --> 00:17:54,266 but basically that there's these fake influencers online that are basically just

216 00:17:54,266 --> 00:17:58,510 this AI generated personalities with

217 00:17:59,662 --> 00:18:04,402 they don't do videos, but it's just photos and they have many likes and, and

218 00:18:04,402 --> 00:18:10,202 influence and they get sponsorships, but they're really not a real thing or person.

219 00:18:10,202 --> 00:18:18,802 It's just this AI generated images of this persona, which is really sad.

220 00:18:18,802 --> 00:18:21,442 So, uh, I don't know.

221 00:18:21,442 --> 00:18:28,182 I mean, I think that with great change comes great responsibility.

222 00:18:28,366 --> 00:18:34,526 And so I hope that we're going to be moving in the right direction with these

223 00:18:34,526 --> 00:18:45,036 new powers at B because I have my hesitations about these potential issues

224 00:18:45,036 --> 00:18:54,866 that I know we're saying that we perceive, but at the same time, I'm not sure.

225 00:18:55,326 --> 00:18:57,716 You know, it just becomes difficult.

226 00:18:58,350 --> 00:19:07,610 to manage some of these massive AI models with trillions of parameters and at what

227 00:19:07,610 --> 00:19:10,830 point does AI become a person?

228 00:19:11,250 --> 00:19:17,790 Or at what point does AI have rights or something like that?

229 00:19:17,790 --> 00:19:19,130 I don't know.

230 00:19:20,190 --> 00:19:23,030 I don't think we're there yet, 100%.

231 00:19:23,030 --> 00:19:27,278 I'm not saying that AI deserves rights now, but.

232 00:19:27,278 --> 00:19:34,558 I think in 20 years from now, if we keep going at the rate that we're going, what

233 00:19:34,558 --> 00:19:43,118 determines a differentiation between a human and AI if the AI is replacing humans

234 00:19:43,118 --> 00:19:47,622 to do general task jobs like...

235 00:19:49,486 --> 00:19:57,366 I don't know, like a lawyer or something or housekeeping that have these kind of

236 00:19:57,366 --> 00:20:02,706 ongoing responsibilities that are changing constantly and require cognitive thought

237 00:20:02,706 --> 00:20:05,386 and that are multifaceted.

238 00:20:06,486 --> 00:20:10,696 I think at a certain point that that would be a determination of conscious, right?

239 00:20:10,696 --> 00:20:15,766 And so if you're conscious, then I guess you would be determined to be a human or

240 00:20:15,766 --> 00:20:18,574 not human, but at least have some.

241 00:20:18,574 --> 00:20:21,754 form of intelligence and be protected.

242 00:20:22,854 --> 00:20:23,934 I don't know.

243 00:20:23,934 --> 00:20:27,654 We're going down a rabbit hole here, so I don't want to go too deep.

244 00:20:27,674 --> 00:20:32,174 But it is scary to think about where things are going.

245 00:20:32,174 --> 00:20:39,764 I showed my Nana that AI video with the figure 01, and she was pretty excited.

246 00:20:39,764 --> 00:20:45,894 She was like, oh, when I was younger, I wanted, I don't know that person's name.

247 00:20:45,894 --> 00:20:47,590 It was the...

248 00:20:47,694 --> 00:20:50,494 the housekeeper of the Jensens?

249 00:20:50,634 --> 00:20:51,894 I'm not sure.

250 00:20:51,894 --> 00:20:54,944 But it was a robot and she's like, oh, I always wanted one of those when I was a

251 00:20:54,944 --> 00:20:55,494 kid.

252 00:20:55,494 --> 00:20:57,494 So I wish she'd visit me.

253 00:20:57,534 --> 00:20:58,462 And so.

254 00:21:00,590 --> 00:21:01,380 There we have it.

255 00:21:01,380 --> 00:21:02,850 I mean, Nana's excited.

256 00:21:02,850 --> 00:21:04,450 Nana's ready for change.

257 00:21:04,450 --> 00:21:06,730 She's been ready for change for a long time.

258 00:21:07,610 --> 00:21:15,510 But it is seemingly closer to like a Black Mirror episode, potentially.

259 00:21:16,590 --> 00:21:19,526 But these all tie back to...

260 00:21:21,196 --> 00:21:26,966 AI improving the well -being of humans.

261 00:21:27,886 --> 00:21:33,656 And I just kind of was questioning at what point are we just stepping on the backs of

262 00:21:33,656 --> 00:21:38,386 AI and what point is too far?

263 00:21:38,386 --> 00:21:44,526 And I don't think we're there or there or ready to have the conversation yet.

264 00:21:45,826 --> 00:21:48,186 What AI news has blown your mind lately?

265 00:21:48,186 --> 00:21:48,938 You know, let's.

266 00:21:48,938 --> 00:21:51,218 discussed that, you know, you put it in the comments.

267 00:21:51,218 --> 00:21:54,198 I'm more active on the YouTube channel.

268 00:21:54,878 --> 00:22:01,998 The YouTube channel is Dalton B Anderson, and then the podcast playlist is just

269 00:22:01,998 --> 00:22:03,058 VentureStep.

270 00:22:03,498 --> 00:22:10,178 Put a comment down and let me know what your thoughts are about the Nvidia chip.

271 00:22:10,178 --> 00:22:13,938 If you have a deeper analysis about the Figma 01.

272 00:22:14,318 --> 00:22:15,428 I said Figma again.

273 00:22:15,428 --> 00:22:16,718 Figma is a programming language.

274 00:22:16,718 --> 00:22:18,094 The figure 01.

275 00:22:18,094 --> 00:22:24,674 robot or, you know, any other suggestions to refine the show or we're still pretty

276 00:22:24,674 --> 00:22:25,834 new here.

277 00:22:26,154 --> 00:22:34,554 One thing I would like to do is talk about before I go, we'll go over last week's

278 00:22:34,554 --> 00:22:35,534 comments.

279 00:22:35,774 --> 00:22:42,974 And I think that is it's it's good to do because it lets people be heard and.

280 00:22:43,674 --> 00:22:47,662 Encourages people to be interactive with.

281 00:22:47,662 --> 00:22:51,382 the show or not interactive, but interact with the show.

282 00:22:51,382 --> 00:22:56,622 So let me go and if I can figure it out on the fly, hopefully I can.

283 00:22:56,982 --> 00:22:58,742 Because I'm not an expert.

284 00:22:59,142 --> 00:23:00,882 See comments.

285 00:23:02,882 --> 00:23:06,362 Let's see.

286 00:23:07,942 --> 00:23:09,422 Oh, man.

287 00:23:10,262 --> 00:23:11,622 So.

288 00:23:12,622 --> 00:23:13,662 Man.

289 00:23:13,662 --> 00:23:13,932 All right.

290 00:23:13,932 --> 00:23:16,922 So we have one by Marco Coconuts.

291 00:23:17,390 --> 00:23:20,150 Love the stash, keep it up.

292 00:23:20,710 --> 00:23:26,030 The growth friend, you earned my sub, tell Nana a fan says hi.

293 00:23:26,030 --> 00:23:29,470 Very nice, I said, you know, thank you so much for the kind words.

294 00:23:29,470 --> 00:23:31,090 Happy you're enjoying the content.

295 00:23:31,090 --> 00:23:34,210 I'll pass my regards to Nana, that's very sweet of you.

296 00:23:34,270 --> 00:23:43,490 Then this guy named gg -mm9hf said who asked?

297 00:23:44,622 --> 00:23:46,782 Yeah, I'm not sure who asked.

298 00:23:47,602 --> 00:23:51,622 I'm glad that you're here, though, and you're you're trying to learn in your free

299 00:23:51,622 --> 00:23:55,842 time, or at least I'm trying to learn and maybe you're learning from me.

300 00:23:55,842 --> 00:24:01,582 Or maybe this speaks to curiosity, but you're welcome here.

301 00:24:01,582 --> 00:24:09,092 And maybe next week you can say who said or who asked?

302 00:24:09,092 --> 00:24:10,282 I don't know.

303 00:24:10,342 --> 00:24:11,682 It's a good question.

304 00:24:12,118 --> 00:24:14,438 But that is the end of today's show.

305 00:24:14,438 --> 00:24:16,258 I'll talk to you next week.

306 00:24:16,278 --> 00:24:17,718 I'm trying to be consistent.

307 00:24:17,718 --> 00:24:19,478 Today was a little tough.

308 00:24:19,558 --> 00:24:24,798 I definitely struggled with the idea of doing a podcast episode today.

309 00:24:24,798 --> 00:24:27,058 We just got to stay disciplined once a week.

310 00:24:27,058 --> 00:24:34,258 Next week I'll be discussing the book review of the 48 Laws of Power and I will

311 00:24:34,258 --> 00:24:39,078 state my opinions on what I think about it and whether I think it's worthy of a read.

312 00:24:39,138 --> 00:24:40,238 Okay.

313 00:24:40,818 --> 00:24:41,294 Well.

314 00:24:41,294 --> 00:24:44,374 Have a great day, night, morning, evening.

315 00:24:44,374 --> 00:24:46,994 Talk to you next week and appreciate your time.

316 00:24:46,994 --> 00:24:48,694 See ya, bye.