WEBVTT

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mathematically, if you freeze everything
in place,

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-then yes, that's correct.
-Thank you.

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-But that's not actually what happened.
-You didn't do any analysis to determine

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whether that twenty percent increase was
commercially justified, correct?

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Um, I did. I, I read everything that
Professor Schizer said and wrote about,

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and I analyzed his analysis, and I brought
to bear my experience in reaching the

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conclusion that it was a perfectly
reasonable, um, business transaction for

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the for-profit to put into place.

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Professor Coates, you wrote an expert
report in this case, correct?

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-I did.
-And that report contained your entire

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analysis?

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No, it contained the entire analysis as of
the date of the report, which was after

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Professor Schizer's first report, but
before his second report and before his

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-testimony in this case.
-And just to be clear, Professor Schizer

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talked about the twenty percent TRA
increase in his first report, right?

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-Uh, he did. So did I in my rebuttal.
-And in your rebuttal, the only mention of

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the twenty percent TRA increase is in one
background paragraph on, in paragraph

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twenty?

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Um, I, I haven't memorized my report with
that level of specificity. Um, I don't

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actually think that's true because I do
have a figure and a table which reflect

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the TRAs, including the total structure of
the TRAs over time.

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And, and that figure doesn't take account
of the twenty percent increase in twenty

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-twenty-five, does it?
-Because we never got to twenty

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-twenty-five.
-Thank you, Professor Coates. Uh, court's

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indulgence, Your Honor.

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-No, I think you probably are done here.
-Thank you, Judge.

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Microsoft?

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-No questions from Microsoft.
-Any

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rebuttal?

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-Very quickly.
-Or reexamination?

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Thank you.

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-You too are very short.
-Appreciate that.

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Yeah, I'm on a clock too. Professor
Coates, a couple of quick questions. Thank

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you. Counsel made reference to your
previous employment at the Wachtell Lipton

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-firm. You recall that?
-Yes.

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-That was about thirty years ago.
-Correct.

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Um, so long ago that you and I never even
overlapped at the firm, and I'm an old

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guy.

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-[laughing]
-We did not overlap-

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-Right
-... at all.

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And in the years since, you've often been
on the other side of Wachtell Lipton in

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-litigation, isn't that true?
-Correct. You're right.

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Ha-have you worked for both defendants and
plaintiffs as an expert?

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In-- Across a whole range of cases on both
sides, correct.

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Do you work for a wide range of law firms
and clients in that capacity?

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I do. I work for dozens of law firms,
including Quinn Emanuel, which is Mr.

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-Musk's primary outside law firm.
-Objection, Your Honor.

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-Overruled.
-Now, y-

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counsel made reference to your work in a
Twitter case. Do you recall that?

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-I do.
-Uh, that case was from twenty twenty.

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Correct.

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Uh, Mr. Musk didn't even own Twitter until
twenty twenty-two, isn't that right? Or

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-twenty twenty-three.
-That's right. At the time of that case, he

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-had no connection to Twitter.
-And counsel suggested that the Wachtell

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Lipton firm was somehow involved in that
lawsuit.

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-They were not. You were not.
-Was Wachtell Lipton involved in that

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-lawsuit at all?
-No.

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So the suggestion that it was was
inaccurate, correct?

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-Correct.
-Did any of all this have anything to do

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-with the substance of your opinions?
-No. I would be-- I am confident I would

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give you the same opinions without regard
to any of the things you just asked me

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-about.
-Nothing more. Thank you.

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Professor, you are excused.

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Let me see the, uh, lawyers at sidebar,
please.

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Not, not you. The primary lawyers.

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Okay,

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-next ones.
-Uh, Your Honor, the OpenAI defendants call

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Lewis Dudney.

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Please remain standing and raise your
right hand to be sworn, sir.

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You solemnly swear or affirm that the
testimony you're about to give before this

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court and jury shall be the truth, the
whole truth, and nothing but the truth, so

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help you God, or so you affirm. Please
say, "I do," or, "I affirm."

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I do.

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Thank you, sir.

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Please be seated. Speak clearly into the
microphone. Please state your full name

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and spell out your last name for the
record.

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My name is Lewis Dudney, and my last name
is spelled D-U-D-N-E-Y.

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-Thank you, sir.
-Good afternoon.

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-Good afternoon.
-You may proceed.

cue-80
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-Good afternoon, Mr. Dudney.
-Good afternoon.

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What do you do for a living?

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Uh, I'm a forensic accountant.

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And what does a forensic accountant do?

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Forensic accountants study financial and
accounting information, uh, to try and

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help, uh, juries or courts understand, um,
the implications of that in a litigated

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case, most typically.

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And how long have you worked as a forensic
accountant, sir?

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-37 years.
-Uh, Mr. Dudney, I understand that you've

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prepared a slide with some of your
qualifications. Would it be helpful to put

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-that on the screen?
-Yes.

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Okay.

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And for the record, this is DDX10.

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Mr. Dudney, do you hold any advanced
degrees?

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Yes, I have a BBA with a concentration in
accounting.

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-And where did you get that degree, sir?
-From William & Mary.

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Do you hold any certifications relevant to
your work as a forensic accountant?

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I do. I hold two. Uh, one is that I'm a
licensed and certified public accountant,

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and then I also am recognized by the
American Institute of Certified Public

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Accountants as certified in financial
forensics.

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Has a court ever qualified you as a
forensic accounting expert, Mr. Dudney?

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Many times.

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H- how many times throughout your career
have you been, um, offered testimony, uh,

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financial testimony, in a case in which
you applied forensic accounting

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-principles?
-Over 75 times.

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Uh, were you retained by counsel for the
OpenAI defendants in this case?

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-Yes, I was.
-And what was your assignment, Mr. Dudney,

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at a, at a high level?

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At a high level, it was to determine, um,
when, uh, the various donations or

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contributions that were claimed by Mr.
Musk were made. It was to determine when

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those donations were spent, uh, for the
cash donations,

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and then it was als- also to determine
how, um, that money was used.

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Uh, Mr. Dudney, did you bill for your time
spent on that assignment?

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-I did.
-Uh, and what was the rate that you

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-charged?
-$1,475 per hour.

cue-115
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And is that your customary rate, Mr.
Dudney?

cue-116
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It is.

cue-117
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Did you review any documents or other
materials to help form the opinions you're

cue-118
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-prepared to offer today, sir?
-A, a number of documents, yes.

cue-119
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Again, at a high level, recognizing that
we're on a clock, uh, could you describe

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-the kinds of documents you looked at?
-Sure. I looked at tax returns. I looked at

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bank statements. I looked at, uh,
underlying accounting records, which are

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referred to the, as the general ledger. I
looked at contemporaneous correspondence.

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I looked at agreements such as lease
agreements, invoices, things of that

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nature.

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I see, and, and you mentioned the general
ledger. That was the general ledger for

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-which entity, sir?
-It's for OpenAI.

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-Yeah. The, the nonprofit?
-Yes, OpenAI, Inc.

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Um, are the opinions you're prepared to
offer today,

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uh, based on recognized principles of
accounting?

cue-130
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-Yes.
-And did you re- reliably a- apply those

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-principles to form your opinion, sir?
-Yes.

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Okay. Uh, at this time, Your Honor, we
would offer Mr. Dudney as an expert in

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forensic accounting.

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Is th- any objection?

cue-135
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-No objection, Your Honor.
-He's admin.

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Okay.

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Um,

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M- Mr. Dudney, you said that you reviewed
Mr. Musk's financial contributions to the

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-OpenAI nonprofit, correct?
-Yes, I did.

cue-140
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Uh, according to your analysis, how, how
much money did Mr. Musk contribute to

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OpenAI, Inc?

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Uh, approximately 37.799 million.

cue-143
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Uh, and I believe you've prepared a slide,
which is already on the screen, uh, of,

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of the categories of contributions you
saw. Is, is that correct?

cue-145
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Yes. This slide is a summary of the, uh,
contributions that I was able to identify.

cue-146
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And that's DDX11, correct?

cue-147
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-Correct.
-Okay. Um, w- were the contributions that

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Mr. Musk provided to OpenAI all of the
same kind?

cue-149
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-No.
-Um, what sorts of contributions did Mr.

cue-150
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Musk make to OpenAI, based on your
analysis?

cue-151
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So I've grouped them on this slide into
three categories. Um, the first category,

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which represents $25 million worth of
contributions,

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is referred to here as, uh, quarterly
contributions.

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Um, the second category, which equals
approximately 12.5 million, that, uh,

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relates to, uh, what are described as
rent-related contributions.

cue-156
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And then the third category is, um,
$262,400 related to

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four Tesla cars and an upgrade or some
upgrades to one of those cars, and that's

cue-158
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an in-kind, um, uh, contribution, meaning
non-cash.

cue-159
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Okay. Um, we can take that down. Thank
you. I'd, I'd like to just talk in a

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little bit more detail with you, Mr.
Dudney, about the cash contributions.

cue-161
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Uh, and to do that, Your Honor, we'd like
to, um, introduce into evidence DX1304.

cue-162
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It's a summary exhibit that's been
stipulated.

cue-163
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-So moved.
-Okay, I need to hand it up to Mr. Cuenco.

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You may.

cue-165
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May I approach, Your Honor?

cue-166
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Thank you.

cue-167
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Thank you.

cue-168
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Okay. Uh, we can put that up, Your Honors.

cue-169
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Uh, Mr. Dudney, you've seen this exhibit
before?

cue-170
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-Yes.
-Okay. What, what does it show?

cue-171
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It shows the cash contributions, um,

cue-172
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demonstrating both the size of those
contributions and the timing of those

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contributions.

cue-174
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Um,

cue-175
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and it d- differentiates between the first
two categories of contributions that were

cue-176
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made in cash that I just discussed a
moment ago.

cue-177
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A- and just for the jury's benefit again,
what, what are those two categories that

cue-178
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-are on this slide?
-So the green bars to the left-hand side

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that are significantly larger, those are
the quarterly contributions, which equal

cue-180
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$25 million. And then the smaller, more
frequent red bars at the bottom, those are

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the rent-related monetary contributions
that I identified.

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And Mr. Dudney, if you could,

cue-183
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did your analysis, uh,

cue-184
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reveal an answer to the following
question: Why, uh, are some of the green

cue-185
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bars larger than others?

cue-186
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Y-y-yes, it's simply a timing, um, uh,
i-issue. And so you can see that, uh, if

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you look at the bottom, uh, you'll see
that some of the green bars are stacked on

cue-188
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little, little red bars, and in other
cases they're not. And so that affects if

cue-189
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you look at the top, um, where the total
funding, if you will, of both, uh, the

cue-190
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green bars and the red bars, um, would
fall, uh, but it's just simply a

cue-191
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presentation, um, question.

cue-192
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Um, and, uh, focusing now on the red bars,
how did you determine, sir, that the red

cue-193
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bars were all rent-related contributions?

cue-194
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So I looked at, um, a variety of
documents, starting with the lease

cue-195
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agreement, um, that, uh, was signed. I
looked at a sublease agreement related to

cue-196
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these payments. I looked at rent invoices.
I looked at, um, cash contributions,

cue-197
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which from a timing perspective and an
amount perspective were consistent with

cue-198
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the lease payments that were called for
under the agreement. And then I also

cue-199
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looked at the payments that OpenAI made to
the landlord to understand that there

cue-200
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was,

cue-201
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um, uh, a, a relationship, if you will,
between all of these things, demonstrating

cue-202
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that the payments that OpenAI was making,
um, were rent-related, and that these

cue-203
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contributions that are shown here were
rent-related contributions.

cue-204
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Okay, thank you. We, we can take that
down.

cue-205
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Uh, drilling down just one more layer, uh,
Mr. Dudney, I'd like to talk briefly

cue-206
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about the quarterly donations in
particular.

cue-207
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-Okay.
-Um,

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based on your analysis, where did OpenAI
Inc. put Mr. Musk's quarterly donations?

cue-209
00:13:47.316 --> 00:13:51.886
In-into the business checking account
that, uh, OpenAI had opened.

cue-210
00:13:51.886 --> 00:13:56.275
And did OpenAI Inc. maintain a separate
checking account for Mr. Musk's donations?

cue-211
00:13:56.275 --> 00:13:58.836
No, not a separate one just for Mr. Musk's

cue-212
00:13:58.836 --> 00:13:59.576
donations.

cue-213
00:14:00.256 --> 00:14:05.256
Okay, and what other sorts of, uh, funds
flo-flowed into that checking account?

cue-214
00:14:05.256 --> 00:14:08.476
So there were der-donations from other
entities that went to that checking

cue-215
00:14:08.476 --> 00:14:13.156
account, and then that checking account
also was the, uh, primary source for

cue-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

cue-217
00:14:18.756 --> 00:14:19.795
in operating its business.

cue-218
00:14:20.836 --> 00:14:24.406
Now, Mr. Dudney, you, you testified
earlier that part of your s-assignment was

cue-219
00:14:24.406 --> 00:14:28.976
figuring out when the nonprofit spent Mr.
Musk's donations. Is that correct?

cue-220
00:14:28.976 --> 00:14:32.776
-Yes.
-Okay. Did the fact that OpenAI Inc. put

cue-221
00:14:32.776 --> 00:14:37.836
all of Mr. Musk's donations into the same
checking account as other donations affect

cue-222
00:14:37.836 --> 00:14:40.076
-that analysis in any way?
-It did.

cue-223
00:14:40.076 --> 00:14:40.996
And, and how was that, sir?

cue-224
00:14:41.676 --> 00:14:46.496
So when monies from different sources are
put into the same, uh, account, uh,

cue-225
00:14:46.496 --> 00:14:52.856
accountants will describe that as a, a
commingling of funds. And so there were,

cue-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

cue-227
00:14:58.826 --> 00:15:03.156
the same account, which is a normal
practice, but it commingles the money from

cue-228
00:15:03.156 --> 00:15:07.516
that perspective. So that impacts then
the, um, sort of analysis that, um, I

cue-229
00:15:07.516 --> 00:15:08.156
engage in.

cue-230
00:15:08.916 --> 00:15:12.936
And did you engage in any particular
accounting analysis to sort through the

cue-231
00:15:12.936 --> 00:15:15.196
-commingling you just described?
-I did.

cue-232
00:15:15.196 --> 00:15:16.916
And, and what was that analysis that you
did?

cue-233
00:15:17.556 --> 00:15:22.716
So accountants refer to the type of
analysis, uh, that I did as a FIFO

cue-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

cue-235
00:15:28.876 --> 00:15:29.876
out.

cue-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

cue-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

cue-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

cue-239
00:15:45.716 --> 00:15:48.786
the monies were, um, donated to OpenAI.

cue-240
00:15:50.296 --> 00:15:51.616
Okay, thank you, Mr. Dudney.

cue-241
00:15:52.356 --> 00:15:56.696
Um, why did you decide to use FIFO in this
particular analysis?

cue-242
00:15:57.316 --> 00:16:01.736
So there were a couple of reasons. Uh, one
is that I had detailed data,

cue-243
00:16:01.736 --> 00:16:05.636
transaction-level data with respect to
OpenAI's funding,

cue-244
00:16:06.256 --> 00:16:08.036
its, um, expenditures,

cue-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

cue-246
00:16:13.996 --> 00:16:15.186
was a, a first, um,

cue-247
00:16:15.876 --> 00:16:20.376
important determination because you need
detailed data to do the analysis I did.

cue-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

cue-249
00:16:26.566 --> 00:16:26.566
, uh,

cue-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

cue-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

cue-252
00:16:40.356 --> 00:16:42.366
that the company would go out, get some
funding,

cue-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

cue-254
00:16:48.336 --> 00:16:52.696
might use the analogy of it was, um, in
the early days, living paycheck to

cue-255
00:16:52.696 --> 00:16:56.356
-paycheck in that regard.
-A-and Mr. Dudney, I understand that you

cue-256
00:16:56.356 --> 00:16:59.676
created a slide to show the phenomenon you
were just describing. Is that right?

cue-257
00:16:59.676 --> 00:17:01.575
-Yes.
-Okay. It would be helpful to put that up.

cue-258
00:17:01.576 --> 00:17:02.936
-Please.
-Okay, let's do that, please.

cue-259
00:17:04.036 --> 00:17:05.516
And this will be DDX-12.

cue-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

cue-261
00:17:11.856 --> 00:17:14.956
balance of OpenAI's checking account.

cue-262
00:17:15.596 --> 00:17:22.536
And so it covers a two-year period from
January 2016 through December 2017,

cue-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

cue-264
00:17:26.536 --> 00:17:30.006
just simply shows, um, how that balance,
uh,

cue-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

cue-266
00:17:36.056 --> 00:17:36.996
this two-year period.

cue-267
00:17:37.606 --> 00:17:42.276
A-and did this checking account, uh, or at
least this representation of the balance

cue-268
00:17:42.276 --> 00:17:45.876
of the checking account, include all of
the donations OpenAI received during this

cue-269
00:17:45.876 --> 00:17:48.075
-period?
-All of the cash donations, yes.

cue-270
00:17:48.076 --> 00:17:51.515
In other words, just to be clear, not, not
limited to Mr. Musk, correct?

cue-271
00:17:51.516 --> 00:17:55.536
C-correct. This would include donations by
others during this time period as well.

cue-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

cue-273
00:17:59.376 --> 00:18:02.616
best way to do your analysis, did you
draw any conclusions from what you

cue-274
00:18:02.616 --> 00:18:03.036
observed?

cue-275
00:18:03.976 --> 00:18:04.426
Yes. This,

cue-276
00:18:05.376 --> 00:18:10.396
this actual, um, funding, then spending,
then funding, then spending pattern was

cue-277
00:18:10.396 --> 00:18:16.436
consistent with my use of a FIFO
methodology for purposes of, um, analyzing

cue-278
00:18:16.436 --> 00:18:20.196
how, uh, Mr. Musk's donations were used.

cue-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,

cue-280
00:18:26.126 --> 00:18:30.206
that ultimately you were asked to figure
out when Mr. Musk's quarterly donations

cue-281
00:18:30.206 --> 00:18:32.245
-had been spent, correct?
-That's correct.

cue-282
00:18:32.246 --> 00:18:32.406
Okay.

cue-283
00:18:33.026 --> 00:18:38.086
Um, based on your application of, of the
FIFO analysis, were you able to isolate

cue-284
00:18:38.706 --> 00:18:42.166
the balance of Mr. Musk's quarterly
contributions to OpenAI

cue-285
00:18:42.786 --> 00:18:45.705
-as distinct from donations from others?
-Yes.

cue-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

cue-287
00:18:49.246 --> 00:18:50.336
-subject, sir?
-That's correct.

cue-288
00:18:50.336 --> 00:18:52.306
-Would it be helpful to put that up?
-Please.

cue-289
00:18:52.306 --> 00:18:53.106
Great. Let's do that.

cue-290
00:18:55.486 --> 00:18:58.456
And this is DDX, uh, 13.1.

cue-291
00:18:59.226 --> 00:19:01.346
Uh, are you familiar with this chart, Mr.
Dudney?

cue-292
00:19:01.346 --> 00:19:03.266
-Yes, I am.
-And what does it depict?

cue-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

cue-294
00:19:10.256 --> 00:19:16.886
the Musk-related quarterly cash donations.
And so this shows the balance of that

cue-295
00:19:16.886 --> 00:19:19.876
element of OpenAI's cash funding.

cue-296
00:19:21.066 --> 00:19:23.066
And Mr. Dudney, you'll see, um,

cue-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

cue-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

cue-299
00:19:31.826 --> 00:19:33.026
happening at that point in the chart.

cue-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

cue-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

cue-302
00:19:43.686 --> 00:19:48.626
zero until it hits roughly June of 2016.
Then there's a small little stairstep

cue-303
00:19:48.626 --> 00:19:53.786
there, and that is the, um, recognition of
the first contribution that is made, uh,

cue-304
00:19:53.786 --> 00:19:56.296
related to Mr. Musk for $500,000.

cue-305
00:19:56.926 --> 00:20:01.886
Then you'll see another stairstep, um,
take you up to about $5.5 million,

cue-306
00:20:02.566 --> 00:20:08.326
um, and that, uh, is recognition of the
second, uh, significant quarterly

cue-307
00:20:08.326 --> 00:20:11.086
contribution that was made of, um, $5
million.

cue-308
00:20:12.086 --> 00:20:15.306
And, and then Mr. Dudney, what, what
happened after that, uh, over the next

cue-309
00:20:15.306 --> 00:20:16.606
several months in 2016?

cue-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

cue-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

cue-312
00:20:26.006 --> 00:20:31.685
line was just superimposed, that, that
shows the usage of that, um, funding that

cue-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

cue-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

cue-315
00:20:41.526 --> 00:20:46.186
-pattern then repeating itself over time.
-And Mr. Dudney, if I could now focus you

cue-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

cue-317
00:20:52.106 --> 00:20:55.326
explain to the jury what you observed
based on your analysis in that time

cue-318
00:20:55.326 --> 00:20:55.566
period?

cue-319
00:20:56.386 --> 00:21:01.006
So from May to July of 2017, you'll see
the line goes to zero,

cue-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

cue-321
00:21:05.866 --> 00:21:11.606
previous funding that Mr. Musk had
provided, um, had been used. And so what's

cue-322
00:21:11.606 --> 00:21:17.826
happening during that period is OpenAI is
funding itself with the, um, most recent

cue-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

cue-324
00:21:22.106 --> 00:21:27.026
they were able to operate in that window,
for example, despite not having

cue-325
00:21:27.026 --> 00:21:28.086
Musk-related money.

cue-326
00:21:29.006 --> 00:21:32.826
A- and then the, the line changes again in
July 2017, correct?

cue-327
00:21:32.826 --> 00:21:34.686
-Correct.
-A- and, and what, what is happening at

cue-328
00:21:34.686 --> 00:21:38.926
-that point, Mr. Dudney?
-M- Mr. Musk makes what is his last, um,

cue-329
00:21:38.926 --> 00:21:41.406
quarterly contribution for $5 million.

cue-330
00:21:44.026 --> 00:21:47.766
Uh, thank you. Um, and then from that
point, uh, Mr. Dudney, over the next

cue-331
00:21:47.766 --> 00:21:49.786
several months, the line is, is flat.

cue-332
00:21:50.406 --> 00:21:52.266
-Am I reading this correctly?
-Yes.

cue-333
00:21:52.266 --> 00:21:57.066
-And can you explain why that is, sir?
-Uh, essentially, Mr. Musk's money is

cue-334
00:21:57.066 --> 00:22:03.266
waiting in line, if you will, until the
previously donated money is used, um, for

cue-335
00:22:03.266 --> 00:22:08.966
purposes of my analysis. So you'll see
that that $5 million balance reflects that

cue-336
00:22:08.966 --> 00:22:15.106
concept of, um, Mr. Musk's money waiting
in line until, um, the just-previous

cue-337
00:22:15.106 --> 00:22:18.126
donor's money is, uh, used up.

cue-338
00:22:18.486 --> 00:22:21.006
Okay, thank you very much. And my
apologies for honor mic.

cue-339
00:22:22.086 --> 00:22:22.646
My apologies.

cue-340
00:22:23.386 --> 00:22:26.586
Uh, and then, um, what happens after that,
Mr. Dudney?

cue-341
00:22:26.586 --> 00:22:29.846
So you see then a very, uh, steep decline,

cue-342
00:22:30.526 --> 00:22:36.686
um, taking place after that, uh, flat area
that is, um, highlighted with the red

cue-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,

cue-344
00:22:42.386 --> 00:22:43.526
last donation

cue-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

cue-346
00:22:49.946 --> 00:22:54.226
month to month. Uh, and so it eats through
that funding quite quickly.

cue-347
00:22:54.886 --> 00:22:58.706
And Mr. Dudney, to sort of land the plane
here, um, based on your forensic

cue-348
00:22:58.706 --> 00:23:03.386
accounting analysis and application of
FIFO, when did you determine that OpenAI,

cue-349
00:23:03.386 --> 00:23:08.066
Inc., uh, completed spending Mr. Musk's
final quarterly donation?

cue-350
00:23:08.126 --> 00:23:09.626
November of 2017.

cue-351
00:23:11.606 --> 00:23:12.646
And we can take that down.

cue-352
00:23:14.626 --> 00:23:18.486
Thank you. Just a few final questions, Mr.
Dudney. Uh, you also explained that you

cue-353
00:23:18.486 --> 00:23:23.606
were asked to analyze the manner in which
the nonprofit spent Mr. Musk's, uh,

cue-354
00:23:24.986 --> 00:23:29.066
to analyze the manner in which the
nonprofit spent Mr. Musk's, uh, quarterly

cue-355
00:23:29.066 --> 00:23:31.165
-donations. Is that correct?
-Yes.

cue-356
00:23:31.166 --> 00:23:33.466
Okay. And how did you go about doing that
work, Mr. Dudney?

cue-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,

cue-358
00:23:39.006 --> 00:23:42.886
made up the analysis that was just
described. I also looked at then

cue-359
00:23:43.706 --> 00:23:49.686
financial statement information to
understand how the company itself, OpenAI,

cue-360
00:23:49.686 --> 00:23:54.426
categorized all the detailed transactions
that I had been analyzing.

cue-361
00:23:55.366 --> 00:23:58.446
See, and did you look at anything other
than the financial statements to do that

cue-362
00:23:58.446 --> 00:24:01.046
-analysis?
-I looked at the financial statements and

cue-363
00:24:01.046 --> 00:24:03.166
the, um, underlying transactions as well.

cue-364
00:24:04.546 --> 00:24:07.626
And when you looked at those, uh,
financial records, Mr. Dudney, what did

cue-365
00:24:07.626 --> 00:24:08.206
you observe?

cue-366
00:24:09.116 --> 00:24:13.546
Uh, I observed that, um, there were
several primary categories, if you will,

cue-367
00:24:13.546 --> 00:24:16.886
of how the money was spent, um, by OpenAI.

cue-368
00:24:16.886 --> 00:24:20.586
And from an accounting perspective, were
those expenses categorized in any way?

cue-369
00:24:21.336 --> 00:24:26.226
Th- they're, as, with respect to a, um, a
nonprofit, they're called functional

cue-370
00:24:26.226 --> 00:24:32.962
expenses.And that's just, um, accounting
terminology to describe, um,

cue-371
00:24:32.962 --> 00:24:38.742
expenses related to the business conduct,
if you will, of the, um, not-for-profit.

cue-372
00:24:39.362 --> 00:24:40.582
And, and again, just in, in

cue-373
00:24:41.242 --> 00:24:45.602
summary form, Mr. Dudney, what were the
categories of, of functional or operating

cue-374
00:24:45.602 --> 00:24:47.442
expenses that you saw OpenAI,

cue-375
00:24:48.162 --> 00:24:53.282
-uh, using its funds on in 2016 and 2017?
-So the primary categories were, um,

cue-376
00:24:53.282 --> 00:24:57.482
compute, which has been talked about as,
um, other witnesses have been mentioning.

cue-377
00:24:57.482 --> 00:25:02.702
Uh, it was salaries and compensation. It
was for professional fees and related

cue-378
00:25:02.702 --> 00:25:04.062
sorts of expenses like that.

cue-379
00:25:06.422 --> 00:25:08.802
Uh, thank you, Mr. Dudney. No further
questions. Thank you, Your Honor. Thank

cue-380
00:25:08.802 --> 00:25:09.182
-you.
-Thank you.

cue-381
00:25:10.942 --> 00:25:12.562
Cross by plaintiffs.

cue-382
00:25:22.102 --> 00:25:24.262
Good afternoon, Mr. Dudney. Walter Haas
for the plaintiff.

cue-383
00:25:25.002 --> 00:25:25.982
Good afternoon, Mr. Haas.

cue-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

cue-385
00:25:37.962 --> 00:25:39.022
claimed contributions,

cue-386
00:25:39.742 --> 00:25:42.542
uh, were in fact received by OpenAI,
correct?

cue-387
00:25:42.542 --> 00:25:43.262
That's correct.

cue-388
00:25:44.302 --> 00:25:47.602
And those funds were important to OpenAI
successfully running its business,

cue-389
00:25:47.602 --> 00:25:47.922
correct?

cue-390
00:25:49.722 --> 00:25:53.202
Uh, they were certainly a significant
portion of the early funding of his

cue-391
00:25:53.202 --> 00:25:55.882
-business.
-Okay. And you testified about how those

cue-392
00:25:55.882 --> 00:25:56.542
funds were spent.

cue-393
00:25:57.602 --> 00:26:00.542
-Yes.
-And OpenAI spent those funds on salaries

cue-394
00:26:00.542 --> 00:26:02.062
for the engineers and other employees.

cue-395
00:26:03.322 --> 00:26:05.442
-Yes.
-And it also spent those funds on the

cue-396
00:26:05.442 --> 00:26:08.602
compute that it used to develop its AI
software, right?

cue-397
00:26:08.602 --> 00:26:09.182
That's correct.

cue-398
00:26:11.022 --> 00:26:15.002
Now, that software, that intellectual
property, was a valuable asset for the

cue-399
00:26:15.002 --> 00:26:15.722
nonprofit, right?

cue-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

cue-401
00:26:20.462 --> 00:26:21.682
developed at that point in time.

cue-402
00:26:22.342 --> 00:26:26.661
Okay. And the nonprofit later transferred
that software that it developed with Mr.

cue-403
00:26:26.662 --> 00:26:30.022
-Musk's funds to the for-profit-
-Objection. Beyond the scope.

cue-404
00:26:33.282 --> 00:26:34.242
I'll withdraw the question, Your Honor.

cue-405
00:26:39.442 --> 00:26:44.282
Mr. Dudney, you testified that OpenAI
commingled Mr. Musk's donations with other

cue-406
00:26:44.282 --> 00:26:46.482
-donations, correct?
-That's correct.

cue-407
00:26:46.482 --> 00:26:51.322
And because OpenAI commingled his
donations in a single account, you can't

cue-408
00:26:51.322 --> 00:26:56.102
actually determine with specificity and
certainty when Elon's contributions were

cue-409
00:26:56.102 --> 00:26:58.772
spent versus the contributions from the
other donors, correct?

cue-410
00:26:59.422 --> 00:27:00.292
You can't, um,

cue-411
00:27:00.942 --> 00:27:05.362
specifically tie specific dollars. You
have to apply one of the forensic

cue-412
00:27:05.362 --> 00:27:07.982
accounting techniques that, uh, I talk
about.

cue-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

cue-414
00:27:11.682 --> 00:27:14.142
what Elon's contributions were spent on,
correct?

cue-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.

cue-416
00:27:18.682 --> 00:27:22.602
Thank you. And you used a method called
FIFO, right? First in, first out.

cue-417
00:27:23.422 --> 00:27:23.922
That's correct.

cue-418
00:27:24.822 --> 00:27:25.182
And

cue-419
00:27:28.162 --> 00:27:30.442
that's what you call a financial tracing
method, isn't it?

cue-420
00:27:31.302 --> 00:27:33.341
-Yes.
-All right. And there are numerous other

cue-421
00:27:33.342 --> 00:27:35.962
financial tracing methods that exist,
right?

cue-422
00:27:35.962 --> 00:27:36.502
That's correct.

cue-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

cue-424
00:27:42.542 --> 00:27:44.022
first money out of the account, correct?

cue-425
00:27:44.982 --> 00:27:47.842
-That's correct.
-But another financial tracing method is

cue-426
00:27:47.842 --> 00:27:50.621
last in, first out, or LIFO. Are you
familiar with that?

cue-427
00:27:50.682 --> 00:27:50.982
I am.

cue-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

cue-429
00:27:57.142 --> 00:27:58.782
-out, right?
-That's correct.

cue-430
00:27:58.782 --> 00:27:59.002
Okay.

cue-431
00:28:01.662 --> 00:28:04.932
And both of those are commonly used
financial tracing methods, right?

cue-432
00:28:04.932 --> 00:28:08.922
-They're both well-known, yes.
-Thank you. And if you applied LIFO here,

cue-433
00:28:08.922 --> 00:28:12.502
you would not have gotten the same result
regarding when Mr. Musk's contributions

cue-434
00:28:12.502 --> 00:28:13.182
were spent, would you?

cue-435
00:28:14.442 --> 00:28:17.982
A- as a matter of just mathematic
application of it, the answer is no.

cue-436
00:28:17.982 --> 00:28:19.841
-Thank you.
-I don't think it's the right one, but no,

cue-437
00:28:19.842 --> 00:28:22.902
-you would not.
-And under the LIFO method, if that's what

cue-438
00:28:22.902 --> 00:28:23.642
you applied here,

cue-439
00:28:24.402 --> 00:28:28.642
you would conclude that OpenAI would not
have spent the 25 million that you

cue-440
00:28:28.642 --> 00:28:32.002
analyzed until sometime after November
'17, right?

cue-441
00:28:34.202 --> 00:28:39.942
You would have concluded that OpenAI did
not spend the 25 million that you analyzed

cue-442
00:28:39.942 --> 00:28:43.362
until sometime after November 2017,
correct?

cue-443
00:28:43.362 --> 00:28:47.721
Well, I wouldn't apply LIFO, but, um, if
one did apply LIFO,

cue-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

cue-445
00:28:51.602 --> 00:28:53.941
-concluded.
-Thank you.

cue-446
00:28:55.722 --> 00:29:00.002
Now, your FIFO analysis that you did
perform, you focused on only the 25

cue-447
00:29:00.002 --> 00:29:02.962
million that you call the quarterly
contributions, right?

cue-448
00:29:02.962 --> 00:29:05.682
-That's correct.
-And your analysis, therefore, didn't

cue-449
00:29:05.682 --> 00:29:10.402
analyze the more than 12 million that Mr.
Musk contributed in rent, right?

cue-450
00:29:10.582 --> 00:29:15.421
Not using, um, FIFO. I used a different
approach with respect to the, um, rents

cue-451
00:29:15.422 --> 00:29:18.801
-because of the data available.
-Correct. So your, your FIFO analysis did

cue-452
00:29:18.802 --> 00:29:19.802
not include that amount.

cue-453
00:29:20.682 --> 00:29:24.742
That's correct. The FIFO analysis was with
respect to the 25 million of quarterly

cue-454
00:29:24.742 --> 00:29:28.582
-contributions.
-And if you had included the other amounts

cue-455
00:29:28.582 --> 00:29:31.742
that you did not include, you would have
come to the conclusion that the

cue-456
00:29:31.742 --> 00:29:36.162
contributions were not spent until
sometime after September 2020. Isn't that

cue-457
00:29:36.162 --> 00:29:36.342
right?

cue-458
00:29:37.282 --> 00:29:40.322
I'm not sure I understand your question
because, um,

cue-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

cue-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

cue-461
00:29:51.332 --> 00:29:54.622
have included them in a FIFO analysis
given the data that I had.

cue-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,

cue-463
00:29:57.992 --> 00:30:00.702
if you had included the rent-related
contributions-

cue-464
00:30:00.702 --> 00:30:02.862
-Sure
-... in the FIFO analysis, your conclusion

cue-465
00:30:02.862 --> 00:30:07.182
under that analysis would, that Mr. --
would be that Mr. Musk's contributions had

cue-466
00:30:07.182 --> 00:30:09.802
not been spent until sometime after
September '20.

cue-467
00:30:11.002 --> 00:30:14.222
-Just mathematically, that's correct.
-Thank you. No further... Or

cue-468
00:30:14.222 --> 00:30:14.942
cross-intelligence.

cue-469
00:30:17.782 --> 00:30:19.262
No further questions. Thank you, Mr.
Dudney.

cue-470
00:30:19.262 --> 00:30:19.622
Thank you.

cue-471
00:30:20.622 --> 00:30:24.502
-Okay. Anything from Microsoft?
-Nothing from Microsoft, no.

cue-472
00:30:24.502 --> 00:30:25.981
Your Honor, 60 seconds, if I may.

cue-473
00:30:26.842 --> 00:30:28.742
I'll give you 60. You're already over.

cue-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

cue-475
00:30:36.438 --> 00:30:37.038
methodology?

cue-476
00:30:38.298 --> 00:30:44.378
Well, it, it... I concluded that it was a
inappropriate methodology given the

cue-477
00:30:44.378 --> 00:30:49.408
pattern that one can easily see that was,
in actuality, taking place. It... This was

cue-478
00:30:49.408 --> 00:30:54.498
a startup company. It would fund itself,
um, make payments with that funding, then

cue-479
00:30:54.498 --> 00:30:58.408
seek additional funding, and that is a
first in, first out, um,

cue-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

cue-481
00:31:04.918 --> 00:31:08.118
determination, was, uh, the nature of the
company and seeing its actual

cue-482
00:31:08.118 --> 00:31:12.238
-transactional activity.
-And based on your 37 years of experience

cue-483
00:31:12.238 --> 00:31:15.818
as a forensic accountant, do you have any
doubt that FIFO was the appropriate

cue-484
00:31:15.818 --> 00:31:18.458
-methodology here?
-N-none whatsoever.

cue-485
00:31:18.458 --> 00:31:19.538
Nothing further, Your Honor. Thank you.

cue-486
00:31:20.198 --> 00:31:20.998
Anything on that?

cue-487
00:31:21.618 --> 00:31:23.478
-Nothing further, Your Honor. Thank you.
-Okay.

cue-488
00:31:24.438 --> 00:31:27.218
Nothing from Microsoft? Nothing from
Microsoft, Your Honor. Thank you. All

cue-489
00:31:27.218 --> 00:31:29.798
-right. Mr. Dudding, you're excused.
-Thank you, Your Honor.

cue-490
00:31:30.958 --> 00:31:32.238
Uh, OpenAI rest.

cue-491
00:31:34.418 --> 00:31:34.878
Yes, Your

cue-492
00:31:35.478 --> 00:31:37.017
-Honor.
-Microsoft. Yes, Your Honor.

cue-493
00:31:38.358 --> 00:31:39.318
No rebuttal case?

cue-494
00:31:40.798 --> 00:31:41.218
All right.

cue-495
00:31:42.058 --> 00:31:42.398
No, Your Honor.

cue-496
00:31:42.998 --> 00:31:46.558
Members of the jury, that concludes the
evidentiary portion-

cue-497
00:31:47.258 --> 00:31:50.368
[clears throat] ... of the trial. So
tomorrow,

cue-498
00:31:51.218 --> 00:31:51.228
uh,

cue-499
00:31:51.878 --> 00:31:54.208
I will give you, uh, instructions,

cue-500
00:31:54.938 --> 00:31:56.438
and then you will get arguments.

cue-501
00:31:57.478 --> 00:31:59.738
Uh, I will remind you tomorrow that,

cue-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

cue-503
00:32:05.118 --> 00:32:06.558
remember I used that puzzle

cue-504
00:32:07.378 --> 00:32:08.058
analogy.

cue-505
00:32:08.698 --> 00:32:10.998
All the pieces of the puzzle are now in
the box,

cue-506
00:32:12.178 --> 00:32:16.338
and tomorrow, the attorneys are gonna make
arguments again to you

cue-507
00:32:16.718 --> 00:32:21.358
to explain to you what they now believe
that box shows. Ultimately,

cue-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

cue-509
00:32:25.578 --> 00:32:25.918
pieces,

cue-510
00:32:27.078 --> 00:32:28.358
and you'll figure it out for yourself.

cue-511
00:32:29.158 --> 00:32:29.458
Okay?

cue-512
00:32:30.478 --> 00:32:31.418
Any questions?

cue-513
00:32:32.678 --> 00:32:32.818
No?

cue-514
00:32:34.318 --> 00:32:37.778
All right. A few smiles. I see some
smiles. That's good.

cue-515
00:32:38.808 --> 00:32:41.677
And we'll stand in recess with the jury
until eight thirty tomorrow morning.

cue-516
00:32:42.558 --> 00:32:43.758
Please rise for the jury.

cue-517
00:32:57.638 --> 00:33:10.498
Okay.

cue-518
00:33:10.498 --> 00:33:13.358
The record will reflect that the jury has

cue-519
00:33:14.598 --> 00:33:15.038
left.

cue-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.

cue-521
00:33:26.798 --> 00:33:30.738
Mr. Cry, you wanna start? Oh, wait, before
you start, Mr. Knitt.

cue-522
00:33:31.438 --> 00:33:36.878
My apologies for confusing you with your
colleague. You were not on my list.

cue-523
00:33:36.878 --> 00:33:39.398
-Oh.
-And you are both about the same height,

cue-524
00:33:40.198 --> 00:33:43.898
-same...
-I, I'll take that as a compliment. Walter

cue-525
00:33:43.898 --> 00:33:46.458
-might be a little offended.
-All right. Good enough.

cue-526
00:33:46.458 --> 00:33:46.638
Good.

cue-527
00:33:49.318 --> 00:33:50.398
Um, okay.

cue-528
00:33:50.478 --> 00:33:53.978
-Mr. Cry.
-Your Honor, the only, uh, small item we

cue-529
00:33:53.978 --> 00:33:58.458
had left was, uh, just to, uh, communicate
to the court the parties' plan for

cue-530
00:33:58.458 --> 00:34:02.938
handling the, uh, excerpt transcripts for
the various videos that were played at

cue-531
00:34:02.938 --> 00:34:03.218
trial.

cue-532
00:34:03.858 --> 00:34:08.338
Following discussions with the court
reporter, the plan is to, uh, submit,

cue-533
00:34:09.038 --> 00:34:12.578
um, copies of the clip reports, which will
be stamped as trial exhibits,

cue-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

cue-535
00:34:18.158 --> 00:34:22.958
absent further order of the court.
[clears throat]

cue-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

cue-537
00:34:29.798 --> 00:34:32.408
-identification only.
-Okay. Everybody agreed?

cue-538
00:34:33.278 --> 00:34:34.838
-Uh, yes, Your Honor.
-Yes, Your Honor.

cue-539
00:34:34.838 --> 00:34:35.178
Okay.

cue-540
00:34:36.398 --> 00:34:37.877
Uh, all right. What else

cue-541
00:34:38.518 --> 00:34:39.938
do you want to do today

cue-542
00:34:40.998 --> 00:34:43.678
so that I can release you to go work on
closings?

cue-543
00:34:45.898 --> 00:34:46.038
Uh,

cue-544
00:34:48.518 --> 00:35:02.858
Your

cue-545
00:35:02.858 --> 00:35:06.438
Honor, my colleagues asked me to confirm
the duration of time we will have for

cue-546
00:35:06.438 --> 00:35:10.418
-closing arguments tomorrow.
-Uh, you all, um, have

cue-547
00:35:10.938 --> 00:35:12.858
plenty of time. So, uh,

cue-548
00:35:15.558 --> 00:35:15.638
w-

cue-549
00:35:16.338 --> 00:35:17.838
because I, um...

cue-550
00:35:20.218 --> 00:35:23.518
I mean, it's over two hours for both
plaintiffs and defense.

cue-551
00:35:24.838 --> 00:35:27.838
Uh, that is the OpenAI defendants. And
then, um,

cue-552
00:35:29.778 --> 00:35:31.958
O- uh, Microsoft had said

cue-553
00:35:33.398 --> 00:35:35.278
forty-one, and

cue-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.

cue-555
00:35:41.398 --> 00:35:43.818
So I, I think you all have plenty of time.

cue-556
00:35:45.158 --> 00:35:47.398
I can send you the final number if you
want by email.

cue-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.

cue-558
00:35:51.678 --> 00:35:55.798
-Okay. Anything, Mr. Cry?
-Nothing else from plaintiff, Your Honor.

cue-559
00:35:55.798 --> 00:35:56.058
Thank you.

cue-560
00:35:56.988 --> 00:36:00.358
-Uh, nothing from the OpenAI defendants.
-Nothing from Microsoft. Thank you.

cue-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.

cue-562
00:36:03.658 --> 00:36:03.998
Thank you.

cue-563
00:36:05.198 --> 00:36:06.038
Court is in recess.

cue-564
00:36:10.858 --> 00:36:12.418
-Should probably just leave our stuff.
-Yep, yeah.

cue-565
00:36:14.498 --> 00:36:32.678
[background chattering]

cue-566
00:39:55.738 --> 00:42:21.878
[background noise]