1
00:00:00,000 --> 00:00:03,000
Wow, AI is everywhere these days, isn't it?

2
00:00:03,000 --> 00:00:04,320
Like every time I check the news,

3
00:00:04,320 --> 00:00:08,040
there's something about some crazy new AI thing.

4
00:00:08,040 --> 00:00:10,280
Yeah, it's a lot to keep up with for sure.

5
00:00:10,280 --> 00:00:12,000
That's why we're doing this deep dive right

6
00:00:12,000 --> 00:00:13,500
to try and make sense of it all.

7
00:00:13,500 --> 00:00:15,240
We're gonna look at a bunch of different stuff today,

8
00:00:15,240 --> 00:00:17,360
like tech articles, research papers,

9
00:00:17,360 --> 00:00:20,000
even a company blog post or two,

10
00:00:20,000 --> 00:00:21,440
you know, to get the full picture.

11
00:00:21,440 --> 00:00:23,760
It's definitely more than just hype at this point though.

12
00:00:23,760 --> 00:00:24,600
Absolutely.

13
00:00:24,600 --> 00:00:27,840
We're seeing real change driven by AI,

14
00:00:27,840 --> 00:00:29,840
like did you hear about the Nobel Prize

15
00:00:29,840 --> 00:00:31,000
in physics this year?

16
00:00:31,000 --> 00:00:31,960
I didn't know.

17
00:00:31,960 --> 00:00:35,280
Yeah, it went to John Hopfield and Jeffrey Hinton

18
00:00:35,280 --> 00:00:39,200
for their work on, get this, artificial neural networks.

19
00:00:39,200 --> 00:00:42,160
Wow, the Nobel Prize, that's a pretty big deal.

20
00:00:42,160 --> 00:00:43,000
Yeah, it is.

21
00:00:43,000 --> 00:00:45,160
Okay, neural networks, so that always kind of sounded

22
00:00:45,160 --> 00:00:47,240
like, I don't know, science fiction to me.

23
00:00:47,240 --> 00:00:48,080
I get that.

24
00:00:48,080 --> 00:00:50,400
What does it actually mean in the real world?

25
00:00:50,400 --> 00:00:53,680
Basically, neural networks are like the brains behind

26
00:00:53,680 --> 00:00:55,920
a lot of the AI we use every single day.

27
00:00:55,920 --> 00:00:56,760
Okay.

28
00:00:56,760 --> 00:00:58,680
Like when your phone unlocks using facial recognition.

29
00:00:58,680 --> 00:01:00,520
That's neural networks.

30
00:01:00,520 --> 00:01:01,920
Or those language translation apps

31
00:01:01,920 --> 00:01:03,280
everyone uses when they travel.

32
00:01:03,280 --> 00:01:04,800
Neural networks, again.

33
00:01:04,800 --> 00:01:06,760
So it's not just some abstract concept then,

34
00:01:06,760 --> 00:01:07,760
it's actually like.

35
00:01:07,760 --> 00:01:08,760
It's already here.

36
00:01:08,760 --> 00:01:10,480
Wow, that's kind of wild.

37
00:01:10,480 --> 00:01:12,800
It makes that Nobel Prize even cooler actually.

38
00:01:12,800 --> 00:01:15,080
Right, and the pace of development is only increasing.

39
00:01:15,080 --> 00:01:15,920
Yeah, for sure.

40
00:01:15,920 --> 00:01:18,120
Which is why it's so important to understand the impact,

41
00:01:18,120 --> 00:01:18,960
you know.

42
00:01:18,960 --> 00:01:21,160
And speaking of impact, I saw this article

43
00:01:21,160 --> 00:01:23,440
from eSchool News and get this,

44
00:01:23,440 --> 00:01:25,920
they're talking about a new AI guide

45
00:01:25,920 --> 00:01:27,760
specifically for students.

46
00:01:27,760 --> 00:01:28,600
Makes sense, right?

47
00:01:28,600 --> 00:01:29,440
Yeah.

48
00:01:29,440 --> 00:01:32,880
AI literacy is gonna be essential for kids going forward.

49
00:01:32,880 --> 00:01:33,920
100%.

50
00:01:33,920 --> 00:01:36,280
We've got to equip them to deal with this stuff.

51
00:01:36,280 --> 00:01:37,600
And that starts with education.

52
00:01:37,600 --> 00:01:38,440
Absolutely.

53
00:01:38,440 --> 00:01:41,440
It's crazy how fast AI research turns into

54
00:01:41,440 --> 00:01:43,920
like actual products and services, you know.

55
00:01:43,920 --> 00:01:45,000
Yeah, it's really impressive.

56
00:01:45,000 --> 00:01:47,600
And one of the coolest areas where that's happening

57
00:01:47,600 --> 00:01:49,040
is reality capture.

58
00:01:49,040 --> 00:01:50,200
Reality capture.

59
00:01:50,200 --> 00:01:51,920
Yeah, there's this video blog post here

60
00:01:51,920 --> 00:01:52,760
that goes into it.

61
00:01:52,760 --> 00:01:53,600
Okay.

62
00:01:53,600 --> 00:01:57,080
It's all about using tech to like recreate

63
00:01:57,080 --> 00:01:58,960
real places in the digital world.

64
00:01:58,960 --> 00:02:00,800
Oh, right, like those 3D standards

65
00:02:00,800 --> 00:02:02,280
they use for video games and stuff?

66
00:02:02,280 --> 00:02:03,960
Exactly, that's one way to do it.

67
00:02:03,960 --> 00:02:04,800
Huh, cool.

68
00:02:04,800 --> 00:02:06,360
It usually involves things like LiDAR,

69
00:02:06,360 --> 00:02:08,600
which is how those self-driving cars see.

70
00:02:08,600 --> 00:02:11,400
LiDAR, so it's like what, lasers instead of radar?

71
00:02:11,400 --> 00:02:13,080
Exactly, it's super precise,

72
00:02:13,080 --> 00:02:15,240
maps out the whole environment in 3D.

73
00:02:15,240 --> 00:02:16,080
Wow.

74
00:02:16,080 --> 00:02:17,480
And then there's photogrammetry,

75
00:02:17,480 --> 00:02:20,280
which is using photos to make 3D models.

76
00:02:20,280 --> 00:02:21,920
Okay, I kinda get that.

77
00:02:21,920 --> 00:02:23,840
This stuff isn't just for games though.

78
00:02:23,840 --> 00:02:24,680
Yeah.

79
00:02:24,680 --> 00:02:26,280
Architects use it, construction companies,

80
00:02:26,280 --> 00:02:29,040
even museums to preserve artifacts.

81
00:02:29,040 --> 00:02:30,120
Wild.

82
00:02:30,120 --> 00:02:31,600
But where does the AI come in?

83
00:02:31,600 --> 00:02:34,200
It can't just be about the scanning, right?

84
00:02:34,200 --> 00:02:37,000
You got AI takes it to a whole other level.

85
00:02:37,000 --> 00:02:38,160
How so?

86
00:02:38,160 --> 00:02:40,720
See, normally you need tons of data

87
00:02:40,720 --> 00:02:42,640
to make these 3D models look real.

88
00:02:42,640 --> 00:02:43,480
Right.

89
00:02:43,480 --> 00:02:45,200
But AI can do it with way less,

90
00:02:45,200 --> 00:02:46,360
which is a game changer.

91
00:02:46,360 --> 00:02:47,200
Really?

92
00:02:47,200 --> 00:02:48,920
Yeah, this Nvidia post talks about these things

93
00:02:48,920 --> 00:02:52,040
called NERF-Fs, which are like neural radiance fields.

94
00:02:52,040 --> 00:02:52,880
There's a lot of them.

95
00:02:52,880 --> 00:02:53,720
NERF-Fs, okay.

96
00:02:53,720 --> 00:02:55,160
And then there's Gaussian splatting,

97
00:02:55,160 --> 00:02:57,360
which I don't even know how to explain that one.

98
00:02:57,360 --> 00:02:58,440
Gaussian what?

99
00:02:58,440 --> 00:02:59,800
Yeah, it's pretty technical.

100
00:02:59,800 --> 00:03:01,560
But basically this means, what?

101
00:03:01,560 --> 00:03:04,560
We can have like digital twins of real things

102
00:03:04,560 --> 00:03:05,960
that look photorealistic.

103
00:03:05,960 --> 00:03:07,200
Basically, yeah.

104
00:03:07,200 --> 00:03:10,280
Imagine like being able to explore ancient Rome

105
00:03:10,280 --> 00:03:13,800
on your VR headset or trying on clothes virtually,

106
00:03:13,800 --> 00:03:15,280
but it's like looking in a mirror.

107
00:03:15,280 --> 00:03:17,440
Okay, that's pretty mind blowing when you put it like that.

108
00:03:17,440 --> 00:03:19,800
It's blurring the lines between real and virtual.

109
00:03:19,800 --> 00:03:20,920
No kidding.

110
00:03:20,920 --> 00:03:22,520
And speaking of blurring lines,

111
00:03:22,520 --> 00:03:24,680
I saw these articles, Bloomberg and US News

112
00:03:24,680 --> 00:03:27,080
both had it about Foxconn,

113
00:03:27,080 --> 00:03:28,640
the company that makes iPhones.

114
00:03:28,640 --> 00:03:29,720
Yeah, I think I saw that.

115
00:03:29,720 --> 00:03:31,800
They're building a huge factory in Mexico

116
00:03:31,800 --> 00:03:34,600
just to make Nvidia AI chips.

117
00:03:34,600 --> 00:03:36,320
See, this is what I mean about a real impact.

118
00:03:36,320 --> 00:03:37,160
Right.

119
00:03:37,160 --> 00:03:38,640
They're making a big bet on AI.

120
00:03:38,640 --> 00:03:39,480
Yeah.

121
00:03:39,480 --> 00:03:40,320
Shows you where things are heading.

122
00:03:40,320 --> 00:03:43,480
It's like global, the shift from education

123
00:03:43,480 --> 00:03:45,280
now this manufacturing thing.

124
00:03:45,280 --> 00:03:46,400
And it goes even deeper,

125
00:03:46,400 --> 00:03:48,600
even into how we write software.

126
00:03:48,600 --> 00:03:49,440
Really?

127
00:03:49,440 --> 00:03:50,680
Yeah, there's this research paper here.

128
00:03:50,680 --> 00:03:53,600
It's about something called SWE Bench,

129
00:03:53,600 --> 00:03:57,560
which is basically a test to see how well AI can code.

130
00:03:57,560 --> 00:03:59,800
So we're making AI prove it can program.

131
00:03:59,800 --> 00:04:01,960
Yeah, like can it find or fix bugs,

132
00:04:01,960 --> 00:04:03,440
write new code from scratch?

133
00:04:03,440 --> 00:04:04,280
And can it?

134
00:04:04,280 --> 00:04:06,240
It's getting good, surprisingly good.

135
00:04:06,240 --> 00:04:07,520
Like scarily good.

136
00:04:07,520 --> 00:04:08,360
Maybe a little.

137
00:04:08,360 --> 00:04:09,200
It's making people wonder

138
00:04:09,200 --> 00:04:11,200
if programmers will even have jobs soon.

139
00:04:11,200 --> 00:04:13,400
Whoa, hold on, seriously.

140
00:04:13,400 --> 00:04:14,920
It's a hot topic,

141
00:04:14,920 --> 00:04:17,240
but I think it's more about AI helping us,

142
00:04:17,240 --> 00:04:19,000
not replacing us entirely.

143
00:04:19,000 --> 00:04:20,280
Like an assistant, you mean?

144
00:04:20,280 --> 00:04:21,120
Exactly.

145
00:04:21,120 --> 00:04:22,360
Take care of the boring stuff

146
00:04:22,360 --> 00:04:24,600
so we can focus on the creative problem solving.

147
00:04:24,600 --> 00:04:26,120
Okay, that makes more sense.

148
00:04:26,120 --> 00:04:28,400
Could even make coding more accessible to people

149
00:04:28,400 --> 00:04:29,760
who never learned it traditionally.

150
00:04:29,760 --> 00:04:31,440
That's a good point, actually.

151
00:04:31,440 --> 00:04:33,480
And speaking of AI shaking things up,

152
00:04:33,480 --> 00:04:36,400
there's this announcement from SAP.

153
00:04:36,400 --> 00:04:37,640
The software company.

154
00:04:37,640 --> 00:04:39,360
Yeah, they're big on this stuff.

155
00:04:39,360 --> 00:04:43,760
They're giving their AI assistant, Jool, a major upgrade.

156
00:04:43,760 --> 00:04:45,680
What can this Jool thing do?

157
00:04:45,680 --> 00:04:46,760
Well, this new version,

158
00:04:46,760 --> 00:04:49,760
it's all about collaborative AI agents.

159
00:04:49,760 --> 00:04:50,600
Collaborative?

160
00:04:50,600 --> 00:04:54,080
Like imagine a whole team of AI is working together.

161
00:04:54,080 --> 00:04:55,560
Each one's specialized.

162
00:04:55,560 --> 00:04:57,120
So instead of just one AI,

163
00:04:57,120 --> 00:04:59,120
it's like having a whole department of them.

164
00:04:59,120 --> 00:05:00,000
Basically, yeah.

165
00:05:00,000 --> 00:05:02,360
Okay, that sounds insanely powerful.

166
00:05:02,360 --> 00:05:04,880
Right, like they give the example of dispute management.

167
00:05:04,880 --> 00:05:06,560
Like customer service stuff.

168
00:05:06,560 --> 00:05:08,720
Kind of, more like when businesses disagree

169
00:05:08,720 --> 00:05:10,320
on invoices and payments.

170
00:05:10,320 --> 00:05:11,200
Oh.

171
00:05:11,200 --> 00:05:14,560
AI could sort through all that, find errors,

172
00:05:14,560 --> 00:05:16,040
maybe even solve them automatically.

173
00:05:16,040 --> 00:05:18,040
No more arguing over paperwork, I like it.

174
00:05:18,040 --> 00:05:19,360
Exactly, or in accounting,

175
00:05:19,360 --> 00:05:21,320
they could automate tons of tasks,

176
00:05:21,320 --> 00:05:23,320
free up humans for more important work.

177
00:05:23,320 --> 00:05:24,680
So no matter what job you do,

178
00:05:24,680 --> 00:05:26,600
there's gonna be an AI for that soon.

179
00:05:26,600 --> 00:05:27,680
It's starting to feel that way.

180
00:05:27,680 --> 00:05:28,600
Wild.

181
00:05:28,600 --> 00:05:31,160
But then there's this RECA announcement,

182
00:05:31,160 --> 00:05:33,880
and this one, this one is something else.

183
00:05:33,880 --> 00:05:35,760
RECA, the AI company, what they do.

184
00:05:35,760 --> 00:05:38,360
They just released a new large language model.

185
00:05:38,360 --> 00:05:39,840
Another one, there's a new one every week now.

186
00:05:39,840 --> 00:05:40,880
I know, right?

187
00:05:40,880 --> 00:05:43,480
But this one is called RECA Flash, and it's different.

188
00:05:43,480 --> 00:05:45,600
Okay, I'm listening, what's so special?

189
00:05:45,600 --> 00:05:48,120
This one understands more than just text.

190
00:05:48,120 --> 00:05:49,800
You mean like what, code or something?

191
00:05:49,800 --> 00:05:51,880
No, like images and audio.

192
00:05:51,880 --> 00:05:53,000
Hold on, seriously?

193
00:05:53,000 --> 00:05:55,240
Seriously, it can like watch a video

194
00:05:55,240 --> 00:05:56,640
and tell you what's happening?

195
00:05:56,640 --> 00:05:57,520
That's insane.

196
00:05:57,520 --> 00:05:59,160
Right, think of the possibilities,

197
00:05:59,160 --> 00:06:00,880
video editing, education,

198
00:06:00,880 --> 00:06:02,640
even just analyzing security footage.

199
00:06:02,640 --> 00:06:04,280
It's like AI is gaining senses.

200
00:06:04,280 --> 00:06:06,440
And it gets even crazier.

201
00:06:06,440 --> 00:06:07,280
How so?

202
00:06:07,280 --> 00:06:08,600
RECA Flash is way better

203
00:06:08,600 --> 00:06:10,480
at following instructions than other models.

204
00:06:10,480 --> 00:06:13,040
Oh wow, that's a big deal for these language models.

205
00:06:13,040 --> 00:06:15,280
Right, like remember that SW bench thing?

206
00:06:15,280 --> 00:06:16,120
The coding test.

207
00:06:16,120 --> 00:06:18,440
Yeah, RECA Flash aced it apparently.

208
00:06:18,440 --> 00:06:20,760
Huh, shows you how fast things are moving.

209
00:06:20,760 --> 00:06:23,120
All this talk about AI doing this and that,

210
00:06:23,120 --> 00:06:24,240
it makes you wonder,

211
00:06:24,240 --> 00:06:26,840
what are we humans even good for anymore?

212
00:06:26,840 --> 00:06:28,000
It's a fair question,

213
00:06:28,000 --> 00:06:29,640
and one we should be asking ourselves.

214
00:06:29,640 --> 00:06:30,480
Right.

215
00:06:30,480 --> 00:06:32,720
Like it's easy to get caught up in all the excitement,

216
00:06:32,720 --> 00:06:36,160
but we can't forget that AI has the potential

217
00:06:36,160 --> 00:06:37,720
to be really disruptive too.

218
00:06:37,720 --> 00:06:39,360
Disruptive how?

219
00:06:39,360 --> 00:06:40,880
Well, we already talked about jobs,

220
00:06:40,880 --> 00:06:42,800
but it goes deeper than that.

221
00:06:42,800 --> 00:06:45,160
It's about tower control.

222
00:06:45,160 --> 00:06:48,200
Who gets to decide how this technology gets used?

223
00:06:48,200 --> 00:06:50,160
Okay, that's getting a bit heavy.

224
00:06:50,160 --> 00:06:51,200
I know, but that's the thing,

225
00:06:51,200 --> 00:06:53,360
this isn't science fiction anymore, it's real life.

226
00:06:53,360 --> 00:06:56,160
It really does feel like we're on the edge of something huge.

227
00:06:56,160 --> 00:06:58,360
Like AI is breaking out of the labs

228
00:06:58,360 --> 00:07:00,520
and into, well, everything.

229
00:07:00,520 --> 00:07:02,360
It's definitely a pivotal moment, that's for sure.

230
00:07:02,360 --> 00:07:05,120
Exciting, yeah, but also a little bit,

231
00:07:05,120 --> 00:07:06,200
I don't know, intimidating.

232
00:07:06,200 --> 00:07:08,880
You know, kidding, it's a lot to process.

233
00:07:08,880 --> 00:07:10,600
It is, and that's why we're talking about it, right?

234
00:07:10,600 --> 00:07:12,040
To try to wrap our heads around it all.

235
00:07:12,040 --> 00:07:14,160
Exactly, so for our listener,

236
00:07:14,160 --> 00:07:16,000
you know, the one who's been with us

237
00:07:16,000 --> 00:07:18,480
through this whole AI roller coaster,

238
00:07:18,480 --> 00:07:20,040
what's the main thing,

239
00:07:20,040 --> 00:07:23,000
the thing they should really take away from all of this?

240
00:07:23,000 --> 00:07:26,600
I think it's that AI isn't some abstract thing anymore.

241
00:07:26,600 --> 00:07:30,840
It's actually real, it's here, it's impacting our lives.

242
00:07:30,840 --> 00:07:33,720
And not just in like small ways either.

243
00:07:33,720 --> 00:07:37,200
Exactly, we're talking big changes, fundamental shifts,

244
00:07:37,200 --> 00:07:38,880
and we're just getting started.

245
00:07:38,880 --> 00:07:41,720
It's like we're seeing the first few cracks in the pavement,

246
00:07:41,720 --> 00:07:44,840
but that whole sidewalk is about to be totally uprooted.

247
00:07:44,840 --> 00:07:45,840
That's a great analogy,

248
00:07:45,840 --> 00:07:47,880
because once these changes start happening,

249
00:07:47,880 --> 00:07:49,080
they tend to happen fast.

250
00:07:49,080 --> 00:07:50,520
So buckle up, basically.

251
00:07:50,520 --> 00:07:51,360
Yeah, pretty much.

252
00:07:51,360 --> 00:07:52,800
But it's not all doom and gloom, right?

253
00:07:52,800 --> 00:07:54,640
There's a lot of good that can come from this, right?

254
00:07:54,640 --> 00:07:57,800
Absolutely, tons potential, but it's up to us,

255
00:07:57,800 --> 00:08:00,160
all of us, to steer it in the right direction.

256
00:08:00,160 --> 00:08:02,480
Okay, so how do we do that?

257
00:08:02,480 --> 00:08:05,760
What can our listener do, like practically,

258
00:08:05,760 --> 00:08:08,560
to navigate this AI-powered future?

259
00:08:08,560 --> 00:08:11,080
First, don't be afraid of it, learn about it.

260
00:08:11,080 --> 00:08:12,320
Easier said than done,

261
00:08:12,320 --> 00:08:14,440
it seems pretty complicated sometimes.

262
00:08:14,440 --> 00:08:17,720
It can be, sure, but there are so many resources

263
00:08:17,720 --> 00:08:21,480
out there now, online courses, books, even podcasts.

264
00:08:21,480 --> 00:08:23,160
Like this one, Shameless Plug.

265
00:08:23,160 --> 00:08:26,200
Exactly, the point is, the more you know about AI,

266
00:08:26,200 --> 00:08:28,480
the better prepared you'll be no matter what you do.

267
00:08:28,480 --> 00:08:31,400
And don't just be a bystander, right, get involved.

268
00:08:31,400 --> 00:08:33,760
Exactly, this technology is gonna impact all of us,

269
00:08:33,760 --> 00:08:35,400
so we need to be part of the conversation.

270
00:08:35,400 --> 00:08:36,800
Make our voices heard, right.

271
00:08:36,800 --> 00:08:40,840
Exactly, be informed, ask questions, challenge assumptions,

272
00:08:40,840 --> 00:08:42,520
that's how we shape the future we want.

273
00:08:42,520 --> 00:08:45,200
Okay, that's a great message, really gets you thinking.

274
00:08:45,200 --> 00:08:48,280
It's not about being an optimist or a pessimist about AI,

275
00:08:48,280 --> 00:08:51,080
it's about being proactive, being engaged.

276
00:08:51,080 --> 00:08:52,800
Couldn't have said it better myself.

277
00:08:52,800 --> 00:08:55,120
Well, this has been quite the deep dive, hasn't it?

278
00:08:55,120 --> 00:08:56,920
It really has, so much to unpack,

279
00:08:56,920 --> 00:08:59,040
and we've just scratched the surface.

280
00:08:59,040 --> 00:09:00,680
That's the thing about AI, right?

281
00:09:00,680 --> 00:09:02,440
There's always something new to learn,

282
00:09:02,440 --> 00:09:04,600
always something more to explore.

283
00:09:04,600 --> 00:09:06,880
Absolutely, it's an ever-evolving field,

284
00:09:06,880 --> 00:09:09,600
which makes it both challenging and endlessly fascinating.

285
00:09:09,600 --> 00:09:12,160
And on that note, we should probably wrap things up.

286
00:09:12,160 --> 00:09:13,080
Yeah, good idea.

287
00:09:13,080 --> 00:09:14,600
But hey, to our listener,

288
00:09:14,600 --> 00:09:16,440
thanks for sticking with us through this,

289
00:09:16,440 --> 00:09:18,000
it's been a wild ride.

290
00:09:18,000 --> 00:09:20,440
It has, but the conversation doesn't end here.

291
00:09:20,440 --> 00:09:24,920
Exactly, so keep learning, keep asking questions,

292
00:09:24,920 --> 00:09:27,760
and most importantly, stay curious.

293
00:09:27,760 --> 00:09:30,120
Couldn't agree more, because the future of AI,

294
00:09:30,120 --> 00:09:31,160
well, that's still being written.

295
00:09:31,160 --> 00:09:32,520
And who knows, maybe our listener

296
00:09:32,520 --> 00:09:33,520
will be the one writing it.

297
00:09:33,520 --> 00:09:35,080
Wouldn't that be something?

298
00:09:35,080 --> 00:09:36,680
That's all the time we have for today,

299
00:09:36,680 --> 00:09:39,680
but we'll be back next time with another deep dive

300
00:09:39,680 --> 00:09:41,440
into the world of AI.

301
00:09:41,440 --> 00:10:07,440
Until then, take care.