1
00:00:11,450 --> 00:00:13,534 
All right, hopefully you can

2
00:00:13,572 --> 00:00:17,518 
hear me. Hopefully this is going

3
00:00:17,604 --> 00:00:21,534 
to work. Figured I would share

4
00:00:21,572 --> 00:00:23,198 
this. A lot of the folks I

5
00:00:23,284 --> 00:00:26,054 
follow on LinkedIn, they, um

6
00:00:26,252 --> 00:00:27,926 
they do some cool stuff. They go

7
00:00:27,948 --> 00:00:30,390 
to some cool places like Dubai,

8
00:00:31,130 --> 00:00:35,158 
Monaco, et cetera. Shout out to

9
00:00:35,164 --> 00:00:36,006 
you, Lauren, for the

10
00:00:36,028 --> 00:00:39,798 
inspiration. And I figured I

11
00:00:39,804 --> 00:00:42,138 
would stream today because I

12
00:00:42,144 --> 00:00:43,226 
haven't streamed in a while this

13
00:00:43,248 --> 00:00:44,122 
month. My bad.

14
00:00:44,176 --> 00:00:45,594 
Totally on me. A lot of family

15
00:00:45,632 --> 00:00:46,730 
stuff going on. I'll explain

16
00:00:46,800 --> 00:00:49,466 
another time in the future. But

17
00:00:49,568 --> 00:00:51,774 
said family stuff brings me to

18
00:00:51,812 --> 00:00:54,206 
this wonderful place in

19
00:00:54,388 --> 00:00:56,346 
basically rural Pennsylvania,

20
00:00:56,538 --> 00:00:58,878 
somewhere between Pittsburgh and

21
00:00:58,884 --> 00:01:01,726 
Philly. And I am literally at an

22
00:01:01,748 --> 00:01:04,562 
airbnb by a stream. I don't know

23
00:01:04,616 --> 00:01:08,980 
how well you can see that, but

24
00:01:10,630 --> 00:01:12,500 
there's a little fire pit there.

25
00:01:13,190 --> 00:01:14,418 
Rock garden. I don't know what

26
00:01:14,424 --> 00:01:14,958 
that is.

27
00:01:15,064 --> 00:01:17,814 
But I figured I would stream by

28
00:01:17,852 --> 00:01:20,758 
a stream because it's kind of a

29
00:01:20,764 --> 00:01:25,638 
dad joke, I guess. And I got to

30
00:01:25,644 --> 00:01:26,726 
clean this camera on this

31
00:01:26,748 --> 00:01:28,306 
laptop. It's a bit of a dad

32
00:01:28,338 --> 00:01:29,826 
joke. And tomorrow is Father's

33
00:01:29,858 --> 00:01:32,186 
Day, so I figured I would just

34
00:01:32,208 --> 00:01:33,562 
share that. A couple of things.

35
00:01:33,696 --> 00:01:34,970 
One, I want to thank everyone

36
00:01:35,040 --> 00:01:36,666 
for the positive feedback I got

37
00:01:36,768 --> 00:01:38,826 
on the latest edition of the

38
00:01:38,848 --> 00:01:41,646 
Frank Diggs Data newsletter. And

39
00:01:41,668 --> 00:01:43,466 
if you're not already subscribed

40
00:01:43,498 --> 00:01:46,366 
on LinkedIn, please do so. Thank

41
00:01:46,388 --> 00:01:47,280 
you for that.

42
00:01:50,450 --> 00:01:52,522 
Ray is a distributed computing

43
00:01:52,666 --> 00:01:56,146 
framework for basically AI and

44
00:01:56,168 --> 00:01:58,018 
ML workloads, more so than, I

45
00:01:58,024 --> 00:01:58,974 
think, data engineering

46
00:01:59,022 --> 00:02:00,834 
workloads. And it's one of those

47
00:02:00,872 --> 00:02:01,938 
things where it says it's going

48
00:02:01,944 --> 00:02:03,266 
to replace Spark. I think it

49
00:02:03,288 --> 00:02:07,814 
will. Will it do that in six

50
00:02:07,852 --> 00:02:11,526 
months? Six quarters? I think

51
00:02:11,548 --> 00:02:13,206 
that's the only thing that is

52
00:02:13,388 --> 00:02:17,000 
the big question. Obviously,

53
00:02:18,990 --> 00:02:20,826 
it's a new technology, and I

54
00:02:20,848 --> 00:02:22,646 
think that the fact that it's

55
00:02:22,678 --> 00:02:25,494 
based on python is a definite

56
00:02:25,542 --> 00:02:30,170 
plus. The fact that it can

57
00:02:30,240 --> 00:02:33,100 
really kind of free people from

58
00:02:33,790 --> 00:02:36,494 
Pi Spark. I know it says sounds

59
00:02:36,532 --> 00:02:37,646 
silly, right? Like free people

60
00:02:37,668 --> 00:02:39,134 
from Pi spark. Like it's this

61
00:02:39,172 --> 00:02:40,926 
horrible thing, but Pi Spark is

62
00:02:40,948 --> 00:02:42,090 
not proper python.

63
00:02:42,170 --> 00:02:43,198 
Yeah, I know there's been a lot

64
00:02:43,204 --> 00:02:44,674 
of work done bridging those two

65
00:02:44,712 --> 00:02:46,820 
worlds, but I also think that

66
00:02:47,190 --> 00:02:51,618 
the problem space that yeah, I

67
00:02:51,624 --> 00:02:53,314 
can't be here. Okay, cool. The

68
00:02:53,352 --> 00:02:54,626 
problem space that Spark was

69
00:02:54,648 --> 00:02:56,530 
meant to solve goes back about

70
00:02:56,600 --> 00:02:58,806 
ten, maybe 15 years at this

71
00:02:58,828 --> 00:03:00,102 
point. Same thing that happened

72
00:03:00,156 --> 00:03:01,986 
with Hadoop. The problem Hadoop

73
00:03:02,018 --> 00:03:03,974 
was meant to solve dates back to

74
00:03:04,012 --> 00:03:05,782 
the early 2000s. So these

75
00:03:05,836 --> 00:03:07,830 
technologies will either adapt

76
00:03:09,370 --> 00:03:10,586 
let me rephrase that the

77
00:03:10,608 --> 00:03:11,690 
technology products themselves.

78
00:03:11,760 --> 00:03:13,270 
These are open source projects.

79
00:03:13,350 --> 00:03:14,954 
Open source projects tend to do

80
00:03:14,992 --> 00:03:16,474 
best when they solve one

81
00:03:16,512 --> 00:03:18,106 
particular problem in a

82
00:03:18,128 --> 00:03:19,340 
particular way.

83
00:03:20,590 --> 00:03:22,378 
I know I'm going to get a lot of

84
00:03:22,384 --> 00:03:23,326 
hate mail on that, but

85
00:03:23,348 --> 00:03:24,558 
ultimately what I'm saying is

86
00:03:24,644 --> 00:03:26,910 
that let's focus on the problem

87
00:03:26,980 --> 00:03:28,462 
we're trying to solve, not

88
00:03:28,516 --> 00:03:30,106 
necessarily the tools that we're

89
00:03:30,138 --> 00:03:32,560 
using to solve them. And I think

90
00:03:32,930 --> 00:03:34,386 
Ray is definitely positioned to

91
00:03:34,408 --> 00:03:36,622 
be an excellent future facing

92
00:03:36,686 --> 00:03:40,174 
thing. Hey, my LinkedIn comment.

93
00:03:40,222 --> 00:03:41,700 
Hey, Boris. How's it going?

94
00:03:42,470 --> 00:03:43,854 
Let's see. Let me get the chat

95
00:03:43,902 --> 00:03:45,720 
overlay going. There we go.

96
00:03:47,930 --> 00:03:49,238 
Usually I don't stream from the

97
00:03:49,244 --> 00:03:49,586 
MacBook.

98
00:03:49,618 --> 00:03:52,918 
I'm on the MacBook now. It's a

99
00:03:52,924 --> 00:03:55,446 
MacBook M two, not an ultra. I

100
00:03:55,468 --> 00:03:58,454 
got this last fall to replace my

101
00:03:58,492 --> 00:04:01,242 
personal laptop because I am

102
00:04:01,296 --> 00:04:04,486 
falling out of love with Windows

103
00:04:04,678 --> 00:04:06,282 
because of Windows Eleven, but

104
00:04:06,336 --> 00:04:07,526 
that is something I've ranted

105
00:04:07,558 --> 00:04:08,758 
about on multiple live streams,

106
00:04:08,774 --> 00:04:10,300 
so I'm going to drop that there.

107
00:04:11,090 --> 00:04:13,214 
So as for me, I'm enjoying my

108
00:04:13,252 --> 00:04:16,526 
stream side streaming. I should

109
00:04:16,548 --> 00:04:19,742 
make that a thing, but

110
00:04:19,796 --> 00:04:21,966 
ultimately I think that check

111
00:04:21,988 --> 00:04:22,798 
out the article, let me know

112
00:04:22,804 --> 00:04:24,238 
what you think. What do you

113
00:04:24,244 --> 00:04:25,086 
think is going to be? I know

114
00:04:25,108 --> 00:04:26,974 
there's another technology. What

115
00:04:27,012 --> 00:04:28,146 
prompted me to write it was

116
00:04:28,168 --> 00:04:29,234 
actually a question that came up

117
00:04:29,272 --> 00:04:31,522 
at work the other day, and I had

118
00:04:31,576 --> 00:04:33,282 
seen something come across

119
00:04:33,336 --> 00:04:34,466 
either my Twitter feed or my

120
00:04:34,488 --> 00:04:35,462 
LinkedIn feed about another

121
00:04:35,516 --> 00:04:37,366 
framework that is claiming to be

122
00:04:37,388 --> 00:04:40,086 
like the next spark, right? The

123
00:04:40,108 --> 00:04:41,234 
next big data processing

124
00:04:41,282 --> 00:04:46,550 
framework. I still think Ray has

125
00:04:46,700 --> 00:04:49,658 
more on it, not the least of

126
00:04:49,664 --> 00:04:54,310 
which is the Python native

127
00:04:54,390 --> 00:04:55,030 
features.

128
00:04:55,110 --> 00:04:55,946 
And if you look at the work

129
00:04:55,968 --> 00:04:57,334 
that's being done to increase

130
00:04:57,382 --> 00:04:58,954 
speed in Python, whether that is

131
00:04:58,992 --> 00:04:59,686 
some of the latest

132
00:04:59,718 --> 00:05:02,438 
optimizations, or Mojo, which is

133
00:05:02,464 --> 00:05:05,694 
basically a kind of like

134
00:05:05,812 --> 00:05:07,326 
TypeScript what TypeScript did

135
00:05:07,348 --> 00:05:08,606 
for JavaScript, mojo is doing

136
00:05:08,628 --> 00:05:09,278 
that. So you're going to get a

137
00:05:09,284 --> 00:05:10,362 
lot more performance

138
00:05:10,426 --> 00:05:12,094 
enhancements depending on who

139
00:05:12,132 --> 00:05:13,726 
you talk to. The performance

140
00:05:13,758 --> 00:05:15,170 
enhancements are ten to twelve

141
00:05:15,240 --> 00:05:17,342 
X, or in some extreme cases,

142
00:05:17,406 --> 00:05:19,106 
thousands of times faster. I

143
00:05:19,128 --> 00:05:21,214 
think those are extreme cases,

144
00:05:21,262 --> 00:05:23,666 
but ten times optimization, ten

145
00:05:23,688 --> 00:05:25,298 
times speed improvement is going

146
00:05:25,304 --> 00:05:26,786 
to be a big deal, particularly

147
00:05:26,818 --> 00:05:28,546 
when you're dealing with neural

148
00:05:28,578 --> 00:05:30,086 
network learning and all the

149
00:05:30,108 --> 00:05:31,414 
computational power that goes

150
00:05:31,452 --> 00:05:34,790 
there. If you marry that to a

151
00:05:34,940 --> 00:05:36,754 
big data distributed processing

152
00:05:36,802 --> 00:05:38,706 
framework, well, then think

153
00:05:38,748 --> 00:05:41,626 
about what that open up. I just

154
00:05:41,648 --> 00:05:42,586 
noticed my hair is a little

155
00:05:42,608 --> 00:05:43,738 
wild. It's time for me to get a

156
00:05:43,744 --> 00:05:48,666 
haircut. So speaking of AI and

157
00:05:48,688 --> 00:05:50,634 
some AI goodness, I want folks

158
00:05:50,682 --> 00:05:53,034 
to know about this upcoming AI

159
00:05:53,082 --> 00:05:53,870 
webinar.

160
00:05:54,210 --> 00:05:57,086 
It's a joint webinar with Red

161
00:05:57,108 --> 00:05:59,038 
Hat and intel where we're going

162
00:05:59,044 --> 00:06:01,006 
to talk about AI application

163
00:06:01,108 --> 00:06:03,198 
benchmarking. I know one of the

164
00:06:03,204 --> 00:06:04,986 
speakers, she's awesome. I don't

165
00:06:05,018 --> 00:06:07,030 
know the other speaker, but it's

166
00:06:07,050 --> 00:06:08,014 
going to be a joint presentation

167
00:06:08,062 --> 00:06:10,466 
between Intel, Red Hat, and

168
00:06:10,488 --> 00:06:11,234 
we're going to talk about how

169
00:06:11,272 --> 00:06:12,798 
OpenVINO and Red Hat OpenShift.

170
00:06:12,814 --> 00:06:14,162 
Data science can be used

171
00:06:14,216 --> 00:06:15,702 
together to optimize your data

172
00:06:15,756 --> 00:06:18,726 
workflows. All right, I think I

173
00:06:18,748 --> 00:06:20,006 
have another comment. There we

174
00:06:20,028 --> 00:06:26,214 
go. Oh, that was me. I love web

175
00:06:26,252 --> 00:06:27,366 
based software because it's so

176
00:06:27,388 --> 00:06:27,814 
easy.

177
00:06:27,932 --> 00:06:29,734 
Browser based streaming software

178
00:06:29,782 --> 00:06:31,626 
or any software. The updates are

179
00:06:31,648 --> 00:06:33,706 
all automatic, so sometimes the

180
00:06:33,728 --> 00:06:35,046 
user interface, they've changed

181
00:06:35,078 --> 00:06:38,026 
that. So just want folks to be

182
00:06:38,048 --> 00:06:40,166 
aware of that upcoming webinar.

183
00:06:40,198 --> 00:06:42,606 
There's another webinar. I think

184
00:06:42,628 --> 00:06:43,806 
it's invite only that I'll be

185
00:06:43,828 --> 00:06:46,186 
doing next week. It's for IBM.

186
00:06:46,218 --> 00:06:48,558 
Watson X IBM partners only, I

187
00:06:48,564 --> 00:06:50,270 
think. And IBM employees.

188
00:06:51,170 --> 00:06:53,186 
I'll be speaking on that, on the

189
00:06:53,208 --> 00:06:54,846 
power of open source artificial

190
00:06:54,878 --> 00:06:56,338 
intelligence and how the

191
00:06:56,344 --> 00:06:57,634 
partnership between IBM and Red

192
00:06:57,672 --> 00:07:00,178 
Hat can really accelerate your

193
00:07:00,344 --> 00:07:03,490 
data endeavors. There's another

194
00:07:03,640 --> 00:07:05,838 
webinar going on that I do have,

195
00:07:05,864 --> 00:07:07,286 
the QR code, but it's not pre

196
00:07:07,308 --> 00:07:10,038 
loaded into the system. You have

197
00:07:10,044 --> 00:07:11,030 
to forgive me. I've been

198
00:07:11,100 --> 00:07:12,918 
traveling with the kids

199
00:07:13,084 --> 00:07:15,286 
business. Travel alone is a

200
00:07:15,308 --> 00:07:18,054 
challenge, but traveling with

201
00:07:18,092 --> 00:07:19,718 
the family now that they're out

202
00:07:19,724 --> 00:07:21,626 
of school adds an extra level of

203
00:07:21,648 --> 00:07:23,578 
fun. However, I do have the

204
00:07:23,584 --> 00:07:25,722 
privilege of having my extra

205
00:07:25,776 --> 00:07:27,286 
production assistant here. Let's

206
00:07:27,318 --> 00:07:29,178 
go and meet her. Hey, you want

207
00:07:29,184 --> 00:07:30,566 
to say hello? Are you camera

208
00:07:30,598 --> 00:07:32,650 
shy? You camera shy? Come on.

209
00:07:32,720 --> 00:07:34,986 
There you go. She's a Weimer on

210
00:07:35,008 --> 00:07:36,686 
her hi. I know, she's very

211
00:07:36,708 --> 00:07:39,422 
excitable. Yes, the link to the

212
00:07:39,476 --> 00:07:41,822 
meeting webinar. Let me post

213
00:07:41,876 --> 00:07:43,566 
that again. Thank you, Thomas.

214
00:07:43,678 --> 00:07:47,826 
Hope things are well. There we

215
00:07:47,848 --> 00:07:48,420 
go.

216
00:07:50,950 --> 00:07:52,706 
You can scan that QR code. Let

217
00:07:52,728 --> 00:07:57,622 
me hide that. Scan that QR code.

218
00:07:57,676 --> 00:08:00,118 
I'll post it in the comments. I

219
00:08:00,124 --> 00:08:01,606 
think I already did mention this

220
00:08:01,628 --> 00:08:03,800 
one in a previous LinkedIn post.

221
00:08:05,050 --> 00:08:06,406 
Restream has really got to up

222
00:08:06,428 --> 00:08:08,214 
their game because I don't think

223
00:08:08,252 --> 00:08:10,906 
you can type. Oh, wait, it looks

224
00:08:10,928 --> 00:08:13,014 
like you can. No, LinkedIn

225
00:08:13,062 --> 00:08:14,090 
comments are read only.

226
00:08:14,160 --> 00:08:21,434 
Still. Oh, well, what a problem

227
00:08:21,472 --> 00:08:22,286 
to have, though. I mean, I

228
00:08:22,308 --> 00:08:23,294 
remember when doing a live

229
00:08:23,332 --> 00:08:25,214 
stream required, like,

230
00:08:25,252 --> 00:08:27,214 
specialized hardware. Even

231
00:08:27,252 --> 00:08:28,270 
before that, it was even more

232
00:08:28,340 --> 00:08:30,560 
specialized hardware. When I was

233
00:08:30,930 --> 00:08:33,306 
doing live streams for the K

234
00:08:33,348 --> 00:08:35,586 
Street office, we had to get a

235
00:08:35,608 --> 00:08:38,642 
Tricaster, which is a $4,000

236
00:08:38,696 --> 00:08:40,366 
machine. And that was the cheap

237
00:08:40,398 --> 00:08:41,358 
one, right? That was the mini

238
00:08:41,374 --> 00:08:45,458 
one. But now I've done this on

239
00:08:45,464 --> 00:08:46,734 
my phone through a browser,

240
00:08:46,782 --> 00:08:47,686 
which is just absolutely

241
00:08:47,788 --> 00:08:48,918 
phenomenal. So for me to

242
00:08:48,924 --> 00:08:50,262 
complain and I can't send a text

243
00:08:50,316 --> 00:08:52,854 
message to LinkedIn from here is

244
00:08:52,892 --> 00:08:54,342 
kind of funny, right? It's about

245
00:08:54,396 --> 00:08:57,190 
the psychology of human

246
00:08:57,260 --> 00:08:58,210 
expectations.

247
00:08:58,370 --> 00:09:00,266 
But seriously, Restream is an

248
00:09:00,288 --> 00:09:01,558 
awesome platform. If they added

249
00:09:01,574 --> 00:09:02,442 
that, it would be the perfect

250
00:09:02,496 --> 00:09:04,646 
platform. So with that, I'm

251
00:09:04,678 --> 00:09:06,822 
going to thank you, Thomas.

252
00:09:06,886 --> 00:09:09,706 
Thank you, Boris, for

253
00:09:09,728 --> 00:09:10,934 
commenting. I really appreciate

254
00:09:10,982 --> 00:09:13,726 
it. I'll leave that QR code up

255
00:09:13,748 --> 00:09:15,006 
there for another minute, but

256
00:09:15,028 --> 00:09:16,878 
let me know what you think. Do

257
00:09:16,884 --> 00:09:17,774 
you think I should put more

258
00:09:17,812 --> 00:09:21,146 
content up on my LinkedIn

259
00:09:21,178 --> 00:09:23,482 
newsletter? I do have a sizable

260
00:09:23,546 --> 00:09:25,038 
subscription there. I am going

261
00:09:25,044 --> 00:09:26,482 
to work on building my own email

262
00:09:26,536 --> 00:09:27,838 
list because I just think that's

263
00:09:27,854 --> 00:09:29,140 
just a good thing to do.

264
00:09:30,790 --> 00:09:32,514 
Anyone has advice on what

265
00:09:32,552 --> 00:09:34,098 
platform to use, please let me

266
00:09:34,104 --> 00:09:35,442 
know in the comments below.

267
00:09:35,576 --> 00:09:36,566 
Definitely looking for some

268
00:09:36,588 --> 00:09:39,558 
advice on that. And there'll be

269
00:09:39,564 --> 00:09:40,994 
a new episode of Data Driven

270
00:09:41,042 --> 00:09:43,634 
coming out. Now that my oldest

271
00:09:43,682 --> 00:09:46,166 
son is out of school for the

272
00:09:46,188 --> 00:09:47,926 
year, I'm going to make it a

273
00:09:47,948 --> 00:09:49,250 
summer job for him to learn how

274
00:09:49,260 --> 00:09:51,098 
to edit podcasts. Figured it'd

275
00:09:51,104 --> 00:09:53,180 
be a good skill for him to have,

276
00:09:55,150 --> 00:09:56,378 
so hopefully I can get the

277
00:09:56,384 --> 00:09:57,674 
backlog. We have a lot of great

278
00:09:57,712 --> 00:09:59,878 
shows. Seriously. I know you're

279
00:09:59,894 --> 00:10:01,162 
thinking I would say that, but

280
00:10:01,216 --> 00:10:02,686 
Andy and I shout out to you,

281
00:10:02,708 --> 00:10:03,902 
andy brother from another

282
00:10:03,956 --> 00:10:04,670 
mother.

283
00:10:07,010 --> 00:10:08,478 
We've been just impressed with

284
00:10:08,484 --> 00:10:09,978 
the quality of guests that we've

285
00:10:09,994 --> 00:10:11,662 
spoken to. We've had some really

286
00:10:11,716 --> 00:10:14,574 
smart people. Some one famous

287
00:10:14,622 --> 00:10:17,186 
person, actually. One famous on

288
00:10:17,208 --> 00:10:18,580 
the Internet person, anyway,

289
00:10:19,190 --> 00:10:20,862 
who's not in the database.

290
00:10:20,926 --> 00:10:22,158 
Actually. She's an entrepreneur.

291
00:10:22,254 --> 00:10:25,330 
Awesome. Lauren Tickner.

292
00:10:26,070 --> 00:10:27,670 
She's cool. I've admired her

293
00:10:27,740 --> 00:10:29,238 
work for a while. She's very

294
00:10:29,324 --> 00:10:31,142 
kind of no nonsense, kind of a

295
00:10:31,196 --> 00:10:33,302 
cool straight shooter. Very

296
00:10:33,356 --> 00:10:36,454 
funny. Very smart, too, in terms

297
00:10:36,492 --> 00:10:38,134 
of how she's built her brand and

298
00:10:38,172 --> 00:10:42,166 
her business. I like this

299
00:10:42,188 --> 00:10:43,178 
street. I mean, it's not the

300
00:10:43,184 --> 00:10:44,474 
Burj Khalifa that I'm looking

301
00:10:44,512 --> 00:10:47,306 
at, but we all do what we can

302
00:10:47,328 --> 00:10:51,126 
with what we have. Who knows,

303
00:10:51,238 --> 00:10:52,442 
maybe your future livestream

304
00:10:52,506 --> 00:10:53,486 
will be over there.

305
00:10:53,588 --> 00:10:54,926 
But in all seriousness, check

306
00:10:54,948 --> 00:10:56,126 
out this webinar. I think this

307
00:10:56,148 --> 00:10:58,526 
is a very exciting time to be in

308
00:10:58,548 --> 00:11:03,386 
artificial intelligence. It's

309
00:11:03,418 --> 00:11:04,562 
definitely an inflection point.

310
00:11:04,616 --> 00:11:08,354 
I think Chat GPT has really put

311
00:11:08,392 --> 00:11:09,714 
gasoline on something that was

312
00:11:09,752 --> 00:11:12,002 
already pretty well lit. And

313
00:11:12,056 --> 00:11:14,098 
it's funny because 18 months ago

314
00:11:14,184 --> 00:11:15,346 
I was saying that there was

315
00:11:15,368 --> 00:11:17,878 
going to be an AI in the

316
00:11:17,884 --> 00:11:19,078 
LinkedIn profile where I talk

317
00:11:19,084 --> 00:11:20,418 
about how only quantum computing

318
00:11:20,434 --> 00:11:22,470 
can save us from AI winter.

319
00:11:23,930 --> 00:11:25,670 
Obviously, I was proven wrong.

320
00:11:25,820 --> 00:11:26,806 
There's been a lot of

321
00:11:26,828 --> 00:11:30,678 
innovation. I did not expect

322
00:11:30,764 --> 00:11:33,930 
Chat GPT to come in 2022.

323
00:11:34,080 --> 00:11:35,930 
That was a type of technology

324
00:11:36,080 --> 00:11:38,330 
and thing that I would have

325
00:11:38,400 --> 00:11:39,754 
anticipated towards the middle

326
00:11:39,792 --> 00:11:40,986 
of the decade. I knew it was

327
00:11:41,008 --> 00:11:41,966 
coming, I just didn't think it

328
00:11:41,968 --> 00:11:43,642 
would be coming this fast. So

329
00:11:43,696 --> 00:11:44,790 
just goes to show you, even if

330
00:11:44,800 --> 00:11:45,742 
you're an expert in the field,

331
00:11:45,796 --> 00:11:48,014 
even if you're in this, this has

332
00:11:48,052 --> 00:11:49,406 
surprised a lot of people, and

333
00:11:49,428 --> 00:11:51,098 
obviously there's a lot of drama

334
00:11:51,114 --> 00:11:57,086 
around Chat GPT. Some people

335
00:11:57,188 --> 00:11:59,266 
kind of dismiss it as, well, the

336
00:11:59,288 --> 00:12:01,202 
latest fad, or it doesn't do

337
00:12:01,256 --> 00:12:03,330 
anything more than your phone

338
00:12:03,400 --> 00:12:06,386 
does when you do the predictive

339
00:12:06,418 --> 00:12:08,914 
text. And while that's

340
00:12:08,962 --> 00:12:11,926 
technically true, right, that is

341
00:12:11,948 --> 00:12:14,326 
the equivalent of comparing a

342
00:12:14,348 --> 00:12:17,526 
paper airplane with, I don't

343
00:12:17,548 --> 00:12:19,834 
know, an Airbus A 380, or a

344
00:12:19,872 --> 00:12:24,154 
Boeing Triple Seven, or an F 35

345
00:12:24,192 --> 00:12:25,546 
fighter. Whatever represents the

346
00:12:25,568 --> 00:12:27,914 
state of the art for you in

347
00:12:27,952 --> 00:12:31,194 
aviation. It's technically true

348
00:12:31,312 --> 00:12:33,438 
because they are based on the

349
00:12:33,444 --> 00:12:35,086 
same type of principles, right?

350
00:12:35,188 --> 00:12:37,726 
Air, lift, thrust, drag, all

351
00:12:37,748 --> 00:12:39,662 
that sort of thing, gravity. But

352
00:12:39,716 --> 00:12:41,534 
they are very different in terms

353
00:12:41,572 --> 00:12:42,994 
of their implementation and

354
00:12:43,032 --> 00:12:46,338 
skill and the amount of just

355
00:12:46,504 --> 00:12:47,682 
technology in it, right.

356
00:12:47,736 --> 00:12:49,038 
The amount of maturity. That's

357
00:12:49,054 --> 00:12:49,874 
probably the word I was looking

358
00:12:49,912 --> 00:12:53,746 
for. Fortunately, I need more

359
00:12:53,768 --> 00:12:54,498 
coffee, basically.

360
00:12:54,584 --> 00:12:56,002 
Unfortunately, this airbnb

361
00:12:56,066 --> 00:12:57,154 
actually has a nice curry

362
00:12:57,202 --> 00:12:58,998 
machine. I know there are a lot

363
00:12:59,004 --> 00:13:00,760 
of curry haters out there, but

364
00:13:01,610 --> 00:13:03,542 
you can't beat push button

365
00:13:03,596 --> 00:13:06,834 
coffee. Do you sacrifice

366
00:13:06,882 --> 00:13:08,598 
quality? Yeah, I guess you do.

367
00:13:08,764 --> 00:13:11,226 
But let's be real, if I make it

368
00:13:11,248 --> 00:13:12,506 
from a drip cup, it's not going

369
00:13:12,528 --> 00:13:15,020 
to be impeccable quality either.

370
00:13:17,150 --> 00:13:18,906 
I'll save the coffee shops and

371
00:13:18,928 --> 00:13:20,206 
the baristas to make the really

372
00:13:20,228 --> 00:13:22,766 
good coffee, but for me, just

373
00:13:22,788 --> 00:13:25,434 
the average kind of day, I'm

374
00:13:25,482 --> 00:13:29,630 
cool with getting the curry cup.

375
00:13:30,050 --> 00:13:31,662 
So with that, I will definitely

376
00:13:31,716 --> 00:13:32,686 
encourage you. Check out that

377
00:13:32,708 --> 00:13:35,682 
webinar. Great speakers, great

378
00:13:35,736 --> 00:13:37,522 
technology. And this is really

379
00:13:37,576 --> 00:13:39,538 
the time for AI to shine. And if

380
00:13:39,544 --> 00:13:40,462 
you look at all the ethical

381
00:13:40,526 --> 00:13:42,014 
concerns in artificial

382
00:13:42,062 --> 00:13:43,586 
intelligence in all of this

383
00:13:43,608 --> 00:13:48,614 
stuff happening, open source is

384
00:13:48,652 --> 00:13:50,486 
now more important than ever in

385
00:13:50,508 --> 00:13:53,270 
terms of transparency, in terms

386
00:13:53,340 --> 00:13:56,242 
of sharing innovation, sharing

387
00:13:56,306 --> 00:13:57,758 
risks, right? Understanding

388
00:13:57,794 --> 00:13:59,722 
these risks to society, that

389
00:13:59,776 --> 00:14:02,700 
open source mentality, right?

390
00:14:03,310 --> 00:14:05,082 
That sounds bad, but that open

391
00:14:05,136 --> 00:14:06,874 
source mindset, that's a better

392
00:14:06,912 --> 00:14:10,154 
word is needed now more than

393
00:14:10,192 --> 00:14:11,738 
ever, because this technology is

394
00:14:11,744 --> 00:14:12,634 
going to affect each and every

395
00:14:12,672 --> 00:14:14,126 
one of us, right? Obviously, for

396
00:14:14,148 --> 00:14:15,498 
those in the industry, it's

397
00:14:15,514 --> 00:14:17,006 
going to affect us first. But if

398
00:14:17,028 --> 00:14:17,998 
you look at what Google is

399
00:14:18,004 --> 00:14:19,630 
doing, I think when Wendy's

400
00:14:20,690 --> 00:14:23,454 
replacing the drive through,

401
00:14:23,492 --> 00:14:24,558 
when you make the order, it's

402
00:14:24,574 --> 00:14:25,778 
going to do that through Google.

403
00:14:25,864 --> 00:14:27,262 
This is going to impact

404
00:14:27,326 --> 00:14:29,266 
everybody, right? From kind of

405
00:14:29,368 --> 00:14:32,722 
entry level jobs to even middle

406
00:14:32,776 --> 00:14:35,538 
layer, white collar jobs. This

407
00:14:35,544 --> 00:14:36,494 
is going to have a profound

408
00:14:36,542 --> 00:14:37,454 
economic impact.

409
00:14:37,502 --> 00:14:38,998 
Now, will it be barred? Will it

410
00:14:39,004 --> 00:14:41,330 
be chat? GBT? Will it be OpenAI?

411
00:14:41,490 --> 00:14:44,434 
Who knows? But the fact is, it's

412
00:14:44,482 --> 00:14:46,278 
here. It's now. A lot of

413
00:14:46,284 --> 00:14:47,046 
governments are trying to

414
00:14:47,068 --> 00:14:50,058 
regulate it. Good luck. The

415
00:14:50,064 --> 00:14:52,058 
cat's out of the bag. It's here.

416
00:14:52,144 --> 00:14:53,978 
And the best way to approach it

417
00:14:54,064 --> 00:14:57,574 
is through a community minded

418
00:14:57,622 --> 00:14:59,722 
approach that's similar to open

419
00:14:59,776 --> 00:15:02,558 
source software. That mindset of

420
00:15:02,644 --> 00:15:03,806 
let's be open, let's be

421
00:15:03,828 --> 00:15:05,146 
transparent about what we're

422
00:15:05,178 --> 00:15:06,800 
building, how we're building it,

423
00:15:08,050 --> 00:15:13,294 
and make sure that we run the

424
00:15:13,332 --> 00:15:15,054 
technology and the technology

425
00:15:15,172 --> 00:15:16,098 
doesn't run us.

426
00:15:16,184 --> 00:15:18,034 
So with that, I will end this

427
00:15:18,072 --> 00:15:20,354 
live stream by a stream. And

428
00:15:20,392 --> 00:15:21,506 
this kind of stream of

429
00:15:21,528 --> 00:15:22,546 
consciousness thing was good

430
00:15:22,568 --> 00:15:23,826 
enough. I might actually make

431
00:15:23,848 --> 00:15:25,442 
this a podcast episode as well.

432
00:15:25,496 --> 00:15:26,758 
So if you are listening to the

433
00:15:26,764 --> 00:15:29,286 
audio of that, just imagine a

434
00:15:29,308 --> 00:15:32,246 
peaceful, tranquil stream in the

435
00:15:32,268 --> 00:15:34,406 
middle of the country with a

436
00:15:34,428 --> 00:15:36,786 
beautiful fire pit and a quaint

437
00:15:36,818 --> 00:15:38,214 
little lodge type thing going

438
00:15:38,252 --> 00:15:39,686 
on. That's where I am. I should

439
00:15:39,708 --> 00:15:40,918 
have painted that picture early,

440
00:15:41,004 --> 00:15:42,406 
but maybe I'll Bailey. Do that

441
00:15:42,428 --> 00:15:43,798 
for me. So with that, I'm going

442
00:15:43,804 --> 00:15:44,690 
to end the stream.

443
00:15:44,770 --> 00:15:46,038 
And if you're wondering who the

444
00:15:46,044 --> 00:15:47,798 
heck is Bailey, bailey is the

445
00:15:47,804 --> 00:15:49,078 
artificial intelligence that we

446
00:15:49,084 --> 00:15:50,640 
have helped run the show. Go,

447
00:15:51,170 --> 00:15:52,458 
that does a lot of the intros

448
00:15:52,474 --> 00:15:54,234 
and the outros for data driven

449
00:15:54,282 --> 00:15:56,606 
and impact quantum. Speaking of

450
00:15:56,628 --> 00:15:58,334 
impact quantum, season three is

451
00:15:58,372 --> 00:16:00,606 
in the works, I promise. So with

452
00:16:00,628 --> 00:16:02,014 
that, I'll end the stream and

453
00:16:02,052 --> 00:16:03,694 
you have a great day. And I

454
00:16:03,732 --> 00:16:04,846 
probably won't stream on

455
00:16:04,868 --> 00:16:06,206 
Father's Day, so if you

456
00:16:06,228 --> 00:16:07,438 
celebrate Father's Day, have an

457
00:16:07,444 --> 00:16:10,174 
awesome one and enjoy the rest

458
00:16:10,212 --> 00:16:12,300 
of your day. You do have.