1 00:00:00,090 --> 00:00:02,369 mathematically, if you freeze everything in place, 2 00:00:03,080 --> 00:00:04,370 -then yes, that's correct. -Thank you. 3 00:00:04,370 --> 00:00:08,240 -But that's not actually what happened. -You didn't do any analysis to determine 4 00:00:08,240 --> 00:00:11,060 whether that twenty percent increase was commercially justified, correct? 5 00:00:12,280 --> 00:00:18,110 Um, I did. I, I read everything that Professor Schizer said and wrote about, 6 00:00:18,110 --> 00:00:22,180 and I analyzed his analysis, and I brought to bear my experience in reaching the 7 00:00:22,180 --> 00:00:27,580 conclusion that it was a perfectly reasonable, um, business transaction for 8 00:00:27,580 --> 00:00:29,200 the for-profit to put into place. 9 00:00:29,990 --> 00:00:33,480 Professor Coates, you wrote an expert report in this case, correct? 10 00:00:33,480 --> 00:00:35,280 -I did. -And that report contained your entire 11 00:00:35,280 --> 00:00:36,260 analysis? 12 00:00:37,040 --> 00:00:41,760 No, it contained the entire analysis as of the date of the report, which was after 13 00:00:41,760 --> 00:00:46,220 Professor Schizer's first report, but before his second report and before his 14 00:00:46,220 --> 00:00:49,120 -testimony in this case. -And just to be clear, Professor Schizer 15 00:00:49,120 --> 00:00:52,520 talked about the twenty percent TRA increase in his first report, right? 16 00:00:52,520 --> 00:00:56,640 -Uh, he did. So did I in my rebuttal. -And in your rebuttal, the only mention of 17 00:00:56,640 --> 00:01:01,360 the twenty percent TRA increase is in one background paragraph on, in paragraph 18 00:01:01,360 --> 00:01:01,660 twenty? 19 00:01:03,200 --> 00:01:07,960 Um, I, I haven't memorized my report with that level of specificity. Um, I don't 20 00:01:07,960 --> 00:01:12,060 actually think that's true because I do have a figure and a table which reflect 21 00:01:12,060 --> 00:01:16,200 the TRAs, including the total structure of the TRAs over time. 22 00:01:16,200 --> 00:01:19,280 And, and that figure doesn't take account of the twenty percent increase in twenty 23 00:01:19,280 --> 00:01:21,460 -twenty-five, does it? -Because we never got to twenty 24 00:01:21,460 --> 00:01:24,080 -twenty-five. -Thank you, Professor Coates. Uh, court's 25 00:01:24,080 --> 00:01:24,640 indulgence, Your Honor. 26 00:01:25,340 --> 00:01:28,860 -No, I think you probably are done here. -Thank you, Judge. 27 00:01:28,860 --> 00:01:29,370 Microsoft? 28 00:01:30,620 --> 00:01:32,600 -No questions from Microsoft. -Any 29 00:01:33,240 --> 00:01:33,940 rebuttal? 30 00:01:35,060 --> 00:01:37,800 -Very quickly. -Or reexamination? 31 00:01:37,800 --> 00:01:38,200 Thank you. 32 00:01:39,040 --> 00:01:41,520 -You too are very short. -Appreciate that. 33 00:01:43,320 --> 00:01:46,000 Yeah, I'm on a clock too. Professor Coates, a couple of quick questions. Thank 34 00:01:46,000 --> 00:01:49,580 you. Counsel made reference to your previous employment at the Wachtell Lipton 35 00:01:49,580 --> 00:01:51,520 -firm. You recall that? -Yes. 36 00:01:51,520 --> 00:01:53,600 -That was about thirty years ago. -Correct. 37 00:01:53,600 --> 00:01:56,660 Um, so long ago that you and I never even overlapped at the firm, and I'm an old 38 00:01:56,660 --> 00:01:56,880 guy. 39 00:01:58,310 --> 00:02:01,320 -[laughing] -We did not overlap- 40 00:02:01,320 --> 00:02:02,200 -Right -... at all. 41 00:02:02,200 --> 00:02:05,320 And in the years since, you've often been on the other side of Wachtell Lipton in 42 00:02:05,320 --> 00:02:07,980 -litigation, isn't that true? -Correct. You're right. 43 00:02:07,980 --> 00:02:10,960 Ha-have you worked for both defendants and plaintiffs as an expert? 44 00:02:11,800 --> 00:02:14,859 In-- Across a whole range of cases on both sides, correct. 45 00:02:14,860 --> 00:02:18,640 Do you work for a wide range of law firms and clients in that capacity? 46 00:02:18,640 --> 00:02:23,140 I do. I work for dozens of law firms, including Quinn Emanuel, which is Mr. 47 00:02:23,140 --> 00:02:26,160 -Musk's primary outside law firm. -Objection, Your Honor. 48 00:02:26,160 --> 00:02:27,500 -Overruled. -Now, y- 49 00:02:28,300 --> 00:02:32,360 counsel made reference to your work in a Twitter case. Do you recall that? 50 00:02:32,360 --> 00:02:34,780 -I do. -Uh, that case was from twenty twenty. 51 00:02:35,500 --> 00:02:35,780 Correct. 52 00:02:36,500 --> 00:02:40,660 Uh, Mr. Musk didn't even own Twitter until twenty twenty-two, isn't that right? Or 53 00:02:40,660 --> 00:02:42,740 -twenty twenty-three. -That's right. At the time of that case, he 54 00:02:42,740 --> 00:02:46,030 -had no connection to Twitter. -And counsel suggested that the Wachtell 55 00:02:46,030 --> 00:02:48,560 Lipton firm was somehow involved in that lawsuit. 56 00:02:48,560 --> 00:02:51,180 -They were not. You were not. -Was Wachtell Lipton involved in that 57 00:02:51,180 --> 00:02:52,880 -lawsuit at all? -No. 58 00:02:52,880 --> 00:02:55,200 So the suggestion that it was was inaccurate, correct? 59 00:02:55,960 --> 00:02:57,820 -Correct. -Did any of all this have anything to do 60 00:02:57,820 --> 00:03:02,040 -with the substance of your opinions? -No. I would be-- I am confident I would 61 00:03:02,040 --> 00:03:04,800 give you the same opinions without regard to any of the things you just asked me 62 00:03:04,800 --> 00:03:06,160 -about. -Nothing more. Thank you. 63 00:03:08,000 --> 00:03:09,960 Professor, you are excused. 64 00:03:10,740 --> 00:03:13,320 Let me see the, uh, lawyers at sidebar, please. 65 00:03:15,520 --> 00:03:17,720 Not, not you. The primary lawyers. 66 00:04:49,220 --> 00:05:09,260 Okay, 67 00:05:09,260 --> 00:05:12,080 -next ones. -Uh, Your Honor, the OpenAI defendants call 68 00:05:12,080 --> 00:05:13,040 Lewis Dudney. 69 00:05:30,920 --> 00:05:34,020 Please remain standing and raise your right hand to be sworn, sir. 70 00:05:36,120 --> 00:05:39,990 You solemnly swear or affirm that the testimony you're about to give before this 71 00:05:39,990 --> 00:05:44,080 court and jury shall be the truth, the whole truth, and nothing but the truth, so 72 00:05:44,080 --> 00:05:48,760 help you God, or so you affirm. Please say, "I do," or, "I affirm." 73 00:05:48,760 --> 00:05:49,039 I do. 74 00:05:49,760 --> 00:05:50,180 Thank you, sir. 75 00:05:50,840 --> 00:05:55,300 Please be seated. Speak clearly into the microphone. Please state your full name 76 00:05:55,300 --> 00:05:57,480 and spell out your last name for the record. 77 00:05:58,600 --> 00:06:04,580 My name is Lewis Dudney, and my last name is spelled D-U-D-N-E-Y. 78 00:06:04,580 --> 00:06:06,400 -Thank you, sir. -Good afternoon. 79 00:06:06,400 --> 00:06:08,140 -Good afternoon. -You may proceed. 80 00:06:08,140 --> 00:06:10,324 -Good afternoon, Mr. Dudney. -Good afternoon. 81 00:06:11,064 --> 00:06:11,924 What do you do for a living? 82 00:06:12,564 --> 00:06:13,744 Uh, I'm a forensic accountant. 83 00:06:14,584 --> 00:06:16,304 And what does a forensic accountant do? 84 00:06:17,144 --> 00:06:22,664 Forensic accountants study financial and accounting information, uh, to try and 85 00:06:22,664 --> 00:06:28,504 help, uh, juries or courts understand, um, the implications of that in a litigated 86 00:06:28,504 --> 00:06:29,444 case, most typically. 87 00:06:30,324 --> 00:06:33,024 And how long have you worked as a forensic accountant, sir? 88 00:06:33,024 --> 00:06:36,704 -37 years. -Uh, Mr. Dudney, I understand that you've 89 00:06:36,704 --> 00:06:40,064 prepared a slide with some of your qualifications. Would it be helpful to put 90 00:06:40,064 --> 00:06:42,304 -that on the screen? -Yes. 91 00:06:42,304 --> 00:06:42,564 Okay. 92 00:06:43,524 --> 00:06:45,304 And for the record, this is DDX10. 93 00:06:46,404 --> 00:06:48,613 Mr. Dudney, do you hold any advanced degrees? 94 00:06:49,444 --> 00:06:52,404 Yes, I have a BBA with a concentration in accounting. 95 00:06:53,084 --> 00:06:55,524 -And where did you get that degree, sir? -From William & Mary. 96 00:06:56,564 --> 00:07:00,804 Do you hold any certifications relevant to your work as a forensic accountant? 97 00:07:01,604 --> 00:07:06,244 I do. I hold two. Uh, one is that I'm a licensed and certified public accountant, 98 00:07:06,864 --> 00:07:10,964 and then I also am recognized by the American Institute of Certified Public 99 00:07:10,964 --> 00:07:13,844 Accountants as certified in financial forensics. 100 00:07:14,544 --> 00:07:18,444 Has a court ever qualified you as a forensic accounting expert, Mr. Dudney? 101 00:07:18,444 --> 00:07:19,004 Many times. 102 00:07:20,104 --> 00:07:24,644 H- how many times throughout your career have you been, um, offered testimony, uh, 103 00:07:24,644 --> 00:07:27,603 financial testimony, in a case in which you applied forensic accounting 104 00:07:27,604 --> 00:07:29,904 -principles? -Over 75 times. 105 00:07:31,744 --> 00:07:35,484 Uh, were you retained by counsel for the OpenAI defendants in this case? 106 00:07:35,484 --> 00:07:38,284 -Yes, I was. -And what was your assignment, Mr. Dudney, 107 00:07:38,284 --> 00:07:39,084 at a, at a high level? 108 00:07:39,744 --> 00:07:45,664 At a high level, it was to determine, um, when, uh, the various donations or 109 00:07:45,664 --> 00:07:50,284 contributions that were claimed by Mr. Musk were made. It was to determine when 110 00:07:50,284 --> 00:07:53,864 those donations were spent, uh, for the cash donations, 111 00:07:54,544 --> 00:07:58,324 and then it was als- also to determine how, um, that money was used. 112 00:07:59,204 --> 00:08:03,244 Uh, Mr. Dudney, did you bill for your time spent on that assignment? 113 00:08:03,244 --> 00:08:05,104 -I did. -Uh, and what was the rate that you 114 00:08:05,104 --> 00:08:08,684 -charged? -$1,475 per hour. 115 00:08:08,684 --> 00:08:10,864 And is that your customary rate, Mr. Dudney? 116 00:08:10,864 --> 00:08:11,144 It is. 117 00:08:12,704 --> 00:08:16,484 Did you review any documents or other materials to help form the opinions you're 118 00:08:16,484 --> 00:08:19,724 -prepared to offer today, sir? -A, a number of documents, yes. 119 00:08:19,724 --> 00:08:23,214 Again, at a high level, recognizing that we're on a clock, uh, could you describe 120 00:08:23,214 --> 00:08:27,764 -the kinds of documents you looked at? -Sure. I looked at tax returns. I looked at 121 00:08:27,764 --> 00:08:32,304 bank statements. I looked at, uh, underlying accounting records, which are 122 00:08:32,304 --> 00:08:36,804 referred to the, as the general ledger. I looked at contemporaneous correspondence. 123 00:08:36,804 --> 00:08:40,744 I looked at agreements such as lease agreements, invoices, things of that 124 00:08:40,744 --> 00:08:41,044 nature. 125 00:08:42,164 --> 00:08:45,664 I see, and, and you mentioned the general ledger. That was the general ledger for 126 00:08:45,664 --> 00:08:48,664 -which entity, sir? -It's for OpenAI. 127 00:08:48,664 --> 00:08:51,404 -Yeah. The, the nonprofit? -Yes, OpenAI, Inc. 128 00:08:52,804 --> 00:08:55,313 Um, are the opinions you're prepared to offer today, 129 00:08:56,204 --> 00:08:58,654 uh, based on recognized principles of accounting? 130 00:08:58,654 --> 00:09:01,224 -Yes. -And did you re- reliably a- apply those 131 00:09:01,224 --> 00:09:03,874 -principles to form your opinion, sir? -Yes. 132 00:09:03,874 --> 00:09:08,004 Okay. Uh, at this time, Your Honor, we would offer Mr. Dudney as an expert in 133 00:09:08,004 --> 00:09:08,844 forensic accounting. 134 00:09:10,064 --> 00:09:11,564 Is th- any objection? 135 00:09:13,104 --> 00:09:15,084 -No objection, Your Honor. -He's admin. 136 00:09:15,084 --> 00:09:15,284 Okay. 137 00:09:16,004 --> 00:09:16,184 Um, 138 00:09:17,124 --> 00:09:20,764 M- Mr. Dudney, you said that you reviewed Mr. Musk's financial contributions to the 139 00:09:20,764 --> 00:09:23,184 -OpenAI nonprofit, correct? -Yes, I did. 140 00:09:24,004 --> 00:09:27,934 Uh, according to your analysis, how, how much money did Mr. Musk contribute to 141 00:09:27,934 --> 00:09:28,584 OpenAI, Inc? 142 00:09:29,344 --> 00:09:33,194 Uh, approximately 37.799 million. 143 00:09:34,284 --> 00:09:38,064 Uh, and I believe you've prepared a slide, which is already on the screen, uh, of, 144 00:09:38,064 --> 00:09:41,444 of the categories of contributions you saw. Is, is that correct? 145 00:09:41,444 --> 00:09:45,404 Yes. This slide is a summary of the, uh, contributions that I was able to identify. 146 00:09:45,404 --> 00:09:47,563 And that's DDX11, correct? 147 00:09:47,564 --> 00:09:50,664 -Correct. -Okay. Um, w- were the contributions that 148 00:09:50,664 --> 00:09:53,464 Mr. Musk provided to OpenAI all of the same kind? 149 00:09:54,084 --> 00:09:56,944 -No. -Um, what sorts of contributions did Mr. 150 00:09:56,944 --> 00:09:59,854 Musk make to OpenAI, based on your analysis? 151 00:09:59,854 --> 00:10:04,384 So I've grouped them on this slide into three categories. Um, the first category, 152 00:10:04,384 --> 00:10:07,564 which represents $25 million worth of contributions, 153 00:10:08,424 --> 00:10:11,084 is referred to here as, uh, quarterly contributions. 154 00:10:11,884 --> 00:10:17,804 Um, the second category, which equals approximately 12.5 million, that, uh, 155 00:10:17,804 --> 00:10:21,764 relates to, uh, what are described as rent-related contributions. 156 00:10:22,404 --> 00:10:29,164 And then the third category is, um, $262,400 related to 157 00:10:29,164 --> 00:10:34,304 four Tesla cars and an upgrade or some upgrades to one of those cars, and that's 158 00:10:34,304 --> 00:10:38,064 an in-kind, um, uh, contribution, meaning non-cash. 159 00:10:38,664 --> 00:10:42,324 Okay. Um, we can take that down. Thank you. I'd, I'd like to just talk in a 160 00:10:42,324 --> 00:10:45,694 little bit more detail with you, Mr. Dudney, about the cash contributions. 161 00:10:46,564 --> 00:10:51,844 Uh, and to do that, Your Honor, we'd like to, um, introduce into evidence DX1304. 162 00:10:51,844 --> 00:10:54,424 It's a summary exhibit that's been stipulated. 163 00:10:54,424 --> 00:10:57,244 -So moved. -Okay, I need to hand it up to Mr. Cuenco. 164 00:10:57,244 --> 00:10:57,474 You may. 165 00:11:03,384 --> 00:11:04,184 May I approach, Your Honor? 166 00:11:08,004 --> 00:11:08,364 Thank you. 167 00:11:09,364 --> 00:11:09,584 Thank you. 168 00:11:13,524 --> 00:11:15,604 Okay. Uh, we can put that up, Your Honors. 169 00:11:17,944 --> 00:11:20,424 Uh, Mr. Dudney, you've seen this exhibit before? 170 00:11:20,424 --> 00:11:21,964 -Yes. -Okay. What, what does it show? 171 00:11:22,884 --> 00:11:26,684 It shows the cash contributions, um, 172 00:11:27,444 --> 00:11:31,264 demonstrating both the size of those contributions and the timing of those 173 00:11:31,264 --> 00:11:32,104 contributions. 174 00:11:32,784 --> 00:11:32,984 Um, 175 00:11:33,984 --> 00:11:39,184 and it d- differentiates between the first two categories of contributions that were 176 00:11:39,184 --> 00:11:41,674 made in cash that I just discussed a moment ago. 177 00:11:41,674 --> 00:11:44,624 A- and just for the jury's benefit again, what, what are those two categories that 178 00:11:44,624 --> 00:11:48,024 -are on this slide? -So the green bars to the left-hand side 179 00:11:48,024 --> 00:11:51,724 that are significantly larger, those are the quarterly contributions, which equal 180 00:11:51,724 --> 00:11:57,624 $25 million. And then the smaller, more frequent red bars at the bottom, those are 181 00:11:57,624 --> 00:12:01,344 the rent-related monetary contributions that I identified. 182 00:12:01,344 --> 00:12:03,004 And Mr. Dudney, if you could, 183 00:12:03,844 --> 00:12:05,134 did your analysis, uh, 184 00:12:05,744 --> 00:12:09,504 reveal an answer to the following question: Why, uh, are some of the green 185 00:12:09,504 --> 00:12:10,523 bars larger than others? 186 00:12:11,776 --> 00:12:17,836 Y-y-yes, it's simply a timing, um, uh, i-issue. And so you can see that, uh, if 187 00:12:17,836 --> 00:12:21,996 you look at the bottom, uh, you'll see that some of the green bars are stacked on 188 00:12:21,996 --> 00:12:26,176 little, little red bars, and in other cases they're not. And so that affects if 189 00:12:26,176 --> 00:12:31,096 you look at the top, um, where the total funding, if you will, of both, uh, the 190 00:12:31,096 --> 00:12:35,116 green bars and the red bars, um, would fall, uh, but it's just simply a 191 00:12:35,116 --> 00:12:37,356 presentation, um, question. 192 00:12:38,436 --> 00:12:42,796 Um, and, uh, focusing now on the red bars, how did you determine, sir, that the red 193 00:12:42,796 --> 00:12:45,016 bars were all rent-related contributions? 194 00:12:45,736 --> 00:12:49,856 So I looked at, um, a variety of documents, starting with the lease 195 00:12:49,856 --> 00:12:55,156 agreement, um, that, uh, was signed. I looked at a sublease agreement related to 196 00:12:55,156 --> 00:13:01,536 these payments. I looked at rent invoices. I looked at, um, cash contributions, 197 00:13:01,536 --> 00:13:06,196 which from a timing perspective and an amount perspective were consistent with 198 00:13:06,196 --> 00:13:10,036 the lease payments that were called for under the agreement. And then I also 199 00:13:10,036 --> 00:13:15,416 looked at the payments that OpenAI made to the landlord to understand that there 200 00:13:15,416 --> 00:13:15,796 was, 201 00:13:16,736 --> 00:13:21,976 um, uh, a, a relationship, if you will, between all of these things, demonstrating 202 00:13:21,976 --> 00:13:26,616 that the payments that OpenAI was making, um, were rent-related, and that these 203 00:13:26,616 --> 00:13:30,156 contributions that are shown here were rent-related contributions. 204 00:13:30,816 --> 00:13:32,516 Okay, thank you. We, we can take that down. 205 00:13:33,336 --> 00:13:37,496 Uh, drilling down just one more layer, uh, Mr. Dudney, I'd like to talk briefly 206 00:13:37,496 --> 00:13:39,516 about the quarterly donations in particular. 207 00:13:40,116 --> 00:13:40,856 -Okay. -Um, 208 00:13:41,636 --> 00:13:47,316 based on your analysis, where did OpenAI Inc. put Mr. Musk's quarterly donations? 209 00:13:47,316 --> 00:13:51,886 In-into the business checking account that, uh, OpenAI had opened. 210 00:13:51,886 --> 00:13:56,275 And did OpenAI Inc. maintain a separate checking account for Mr. Musk's donations? 211 00:13:56,275 --> 00:13:58,836 No, not a separate one just for Mr. Musk's 212 00:13:58,836 --> 00:13:59,576 donations. 213 00:14:00,256 --> 00:14:05,256 Okay, and what other sorts of, uh, funds flo-flowed into that checking account? 214 00:14:05,256 --> 00:14:08,476 So there were der-donations from other entities that went to that checking 215 00:14:08,476 --> 00:14:13,156 account, and then that checking account also was the, uh, primary source for 216 00:14:13,156 --> 00:14:18,756 payments that OpenAI made to pay various vendors and, uh, bills that it had to pay 217 00:14:18,756 --> 00:14:19,795 in operating its business. 218 00:14:20,836 --> 00:14:24,406 Now, Mr. Dudney, you, you testified earlier that part of your s-assignment was 219 00:14:24,406 --> 00:14:28,976 figuring out when the nonprofit spent Mr. Musk's donations. Is that correct? 220 00:14:28,976 --> 00:14:32,776 -Yes. -Okay. Did the fact that OpenAI Inc. put 221 00:14:32,776 --> 00:14:37,836 all of Mr. Musk's donations into the same checking account as other donations affect 222 00:14:37,836 --> 00:14:40,076 -that analysis in any way? -It did. 223 00:14:40,076 --> 00:14:40,996 And, and how was that, sir? 224 00:14:41,676 --> 00:14:46,496 So when monies from different sources are put into the same, uh, account, uh, 225 00:14:46,496 --> 00:14:52,856 accountants will describe that as a, a commingling of funds. And so there were, 226 00:14:52,856 --> 00:14:58,826 uh, monies from not just Mr. Musk, uh, but also from other donors that were put into 227 00:14:58,826 --> 00:15:03,156 the same account, which is a normal practice, but it commingles the money from 228 00:15:03,156 --> 00:15:07,516 that perspective. So that impacts then the, um, sort of analysis that, um, I 229 00:15:07,516 --> 00:15:08,156 engage in. 230 00:15:08,916 --> 00:15:12,936 And did you engage in any particular accounting analysis to sort through the 231 00:15:12,936 --> 00:15:15,196 -commingling you just described? -I did. 232 00:15:15,196 --> 00:15:16,916 And, and what was that analysis that you did? 233 00:15:17,556 --> 00:15:22,716 So accountants refer to the type of analysis, uh, that I did as a FIFO 234 00:15:22,716 --> 00:15:28,876 analysis, and that's an acronym. It's F-I-F-O, and it stands for first in, first 235 00:15:28,876 --> 00:15:29,876 out. 236 00:15:29,936 --> 00:15:35,455 Uh, and essentially what it means is that just like, um, if you stand in line at a 237 00:15:35,456 --> 00:15:39,916 restaurant to get in, the first person in the line gets in first, the second person 238 00:15:39,916 --> 00:15:45,716 gets in second, and so forth. And so it's a, um, way to consider the timing of when 239 00:15:45,716 --> 00:15:48,786 the monies were, um, donated to OpenAI. 240 00:15:50,296 --> 00:15:51,616 Okay, thank you, Mr. Dudney. 241 00:15:52,356 --> 00:15:56,696 Um, why did you decide to use FIFO in this particular analysis? 242 00:15:57,316 --> 00:16:01,736 So there were a couple of reasons. Uh, one is that I had detailed data, 243 00:16:01,736 --> 00:16:05,636 transaction-level data with respect to OpenAI's funding, 244 00:16:06,256 --> 00:16:08,036 its, um, expenditures, 245 00:16:08,856 --> 00:16:13,996 and how the timing of all that related, uh, to one another in actuality. So that 246 00:16:13,996 --> 00:16:15,186 was a, a first, um, 247 00:16:15,876 --> 00:16:20,376 important determination because you need detailed data to do the analysis I did. 248 00:16:20,376 --> 00:16:26,566 Second, i-it's because the periods, um, that I looked at primarily, which were and 249 00:16:26,566 --> 00:16:26,566 , uh, 250 00:16:28,856 --> 00:16:33,676 OpenAI was very much a startup company at that point. And so it didn't... In the 251 00:16:33,676 --> 00:16:40,356 first day it didn't have any funding. And so it was clear as I looked at the data 252 00:16:40,356 --> 00:16:42,366 that the company would go out, get some funding, 253 00:16:43,056 --> 00:16:48,336 spend that, get some funding. As it got low, get some more, et cetera. And one 254 00:16:48,336 --> 00:16:52,696 might use the analogy of it was, um, in the early days, living paycheck to 255 00:16:52,696 --> 00:16:56,356 -paycheck in that regard. -A-and Mr. Dudney, I understand that you 256 00:16:56,356 --> 00:16:59,676 created a slide to show the phenomenon you were just describing. Is that right? 257 00:16:59,676 --> 00:17:01,575 -Yes. -Okay. It would be helpful to put that up. 258 00:17:01,576 --> 00:17:02,936 -Please. -Okay, let's do that, please. 259 00:17:04,036 --> 00:17:05,516 And this will be DDX-12. 260 00:17:06,716 --> 00:17:11,856 -Um, what is this chart, Mr. Dudney? -So this is simply a line graph of the 261 00:17:11,856 --> 00:17:14,956 balance of OpenAI's checking account. 262 00:17:15,596 --> 00:17:22,536 And so it covers a two-year period from January 2016 through December 2017, 263 00:17:22,536 --> 00:17:26,536 and on the left-hand side you can see the balance in millions of dollars, and it 264 00:17:26,536 --> 00:17:30,006 just simply shows, um, how that balance, uh, 265 00:17:30,756 --> 00:17:36,056 went up and then would go down in what I would call a sawtooth pattern, um, over 266 00:17:36,056 --> 00:17:36,996 this two-year period. 267 00:17:37,606 --> 00:17:42,276 A-and did this checking account, uh, or at least this representation of the balance 268 00:17:42,276 --> 00:17:45,876 of the checking account, include all of the donations OpenAI received during this 269 00:17:45,876 --> 00:17:48,075 -period? -All of the cash donations, yes. 270 00:17:48,076 --> 00:17:51,515 In other words, just to be clear, not, not limited to Mr. Musk, correct? 271 00:17:51,516 --> 00:17:55,536 C-correct. This would include donations by others during this time period as well. 272 00:17:55,536 --> 00:17:59,376 And Mr. Dudney, when you looked at this chart, uh, and you were thinking about the 273 00:17:59,376 --> 00:18:02,616 best way to do your analysis, did you draw any conclusions from what you 274 00:18:02,616 --> 00:18:03,036 observed? 275 00:18:03,976 --> 00:18:04,426 Yes. This, 276 00:18:05,376 --> 00:18:10,396 this actual, um, funding, then spending, then funding, then spending pattern was 277 00:18:10,396 --> 00:18:16,436 consistent with my use of a FIFO methodology for purposes of, um, analyzing 278 00:18:16,436 --> 00:18:20,196 how, uh, Mr. Musk's donations were used. 279 00:18:21,246 --> 00:18:26,126 Okay. Uh, we can take that down. Uh, Mr. Dudney, you also, uh, testified, uh, uh, 280 00:18:26,126 --> 00:18:30,206 that ultimately you were asked to figure out when Mr. Musk's quarterly donations 281 00:18:30,206 --> 00:18:32,245 -had been spent, correct? -That's correct. 282 00:18:32,246 --> 00:18:32,406 Okay. 283 00:18:33,026 --> 00:18:38,086 Um, based on your application of, of the FIFO analysis, were you able to isolate 284 00:18:38,706 --> 00:18:42,166 the balance of Mr. Musk's quarterly contributions to OpenAI 285 00:18:42,786 --> 00:18:45,705 -as distinct from donations from others? -Yes. 286 00:18:45,706 --> 00:18:49,246 Okay. And again, we have a slide that you've prepared, correct, on that, on that 287 00:18:49,246 --> 00:18:50,336 -subject, sir? -That's correct. 288 00:18:50,336 --> 00:18:52,306 -Would it be helpful to put that up? -Please. 289 00:18:52,306 --> 00:18:53,106 Great. Let's do that. 290 00:18:55,486 --> 00:18:58,456 And this is DDX, uh, 13.1. 291 00:18:59,226 --> 00:19:01,346 Uh, are you familiar with this chart, Mr. Dudney? 292 00:19:01,346 --> 00:19:03,266 -Yes, I am. -And what does it depict? 293 00:19:04,166 --> 00:19:10,256 This depicts the results of my FIFO analysis, um, as it relates to the use of 294 00:19:10,256 --> 00:19:16,886 the Musk-related quarterly cash donations. And so this shows the balance of that 295 00:19:16,886 --> 00:19:19,876 element of OpenAI's cash funding. 296 00:19:21,066 --> 00:19:23,066 And Mr. Dudney, you'll see, um, 297 00:19:23,786 --> 00:19:28,206 in June of 2016, the, the balance begins to increase, and I'm, I'm wondering if you 298 00:19:28,206 --> 00:19:31,826 could focus your attention there and just to briefly explain to the jury w- what's 299 00:19:31,826 --> 00:19:33,026 happening at that point in the chart. 300 00:19:33,746 --> 00:19:38,446 So if, if we look at the bottom of the chart and we just start looking from left 301 00:19:38,446 --> 00:19:43,686 to right, you'll see that, um, the line, the blue line or the, the main line is 302 00:19:43,686 --> 00:19:48,626 zero until it hits roughly June of 2016. Then there's a small little stairstep 303 00:19:48,626 --> 00:19:53,786 there, and that is the, um, recognition of the first contribution that is made, uh, 304 00:19:53,786 --> 00:19:56,296 related to Mr. Musk for $500,000. 305 00:19:56,926 --> 00:20:01,886 Then you'll see another stairstep, um, take you up to about $5.5 million, 306 00:20:02,566 --> 00:20:08,326 um, and that, uh, is recognition of the second, uh, significant quarterly 307 00:20:08,326 --> 00:20:11,086 contribution that was made of, um, $5 million. 308 00:20:12,086 --> 00:20:15,306 And, and then Mr. Dudney, what, what happened after that, uh, over the next 309 00:20:15,306 --> 00:20:16,606 several months in 2016? 310 00:20:17,286 --> 00:20:22,206 So what happens then is you see a stairstep going down, um, and I'll try 311 00:20:22,206 --> 00:20:26,006 and, uh, use the telus- oh, there it is. Um, you'll see that, uh, where the red 312 00:20:26,006 --> 00:20:31,685 line was just superimposed, that, that shows the usage of that, um, funding that 313 00:20:31,686 --> 00:20:36,626 was provided by Mr. Musk based on my application of a FIFO analysis. And so you 314 00:20:36,626 --> 00:20:41,525 see funding, and then you see usage of that funding and, uh, that you see that 315 00:20:41,526 --> 00:20:46,186 -pattern then repeating itself over time. -And Mr. Dudney, if I could now focus you 316 00:20:46,186 --> 00:20:52,106 on the period around May of 2017, uh, May to July of 2017. Again, briefly, could you 317 00:20:52,106 --> 00:20:55,326 explain to the jury what you observed based on your analysis in that time 318 00:20:55,326 --> 00:20:55,566 period? 319 00:20:56,386 --> 00:21:01,006 So from May to July of 2017, you'll see the line goes to zero, 320 00:21:01,706 --> 00:21:05,866 and the reason that it goes to zero during that period is because all of the 321 00:21:05,866 --> 00:21:11,606 previous funding that Mr. Musk had provided, um, had been used. And so what's 322 00:21:11,606 --> 00:21:17,826 happening during that period is OpenAI is funding itself with the, um, most recent 323 00:21:17,826 --> 00:21:22,106 funding that it had received from another donor other than Mr. Musk, and that's why 324 00:21:22,106 --> 00:21:27,026 they were able to operate in that window, for example, despite not having 325 00:21:27,026 --> 00:21:28,086 Musk-related money. 326 00:21:29,006 --> 00:21:32,826 A- and then the, the line changes again in July 2017, correct? 327 00:21:32,826 --> 00:21:34,686 -Correct. -A- and, and what, what is happening at 328 00:21:34,686 --> 00:21:38,926 -that point, Mr. Dudney? -M- Mr. Musk makes what is his last, um, 329 00:21:38,926 --> 00:21:41,406 quarterly contribution for $5 million. 330 00:21:44,026 --> 00:21:47,766 Uh, thank you. Um, and then from that point, uh, Mr. Dudney, over the next 331 00:21:47,766 --> 00:21:49,786 several months, the line is, is flat. 332 00:21:50,406 --> 00:21:52,266 -Am I reading this correctly? -Yes. 333 00:21:52,266 --> 00:21:57,066 -And can you explain why that is, sir? -Uh, essentially, Mr. Musk's money is 334 00:21:57,066 --> 00:22:03,266 waiting in line, if you will, until the previously donated money is used, um, for 335 00:22:03,266 --> 00:22:08,966 purposes of my analysis. So you'll see that that $5 million balance reflects that 336 00:22:08,966 --> 00:22:15,106 concept of, um, Mr. Musk's money waiting in line until, um, the just-previous 337 00:22:15,106 --> 00:22:18,126 donor's money is, uh, used up. 338 00:22:18,486 --> 00:22:21,006 Okay, thank you very much. And my apologies for honor mic. 339 00:22:22,086 --> 00:22:22,646 My apologies. 340 00:22:23,386 --> 00:22:26,586 Uh, and then, um, what happens after that, Mr. Dudney? 341 00:22:26,586 --> 00:22:29,846 So you see then a very, uh, steep decline, 342 00:22:30,526 --> 00:22:36,686 um, taking place after that, uh, flat area that is, um, highlighted with the red 343 00:22:36,686 --> 00:22:42,386 arrow, and that steep decline is, again, just simply the usage of Mr. Musk's, um, 344 00:22:42,386 --> 00:22:43,526 last donation 345 00:22:44,206 --> 00:22:49,946 by OpenAI. And the reason that it's so steep is because OpenAI is spending more 346 00:22:49,946 --> 00:22:54,226 month to month. Uh, and so it eats through that funding quite quickly. 347 00:22:54,886 --> 00:22:58,706 And Mr. Dudney, to sort of land the plane here, um, based on your forensic 348 00:22:58,706 --> 00:23:03,386 accounting analysis and application of FIFO, when did you determine that OpenAI, 349 00:23:03,386 --> 00:23:08,066 Inc., uh, completed spending Mr. Musk's final quarterly donation? 350 00:23:08,126 --> 00:23:09,626 November of 2017. 351 00:23:11,606 --> 00:23:12,646 And we can take that down. 352 00:23:14,626 --> 00:23:18,486 Thank you. Just a few final questions, Mr. Dudney. Uh, you also explained that you 353 00:23:18,486 --> 00:23:23,606 were asked to analyze the manner in which the nonprofit spent Mr. Musk's, uh, 354 00:23:24,986 --> 00:23:29,066 to analyze the manner in which the nonprofit spent Mr. Musk's, uh, quarterly 355 00:23:29,066 --> 00:23:31,165 -donations. Is that correct? -Yes. 356 00:23:31,166 --> 00:23:33,466 Okay. And how did you go about doing that work, Mr. Dudney? 357 00:23:34,146 --> 00:23:39,006 So in part, it was, um, having looked at all of the detailed transactions that, uh, 358 00:23:39,006 --> 00:23:42,886 made up the analysis that was just described. I also looked at then 359 00:23:43,706 --> 00:23:49,686 financial statement information to understand how the company itself, OpenAI, 360 00:23:49,686 --> 00:23:54,426 categorized all the detailed transactions that I had been analyzing. 361 00:23:55,366 --> 00:23:58,446 See, and did you look at anything other than the financial statements to do that 362 00:23:58,446 --> 00:24:01,046 -analysis? -I looked at the financial statements and 363 00:24:01,046 --> 00:24:03,166 the, um, underlying transactions as well. 364 00:24:04,546 --> 00:24:07,626 And when you looked at those, uh, financial records, Mr. Dudney, what did 365 00:24:07,626 --> 00:24:08,206 you observe? 366 00:24:09,116 --> 00:24:13,546 Uh, I observed that, um, there were several primary categories, if you will, 367 00:24:13,546 --> 00:24:16,886 of how the money was spent, um, by OpenAI. 368 00:24:16,886 --> 00:24:20,586 And from an accounting perspective, were those expenses categorized in any way? 369 00:24:21,336 --> 00:24:26,226 Th- they're, as, with respect to a, um, a nonprofit, they're called functional 370 00:24:26,226 --> 00:24:32,962 expenses.And that's just, um, accounting terminology to describe, um, 371 00:24:32,962 --> 00:24:38,742 expenses related to the business conduct, if you will, of the, um, not-for-profit. 372 00:24:39,362 --> 00:24:40,582 And, and again, just in, in 373 00:24:41,242 --> 00:24:45,602 summary form, Mr. Dudney, what were the categories of, of functional or operating 374 00:24:45,602 --> 00:24:47,442 expenses that you saw OpenAI, 375 00:24:48,162 --> 00:24:53,282 -uh, using its funds on in 2016 and 2017? -So the primary categories were, um, 376 00:24:53,282 --> 00:24:57,482 compute, which has been talked about as, um, other witnesses have been mentioning. 377 00:24:57,482 --> 00:25:02,702 Uh, it was salaries and compensation. It was for professional fees and related 378 00:25:02,702 --> 00:25:04,062 sorts of expenses like that. 379 00:25:06,422 --> 00:25:08,802 Uh, thank you, Mr. Dudney. No further questions. Thank you, Your Honor. Thank 380 00:25:08,802 --> 00:25:09,182 -you. -Thank you. 381 00:25:10,942 --> 00:25:12,562 Cross by plaintiffs. 382 00:25:22,102 --> 00:25:24,262 Good afternoon, Mr. Dudney. Walter Haas for the plaintiff. 383 00:25:25,002 --> 00:25:25,982 Good afternoon, Mr. Haas. 384 00:25:31,402 --> 00:25:37,962 Um, Mr. Dudney, you testified that 37 million and roughly 800,000 of Mr. Musk's 385 00:25:37,962 --> 00:25:39,022 claimed contributions, 386 00:25:39,742 --> 00:25:42,542 uh, were in fact received by OpenAI, correct? 387 00:25:42,542 --> 00:25:43,262 That's correct. 388 00:25:44,302 --> 00:25:47,602 And those funds were important to OpenAI successfully running its business, 389 00:25:47,602 --> 00:25:47,922 correct? 390 00:25:49,722 --> 00:25:53,202 Uh, they were certainly a significant portion of the early funding of his 391 00:25:53,202 --> 00:25:55,882 -business. -Okay. And you testified about how those 392 00:25:55,882 --> 00:25:56,542 funds were spent. 393 00:25:57,602 --> 00:26:00,542 -Yes. -And OpenAI spent those funds on salaries 394 00:26:00,542 --> 00:26:02,062 for the engineers and other employees. 395 00:26:03,322 --> 00:26:05,442 -Yes. -And it also spent those funds on the 396 00:26:05,442 --> 00:26:08,602 compute that it used to develop its AI software, right? 397 00:26:08,602 --> 00:26:09,182 That's correct. 398 00:26:11,022 --> 00:26:15,002 Now, that software, that intellectual property, was a valuable asset for the 399 00:26:15,002 --> 00:26:15,722 nonprofit, right? 400 00:26:16,722 --> 00:26:20,462 I, I, I can't comment on to what extent there was intellectual property that was 401 00:26:20,462 --> 00:26:21,682 developed at that point in time. 402 00:26:22,342 --> 00:26:26,661 Okay. And the nonprofit later transferred that software that it developed with Mr. 403 00:26:26,662 --> 00:26:30,022 -Musk's funds to the for-profit- -Objection. Beyond the scope. 404 00:26:33,282 --> 00:26:34,242 I'll withdraw the question, Your Honor. 405 00:26:39,442 --> 00:26:44,282 Mr. Dudney, you testified that OpenAI commingled Mr. Musk's donations with other 406 00:26:44,282 --> 00:26:46,482 -donations, correct? -That's correct. 407 00:26:46,482 --> 00:26:51,322 And because OpenAI commingled his donations in a single account, you can't 408 00:26:51,322 --> 00:26:56,102 actually determine with specificity and certainty when Elon's contributions were 409 00:26:56,102 --> 00:26:58,772 spent versus the contributions from the other donors, correct? 410 00:26:59,422 --> 00:27:00,292 You can't, um, 411 00:27:00,942 --> 00:27:05,362 specifically tie specific dollars. You have to apply one of the forensic 412 00:27:05,362 --> 00:27:07,982 accounting techniques that, uh, I talk about. 413 00:27:07,982 --> 00:27:10,822 Thank you. So that, that's a yes, right? That you can't determine with certainty 414 00:27:11,682 --> 00:27:14,142 what Elon's contributions were spent on, correct? 415 00:27:14,142 --> 00:27:18,682 Not specific, um, expenses. You have to, as I said, apply the approach that I did. 416 00:27:18,682 --> 00:27:22,602 Thank you. And you used a method called FIFO, right? First in, first out. 417 00:27:23,422 --> 00:27:23,922 That's correct. 418 00:27:24,822 --> 00:27:25,182 And 419 00:27:28,162 --> 00:27:30,442 that's what you call a financial tracing method, isn't it? 420 00:27:31,302 --> 00:27:33,341 -Yes. -All right. And there are numerous other 421 00:27:33,342 --> 00:27:35,962 financial tracing methods that exist, right? 422 00:27:35,962 --> 00:27:36,502 That's correct. 423 00:27:38,322 --> 00:27:42,542 Now, FIFO, the one you used, assumes that the first money into an account is the 424 00:27:42,542 --> 00:27:44,022 first money out of the account, correct? 425 00:27:44,982 --> 00:27:47,842 -That's correct. -But another financial tracing method is 426 00:27:47,842 --> 00:27:50,621 last in, first out, or LIFO. Are you familiar with that? 427 00:27:50,682 --> 00:27:50,982 I am. 428 00:27:51,582 --> 00:27:57,142 And under the LIFO method, one assumes that the last money in is the first money 429 00:27:57,142 --> 00:27:58,782 -out, right? -That's correct. 430 00:27:58,782 --> 00:27:59,002 Okay. 431 00:28:01,662 --> 00:28:04,932 And both of those are commonly used financial tracing methods, right? 432 00:28:04,932 --> 00:28:08,922 -They're both well-known, yes. -Thank you. And if you applied LIFO here, 433 00:28:08,922 --> 00:28:12,502 you would not have gotten the same result regarding when Mr. Musk's contributions 434 00:28:12,502 --> 00:28:13,182 were spent, would you? 435 00:28:14,442 --> 00:28:17,982 A- as a matter of just mathematic application of it, the answer is no. 436 00:28:17,982 --> 00:28:19,841 -Thank you. -I don't think it's the right one, but no, 437 00:28:19,842 --> 00:28:22,902 -you would not. -And under the LIFO method, if that's what 438 00:28:22,902 --> 00:28:23,642 you applied here, 439 00:28:24,402 --> 00:28:28,642 you would conclude that OpenAI would not have spent the 25 million that you 440 00:28:28,642 --> 00:28:32,002 analyzed until sometime after November '17, right? 441 00:28:34,202 --> 00:28:39,942 You would have concluded that OpenAI did not spend the 25 million that you analyzed 442 00:28:39,942 --> 00:28:43,362 until sometime after November 2017, correct? 443 00:28:43,362 --> 00:28:47,721 Well, I wouldn't apply LIFO, but, um, if one did apply LIFO, 444 00:28:48,362 --> 00:28:51,602 it would give you a different answer, and it would be later in time than what I 445 00:28:51,602 --> 00:28:53,941 -concluded. -Thank you. 446 00:28:55,722 --> 00:29:00,002 Now, your FIFO analysis that you did perform, you focused on only the 25 447 00:29:00,002 --> 00:29:02,962 million that you call the quarterly contributions, right? 448 00:29:02,962 --> 00:29:05,682 -That's correct. -And your analysis, therefore, didn't 449 00:29:05,682 --> 00:29:10,402 analyze the more than 12 million that Mr. Musk contributed in rent, right? 450 00:29:10,582 --> 00:29:15,421 Not using, um, FIFO. I used a different approach with respect to the, um, rents 451 00:29:15,422 --> 00:29:18,801 -because of the data available. -Correct. So your, your FIFO analysis did 452 00:29:18,802 --> 00:29:19,802 not include that amount. 453 00:29:20,682 --> 00:29:24,742 That's correct. The FIFO analysis was with respect to the 25 million of quarterly 454 00:29:24,742 --> 00:29:28,582 -contributions. -And if you had included the other amounts 455 00:29:28,582 --> 00:29:31,742 that you did not include, you would have come to the conclusion that the 456 00:29:31,742 --> 00:29:36,162 contributions were not spent until sometime after September 2020. Isn't that 457 00:29:36,162 --> 00:29:36,342 right? 458 00:29:37,282 --> 00:29:40,322 I'm not sure I understand your question because, um, 459 00:29:40,942 --> 00:29:45,602 I did do an analysis of the rent-related payments, and I drew conclusions as to 460 00:29:45,602 --> 00:29:51,332 when those, um, took place from a time period perspective. So I, I, I wouldn't 461 00:29:51,332 --> 00:29:54,622 have included them in a FIFO analysis given the data that I had. 462 00:29:54,622 --> 00:29:57,992 I, I understand that you did not include them in the FIFO analysis. My question is, 463 00:29:57,992 --> 00:30:00,702 if you had included the rent-related contributions- 464 00:30:00,702 --> 00:30:02,862 -Sure -... in the FIFO analysis, your conclusion 465 00:30:02,862 --> 00:30:07,182 under that analysis would, that Mr. -- would be that Mr. Musk's contributions had 466 00:30:07,182 --> 00:30:09,802 not been spent until sometime after September '20. 467 00:30:11,002 --> 00:30:14,222 -Just mathematically, that's correct. -Thank you. No further... Or 468 00:30:14,222 --> 00:30:14,942 cross-intelligence. 469 00:30:17,782 --> 00:30:19,262 No further questions. Thank you, Mr. Dudney. 470 00:30:19,262 --> 00:30:19,622 Thank you. 471 00:30:20,622 --> 00:30:24,502 -Okay. Anything from Microsoft? -Nothing from Microsoft, no. 472 00:30:24,502 --> 00:30:25,981 Your Honor, 60 seconds, if I may. 473 00:30:26,842 --> 00:30:28,742 I'll give you 60. You're already over. 474 00:30:32,158 --> 00:30:36,438 Thank you, Your Honor. M-Mr. Dudding, very briefly, why did you not use the LIFO 475 00:30:36,438 --> 00:30:37,038 methodology? 476 00:30:38,298 --> 00:30:44,378 Well, it, it... I concluded that it was a inappropriate methodology given the 477 00:30:44,378 --> 00:30:49,408 pattern that one can easily see that was, in actuality, taking place. It... This was 478 00:30:49,408 --> 00:30:54,498 a startup company. It would fund itself, um, make payments with that funding, then 479 00:30:54,498 --> 00:30:58,408 seek additional funding, and that is a first in, first out, um, 480 00:30:59,098 --> 00:31:04,918 demonstration if I've ever seen it. And so that, uh, was very impactful to my 481 00:31:04,918 --> 00:31:08,118 determination, was, uh, the nature of the company and seeing its actual 482 00:31:08,118 --> 00:31:12,238 -transactional activity. -And based on your 37 years of experience 483 00:31:12,238 --> 00:31:15,818 as a forensic accountant, do you have any doubt that FIFO was the appropriate 484 00:31:15,818 --> 00:31:18,458 -methodology here? -N-none whatsoever. 485 00:31:18,458 --> 00:31:19,538 Nothing further, Your Honor. Thank you. 486 00:31:20,198 --> 00:31:20,998 Anything on that? 487 00:31:21,618 --> 00:31:23,478 -Nothing further, Your Honor. Thank you. -Okay. 488 00:31:24,438 --> 00:31:27,218 Nothing from Microsoft? Nothing from Microsoft, Your Honor. Thank you. All 489 00:31:27,218 --> 00:31:29,798 -right. Mr. Dudding, you're excused. -Thank you, Your Honor. 490 00:31:30,958 --> 00:31:32,238 Uh, OpenAI rest. 491 00:31:34,418 --> 00:31:34,878 Yes, Your 492 00:31:35,478 --> 00:31:37,017 -Honor. -Microsoft. Yes, Your Honor. 493 00:31:38,358 --> 00:31:39,318 No rebuttal case? 494 00:31:40,798 --> 00:31:41,218 All right. 495 00:31:42,058 --> 00:31:42,398 No, Your Honor. 496 00:31:42,998 --> 00:31:46,558 Members of the jury, that concludes the evidentiary portion- 497 00:31:47,258 --> 00:31:50,368 [clears throat] ... of the trial. So tomorrow, 498 00:31:51,218 --> 00:31:51,228 uh, 499 00:31:51,878 --> 00:31:54,208 I will give you, uh, instructions, 500 00:31:54,938 --> 00:31:56,438 and then you will get arguments. 501 00:31:57,478 --> 00:31:59,738 Uh, I will remind you tomorrow that, 502 00:32:00,798 --> 00:32:05,118 uh, I don't know, way at the beginning of all of this when we were together, I 503 00:32:05,118 --> 00:32:06,558 remember I used that puzzle 504 00:32:07,378 --> 00:32:08,058 analogy. 505 00:32:08,698 --> 00:32:10,998 All the pieces of the puzzle are now in the box, 506 00:32:12,178 --> 00:32:16,338 and tomorrow, the attorneys are gonna make arguments again to you 507 00:32:16,718 --> 00:32:21,358 to explain to you what they now believe that box shows. Ultimately, 508 00:32:22,008 --> 00:32:25,538 you'll go into that jury room, and you'll take all that evidence, all those puzzle 509 00:32:25,578 --> 00:32:25,918 pieces, 510 00:32:27,078 --> 00:32:28,358 and you'll figure it out for yourself. 511 00:32:29,158 --> 00:32:29,458 Okay? 512 00:32:30,478 --> 00:32:31,418 Any questions? 513 00:32:32,678 --> 00:32:32,818 No? 514 00:32:34,318 --> 00:32:37,778 All right. A few smiles. I see some smiles. That's good. 515 00:32:38,808 --> 00:32:41,677 And we'll stand in recess with the jury until eight thirty tomorrow morning. 516 00:32:42,558 --> 00:32:43,758 Please rise for the jury. 517 00:32:57,638 --> 00:33:10,498 Okay. 518 00:33:10,498 --> 00:33:13,358 The record will reflect that the jury has 519 00:33:14,598 --> 00:33:15,038 left. 520 00:33:16,998 --> 00:33:20,958 We have some cleanup things to do, so let's go ahead and do those now. 521 00:33:26,798 --> 00:33:30,738 Mr. Cry, you wanna start? Oh, wait, before you start, Mr. Knitt. 522 00:33:31,438 --> 00:33:36,878 My apologies for confusing you with your colleague. You were not on my list. 523 00:33:36,878 --> 00:33:39,398 -Oh. -And you are both about the same height, 524 00:33:40,198 --> 00:33:43,898 -same... -I, I'll take that as a compliment. Walter 525 00:33:43,898 --> 00:33:46,458 -might be a little offended. -All right. Good enough. 526 00:33:46,458 --> 00:33:46,638 Good. 527 00:33:49,318 --> 00:33:50,398 Um, okay. 528 00:33:50,478 --> 00:33:53,978 -Mr. Cry. -Your Honor, the only, uh, small item we 529 00:33:53,978 --> 00:33:58,458 had left was, uh, just to, uh, communicate to the court the parties' plan for 530 00:33:58,458 --> 00:34:02,938 handling the, uh, excerpt transcripts for the various videos that were played at 531 00:34:02,938 --> 00:34:03,218 trial. 532 00:34:03,858 --> 00:34:08,338 Following discussions with the court reporter, the plan is to, uh, submit, 533 00:34:09,038 --> 00:34:12,578 um, copies of the clip reports, which will be stamped as trial exhibits, 534 00:34:13,198 --> 00:34:18,158 and then our understanding is that, uh, those will not go back to the jury room 535 00:34:18,158 --> 00:34:22,958 absent further order of the court. [clears throat] 536 00:34:25,678 --> 00:34:29,798 We've been asked that there's no need to, um, indicate that they've been marked for 537 00:34:29,798 --> 00:34:32,408 -identification only. -Okay. Everybody agreed? 538 00:34:33,278 --> 00:34:34,838 -Uh, yes, Your Honor. -Yes, Your Honor. 539 00:34:34,838 --> 00:34:35,178 Okay. 540 00:34:36,398 --> 00:34:37,877 Uh, all right. What else 541 00:34:38,518 --> 00:34:39,938 do you want to do today 542 00:34:40,998 --> 00:34:43,678 so that I can release you to go work on closings? 543 00:34:45,898 --> 00:34:46,038 Uh, 544 00:34:48,518 --> 00:35:02,858 Your 545 00:35:02,858 --> 00:35:06,438 Honor, my colleagues asked me to confirm the duration of time we will have for 546 00:35:06,438 --> 00:35:10,418 -closing arguments tomorrow. -Uh, you all, um, have 547 00:35:10,938 --> 00:35:12,858 plenty of time. So, uh, 548 00:35:15,558 --> 00:35:15,638 w- 549 00:35:16,338 --> 00:35:17,838 because I, um... 550 00:35:20,218 --> 00:35:23,518 I mean, it's over two hours for both plaintiffs and defense. 551 00:35:24,838 --> 00:35:27,838 Uh, that is the OpenAI defendants. And then, um, 552 00:35:29,778 --> 00:35:31,958 O- uh, Microsoft had said 553 00:35:33,398 --> 00:35:35,278 forty-one, and 554 00:35:37,758 --> 00:35:41,398 if you need a little bit more time, I don't think you used all your allocation. 555 00:35:41,398 --> 00:35:43,818 So I, I think you all have plenty of time. 556 00:35:45,158 --> 00:35:47,398 I can send you the final number if you want by email. 557 00:35:48,958 --> 00:35:51,678 Thank you. Thank you, Your Honor. I think we have a pretty good idea based on that. 558 00:35:51,678 --> 00:35:55,798 -Okay. Anything, Mr. Cry? -Nothing else from plaintiff, Your Honor. 559 00:35:55,798 --> 00:35:56,058 Thank you. 560 00:35:56,988 --> 00:36:00,358 -Uh, nothing from the OpenAI defendants. -Nothing from Microsoft. Thank you. 561 00:36:00,358 --> 00:36:03,658 Okay. Then we will see you tomorrow, and we'll stand in recess until eight AM. 562 00:36:03,658 --> 00:36:03,998 Thank you. 563 00:36:05,198 --> 00:36:06,038 Court is in recess. 564 00:36:10,858 --> 00:36:12,418 -Should probably just leave our stuff. -Yep, yeah. 565 00:36:14,498 --> 00:36:32,678 [background chattering] 566 00:39:55,738 --> 00:42:21,878 [background noise]