UNITED STATES PATENT AND TRADEMARK OFFICE
` BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`Page 186
`
` LIBERTY MUTUAL INSURANCE )
` COMPANY, ) No. CBM2012-00002
` ) CBM2012-00004 (JL)
` Petitioner, ) Patent 6,064,970
` )
` vs. ) No. CBM2013-0004 (JL)
` ) Patent 8,090,598
` PROGRESSIVE CASUALTY )
` INSURANCE COMPANY, ) No. CBM2012-0003
` ) CBM2013-0009 (JL)
` Patent Owner. ) Patent 8,140,358
` ______________________________)
`
` VIDEOTAPED DEPOSITION OF SCOTT ANDREWS
` Palo Alto, California
` Tuesday, September 24, 2013
` Volume 2
`
`Reported by:
`LESLIE ROCKWOOD, RPR, CSR 3462
`Job No. 65807
`
`TSG Reporting - Worldwide 877-702-9580
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`Liberty Mutual Exhibit 1038
`Liberty Mutual v. Progressive
`CBM2012-00002
`Page 00001
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`Page 195
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`Page 196
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`(Exhibit Liberty Mutual 1004, Japanese
`Unexamined Patent Application Publication,
`I-I4-182868. llll9f90, pages I - 42, having
`been previously marked. was referred to.)
`BY MR. WAMSLEY:
`
`Q. We also have Liberty Mutual Exhibit [02] in
`that matter, which is an excerpt from a book on fuzzy
`logic by Yen and Langari.
`Am I correct?
`A. Thafs correct.
`
`[Exhibit Liberty Mutual 102], Fuzzy Logic,
`Intelligence, Control, and Information, Yen
`and Langari, pages 1 - 55, having been
`previously marked, was referred to.)
`BY MR. WAMSLEY:
`
`Q. And then finally we have a paper called "Black
`Magic," which is Liberty Mutual Exhibit 1008 in this
`matter; is that correct?
`A. That's correct.
`
`("Exhibit Liberty Mutual 1008, An Interest
`in Black Magic - Motor ‘Technology, pages I
`- 2, having been previously marked, was
`referred to.)
`BY MR. WAMSLEY:
`
`Q. Okay. I'd like to direct you to your rebuttal
`
`Page 197
`
`MR. MYERS: Objection. 402, 403. And for the
`record. as in previous depositions, I'm simply going to
`cite the number of the Federal Rule of Evidence going
`forward in the deposition rather than make a full
`citation or state a full grounds for my objection, I'll
`simply state the mic number.
`MR. WAMSLEY: Well, let me just follow up to
`clarify. You're not intending to reserve the right to
`assert a different objection later to my question, are
`you?
`
`MR. MYERS: I'm not going to assert a different
`
`rule.
`
`MR. WAMSIJ”-.Y: Okay. So any objection within
`that rule is what you're saying‘?
`MR. MYERS: Correct.
`
`MR. WAMSLEY: Okay.
`MR. MYERS:
`I -- it's my --
`MR. WAMSLEY: Now we understand each other.
`
`MR. MYERS: Right. My understanding is the
`Patent Trial and Appeal Board doesn't want speaking
`objections or a full explanation on the record, and as a
`consequence, I'm going to give you the rule number of
`the Federal Rule oflividenee that I'm objecting under.
`And then if that comes up, then I'll have the
`opportunity to explain the basis for that objection in
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`declaration, Mr. Andrews, Exhibit 1019.
`A. Okay.
`Q. And in particular to paragraph 6. And in the
`first sentence of that paragraph, you testify that fuzzy
`logic was well-established and fairly common by 1996.
`Do you see that‘?
`I see that.
`
`A.
`
`Q. Okay. And is the basis for that opinion the
`existence of the book by Wang called "Adaptive Furzy
`System and Control," dated 1994‘?
`A. Well, actually the basis for that is described
`in the subsequent paragraph. Part of it is the book by
`Wang. Let me find it here. Yes, part ofit is the book
`by Wang. Part of it is the book by Langari and Yen.
`Part of it is from my own experience leading a group of
`engineers that were doing work with fuzzy logic.
`Q. All as described in this paragraph; is that
`right‘?
`A. Yes.
`
`Q. Okay. The book that you cite which is
`Exhibit 102] by Langari and Yen --
`A. That's right.
`Q.
`-- what you have quoted there indicates that
`the book takes the view that fuzzy logic is an emerging
`technology; correct?
`
`Page 198
`
`either in front of the board or in a paper that‘s filed
`with the board ifit becomes necessary.
`MR. WAMSLEY: We understand each other, then,
`Jim. Thank you for the clarification.
`Could I ask you to read the question back,
`please.
`(The record was read by the reporter
`as follows:
`
`"QUESTION: What you have quoted there
`indicates that the book takes the view that
`
`fuzzy logic is an emerging technology;
`correct‘?")
`'l‘IIE WITNESS:
`
`I wouldn't characterize it that
`
`way. Actually, it says that it's been accepted as an
`emerging technology since the late 1980s.
`BY MR. WAMSLEY:
`
`Q. And this is as of 1999, when this book was
`published; correct‘?
`A. That's correct, I think, yes.
`Q. Now you say in the next sentence that by 1996,
`you had studied several fuzzy logic systems and
`supervised many engineers with similar fuzzy logic
`experience.
`Do you see that‘?
`I see that.
`
`A.
`
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`identify these particular parameter values associated
`with Kosaka's membership functions.
`Do 1 have that right‘?
`I think almost.
`I think I said that last time
`A.
`we did this.
`
`I think the way I've stated it here in the
`declaration is not that a person of skill in insurance
`would have that ability.
`I've stated that in order to
`determine these values, you would need someone who was a
`person of ordinary skill in the insurance aspects of
`this kind of system.
`Again, it's not just any old pflson who knows
`something about insurance; it's somebody who is actually
`knowledgeable about. for example, understanding the
`risks associated with following distances and swerving
`and the other parameters that Kosaka identifies here.
`So you'd need a person who was knowledgeable
`about risks associated with that so that they would then
`be able to actually dctennine what these values are.
`And that's what I mean by a person skilled in the
`insurance aspects of the '970 patent.
`Q. But in fact, you have no expertise that would
`allow you to testify whether that person knowledgeable
`about those risks that you just referred to would be an
`expen or instead someone with lesser skill, do you‘?
`
`MR. MYERS: Objection. 402, 403.
`THE WITNESS: Are you asking me ifl would be
`able to determine whether a given person was an expert
`versus a person of ordinary skill in those aspects?
`BY MR. WAMSLEY:
`
`‘l‘hat‘s a different question than the one I
`
`Q.
`asked.
`
`A. Okay.
`MR. WAMSLEY: Let me try having it read back,
`and if it's still not working, we'll rephrase.
`[The record was read by the reporter
`as follows:
`
`"QUESTION: But in fact, you have no expertise
`that would allow you to testify whether that
`person knowledgeable about those risks that you
`just referred to would be an expert or instead
`someone with lesser skill, do you'?")
`MR. MYERS: Objection. 402, 403.
`TI IE WITNESS:
`I guess probably not because the
`delineation of a person of ordinary skill versus
`expertise in insurance isn't really my field.
`BY MR. WAMSLEY:
`
`Q. Okay. Let's move on to paragraph 9 of your
`rebuttal declaration. And here, among other things, you
`testify as to the risk evaluation value in Kosaka;
`
`Page 221
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`Page 222
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`correct?
`
`A. That's right.
`Q. And in your opinion, you say a person of
`ordinary skill would understand that risk evaluation
`value to be a single crisp value; correct?
`A. That's what I said.
`
`Q. And that's because of what you describe in the
`next sentence there of the process called
`dcfuzzification.
`
`Am I right?
`MR. MYERS: Objection. 402, 403.
`THE WITNESS: The process called
`dcfuzzifcation is the process that would take the
`membership -- the output membership values, membership
`function values, and convert them into a single crisp
`value.
`BY MR. WAMSLEY:
`
`Q. And with that understanding, am I correct that
`it's because of that, the existence of that
`defuzzification process. that you are of the opinion
`that Kosaka's risk evaluation value would be a single
`crisp value‘?
`MR. MYERS: Objection. 402, 403.
`THE WITN ESS:
`I'm not sure that I would
`
`characterize it that way.
`
`It's not because of the
`
`defuzzilication process. The issue is that there would
`be no usable output until you defuzzified it.
`BY MR. WAMSLI-LY:
`
`Q. In your testimony in your declaration about
`defuzzifieation, you cite to the Langari book; correct?
`A. That's right.
`Q. So let's look at that. That's Exhibit 102].
`And you particularly cite a couple ofpages
`there. Let's look at the first such citation at page
`38. Tell me when you're there.
`A.
`I'm there.
`
`Q. And you see the reference to defurzitication in
`the middle of the page there; correct‘?
`A. Yes.
`
`Q. And according to this text, this is an optional
`step in fuzzy logic; correct?
`A. That's what it says here.
`Q. So in that respect, a designer would be free to
`not use defuzzitication as part of the fuzzy logic
`system.
`Am I right‘?
`MR. MYERS: Objection. 402, 403.
`THE WITNESS:
`I don't think it really says
`I mean, he says for applications that need a
`that.
`crisp output, for example, in control systems. So any
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`time you are going to ultimately try to make use ofthe
`output in some specific way, you need a value that you
`can use. You don‘t need percentages of membership in a
`membership function.
`I don't know what you would -- in '970, I don't
`know how you would determine an insurance premium based '
`on the notion that someone was 20 percent low risk and
`50 percent medium risk and 70 or 30 percent high risk.
`You would ultimately have to calculate what is the
`aggregate risk from that, which is ultimately getting a
`crisp value out of the fuzzy system.
`I think the fact that he says these are
`optional is more if you were having cascaded fuzzy logic
`functions, you don't necessarily have to defuzzify and
`refuzzify and defuzzify and refuzzify every single time.
`But at the end of the day, having an output of
`a fuzzy system that isn't a value that you can use isn't
`very useful.
`BY MR. WAMSLEY:
`
`Q. You made a reference to control systems in your
`last answer. You'd agree widi me that the way fiizzy
`logic is used in Kosaka is it's not controlling
`anything, is it?
`MR. MYERS: Objection. 402, 403.
`THE WITNESS:
`I think it's ultimately
`
`have to defuzzify this.
`Q. And in your rebuttal declaration in
`paragraph 9, you say: "Kosaka explicitly describes
`using defuzzification."
`Do you see that‘?
`A. Yes, I do.
`
`Q. So you've still got Kosaka in front of you;
`right, Mr. Andrews?
`A. Uh-huh.
`
`Q. Would you agree with me that the mention of
`defuzzification that you've cited to at page 8 of Kosaka
`is with respect to Kosaka‘s first fuzzy logic part 62 as
`shown in Figure 9‘?
`A. That's coneet.
`
`Q. Would you also agree with me that nowhere else
`does Kosaka mention using defuzzification processes with
`respect to any other output?
`A. Well, he says the logical output level says
`the — this is in the right-hand paragraph of page 8,
`second paragraph down. So the risk evaluation value
`resulting from a comprehensive determination carried out
`at this third fuzzy logic part 65 is then output to the
`output controller, 66, where the logical output level
`and the output in accordance with hold time level are
`sent to the warning device and the monetary amount file.
`
`controlling the insurance premium.
`BY MR. WAMSLEY:
`
`Q. You -- so, in your opinion. coming up with risk
`evaluation values that are then used in insurance
`
`premitun calculation is an example of a control system‘?
`A.
`I mean, I could take you through my logic on
`that, but it's not a control system as in a -- you know,
`a stability control for an airplane or something like
`that or a cruise control system, but in fact, it is --
`Q. Or an elevator control system?
`A. Right. But it is in fact something of a
`feedback system. If you consider that you are going to
`measure risk and the associated potential for loss
`associated with that and then decide what factors in
`
`driving contribute to that, you are actually ultimately
`building a system that is a control system. Because if
`you base your premiums on the -- on these factors in the
`right way, then eventually new drivers are going to
`drive in that way, and you'll be able to assess their
`risk accurately.
`So at the end of the day. you have to have a
`crisp value to assign some level of risk. You just
`can't think that a system that has real-world
`application is going to end up with a membership set
`function and you're going to use that. So somewhere you
`
`Page 226
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`So he's talking about an output level. He's
`not talking about a series of membership function
`values.
`I'm not sure what a warning device or what the
`controller would do with a series of membership values.
`And you asked about a control system earlier in
`relation to Langari, and he's actually saying you output
`it to an output controller. So maybe it is a control
`system.
`
`He doesn't say explicitly here that the output
`of the — or the resulting membership function from
`fuzzy logic unit 3 is clcfuzzified, but I don't think he
`needs to say that.
`Q. You understand in looking at Figure 9 -- and
`feel free to consult the accompanying text -- you agree
`with me that the inputs to Box 65, which is fuzzy logic
`unit 3, are themselves fuzzy values?
`A. He talks about that in the top of page 8. So
`you'll see these are also input as fuzzy input values.
`Q. And that's what you would expect; right?
`Because fuzzy values are -- being used in fuzzy logic
`unit I and 2; right‘?
`A. That is what you would expect. You could have
`them be completely freestanding. So you could implement
`fuzzy logic I as a standalone unit that takes analog
`inputs or even digital representations of analog input
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