WEBVTT 1 00:00:00.160 --> 00:00:03.040 If you like this episode, just like, share and follow 2 00:00:03.080 --> 00:00:06.879 this podcast. Thank you, Back to the show, Welcome. 3 00:00:06.559 --> 00:00:10.000 To the Xai All Hands. We've been a very exciting 4 00:00:10.080 --> 00:00:10.880 presentation for you. 5 00:00:11.279 --> 00:00:14.480 We're going to start off by recapping the incredible progress 6 00:00:14.519 --> 00:00:17.120 that the Xai team has made in just two and 7 00:00:17.120 --> 00:00:20.800 a half years. It's really remarkable in pursuit of our 8 00:00:20.839 --> 00:00:22.920 goal of understanding the universe. So, just going of our 9 00:00:23.320 --> 00:00:27.440 accomplishments since inception, it's important for bear in mind that 10 00:00:28.120 --> 00:00:30.320 XI is only two and a half years old, basically 11 00:00:30.359 --> 00:00:34.280 a toddler, and we've nonetheless achieved an incredible amount in 12 00:00:34.320 --> 00:00:37.000 a very short period of time. So our competitors are 13 00:00:38.000 --> 00:00:42.679 five ten, some cases twenty years old, they have much 14 00:00:42.759 --> 00:00:45.679 larger teams they started off with for more resources, and 15 00:00:45.719 --> 00:00:49.399 yet nonetheless we have achieved number one in many arenas 16 00:00:50.159 --> 00:00:54.159 in just a few years. So we've achieved number one 17 00:00:54.240 --> 00:00:57.560 in voice, in image and video generation. I think we 18 00:00:57.719 --> 00:01:00.719 now at this point are actually generating more images and 19 00:01:00.840 --> 00:01:03.679 video based on the last numbers I saw then all 20 00:01:03.679 --> 00:01:08.680 of our competitors combined, we are winning in terms of forecasting, 21 00:01:08.920 --> 00:01:11.400 which is one of the key metrics of intelligence. So 22 00:01:11.680 --> 00:01:15.040 up the grock four to twenty forecasting model beat all 23 00:01:15.040 --> 00:01:19.359 the other AIS and forecasting, and we've talked many leaderboards. 24 00:01:19.680 --> 00:01:24.879 We've got now a great app with the Imagine, with 25 00:01:25.000 --> 00:01:28.319 the core Rock, we've made radical improvements to the x app, 26 00:01:28.560 --> 00:01:31.760 and we've launched a Grokipedia which is on its way 27 00:01:31.840 --> 00:01:36.560 too far exceeding Wikipedia and ultimately be Audersmatitude are more 28 00:01:36.560 --> 00:01:39.879 comprehensive and more accurate and have more information as well 29 00:01:40.120 --> 00:01:45.239 as video and image data that simply isn't there on Wikipedia. 30 00:01:45.359 --> 00:01:49.159 So it's it's intended ultimately to be Encyclopedia Galactica, a 31 00:01:49.239 --> 00:01:55.480 distallation of all knowledge, of all knowledge. And we're the 32 00:01:55.480 --> 00:01:59.280 first to achieve one hundred thousand, h one hundred GPU 33 00:01:59.359 --> 00:02:03.040 training clusters, and we're now about to achieve the first 34 00:02:03.120 --> 00:02:06.159 one hundred I should say, one million, h one hundred 35 00:02:06.280 --> 00:02:10.759 GPU equivalents in training. So really an incredible amount of 36 00:02:10.840 --> 00:02:13.319 work in a very short period of time. And it's 37 00:02:13.319 --> 00:02:17.479 important to consider for competitiveness of any technology company. 38 00:02:17.680 --> 00:02:20.240 What matters. It's not the position at any point in time, but. 39 00:02:20.199 --> 00:02:23.639 What is your velocity and acceleration And if you're moving 40 00:02:23.680 --> 00:02:27.360 faster than anyone else in any given technology arena, you 41 00:02:27.400 --> 00:02:30.039 will be the leader, and Xai is moving faster than 42 00:02:30.080 --> 00:02:30.840 any other company. 43 00:02:30.960 --> 00:02:33.120 No one's even close. So let's go to our team. 44 00:02:34.039 --> 00:02:37.120 As we grow as a company, a natural thing that 45 00:02:37.199 --> 00:02:40.719 happens is you reorganize the company as it scales up. 46 00:02:40.840 --> 00:02:42.639 So when you first have a startup, you. 47 00:02:42.639 --> 00:02:45.560 Might have just a few dozen people and they'll just 48 00:02:45.639 --> 00:02:48.759 chat amongs themselves. As you grow to several hundred people, 49 00:02:49.000 --> 00:02:51.800 you have to then add more structure, just like an 50 00:02:51.840 --> 00:02:54.240 organism that grows from a single like we all just 51 00:02:54.319 --> 00:02:56.840 grow from a single cell and then to a blob 52 00:02:56.879 --> 00:03:00.400 of sales. Then you get organ differentiation limbs, you grow 53 00:03:00.400 --> 00:03:04.319 a tail, hopefully the ptail disappears, and then you become 54 00:03:04.360 --> 00:03:07.400 a baby. You go through these stages, and so we're 55 00:03:07.719 --> 00:03:09.639 uh organizing because. 56 00:03:09.439 --> 00:03:11.080 We've we've reached a certain scale. 57 00:03:11.080 --> 00:03:14.199 We're organizing the company h to be more effective at 58 00:03:14.199 --> 00:03:17.599 this scale. And naturally, when when this happens, that there's 59 00:03:17.639 --> 00:03:20.400 some people who are better suited for the early stages 60 00:03:20.439 --> 00:03:23.360 of the company and and less suited for the later stages. 61 00:03:23.680 --> 00:03:27.639 And so uh and for the people that have departed, 62 00:03:27.680 --> 00:03:29.759 I'd just like to say thank you for a contribution, 63 00:03:30.280 --> 00:03:32.400 thank you for getting us this far. And we wish 64 00:03:32.479 --> 00:03:34.759 you very well in your future endeavors. So now going 65 00:03:34.800 --> 00:03:37.879 on to h the new structure of the company. Uh, 66 00:03:38.080 --> 00:03:42.759 the companies organized in four main application areas. There's there's 67 00:03:42.840 --> 00:03:45.560 Grock Main in voice, which is really the main Grock 68 00:03:45.599 --> 00:03:48.439 model as much as called Grock Main. Then there's a 69 00:03:48.680 --> 00:03:52.039 coding specific model. There's an image and video model which 70 00:03:52.080 --> 00:03:55.080 is Imagine, and then Macrohard which is intended to do 71 00:03:55.400 --> 00:03:58.960 full digital emulation of entire companies. And then we've got 72 00:03:59.560 --> 00:04:02.080 the Impress ructural ayers. So I'd like to invite members 73 00:04:02.120 --> 00:04:03.560 of the teams come up and talk about each of 74 00:04:03.599 --> 00:04:04.479 their areas. 75 00:04:09.080 --> 00:04:10.080 Hip. Thanks you long. 76 00:04:10.319 --> 00:04:13.240 So Grock, Maine and Boys are going to be merged 77 00:04:13.280 --> 00:04:16.279 into one team. And you know on Boys when anecdote 78 00:04:16.319 --> 00:04:19.040 is September twenty twenty four opening, I had this product 79 00:04:19.079 --> 00:04:21.360 you could talk to advanced voice mode, and we had nothing, 80 00:04:21.439 --> 00:04:23.519 no model, of course, in no product. 81 00:04:24.040 --> 00:04:25.480 We started much after. 82 00:04:25.279 --> 00:04:27.560 That and in a span of few months, six months, 83 00:04:27.639 --> 00:04:30.079 we developed the model in house from scratch without a 84 00:04:30.120 --> 00:04:32.439 bunch of people who knew audio, and had a product 85 00:04:32.600 --> 00:04:35.199 that was surpassing open air. And six months fast forward 86 00:04:35.240 --> 00:04:37.959 six more months and now we have Grock in more 87 00:04:37.959 --> 00:04:40.279 than two billion test las. We have a Rock Voice 88 00:04:40.319 --> 00:04:42.800 Agent API. You can do all kinds of amazing things. 89 00:04:43.040 --> 00:04:44.839 In a span of one year, we went from nothing 90 00:04:45.000 --> 00:04:47.240 to being leaders. That kind of stuff is only possible 91 00:04:47.279 --> 00:04:49.759 in a place like XCI. We have small teams, committed 92 00:04:49.800 --> 00:04:53.000 mission focus, lots of compute, and we really really want 93 00:04:53.079 --> 00:04:55.920 to keep pushing same story on the chat models. You know, 94 00:04:55.920 --> 00:04:59.040 we've always been at the forefront of reasoning, starting from 95 00:04:59.079 --> 00:05:01.600 Rock one point five two Doc three, and we want 96 00:05:01.639 --> 00:05:04.360 to really move to a world where it's no longer 97 00:05:04.360 --> 00:05:06.959 about this question answering. We want to build and everything 98 00:05:07.040 --> 00:05:08.560 up so you should be able to come to it 99 00:05:08.759 --> 00:05:10.920 and really get done whatever you want. You know, ask 100 00:05:10.959 --> 00:05:13.920 a leave question, make a slide deck, or you know, 101 00:05:14.240 --> 00:05:15.800 solid pizzle stuff like that. 102 00:05:15.920 --> 00:05:18.079 Yeah, So I really think on the product side, we're 103 00:05:18.120 --> 00:05:20.720 really going to see a huge transformation happening in a 104 00:05:20.800 --> 00:05:21.959 very short period of time. 105 00:05:22.800 --> 00:05:23.920 We're going to see work. 106 00:05:24.199 --> 00:05:27.439 The magnitude of amount of work that all knowledge workers 107 00:05:27.519 --> 00:05:30.199 are going to be able to produce increase tenfold in 108 00:05:30.240 --> 00:05:33.160 the next short period of a few months. The models 109 00:05:33.160 --> 00:05:36.360 that we are building out are incredibly amazing, and we 110 00:05:36.480 --> 00:05:38.319 have a lot on the way and we're really excited 111 00:05:38.319 --> 00:05:41.360 to share that with you all. And on a product side, 112 00:05:41.399 --> 00:05:43.759 the goal is to just build that portal that allows 113 00:05:43.839 --> 00:05:46.079 you to accomplish all of your work and how do 114 00:05:46.120 --> 00:05:49.199 we amplify everyone to achieve much much more than what 115 00:05:49.240 --> 00:05:51.800 they can accomplish alone. And we're building that out and 116 00:05:51.800 --> 00:05:54.040 it's going to be an incredibly easy. 117 00:05:53.759 --> 00:05:55.959 To use experience that just works seamlessly. 118 00:05:56.199 --> 00:05:56.360 Too. 119 00:05:57.000 --> 00:05:59.639 Being said, we are hiring and we're looking for intelligent 120 00:05:59.680 --> 00:06:00.399 and smart people. 121 00:06:00.439 --> 00:06:02.439 This is not an easy place to work guys like 122 00:06:02.519 --> 00:06:02.879 this is. 123 00:06:03.240 --> 00:06:07.319 It's a grind, but we have I guess like intersellar ambitions, 124 00:06:07.360 --> 00:06:09.519 so it's it's not going to be easy, right. So 125 00:06:10.000 --> 00:06:13.240 I will say, having come to x Ai, uh, it 126 00:06:13.319 --> 00:06:15.959 has been an opportunity for lifetime to work among really 127 00:06:16.000 --> 00:06:19.600 smart and really passionate people. The vibes here are amazing 128 00:06:19.879 --> 00:06:22.040 and it's truly an environment where if you're a smart 129 00:06:22.079 --> 00:06:24.279 person you want to get shipped done, you can get 130 00:06:24.240 --> 00:06:28.120 shipped done. There isn't like organizational overhead getting your way 131 00:06:28.240 --> 00:06:30.399 or kind of I don't know, like having to write 132 00:06:30.480 --> 00:06:32.879 docs and all this kind of stuff. You just do stuff, 133 00:06:32.920 --> 00:06:34.959 at least at least for me, I just you know, 134 00:06:35.120 --> 00:06:37.519 just you can do things here and that's amazing, and 135 00:06:37.720 --> 00:06:39.560 I invite more people to come here and just do 136 00:06:39.600 --> 00:06:40.519 it awesome things. 137 00:06:40.720 --> 00:06:44.040 Yeah, So with with the grockmin the sort of main 138 00:06:44.560 --> 00:06:48.040 foundation model, the intent is that it's it's genuinely useful 139 00:06:48.160 --> 00:06:49.480 in a wide range of areas. 140 00:06:49.600 --> 00:06:53.560 So if you're doing engineering or law or tit or. 141 00:06:53.519 --> 00:06:57.600 Medicine, any anything, it is useful to you in your 142 00:06:57.920 --> 00:07:02.439 in your job. That's essential to understand the universe and 143 00:07:03.000 --> 00:07:06.199 make things as useful as possible, like when God gives 144 00:07:06.199 --> 00:07:07.120 you an answer that you can. 145 00:07:07.000 --> 00:07:09.680 Count it right, all right, thank you, Thanks. 146 00:07:14.360 --> 00:07:15.399 Everybody. I'm Macro. 147 00:07:15.800 --> 00:07:18.639 So the world changed a lot recently in terms of coding, 148 00:07:19.639 --> 00:07:22.319 the coding models. I was always complaining people are trying 149 00:07:22.319 --> 00:07:24.000 to convince me to use a coding model, and I 150 00:07:24.040 --> 00:07:26.959 was like trusting it, and I wasn't really convinced. But 151 00:07:27.240 --> 00:07:31.720 as of recently, the models they actually produce good, decent 152 00:07:31.800 --> 00:07:34.240 quality code. I mean, you still need to review and 153 00:07:34.240 --> 00:07:37.759 give feedback, but you can. It's easy to see how 154 00:07:37.759 --> 00:07:40.120 they can accelerate you quite a lot. So it's not 155 00:07:40.160 --> 00:07:43.879 only about coding. It's like they understand your intuition like 156 00:07:44.160 --> 00:07:47.079 much better than before. Like now when you are. When 157 00:07:47.079 --> 00:07:50.000 I describe a problem, I only have to phrase it 158 00:07:50.079 --> 00:07:52.240 like I would to another colleague engineer who has already 159 00:07:52.240 --> 00:07:54.399 seen the code base. That's a huge change before you 160 00:07:54.519 --> 00:07:56.759 kind of need to handhold a toddler to make a change, 161 00:07:56.839 --> 00:07:59.680 and they don't only write your code, but they also 162 00:07:59.680 --> 00:08:00.839 can bugio code. 163 00:08:00.920 --> 00:08:03.160 So now we have I do like what we. 164 00:08:03.079 --> 00:08:06.959 Do, like hours of grog code running continuously to make 165 00:08:07.000 --> 00:08:11.879 sure that a more complex changed the training system actually 166 00:08:11.959 --> 00:08:14.120 works in production. So it's easy to see for us 167 00:08:14.360 --> 00:08:17.879 that this is not only about accelerating us ourselves writing 168 00:08:18.000 --> 00:08:20.480 code and making us ten x more productive, but we're 169 00:08:20.519 --> 00:08:24.439 really on this path for recursive self improvement where the 170 00:08:24.519 --> 00:08:27.680 current generation of grock code is training the next generation 171 00:08:27.720 --> 00:08:30.519 of Crock code. And we see that this path and 172 00:08:30.560 --> 00:08:33.639 on exponential takeoff here this path will continue. So we 173 00:08:33.679 --> 00:08:36.039 are doubling down on coding and making coding one of 174 00:08:36.039 --> 00:08:38.200 the highest party efforts in the company. So if you're 175 00:08:38.240 --> 00:08:41.600 out there and you're excited about coding, and you're inner 176 00:08:41.759 --> 00:08:44.600 either very good at training modeling, or you're a really 177 00:08:44.639 --> 00:08:48.440 good low level software engineer interesting in systems design, this 178 00:08:48.679 --> 00:08:51.320 is the place to work. Like we have a million 179 00:08:52.000 --> 00:08:55.240 h one hundred equivalents to train the best coding medal 180 00:08:55.279 --> 00:08:56.000 in the world right. 181 00:08:55.840 --> 00:08:57.679 Now, so please join us. 182 00:08:58.080 --> 00:09:01.440 Yeah, I'm going on a compare with Macro on coding, 183 00:09:01.639 --> 00:09:03.799 so it'll become one and more obvious to us, like 184 00:09:03.840 --> 00:09:05.840 you know, over time, like we are on the past 185 00:09:05.960 --> 00:09:08.879 to singularity at least on coding. So we decided, like 186 00:09:08.879 --> 00:09:10.919 you know, have our best engineer in the company in 187 00:09:11.000 --> 00:09:13.679 Macro to lead the coding, and we are building the 188 00:09:13.679 --> 00:09:16.559 best coding model for everyone to empower everyone to build 189 00:09:16.879 --> 00:09:19.919 and for me, like the man like limiting factor is 190 00:09:19.960 --> 00:09:23.159 probably computer and energy where they can run the best 191 00:09:23.200 --> 00:09:26.840 model to support everyone, to empower everyone and respects. 192 00:09:26.960 --> 00:09:29.279 Now we are one keeam and we will win on 193 00:09:29.320 --> 00:09:30.720 the compute and we are. 194 00:09:30.679 --> 00:09:34.759 Wing with space compute and also like for every engineer 195 00:09:34.919 --> 00:09:37.600 right so, if you're like writing kernel, if you're writing 196 00:09:37.559 --> 00:09:40.080 a compiler, to think about like whether is still all 197 00:09:40.120 --> 00:09:41.879 worth it, maybe you should join us, you know, for 198 00:09:41.960 --> 00:09:44.759 coding effort to automate yourself alt the like, to speed 199 00:09:44.759 --> 00:09:45.519 it ourselves up. 200 00:09:46.200 --> 00:09:48.200 Yeah, I think it's like really a million. 201 00:09:48.039 --> 00:09:51.639 Year basically with the year to be alive, and I 202 00:09:51.639 --> 00:09:53.879 can already feel the AGI, feel the hi at least 203 00:09:53.919 --> 00:09:54.360 for coding. 204 00:09:54.600 --> 00:09:57.720 Yeah, yeah, I think actually things will move, maybe even 205 00:09:57.840 --> 00:10:00.600 by the end of this year, to where you don't 206 00:10:00.639 --> 00:10:04.159 even bother do during coding. The AI just creates the 207 00:10:04.200 --> 00:10:07.080 binary directly, and the AI can create a much more 208 00:10:07.080 --> 00:10:11.360 efficient binary than can be done by any compiler. So 209 00:10:11.639 --> 00:10:14.679 just say create optimized binary for this particular outcome, and 210 00:10:15.360 --> 00:10:18.960 and you actually bypass even traditional coding. There's there's no 211 00:10:19.440 --> 00:10:22.720 that that's an intermediate step that actually will not be 212 00:10:22.759 --> 00:10:25.320 needed probably if by i'd say the end of this year. 213 00:10:26.120 --> 00:10:27.799 And we do expect. 214 00:10:29.039 --> 00:10:31.080 Code to be stead of the art in two to 215 00:10:31.120 --> 00:10:32.840 three months, so it's happening very quickly. 216 00:10:38.240 --> 00:10:41.519 Also, do Imagine, so you know, I mean, what will 217 00:10:41.559 --> 00:10:43.000 you do right after post aga? 218 00:10:43.120 --> 00:10:43.279 Right? 219 00:10:43.320 --> 00:10:45.360 You probably do, like digital life, So that's what we 220 00:10:45.360 --> 00:10:48.080 are doing here as well. We have the Imagine team 221 00:10:48.279 --> 00:10:50.600 like started pretty much from Squash like six months ago. 222 00:10:50.639 --> 00:10:53.080 We have a few people we decided will to do 223 00:10:53.120 --> 00:10:55.679 the image and we'll do the video gen like, yeah, 224 00:10:55.679 --> 00:10:57.440 look at it. What do we achieved today, Like you know, 225 00:10:57.639 --> 00:11:00.840 like two weeks ago. We'll recently Imagine we actually thought 226 00:11:00.919 --> 00:11:03.679 of a leader ball across like many of them, and 227 00:11:03.799 --> 00:11:06.639 people really love our product, love our model. And we 228 00:11:06.759 --> 00:11:09.399 have many more releases actually this month and next months. 229 00:11:09.559 --> 00:11:13.000 So yeah, to me, there's like a very high chance, 230 00:11:13.240 --> 00:11:16.679 like we actually made view the Metaverse before Mada. Yeah, 231 00:11:16.720 --> 00:11:18.960 I'll also pass to try to to talk Abaul, like 232 00:11:18.960 --> 00:11:21.519 you know, the metrics we have, the products. 233 00:11:21.600 --> 00:11:24.279 Yeah, yeah, Like like Godong said, it's only been six 234 00:11:24.320 --> 00:11:26.320 months since we started working on Imagine, we had we 235 00:11:26.360 --> 00:11:30.200 had no code internally for Diffusion at all six months ago, 236 00:11:30.480 --> 00:11:34.080 and basically now we've launched Imagine on every product surface 237 00:11:34.159 --> 00:11:37.000 that we have, including seamlessly integrating into X so you 238 00:11:37.039 --> 00:11:38.919 can open the except right now. You can long press 239 00:11:38.919 --> 00:11:40.559 on any image, you can edit the image, you can 240 00:11:40.559 --> 00:11:42.639 make a video out of the image. We also ran 241 00:11:42.679 --> 00:11:45.320 a contest recently where we had some really funny submissions 242 00:11:45.320 --> 00:11:46.559 that I'm sure many of you have seen. 243 00:11:47.240 --> 00:11:49.039 So Imagine it's growing extremely. 244 00:11:48.639 --> 00:11:51.240 Extremely fast, and it's because of the speed at which 245 00:11:51.279 --> 00:11:54.120 we iterate. Basically, we do multiple product updates every day, 246 00:11:54.159 --> 00:11:56.960 we do model updates every other week, and effectively what 247 00:11:57.000 --> 00:11:59.519 this has led to is now users are generating close 248 00:11:59.559 --> 00:12:02.000 to fifty million videos every day using Imagine. 249 00:12:02.279 --> 00:12:02.759 And just to. 250 00:12:02.720 --> 00:12:05.080 Reiterate what Elon said earlier that to the best of 251 00:12:05.080 --> 00:12:08.039 our knowledge that is more than every other provider combined, 252 00:12:08.120 --> 00:12:10.600 which again is an astonishing place to be compared to 253 00:12:10.600 --> 00:12:13.240 where we were six months ago. We are also generating 254 00:12:13.279 --> 00:12:17.120 six billion images in the last thirty days nano You know, 255 00:12:17.159 --> 00:12:20.240 Google recently posted that, you know, one billion images were 256 00:12:20.279 --> 00:12:23.120 generated using nano Vana in thirty days, So you know 257 00:12:23.120 --> 00:12:26.159 we're six times that, right, And really the goal is 258 00:12:26.440 --> 00:12:28.559 it's not like we don't just want to win. We 259 00:12:28.600 --> 00:12:30.679 want to win like like over a long period of 260 00:12:30.720 --> 00:12:33.559 time and have sustained greatness. And so the goal with 261 00:12:33.679 --> 00:12:35.759 Imagine is to take anything that you can you know, 262 00:12:35.919 --> 00:12:39.000 imagine and turn it into reality. And so that's that's 263 00:12:39.039 --> 00:12:40.879 what we're gonna you know that we're going to speed 264 00:12:40.960 --> 00:12:42.120 run that basically is the goal. 265 00:12:42.279 --> 00:12:43.559 Yeah, Hey, I'm haatin. 266 00:12:44.279 --> 00:12:48.519 We As we keep scaling our model capabilities puwing visual 267 00:12:48.519 --> 00:12:53.720 worlds that's indistinguishable from reality, we're also puling systems that 268 00:12:53.799 --> 00:12:56.879 onlocks much more possibility than what we have right now, 269 00:12:57.559 --> 00:13:00.000 never be able to generate the videos that's much longer 270 00:13:00.080 --> 00:13:02.440 and what we have right now with stories or with 271 00:13:02.600 --> 00:13:06.200 souls of your imagine, And by the end of the year, 272 00:13:06.240 --> 00:13:09.240 we likely will be having models that allow you to 273 00:13:09.320 --> 00:13:12.679 generate videos of ten minutes or twenty minutes in one 274 00:13:12.679 --> 00:13:16.720 shot without any intervention. You just need to give your 275 00:13:16.759 --> 00:13:19.360 imagination and our model, our agents. 276 00:13:19.000 --> 00:13:19.759 Will do it for you. 277 00:13:20.000 --> 00:13:25.159 And moreover, those are the videos we generate, and we're 278 00:13:25.200 --> 00:13:29.639 also going to allow rendering those. We're already the fastest 279 00:13:29.720 --> 00:13:32.120 in generating the videos, and we're going to keep pushing 280 00:13:32.120 --> 00:13:35.120 the extreme where we're going to render those videos in 281 00:13:35.159 --> 00:13:38.240 real time and you will be able to imagine, build 282 00:13:38.320 --> 00:13:41.960 and interact with your own world, and the world will 283 00:13:42.000 --> 00:13:45.000 respond to you in real time, and it is exciting 284 00:13:45.279 --> 00:13:47.559 future that we are going to build with ourself. 285 00:13:47.679 --> 00:13:52.240 Absolutely, my friction is that most of AI compute is 286 00:13:52.240 --> 00:13:54.799 going to be real time, but your understanding and real 287 00:13:54.840 --> 00:13:57.639 time video generation and we expect. 288 00:13:57.360 --> 00:13:58.120 To people leaves in that. 289 00:13:58.679 --> 00:14:01.840 It's really emphsizing these points that you know, six months 290 00:14:01.840 --> 00:14:04.639 ago we didn't even have. We had basically nothing in 291 00:14:05.759 --> 00:14:09.080 very weak in video and image generation and editing, and 292 00:14:09.159 --> 00:14:12.039 we're in six months to number one spot and in 293 00:14:12.039 --> 00:14:15.080 fact generally more more videos and images than everyone else combined. 294 00:14:15.159 --> 00:14:16.879 We're going to do the same thing with coding, and 295 00:14:16.919 --> 00:14:20.080 we're going to do the same thing with Macrohart and 296 00:14:20.080 --> 00:14:23.320 I think people will be pretty impressed with the clock 297 00:14:23.360 --> 00:14:26.279 four point two models coming out. That's a it's a 298 00:14:26.360 --> 00:14:29.559 it's a significant improvement, and that's really just that's that's 299 00:14:29.600 --> 00:14:33.960 the small version of our new model. So we will 300 00:14:33.960 --> 00:14:36.440 have a medium and a large version that are even 301 00:14:36.440 --> 00:14:37.080 more intelligent. 302 00:14:41.799 --> 00:14:45.919 All right, Hi everyone, I'm Toby and I work on Macrohart, 303 00:14:46.120 --> 00:14:50.639 the most series of all product names. So arguably, giving 304 00:14:50.720 --> 00:14:53.559 computers to humans was a good idea, So we're doing 305 00:14:53.559 --> 00:14:56.200 the same thing thing for AI. It's kind of like Inception. 306 00:14:56.279 --> 00:15:00.360 We're giving computers to computers. So Macrohart is building fully 307 00:15:00.360 --> 00:15:05.000 capable digital review time, very important human emulator, so it's 308 00:15:05.120 --> 00:15:07.600 able to do anything on a computer that a human 309 00:15:07.679 --> 00:15:11.279 is able to do, including using advanced tools and engineering 310 00:15:11.399 --> 00:15:15.000 and medicine. So there should be rocket engines fully designed 311 00:15:15.200 --> 00:15:16.080 by AI. 312 00:15:16.440 --> 00:15:19.120 And in a sense, it's one of the last few. 313 00:15:18.919 --> 00:15:22.679 Remaining areas where AI is significantly worse than humans, which 314 00:15:22.840 --> 00:15:25.279 is why I think it's one of the most exciting 315 00:15:25.360 --> 00:15:29.200 areas to actually innovate in and actually change change the field. 316 00:15:29.440 --> 00:15:32.639 Hi everyone, So yeah, my name is John and yeah, 317 00:15:32.679 --> 00:15:35.120 so we're building these strong reasoning models which are now 318 00:15:35.240 --> 00:15:36.360 going to control our CLI. 319 00:15:36.799 --> 00:15:38.559 Like we're actively using these every day. 320 00:15:38.879 --> 00:15:42.399 They are like tremendous, like productivity bursts to the whole team. 321 00:15:42.440 --> 00:15:44.360 I know, the voice team is like killing on that. 322 00:15:44.679 --> 00:15:46.720 And you know, this is the reason why we need 323 00:15:46.720 --> 00:15:48.840 the compute. You know, we need a large scale computer 324 00:15:48.919 --> 00:15:51.320 run these models to boost our own productivity. 325 00:15:51.519 --> 00:15:55.200 But you know, to ninety five percent of the world 326 00:15:55.919 --> 00:15:57.519 world software has a GUI. 327 00:15:58.320 --> 00:16:01.360 So that's like, you know, great representation, and you know, 328 00:16:01.440 --> 00:16:04.840 to truly make people's lives easier, we need to develop models. 329 00:16:04.600 --> 00:16:07.600 That are capable of solving day to day tasks on GUI. 330 00:16:07.919 --> 00:16:11.639 So Macrohart, you know, we will emulate a company where 331 00:16:11.639 --> 00:16:13.639 the output is digital and so this is. 332 00:16:13.600 --> 00:16:15.080 The obvious next step for agents. 333 00:16:15.600 --> 00:16:18.200 Macrohard will and the able true end to end orchestration 334 00:16:18.279 --> 00:16:21.919 across the desktop, and it will lead to immense economic prosperity. 335 00:16:22.720 --> 00:16:25.120 So yeah, we're entering in there where we need to 336 00:16:25.120 --> 00:16:27.679 tackle the hardest of tech problems. But in order to 337 00:16:27.679 --> 00:16:29.519 solve this, we need to hire the best people. So 338 00:16:30.120 --> 00:16:32.080 you know, think of the smartest people that you've worked 339 00:16:32.080 --> 00:16:35.080 with and and put them forward for a position here. 340 00:16:35.320 --> 00:16:37.799 And if you can't think of anybody, like, go through 341 00:16:37.840 --> 00:16:41.159 your phone book, go for your LinkedIn you'll be surprised 342 00:16:41.240 --> 00:16:43.919 like how big your actual network is. And they just 343 00:16:43.960 --> 00:16:46.840 need three properties obviously that we want to optimize for. 344 00:16:47.200 --> 00:16:50.320 Are they clever, can we solve hard problems? And the 345 00:16:50.320 --> 00:16:52.720 second property is are they driven? Do they have the ambition? 346 00:16:52.919 --> 00:16:55.000 Do they want to win? And the third is are 347 00:16:55.000 --> 00:16:56.840 they a nice person? Like do you want to actually 348 00:16:56.840 --> 00:16:58.200 work with them? 349 00:16:58.480 --> 00:16:58.720 Yeah? 350 00:16:58.840 --> 00:16:59.559 So thank you. 351 00:16:59.759 --> 00:17:02.759 Yeah. The Macrohart project is over time. 352 00:17:02.799 --> 00:17:07.079 Actually, we'll probably be the most important project because what 353 00:17:07.160 --> 00:17:11.200 we're talking about is emulation of entire human companies. So 354 00:17:11.440 --> 00:17:13.759 when you look at the most valuable companies in the world, 355 00:17:13.799 --> 00:17:14.400 they are. 356 00:17:15.000 --> 00:17:19.319 That their their output is digital, so they don't actually 357 00:17:19.920 --> 00:17:23.240 make hardware. So it should be possible to completely emulate 358 00:17:23.720 --> 00:17:25.000 any company that where. 359 00:17:24.799 --> 00:17:25.799 The output is digital. 360 00:17:26.240 --> 00:17:29.240 And this will usher in an age of prosperity lives 361 00:17:29.279 --> 00:17:31.319 which we can barely imagine at this point. 362 00:17:31.359 --> 00:17:32.680 You need imagine to imagine it. 363 00:17:33.400 --> 00:17:35.200 So this is a big This is a big deal, 364 00:17:35.240 --> 00:17:38.160 and this is why the words macrohard are painted on 365 00:17:38.240 --> 00:17:40.960 the roof of the training cluster, because that's what it's 366 00:17:40.960 --> 00:17:41.680 going to build. 367 00:17:41.720 --> 00:17:49.799 It's also pretty funny, meant to be a joke. It's 368 00:17:49.839 --> 00:17:50.279 me again. 369 00:17:50.519 --> 00:17:53.440 You might remember me from macrohart in computer used from 370 00:17:53.480 --> 00:17:56.319 a long time ago, but I also actually work on 371 00:17:56.440 --> 00:17:59.319 a core product infrastructure and API. In fact, this is 372 00:17:59.319 --> 00:18:02.759 what I've done for most time at XAI. So anytime 373 00:18:03.039 --> 00:18:05.400 you use any of our products like Cork dot Com 374 00:18:05.440 --> 00:18:09.160 API authentication, you go to status at xot Ai. This 375 00:18:09.240 --> 00:18:12.160 is done by the core product infront team, and a 376 00:18:12.279 --> 00:18:14.519 large portion of them actually sit in London and we 377 00:18:14.599 --> 00:18:17.319 work with himI over there, so we keep the lights 378 00:18:17.359 --> 00:18:21.359 on peak our four pm every day. We get paged 379 00:18:21.440 --> 00:18:23.160 at night when stuff goes down. 380 00:18:23.359 --> 00:18:25.599 Also, thank you to anyone in paleal to getting paged. 381 00:18:26.319 --> 00:18:30.119 This is really important work reliability, security, core product infrastructure. 382 00:18:30.279 --> 00:18:33.079 So if you actually if you're really interested in solving 383 00:18:33.160 --> 00:18:36.480 difficult distributed problems with like messy data, this is. 384 00:18:36.440 --> 00:18:37.160 The team to join. 385 00:18:40.039 --> 00:18:42.400 Hey everyone, manasiego. Yeah. 386 00:18:42.440 --> 00:18:44.440 So, I think one of the main bottlenecks in this 387 00:18:44.480 --> 00:18:46.519 next year for these models is gonna be very high 388 00:18:46.559 --> 00:18:48.920 quality emails and training data. And one of the ways 389 00:18:48.920 --> 00:18:51.160 we solve that is by taking the world's foremost experts 390 00:18:51.160 --> 00:18:54.640 in these domains, bringing them here and having them a 391 00:18:54.680 --> 00:18:56.839 value with them up. We do this for domains like medicine, 392 00:18:56.960 --> 00:19:00.920 finance law with voice actors. We have video editors who 393 00:19:00.920 --> 00:19:04.680 contribute daily to making GROW better and uh yeah, we're 394 00:19:04.720 --> 00:19:06.559 going to be continuing to work on very high quality 395 00:19:06.599 --> 00:19:07.119 emails over the. 396 00:19:07.079 --> 00:19:07.640 Next few months. 397 00:19:07.759 --> 00:19:10.680 We have some same stuff in you know, the frontier 398 00:19:10.680 --> 00:19:14.440 of useful tast and finance and law. You know, we're 399 00:19:14.440 --> 00:19:16.960 trying to build evls that are are are useful in 400 00:19:17.039 --> 00:19:20.680 training data that that represents useful work and not necessarily 401 00:19:20.759 --> 00:19:23.720