Let me show you how to be a good lazy and

change your predictions You know I'm a big

2

fan of everything physics, so when I heard

that Bayesian stats was especially useful

3

in quantum physics, I had to make an

episode about it.

4

You'll hear from Chris Ferry, an associate

professor at the Center for Quantum

5

Software and Information of the University

of Technology, Sydney.

6

Chris also has a foot in industry, as a

co-founder of Eigen Systems, an Australian

7

startup

8

with a mission to democratize access to

quantum computing.

9

Of course, we talked about why Bayesian

stats are helpful in quantum physics

10

research, and about the burning challenges

in this line of research, but Chris is

11

also a renowned author.

12

In addition to writing Bayesian

Probability for Babies, he's the author of

13

Quantum Physics for Babies and Quantum

Bullshit, How to Ruin Your Life with

14

Advice from Quantum Physics.

15

So we ended up talking about science

communication, science education, and a

16

shocking revelation.

17

about Ant-Man.

18

A big thank you to one of my best patrons,

Stefan Lawrence, for recommending me an

19

episode with Chris.

20

This is Learning Asians Statistics,

21

Hello my dear Asians, I want to share an

exciting webinar I have coming up on March

22

1st with Nathaniel Ford.

23

fellow Pimc Cardiff and causal inference

expert.

24

In this modeling webinar, Nathaniel will

explore the world of causal inference and

25

how propensity scores can be a powerful

tool.

26

We will learn how to estimate propensity

scores and use them to tackle selection

27

bias in our analysis.

28

If that sounds like fun, go to topmate.io

slash Alex underscore and Dora to secure

29

your seat.

30

And of course, if you're a patron of the

show, you get bonuses.

31

submitting questions in advance, early

access to the recordings, etc.

32

You are my favorite listeners after all.

33

Okay, now back to the show.

34

It's Ferry.

35

Welcome to Learning Bayesian Statistics.

36

Thanks for having me.

37

Yeah, thanks a lot for taking the time.

38

I'm personally super psyched to have you

on.

39

And also, I know a lot of my patrons will

be

40

very happy to see you and hear you on the

show because they have asked me for a

41

little while now if that was possible to

have you on the show and well apparently

42

nothing is impossible in the baysan world

so really thanks a lot for taking the time

43

Chris and actually let's start by talking

about what you're doing these days right

44

how would you define the work you're doing

nowadays?

45

and what are the topics that you're

particularly interested in.

46

Sure.

47

Yeah.

48

So I'm an associate professor at the

University of Technology, Sydney.

49

I'm also a co-founder of a tech startup

company.

50

And both of these kind of have transformed

me, like at least hopefully temporarily

51

into more of a manager than a researcher.

52

So the business is developing small,

affordable desktop quantum emulators,

53

trying to kind of beef up, enhance, enable

new forms of teaching in quantum

54

programming, which doesn't really exist.

55

And as a professor, I supervise a handful

of graduate students postdocs.

56

I made the mistake, maybe this is like

advice for early career researchers, of

57

allowing them all to select their own

projects.

58

So I'm supervising students who are all

doing separate projects, all chosen by

59

themselves.

60

That means that they get to dive deep into

their projects, but I kind of remain at

61

the surface level.

62

If I'd done it over again, I'd do it

differently with maybe.

63

fewer students and working on topics that

really interest me.

64

But unfortunately, that doesn't usually

generate much funding because I'm

65

interested in the foundations of quantum

physics, and that's more metaphysics or

66

you might even say philosophy.

67

But it's not bad.

68

I get to help young students advance their

careers and learn about new interesting

69

topics and there's always time in the

future to eventually settle down.

70

Yeah, for sure.

71

I didn't know you were also working on an

EdTech company.

72

Yeah, you want to tell us a bit more about

that?

73

That sounds like fun.

74

Well, I'm an elder millennial.

75

I was born in the really early eighties,

so that means I have to have side gigs.

76

And yeah, it was something that we were

interested in doing at the university

77

quantum computing at the university.

78

And what I realized was it's a very

abstract thing.

79

And it's usually taught from the context

of physics and physics students are happy

80

to just be, you know, do what they're

told.

81

But computer science students are a little

bit more challenging because they want to

82

see something tangible and they want to

build things and see the results of what

83

they build.

84

So we thought about building this kind of

thing that they can interact with.

85

And we made some prototypes and it worked

really well in the context of teaching the

86

teaching that I do.

87

And we thought, well, and everyone we

talked to in our field about this said

88

that they wanted one too.

89

And then that kind of led us to the idea

of starting a company.

90

So we're at the stage of, of we have, we

have customers, we've built prototypes, we

91

have customers, uh, all around the world.

92

And, uh, we'll make a big announcement

actually at an event called quantum

93

Australia and.

94

that will, and then people can pre-order

them, hopefully for shipping later this

95

year.

96

And it's, so the product is a small

desktop quantum emulator.

97

Think about like the relationship between

3D printers that are in classrooms and

98

commercial industrial scale 3D printers.

99

So our small classroom thing is emulating

the real thing.

100

So,

101

but it does everything that you need to do

in the context of teaching.

102

And it'll come with a full kit to teach

quantum programming to hopefully

103

eventually down to the high school and

elementary school levels.

104

Nice.

105

Yeah, that's super cool.

106

And I am going to be honest that I don't

think I can say I know anything about

107

quantum computing.

108

So why...

109

Why would you like to do that?

110

What are you, what do you think will that

allow for a better education, basically,

111

why would quantum computing help here?

112

Well, when we make projections into the

future, we see that we're going to need,

113

the quantum industry will need lots of

people, way more people than are in the

114

pipeline now.

115

So this addresses that market need really.

116

So the reason that we want to do it is to

address that market need and do something

117

that we think is best fit for it.

118

Now as an individual,

119

Why would you buy a desktop quantum

emulator and learn about quantum

120

programming?

121

Well, you know, I think it appeals to the

hobbyists in some sense.

122

So if you're someone who buys new tech

stuff on Kickstarter, then you, this is

123

the sort of thing that you would buy

because you're curious about it.

124

Or maybe you just want to develop new

skills.

125

Uh, eventually it will be a subject in, in

high school that students can, can choose

126

just like they can choose to do coding now

in high school and programming.

127

So quantum computing is something that is,

it's a nascent field, but the 21st century

128

will come to be known eventually as the

quantum age, as quantum technologies

129

develop.

130

Okay.

131

And what will that allow us to do?

132

I think the only thing I know about

quantum computing is that it's supposed to

133

allow you to compute way faster.

134

So first of all, the idea I understand

that well,

135

And yeah, just can you give us maybe a

rundown on quantum computing?

136

Yeah.

137

Well, it's not about speed.

138

So there are some things that a quantum

computer will be able to do that

139

conventional, we call them classical

computers, can't do.

140

So the individual steps that occur within

a quantum computer, carrying out an

141

instruction is actually slower.

142

It's the number

143

are way fewer.

144

So the device itself is slow, which means

that you wouldn't want to use it for

145

simple things like adding numbers.

146

Like there's not going to be a quantum

calculator that calculates, that does

147

addition faster.

148

It's more obscure mathematical problems

that people have connected to real world

149

things like applications in cryptography,

in the simulation of chemistry, those

150

sorts of things.

151

all boil down to these mathematical

problems that are difficult to solve when

152

you encode information digitally with ones

and zeros, as you would necessarily have

153

to do with your computer.

154

If you encode those problems into numbers

that have complex numbers and real numbers

155

and negative numbers rather than ones and

zeros, then you can carry out far fewer

156

steps to solve your problem.

157

And a quantum computer would naturally

encode those numbers.

158

and be able to carry out those steps.

159

So it's select problems that you would use

this device for.

160

It's not just, you know, it's not in the,

it's not this in the faster in the sense

161

that eventually we'll have like a iPhone

quantum or something like that.

162

It'll be a special purpose component of a

larger computer.

163

Just like your CPU outsources graphics

calculations to the GPU, it will outsource

164

some quantum

165

physics calculations to the QPU in the

future.

166

Okay, yeah, yeah.

167

Yeah, I see.

168

Thanks.

169

Much clearer now.

170

So, yeah, and I get at least the main

point.

171

So, of course, I've already started on

tensions, but I have so many questions for

172

you.

173

One of my actually planned questions was

that...

174

You have a very original origin story

because you claim and you wrote actually

175

that quantum physics actually turned you

into a Bajan.

176

So tell us why and I'm also curious if

there are any key moments that shifted

177

your perspective.

178

Right.

179

Yeah.

180

So yeah, we've been talking about quantum

physics and not Bayesian statistics.

181

So it all started when I was a graduate

student and I was interested in this field

182

called quantum foundation.

183

So it's kind of really trying to

understand the deep underlying questions

184

about quantum physics.

185

The problem is if you dig deep enough, you

find that quantum physics is just a

186

framework built on top of probability

theory.

187

You've probably heard of things like the

uncertainty principle, things like that,

188

or that quantum physics is a probabilistic

theory.

189

And if you look at all of the debates that

happen at the fundamental level and the

190

foundational level of the field, they have

more to do with the interpretation of

191

probability than they have to do with

physics.

192

So when I was a graduate student, I

thought, well, I mean, I'm not going to be

193

able to answer these questions until I

understand probability.

194

And I suppose in this...

195

podcast, I'm preaching to the choir, but I

came out on the other side of that as a

196

Bayesian.

197

Bayesian, I would put in sort of scare

quotes because I think nowadays you can

198

follow the recipes in a book that uses

priors and Bayes' rule and it has the

199

title Bayes on it without the need to

actually have an interpretation of

200

probability at all.

201

So it was more like in order to answer

these questions and have a satisfactory

202

understanding of what's going on in

quantum physics,

203

You need to have an interpretation of

probability.

204

Um, for most physicists, it's just an

implied interpretation that they don't

205

really think about.

206

But for me, it, you know, it's, it came

out with a subjective interpretation and

207

that really helped me understand it.

208

Uh, but then I think at some point I was

talking to my thesis committee and they

209

didn't like this at all.

210

And so most physicists, especially quantum

ones, think probabilities are objective.

211

So they told me to do something practical.

212

So I transitioned and then tried to start

to apply Bayesian statistics to, you know,

213

problems in quantum and quantum physics,

which yeah, they're, it's essentially just

214

classical statistics with unfamiliar

models and different loss functions and

215

you know, complex numbers are involved in

some sense.

216

Um, but yeah, it's basically just a way

to, to derive a likelihood function.

217

Now, once you have a likelihood function,

then you're just doing classical

218

statistics, it's just a weird likelihood

function.

219

Um, so I was able to apply Bayesian

statistics to problems in quantum physics.

220

Um, so it was like, I started from this

sort of philosophical point of view and

221

then was told to do something practical.

222

And so then I was able to.

223

some practical things in applying Bayesian

statistics to quantum physics problems.

224

Did that change the view that your

supervisors had?

225

I think to some extent it did.

226

Those techniques and tools that we

developed

227

that they're being used in the field,

although it's still dominated with

228

frequentist methods.

229

Yeah, interesting.

230

Yeah.

231

In my experience, that's the same.

232

So usually people I talk to came to Bass

through practical concern.

233

You know, like for instance, a PhD student

who was completely blocked on her paper

234

with the classic framework and then she

just tried Bass because while it was...

235

of her last resort and it solved all of

her problems and now she's just doing

236

that.

237

But that's a very practical motivation.

238

And yeah, I see most people coming from

that angle.

239

You're actually more in the outlier side

where you've been more interested in the

240

epistemological point of view and then

shifted to actually doing it.

241

And yeah, actually what I've

242

It's actually useful.

243

Just show them.

244

And then they'll be like, yeah, that does

look good.

245

And that does solve the problem we were

having.

246

So why not try that?

247

So in my experience, that's been the same,

too.

248

And I'm curious, when was that work you

did on practical Bayesian inference?

249

When did you do that?

250

Oh, that's gotta be 16.

251

Yeah.

252

12, 16 years ago.

253

And we, so it kind of culminated in, we

built this tool, we call it Qinfer, and

254

it's basically a sequential Monte Carlo

integrator that just naturally was able to

255

solve the kinds of problems that people

have in quantum

256

Because it's quite difficult actually to

use standard tools.

257

Often they don't play nice with complex

numbers and things like that.

258

Don't naturally have the kind of loss

functions and things that we use in

259

quantum physics, kind of matrix

manipulations that we have to do.

260

And at the time there wasn't that many,

right?

261

Computation-based statistics is a

relatively new thing.

262

There was a few tools, but not many.

263

And so we ended up building our own and

it's been used many times over the years.

264

And that was maybe 10 years ago.

265

I stepped back from that and handed it off

to the next graduate student.

266

Yeah, that's why I asked you, when did you

do that?

267

Because just a few years ago, there wasn't

a lot of tools to do that.

268

So yeah, like you had, I'm guessing you

had to write the algorithm from, from top

269

to finish on your own.

270

Yeah.

271

And honestly, sometimes that's, that's

better to do it that way.

272

I mean, if you want to really deeply

understand something, you have to build it

273

yourself.

274

You know, we can't build everything from

scratch.

275

I mean, if, if you want to understand

particle physics, you can't go build your

276

own particle collider, but, uh, for things

that you, you have the capacity to build,

277

I would always recommend building it

yourself or at least attempt to, and then

278

realize what all of the problems, uh, are

going to be if you wanted to make a really

279

slick product.

280

So get it to the point where you've built

a prototype and then you really kind of

281

deep start to deeply understand.

282

what's going on because a lot of times,

especially with really usable products,

283

they're really slick and they're just

black boxes.

284

And yeah, you can push the buttons and use

them, but you don't end up developing a

285

deep understanding of, of what's going on.

286

Yeah, yeah, for sure.

287

Even though hopefully if you had to do

that today, that would be easier.

288

You could use building blocks instead of

really just starting from scratch.

289

And thankfully- Well, I mean, an example

is I...

290

Yeah, I can give you an example.

291

So I have a student, an undergraduate

student that I suggested trying a new

292

it's jargon, but I'm sure people have

heard about it.

293

Maybe you heard about it.

294

The Stein variational gradient descent

method, which is a deterministic

295

integration method and, you know, it's

built into, um, Pi MC.

296

Uh, so I, the student can go and can go

and try that, although it is quite, it's

297

still quite difficult for them to build,

build the quantum mechanical models that

298

they have to build.

299

So first I have them do it from scratch.

300

And, uh, of course it

301

It works to some extent, but it's not very

efficient.

302

There are a lot of things that tricks that

come up in numerics.

303

Like, what do you do if you're trying to

take a logarithm and there's something

304

close to zero, right?

305

Then you don't want them to have to figure

out all those things.

306

Have them build it first and then go.

307

Yeah, yeah.

308

Yeah, basically using...

309

Yeah, I like that.

310

Basically using a version from scratch

that's...

311

Simplified and then when you need to go

industrialize that, well, just use the

312

tools you have already on the shelf and

maybe customize them if need.

313

That's the beauty of.mc where you building

blocks basically that you can personalize

314

into your own Lego construction in a way.

315

Yeah, for sure.

316

But that's awesome.

317

Well done on doing that thing.

318

And were you already using Python at the

time, 16 years ago, when you were doing

319

your own SMC or was it something else?

320

No, the first version was built in Matlab,

but as you might anticipate, we ran into

321

license issues when we ended up using

every one of the entire university's

322

global optimization toolbox licenses.

323

And so then we thought, well, this is

silly.

324

So then we moved over to Python.

325

The first one, yeah, it was kind of like

the transition.

326

So we had an early version built in 2.7,

and then we moved to 3.

327

Nice.

328

Yeah.

329

That's really fun.

330

Yeah, in SMC, I know there are also some,

like you can do that here with PMC now.

331

So yeah, if one of your students is

interested,

332

They can contact me and I'll direct them

to the persons who like doing that on the,

333

on the PIMC community.

334

And, and you personally, do you have any

specific instances to share or insights

335

that you gained by adopting a Bayesian

approach in your, in your research?

336

I mean, it's hard to know, I suppose.

337

I mean, I haven't given it a lot of

thought, right?

338

Because it wasn't like I had this problem

and classical techniques weren't working

339

for me.

340

And then I switched over and found, you

know, a particular set of Bayesian

341

techniques that ended up working.

342

I recommend it to people because a lot of

times, especially when you're thinking

343

about things deeply and foundationally,

like...

344

You know, what are these things mean in

quantum physics?

345

Um, it, I always go back to simple

classical examples and say, if you can

346

understand this, or I guess it's a more

negative thing, like if you can't

347

understand this, then you're not going to

even have a chance at understanding the

348

more complicated thing.

349

So, you know, I go back to coin tosses and

I say, okay, what does it mean in the

350

context of a coin toss?

351

And if you don't understand it there,

you're not going to understand that

352

quantum version of it.

353

And the, yeah, the subjective

interpretation of

354

of probability just makes things more

natural.

355

I mean, it gives you a framework for

thinking about things that you can always

356

build on rather than the classical

approach, which it doesn't give you that

357

framework at all.

358

It's just grasping at straws and saying,

okay, you know, what recipes work in this

359

situation?

360

And there isn't one coherent framework

sitting behind it.

361

Whereas the subjective interpretation

gives you that.

362

And so you might not, yeah, you might not

363

It's not like it gives you a specific set

of tools that you can apply in every

364

situation, but it gives you that footing,

that foundation that you can build upon

365

and always have that level of comfort,

philosophical comfort saying, I

366

understand, I know what's going on.

367

Yeah, for sure.

368

And to build on that question, do you have

a favorite study or paper of yours where

369

you used some Bayesian stuff at one point?

370

I'm curious to see, and I'm guessing

listeners too, curious to see where

371

Bayesian stats is useful when you do

research in quantum physics.

372

Yeah, there's lots of papers.

373

I think most of them would be readable for

someone coming from Bayesian statistics

374

without knowledge of quantum physics.

375

Because again, I try to frame it in this

way where the quantum physics, the only

376

point of the quantum physics is to arrive

at the likelihood function.

377

And once you have that, then you can just

do all the things that you're used to

378

doing.

379

Is it because your likelihood functions

are always extremely exotic?

380

Yeah, so the standard simple quantum

experiment would be about estimating the

381

parameter in a multinomial distribution.

382

So you can think of a quantum experiment

as rolling a die and trying to estimate

383

the probabilities for the faces of the

die.

384

Yeah, but...

385

The thing is we don't, um, the, we have

like loss functions that, I mean, yeah,

386

they, there's some, some major season

things in there.

387

And then the issue is like, we have these

loss functions that aren't, aren't ever

388

used in, in classical statistics.

389

And so a lot of the results, uh, just

don't apply.

390

So you, you know, you, you can, you can

sometimes appeal to, uh, like the law of

391

large numbers or, or some of these

392

you know, these theorems, but they,

strictly speaking, our models don't really

393

adhere to those, the assumptions that go

into those theorems.

394

So not only do we have weird loss

functions, that allowed probabilities for

395

the faces of the die are constrained in a

weird way that relates to a positivity of

396

some matrix that sits down the pipeline.

397

So it's, yeah.

398

So oftentimes you would, you would, if you

did it naively, you would end up

399

estimating, um, things that make

probabilities negative, which obviously

400

doesn't make sense.

401

So, um, yeah, there's weird constraints.

402

There's an atypical, um, statistical

models and, and then the loss functions

403

that we use are quite different.

404

So, but, you know, if, if you know enough

statistics and, and

405

can accept that there are different, you

know, that the possibilities extend beyond

406

what you're used to, then yeah, you can

you can work with it.

407

A lot of times the things that you'd

naturally try don't work.

408

But, you know, it is still just a

classical statistical problem.

409

We there was there was one paper where we

were trying to find another way to

410

problem in parameter estimation in quantum

physics is the parameter that you're

411

trying to estimate is itself a matrix.

412

So it's not a real value.

413

It's not a real value vector.

414

It's a complex value matrix.

415

And that's the thing you're trying to

estimate.

416

So I don't know if you're doing density

estimation, that sort of thing.

417

It's similar to that.

418

But we wanted to find the Bayes estimator

for a particular loss function that

419

involves square roots of

420

And if you assume that all the matrices

are diagonal, then you're back to a

421

classical statistical problem and you end

up with this funny loss function for

422

classical probabilities that's somewhat

related to some loss functions that are

423

used in learning theory.

424

And then we said, oh, well, people

actually haven't found the Bayes estimator

425

or, let's just say, the minimax estimator

for that particular function.

426

So our quantum result immediately implied

a result just that was purely classical.

427

And we, the papers titled the papers

estimating the bias of a noisy coin.

428

So it's, uh, this, this actually crops up

in, in social, uh, some social studies.

429

So if I, if I ask you, if you cheat on

your taxes, you're going to say no.

430

So how do they do the sampling?

431

What they do is they, they introduce some

randomness.

432

So they they'll say, okay.

433

roll a die, if the die comes up one, say

yes no matter what.

434

And so that the person who says yes can

always claim that the die came up one.

435

And so they feel like they can be honest.

436

But if that probability of people cheating

is really low, then you might get only one

437

or two people saying yes, but one in six

times they were supposed to say yes

438

anyway.

439

So if you just naively kind of

440

did methods of moments or some linear

inversion, you would come up with negative

441

probabilities.

442

So this is exactly a problem that's

embedded in a quantum mechanical problem.

443

And so sometimes there's some nice overlap

there.

444

Yeah, for sure.

445

That sounds like fun.

446

And for sure, if you can add these papers

to the show notes, please do, because I'm

447

pretty sure listeners are going to be

happy to.

448

to check those out.

449

I already put some cool links in the show

notes for people, but definitely papers

450

are always appreciated, so feel free to do

that.

451

This is a safe place where we can all

share our love for academic papers.

452

Great.

453

Yeah, I should warn the listeners though.

454

Yeah, a lot of them are, they're cavalier,

like a typical physicist.

455

So it's very...

456

We often take a conceptual approach to

these things.

457

Okay, interesting.

458

Well, I read it because it must be pretty

different from a statistics paper.

459

I don't think I've ever read a quantum

physics paper.

460

So yeah, for sure.

461

I think I'm going to start by your books

though, your books for children.

462

I'm embarrassed to say, I think I'm going

to learn a lot from them.

463

So I'm going to start by getting to walk

my way up to your papers.

464

Sounds much, much clearer.

465

And maybe before actually talking a bit

more about quantum physics and what you do

466

and also the work you do on your

children's books, but also science

467

communication in general, and I'd like to

keep talking a bit more about Bayesian

468

stats because I'm curious, I'm always

curious when I talk to a practitioner like

469

you and so someone who is not...

470

by training a statistician, but someone

who really uses Bayesian statistics for

471

their area of expertise.

472

What do you see as the biggest pain points

in the Bayesian workflow right now?

473

I think, as I mentioned before, the

software that is typically used off the

474

shelf doesn't accommodate the quirks and

things that come up in quantum models.

475

Some of them, they just won't accept

complex numbers, for example.

476

When I first attempted to use TensorFlow

way back, TensorFlow 1, you couldn't even

477

use complex numbers.

478

to go back to the source code.

479

And at that point, you might as well just

build it yourself.

480

So yeah, complex numbers, matrix

manipulations, we often have, as I said,

481

lots of constraints.

482

And when you attempt to use something out

of the box, if it works at all, your whole

483

screen is filled with warnings.

484

And it isn't.

485

It isn't as nice as the demos of the

software.

486

So I think for me, and possibly for people

that are running models with lots of

487

constraints, this is the biggest pain

point at the moment.

488

Obviously, the software will accommodate

constraints, but it doesn't.

489

It doesn't seem to do so in a way that's

natural and easy.

490

Yeah.

491

So ideally that like in an ideal world,

that would be what you'd like to see to

492

help adoption of patient training.

493

Yeah.

494

I mean, like a really concrete example

would be, you know, I want to do

495

sequential Monte Carlo on some simple

estimates.

496

I'm doing an experiment where I roll a die

several times and I want to estimate the

497

probabilities.

498

It's of some biased die, but the

probabilities come with a long list of

499

linear constraints.

500

So not any probability will do.

501

When you're doing the resampling, what is

it that the software is doing to

502

accommodate those constraints?

503

approach is like, what doesn't really

matter because there is no constraints.

504

And so you can just throw a Gaussian on it

and you know, it, nothing.

505

Yeah, it's simple, but when you have these

constraints, um, yeah, it makes, it makes

506

things far, far more challenging.

507

And sometimes the software just doesn't,

doesn't accommodate those.

508

Yeah, yeah, no, for sure.

509

I understand your pain.

510

And I'd like to make your wish come true,

but that's a hard one because in here,

511

you're hitting a limitation, I would say,

of the development process where you have

512

to choose at some point if your package is

going to be general or specific.

513

And packages like Stan, Climacy,

TensorFlow, they have to be general

514

because they are adopted by so many people

with so many different backgrounds and so

515

many different uses that we have to make

choices that are going to work for most

516

people and that are going to be optimal

for most use cases.

517

But that means for sure it's like

518

If you're trying to accommodate everybody,

nobody's going to be accommodated

519

perfectly.

520

Right.

521

So, yeah, like it seems to me like someone

should go there and basically build a

522

package on top of PIMC that just like

addresses what you folks pain points are

523

in quantum physics.

524

Basically.

525

I know there is such a package for

astrophysicists.

526

Of course, I don't remember the package

name right now, but I'll try to remember

527

and put that in the show notes.

528

And I know that package built on top of

times is really, really used a lot in the

529

astrophysics field.

530

I'm not aware of any package like that in

the quantum physics realm.

531

But if any listeners do, but then please

reach out to me and I'll pass that on to

532

Chris.

533

I'm sure his PhD students are going to be

grateful.

534

Yeah.

535

Or if anybody wants to do that, get in

contact with Chris, I'm sure he would have

536

valuable points for you about what he'd

like to see in particular.

537

I think it's honestly there's a research

question in there as well, right?

538

At least when we were doing it, that

particular method that we were using, it

539

was never applied or developed in the

context of constraints.

540

And so what you do when you're faced with

constraints, at the time anyway, it was

541

like sort of an open research question.

542

So yeah, it's fair that...

543

It's fair that the software just doesn't

solve it for you because it may not be a

544

there may not be an actual solution yet.

545

Yeah, that's a good point also.

546

And so now I'd like to ask you a bit more

about quantum physics per se, because,

547

well, I'm always very curious about

physics.

548

So what in your line of research, what are

the biggest questions, the biggest

549

challenging you face currently?

550

So we're at this weird transition point in

the field of quantum technology where we

551

can't in laboratories, university

laboratories, build bigger devices.

552

So we kind of count the power of a quantum

computer in the number of quantum bits or

553

qubits that we can control.

554

And nowadays it's very easy to get one

qubit.

555

was very difficult, but now there are many

different modalities, trapping atoms,

556

using states of light.

557

All of these sorts of things can now be

used to encode a single qubit, and that

558

can be done in the standard physics lab.

559

Going beyond that becomes more difficult

and you need much more funding to do it,

560

but going much further beyond that is not

a possibility within an academic.

561

context.

562

And so you need some large government

organization or collaboration to do it, or

563

you need industry to take over.

564

So we're at that cusp where the largest

devices are ones that are being developed

565

by companies, companies like IBM, Google,

startup companies like Rigetti, IonQ.

566

There's a whole host of them now.

567

And what they're doing, obviously,

568

secret now.

569

So it's a weird place to be.

570

I can't tell you, I can make guesses about

where they are, what they're doing, what

571

their problems are.

572

But if they wanted my help, I'd have to

sign an NDA, or they'd have to pay me and

573

I wouldn't be able to tell you.

574

So we've kind of transitioned into

575

We're moving out of university research

labs into government and company and

576

multinational company R&D labs.

577

They have the same problems, but at a

larger scale that university researchers

578

had, which is just that to maintain the

state of an isolated quantum system is

579

very difficult.

580

Any interaction.

581

cosmic ray that comes in that you

obviously can't control will degrade the

582

information that's being encoded in these

systems.

583

And so they're very fragile.

584

We need to work out ways to provide better

isolation, but complete isolation is not

585

good either because you have to control

them to carry out the instructions that

586

you want.

587

So it's kind of this Catch-22 where you

want it to be completely isolated from

588

everything except for when you want to

actually.

589

go in there and manipulate it in some way.

590

So yeah, these are the problems.

591

And I think theoretically there's still

that big question about can it even be

592

done?

593

Can we even build a quantum computer?

594

There doesn't seem to be a reason why.

595

If it turns out that we couldn't, we'd

learn a lot about the nature of reality

596

and the reason for why that's the case.

597

But

598

I think have the potential to be answered

in my lifetime.

599

Can we build a large scale fault tolerant

error corrected quantum computer that

600

carries out some calculation that would

have been impossible to carry out with

601

digital electronics?

602

Yeah, yeah, that's pretty fascinating.

603

And I'm really impressed by the depth and

the width.

604

of topics in the research of physics.

605

It's just incredible.

606

I would refer to listeners to episode 93

that I did at CERN, the summer, I mean,

607

they do at CERN, what type of research,

608

what does that mean, why even do that.

609

And you'll see, well, some, you know,

cross topics with what Chris is talking

610

about, but also things that are completely

different.

611

And that's just incredible to see how wide

these fields are.

612

And that sounds to me that's pretty

incredible because in the end, that's

613

just, you know, trying to understand the

universe.

614

So it's kind of doing the same thing, but

it brings you...

615

to directions that are completely,

completely different.

616

And that's really the funny, one of the

fascinating things, I think, of these

617

topics.

618

And of course, go to the video version of

the episode 93.

619

You have the audio version if you have,

but that was a video documentary inside

620

CERN.

621

So I highly recommend checking out the

YouTube link that I will put in the show

622

notes.

623

And actually, I'm curious, Chris, about

also because now, as you were saying, you

624

kind of have a management role, which

implies thinking a lot about the future.

625

So I'm wondering, where do you see the

field of quantum mechanics headed in the

626

next decade?

627

Also, maybe how do you see patient stats

still helping in this endeavor?

628

That's a good question.

629

I think much like astronomy, for example,

Bayesian techniques will see a wider

630

adoption because at the moment, the way

that a laboratory quantum physics

631

experiment happens is really foreign to

someone who does machine learning or data

632

science where you have some data set and

then you need to analyze it.

633

No, what they do in labs in physics

departments is if the data isn't what you

634

wanted, then you just throw it out and

start again.

635

And, and you work until you have like

really clean data sets.

636

So all of the all of the problems with

data sets and things like that don't

637

happen in physics labs.

638

The physicists want to see the answer in

their data.

639

So the really sort of data scarce regime

is unacceptable to them.

640

They need to see it on an oscilloscope or

something.

641

The probability distributions essentially

have to be delta functions for them before

642

they accept that the experiment actually

worked.

643

But that's because we're doing really

small-scale experiments.

644

Once those experiments grow and become

large, we won't be able to do that

645

anymore.

646

If an experiment takes a week to run,

647

You're not going to say, do it over again

until you see a nicer data.

648

You're just going to have to accept that

that's the data set and you have to, you

649

know, get as much information out of it as

possible.

650

And that's going to require utilizing the

assumptions that you're making.

651

In a sensible way, which will lead you to

sort of Bayesian techniques.

652

So I think we will see wider and wider

adoption within the quantum research

653

fields.

654

of Bayesian techniques going into the

future, much like we have in the last two

655

decades in astronomy.

656

Hmm.

657

Yeah.

658

Uh-oh.

659

Yeah, fascinating and...

660

I really hope that these big questions you

were talking about are going to be

661

answered, at least some of them, because

I'm just so curious about that.

662

That would be just fascinating to have

some of these answers at least come our

663

way in the coming years.

664

um, relativity in quantum physics and how

you can merge that.

665

And so that's definitely would be

incredible to at least understand that a

666

bit better.

667

And also, and I'm also fascinated by the

fact that how do you do the experiments on

668

this realm for now is just super

complicated.

669

Yeah, I think those are huge questions.

670

I don't even think we've really formulated

the questions correctly.

671

I mean, that's my take on it.

672

We have a theory that works really well at

the moment.

673

In every regime we can test, our current

best model quantum field theory works

674

incredibly well.

675

It's places that we don't even understand

like inside the event horizon of a black

676

hole.

677

in principle, we can't even go there to

get the data that we would need to find

678

out if the theory works there.

679

There's various takes on it.

680

It's just a pessimistic take, which is

like, maybe we've hit the limits of what

681

we can understand given our capabilities

in the universe.

682

And then, yeah, a more positive view is

like, well, eventually someone will come

683

up with some idea

684

there was something that nobody could have

seen coming.

685

That's typically how paradigm shifts have

worked in the past.

686

So there's no reason to think

pessimistically that will stop.

687

But who knows, it might be the case.

688

Yeah.

689

I mean, I do hope for the second option,

but you can never know.

690

And actually now

691

I love the fact that you do a lot of

science communication, of course it's also

692

a job of these podcasts, so it's always

something I'm very happy to talk about and

693

I'm wondering if there are some common

misconceptions you've seen about quantum

694

physics, maybe even about

695

Oh, yeah.

696

Well, I wrote an entire book for, not for

children.

697

It's, yeah, you may have to edit this part

out because the book's called Quantum

698

Bullshit.

699

I don't know if that's allowed in the

podcast.

700

I'm French, so we have no worries with

swear words.

701

Yeah, in Australia it's similar.

702

Yeah, so that's the title of the book.

703

The subtitle is kind of a science comedy.

704

So the subtitle is How to Ruin Your Life

with advice from quantum physics.

705

And it kind of goes through a lot of the

common misconceptions and how each of

706

these major concepts in quantum physics

are misused.

707

Things like superposition, entanglement,

quantum energy, quantum uncertainty, these

708

sorts of things, how they typically are

misused.

709

And yeah, what's the most sensible kind of

way to understand them without having the

710

mathematical background that underpins the

framework of the theory?

711

So yeah, there's lots of them.

712

And if you want the comprehensive list,

definitely check out the book.

713

I'll give you like a typical

714

means things can be in two places at once.

715

And that just like, just saying it out

loud should make it clear that that's a

716

logical contradiction.

717

Because, you know, a dichotomy between

true and false, and you can't have

718

something that's both true and false.

719

So sort of a logical contradiction.

720

But that being said, you still, you know,

physicists will still say things

721

that sound kind of like that.

722

So an example might be this famous double

slit experiment where you have some sort

723

of screen, it has two holes in it, and you

fire electrons at it and you see an

724

interference pattern on the other side

instead of just two dots where the

725

electrons landed, suggesting that the

particles interfere with each other.

726

And if you do it one particle at a time,

that means it has to interfere with

727

itself.

728

which means it had to have gone through

both slits at the same time.

729

So the electron had, or whatever particle

it is, had to be in both of those places

730

at the same time.

731

But we always run into these problems when

we try to explain what's going on in

732

quantum physics by analogy to our everyday

world.

733

It's just a different world that we don't

have access to.

734

We don't have a language and a familiarity

with.

735

So we have to use these analogies.

736

But...

737

you know, they very quickly break down.

738

So that's absolutely not what's happening.

739

Uh, and things can't be in two places at

once.

740

And yeah, you shouldn't, uh, you should

buy a quantum crystal or something because

741

it promises that, that it can do that.

742

And for the Bayesian, I find actually, um,

uh, yeah.

743

So, you know, when you

744

You can kind of explain to people the way

I do it now is to walk through that idea

745

that in quantum physics we have these

concepts and we have to use a language

746

that we're familiar with but that language

isn't really suited for trying to do

747

anything beyond explain that one special

thing.

748

You can't extrapolate using those

analogies because you'll quickly fall prey

749

to misconceptions.

750

So

751

That's typically how I explain it in the

context of quantum physics.

752

And quantum physics is actually quite

popular in the popular culture.

753

I don't find that Bayesian probability is

so popular in popular culture.

754

So, you know, the word quantum crops up

all the time, attached to things.

755

Nobody's selling Bayesian healing

crystals.

756

So, these aren't like popular.

757

Oh, that's actually not a bad idea.

758

Yeah.

759

But so you don't need to approach it the

same way because you're not typically

760

talking to a lay audience when you're

talking about misconceptions and Bayesian

761

probability.

762

Usually it's someone technically minded

who knows something about some technical

763

topic that the probability is being

applied to or probability itself.

764

In physics, the main problem that people

have, you could call it a misconception,

765

is that Bayesian methods are subjective,

whereas frequentist methods are objective.

766

And as a scientist, you need to strive for

objectivity.

767

So that means that you shouldn't use

Bayesian methods and you have to use

768

frequentist methods.

769

But the easy thing to point out is to...

770

What you could do is just...

771

have them walk through how they would

apply frequentist methods and then point

772

out that they had options and then they

made their subjective judgments on which

773

options they were going to choose to solve

their problem.

774

So it's no less subjective.

775

And in some sense, it's worse in the sense

that you're not being honest about the

776

biases that are going into what you're

doing.

777

So yes, Bayesian methods are absolutely

subjective, but they're subjective in the

778

most honest way possible.

779

Yeah, that's usually the way I go about it

also.

780

The faster you're going to abandon the

idea that there is an objective way of

781

seeing reality, at least the way we are

made, you know, if you're homo sapiens,

782

the faster you'll be able to think about

real ways to actually try to understand

783

what's going on.

784

And so, yeah.

785

It's usually the way I go about it.

786

But yeah, I mean, these are fascinating

topics.

787

I, we've actually covered some of them in

some of the episodes we've already done on

788

the show.

789

So the one, one before you was episode 97

with Alien Downey where he actually talked

790

about that where.

791

He has also a blog post about it comparing

this idea that Bayesian results converge

792

to the frequentist results to the limit.

793

And so that was interesting to talk about

it with him because he actually argues

794

that it's never the same.

795

And that's not a problem.

796

You should still choose the Bayesian

framework, actually.

797

But that was interesting.

798

So you have that for people interested and

also I'll put in the show notes.

799

So I'll put that one and I'll put in the

show notes, episode 50 and 51.

800

50 was with Aubrey Clayton, who wrote an

amazing book called Bernoulli's Fantasy

801

and the Crisis of Modern Science.

802

So that's more about the history of

statistics and how basically, how and why

803

came to dominate the scientific world.

804

So much more epistemological, very, very

fascinating book.

805

And episode 51 with Sir, only Sir we've

had on the podcast, I think, Sir David

806

Spiegelhalter about risk communication,

how to talk about risk, especially to a

807

lay audience.

808

and people who are not educated in stats

or in the scientific method.

809

And that was, that was way closer to the

COVID pandemic.

810

So that was very interesting to talk about

that with him, because these topics were

811

absolutely important in time of pandemic

or very stressful situations.

812

Right.

813

Who would think so, right?

814

That the nerds actually had tried all

along to talk about stats and

815

probabilities.

816

This can save you during a pandemic.

817

But yeah, I mean, this is also something

that I think must be added in these

818

discussions.

819

Often, it's not really in the papers that

you see these misconceptions, but it's

820

more in the way the papers are interpreted

by people who are not equipped to read the

821

papers.

822

And so I think there is a...

823

a job in the world that needs to be

filled, which is basically making the

824

bridge between scientific papers and then

what ends up in the newspapers.

825

And that is a bridge that still has to be

built.

826

And we're trying to do that in a way with

our work, but it's still so much things to

827

do still.

828

Sometimes my game is really to do that.

829

It's trying to see what people are talking

about on Instagram or stuff like that.

830

And then actually try and go to the source

that they are supposed to quote, you know,

831

to site.

832

And then you see that basically it's just

like the first person who reported on the

833

paper did understand the paper or just

read the abstract and the title.

834

And then just everybody cite that first

source.

835

So basically the first error is just like

trickled down and that's just fascinating.

836

Yeah.

837

Yeah, I think the solution has to sort of

include actually that people write fewer

838

papers.

839

I mean, there's over a million academic

journal articles published every year, and

840

that's more than we can read, right?

841

But there's the perverse incentives in

academia now that kind of force you to do

842

this, which means also that like most of

those papers shouldn't have been written,

843

I think it would be better if we had a

more careful approach where the result is

844

fewer papers that are better written.

845

Yeah, that could have been more.

846

And also it's something we've talked about

on the podcast several times, incentives

847

in academia.

848

It's hard to change, but needs to be

changed.

849

But yeah, hopefully that will...

850

And having people like you in academia

definitely helps.

851

Well, hopefully with time, it's going to

evolve.

852

But yeah, and we could continue on that

road, but it's going to be a three-hours

853

episode, and I don't want to take too much

time to you.

854

And actually, that's a very, it's the very

first episode that we do where we are

855

actually time traveling, right?

856

Because it's still January 15 for me.

857

at night and it is January 16th in the

morning for Chris.

858

So thank you for calling from the future,

Chris.

859

We solved the glass problem.

860

The sun rises tomorrow.

861

Yeah, I can tell you that.

862

Yeah, I can see for now, no apocalypse.

863

So that's cool.

864

Glad about that.

865

Yeah, I had other things to add about your

very good points about communication and

866

so on.

867

But of course I...

868

I think I forgot about them.

869

I will just refer people to the show

notes.

870

I'm gonna put the episodes I mentioned in

there.

871

And oh yeah, one thing, I tracked down the

Python package I was talking about for

872

Astrophysics.

873

So the package is actually called

Exoplanet.

874

And yeah, it's a package that's built on

top of PymC.

875

to do probabilistic modeling of time

series data in astronomy with a focus on

876

observations of exoplanets.

877

So I put the notes, the link already in

the show notes, and that's developed

878

mainly by Dan, Ferm, and Mackey.

879

So people who are working on that

definitely take a look at a very cool

880

package, very well maintained.

881

So Chris.

882

I've already taken a lot of time from you,

but I'm curious.

883

I want to talk a bit about your children's

book.

884

Of course, you've written about quantum

physics, about general relativity.

885

Patient statistics also, you've written a

book, I think, about that.

886

First, I'm definitely going to buy those

books if one day I have kids.

887

That's for sure.

888

I'm not going to read them stories

about...

889

crystals and things like that, much more

about that kind of thing.

890

No, first, keening aside that I think

that's a very good service you're making

891

because definitely there is a big lack of

scientific culture, I would say in

892

general, in the audience, just

understanding probability.

893

The main thing I have to face is often

things like

894

Well, you said that thing would happen

with a 30% chance.

895

It didn't happen.

896

Hence the model was wrong.

897

And that's just like, this is kind of the,

this part of the misconceptions on, on the

898

part of, this is the burden of a

statistician.

899

But I think it's extremely important to

make people more aware of the scientific

900

methods, more scientific savvy.

901

First pick is way more interesting than

what pop culture makes it look like.

902

You know, you don't have to be crazy.

903

You don't have to wear a white coat.

904

You don't have to be a genius to

understand science.

905

And you don't have to be a genius to use

science.

906

So, yeah, I think it's extremely important

what you're doing.

907

And mainly to go to my question, how, how

do you approach simply

908

simplifying such complex topics for young

minds and yeah, how do you think about the

909

way you teach that?

910

Yeah, that's a good question.

911

I think you hit on a lot of good points.

912

And there's a lot of obvious traps that

people fall into, right?

913

That you might think, well, science is

boring, so we need to spice it up.

914

This happens all the time.

915

If you see scientists on daytime

television or whatever, they inevitably do

916

some chemistry experiment where there's

some explosion and gives people a really

917

distorted view of what science is.

918

Not only is it...

919

People think that it's old white dudes in

lab coats and geniuses, but also people

920

have this misconception that it's all

about excitement and explosions and

921

chemical reactions and cosmic awesomeness.

922

But science is at its core, this

fundamental framework for navigating the

923

world in the...

924

most sensible way possible.

925

So when I approach the children's books, I

try to really simplify not only the

926

concepts, but just that overall sense of

what I'm trying to do.

927

I'm not trying to create some extrapolated

vision, some way too exciting picture of

928

what science is.

929

What I try to do is I try to give

examples, analogies, categories, kind of

930

abstract things that give people some

comfort, some tools that they can use to

931

try to understand or appreciate what's

happening in these fields.

932

it becomes obvious that the books are for

parents, not necessarily for babies.

933

Um, and I think a lot of the feedback that

I get is from parents who say things like,

934

Oh, I wish I had learned this topic in

school in this way.

935

Right.

936

Uh, and you know, it all boils down to

this, this notion that when we learn

937

things, what, what we're doing is just

building up our repertoire of

938

of analogies that we can use to understand

them.

939

And the more that you have, the better,

right?

940

And the sooner you start, the better.

941

I think there is a misconception that

there's one unique special way to

942

understand a concept.

943

And if it's only told to you in that way,

some light bulb moment will happen in

944

which you all of a sudden understand it.

945

But that's just not

946

you at some point in the future, you say,

Oh, I feel like I understand that.

947

But there wasn't a, there wasn't a turning

point.

948

There wasn't a light bulb moment.

949

There wasn't a switch.

950

It was just time and, and building up

those, those analogies and examples that

951

at some point you just feel comfortable

and that's all there is to it.

952

So it's actually surprisingly easy.

953

It's a lot easier than people think.

954

Uh, you know, because the, the task that I

set myself is, is not such a high bar, you

955

know, just give a simple palatable analogy

for some core concept in the thing that

956

you're talking about that, that anyone can

understand.

957

Hmm.

958

Mm hmm.

959

Yeah.

960

Um, yeah, definitely.

961

It's.

962

Again, extremely important, so thanks a

lot for doing that.

963

And I do think that it's very important to

make science more, look more human and

964

write it more and more approachable

because I often people see that as very

965

dry endeavor, but I think actually

counting stories.

966

about science and scientists and normal

scientists, right?

967

Not the weird scientists from the movies

is extremely important because that's also

968

how we learn, right?

969

We learn a lot.

970

Our brain is like that.

971

We love stories and we love learning

through stories.

972

Like every equation you learned at school

has actually a story behind it.

973

Lots of people have worked on it.

974

Lots of people have.

975

failed and depressed because they couldn't

find the solution.

976

And thanks to their work, then afterwards

it unblocked a lot of things that you can

977

actually do now.

978

Just knowing about relativity makes us

able to be located through our phone.

979

We can use GPS very accurately because we

actually take into account relativity.

980

Well, it's pretty incredible, right?

981

I'm guessing most people don't know that.

982

So yeah, I think it's extremely important.

983

And actually I've watched very recently a

series, a Netflix series that does an

984

extremely good job, I found illustrating

science like that.

985

So it's still of course romanticized a

bit, but first the physics that's in the

986

show is pretty good and...

987

accurate, they don't refer to absolutely

completely crazy theories because the

988

series is called Lost in Space and the

beaches unite.

989

Something happened on Earth, I'm not going

to spoil it, but something happened on

990

Earth and then some people had to go and

try and colonize Alpha Centauri and we

991

follow the adventures of the families who

do that.

992

The science is pretty good on that and

also the depiction of the science is, I

993

found, very interesting.

994

We have some very interesting scenes where

it's like, oh, that's magic.

995

That's not magic.

996

That's math.

997

That was really cool.

998

I'm not going to spoil, but I definitely

recommend this series.

999

It's really well done.

And of course, well, your book, Chris.

And well, I think we could, we can call it

a show, I think, because I've already

taken a lot of time from you.

And for people watching the video, you can

see that the sun is setting down for me.

So the, the luminosity is getting down.

But I'd like, so before the last two

questions, my last question would be a bit

of a general one.

If you have any.

advice, Chris, for students or young

researchers interested in quantum physics

or even patient statistics, what advice

would you give them to start in these

fields?

Yeah, I think for young people that have

time on their hands, my advice is quite

simple is to study mathematics.

Mathematics is obviously the foundation of

statistics, also the foundation of quantum

physics and all of physics.

I see students coming into university who

are very excited about science.

They come in, they say, I've read all of

Brian Greene's books and Stephen Hawking's

books.

I'm here to be a scientist.

I live to be a quantum physicist.

And then you hand them a test with only

math problems on it.

And they get very deflated because nobody

told them that it was all about math.

So it's the way that I came into the

field.

I was never really interested in physics

or science.

I was a math student.

And when I finished my degree, it was more

about how am I going to apply my skills in

solving math problems.

And that served me very well.

So yeah, become proficient at mathematics.

There's lots of fun stuff in mathematics

when you, you know, at the surface level,

depending on the way it's taught can feel

boring.

And, but yeah, the further you dig deep

into it, the more interesting and more

exciting it gets, and it will provide you

with a deeper understanding of the field

that you end up applying it to then.

than you could have ever imagined and

certainly more so than the people that are

just still at that surface level.

So yeah, that would be my advice.

Also, especially for young people, for

students, life is very long and now is the

time that you're encouraged to make

mistakes.

And it's really the only time in your life

where you can make mistakes and get rapid

feedback.

And that's the thing that's encouraged and

that's the best way to learn.

So, you know, approach it from that

perspective and also drag it out as long

as you possibly can.

Yeah.

Completely agree with these

recommendations.

Learn math and learn it well and take

risks very, very young and for the most

time you can.

Because yeah, that's definitely helpful.

Even financially, like a good financial

advice, if you have to take risk and put

all most of your money on stocks, that

would be when you're young and then when

you get older, you get a bit less, a bit

more risk averse on your portfolio

investment.

Well, I would say that's the same thing

for life and for rapid feedback and

failure when you are young and not having

your responsibilities to do that, you

know, take the risks.

And learn math.

That's not a risk at all.

Awesome, Chris.

Well, I'm going to let you go.

But before that, I'm going to ask you the

last two questions I gave a guest at the

end of the show.

First one, if you had unlimited time and

resources, which problem would you try to

solve?

I think that's easy, at least in my

discipline, I would build a large scale

quantum computer and then I would set it

on the task of simulating various

materials until it found a high

temperature or room temperature

superconducting material.

And then we'd build that and go, have free

energy around the world.

That sounds nice.

I love that.

Yeah, awesome.

You're the first one to answer that, but

love it.

And second question, if you could have

dinner with any great scientific mind that

alive or fictional, who would it be?

Yeah, I mean, these sorts of questions I

think are difficult, especially for

someone with an analytical brain.

You know, you've got the one, the devil on

your shoulder saying, yeah, play along,

it's a whimsical game.

I thought about this actually.

So I think there'd be some inherent

problems with obviously with a dead

scientist.

You know, there's obvious problems, but I

think the ones that people don't think

about are Say, you know, I brought what I

Guess this is a magical scenario, but I

don't know if it's I go back in time or

they come to our time But in some sense,

it doesn't matter So I would prefer they

come to our time because you know, if go

far enough in the past and they don't even

have toilets So let's bring them to our

time, but there's a problem.

Like if I brought Einstein here what

what would I have to do?

Would I have to explain a century of

advancements in like the actual field that

he came up with?

And would he even accept it?

Like even in his lifetime, he refused to

accept all of the consequences of quantum

physics.

So, you know, it actually wouldn't be a

great conversation.

I think scientists from the past would

just be, it would be too difficult to

communicate.

magically overcome say some language

barrier.

Like they're, yeah, the contributions they

made obviously are timeless, but like that

conversation that you could have wouldn't

be very insightful.

So I feel like you'd have to go with a

living scientist, but then the problem

with a living scientist is like, I can

just email them if I had a specific

question.

So it seems like far more, far easier

than...

than organizing some dinner, which you can

have when you go to conferences anyway.

So I've been to dinner with Nobel

laureates and stuff and celebrity

scientists, and one of them was probably

enough.

So then I think you're forced to go with a

fictional character.

I don't know how many of your guests pick

a fictional character, but my favorite

fictional character with a self-proclaimed

great mind is Marvin.

paranoid android from the Hitchhiker's

Guide to the Galaxy.

So I would uh, I'd have dinner with Marvin

and I know exactly what I'd ask him to.

I'd ask him about AI alignment.

Um, because I think it seems to, he seems

to have been solved with Marvin and uh, I

think he would just give a wonderfully

nihilistic answer to what is AI alignment.

Yeah.

Yeah, no, that'd be fun.

Yeah.

I take part in this dinner.

I don't know.

Let me know when that happens.

You want, oh, you want a bonus question,

uh, physics related, a choice like that.

We had to make, uh, last time we did a

retreat at PIMC Labs, we do a retreat, uh,

every year.

And, uh, of course, it's just a bunch of

nerds getting together.

So we always end up with, uh, very nerdy

questions.

And, um, yeah, this year, I think one of

the main questions where

So yeah, the year before, one of the main

questions was who would win in a plane

war, so in an airplane war, Earth or

Jupiterians.

And this year, but the one I want your

input on is this year was, if you could

choose between these three options, which

one would you choose?

If you could know what's...

like what it's like to be in the quantum

realm?

Or if you could go inside a black hole and

know what's there?

Or if you could go to an alien planet and

meet them and talk with them, what would

you choose?

Right.

Uh, there's only one, there's only one

correct choice.

It's the third one because the other, the

other two, uh, would be bad.

bad decisions.

So it's the alien planet, yeah.

There is no quantum realm.

I wrote a blog post about that.

I'll give you the link for the listeners.

Oh, perfect.

So you can't go there, obviously.

There's technical challenges clearly with

shrinking a human, but also, yeah, our

entire sense of perception is built on our

mesoscopic relationship with the world.

Like clearly there'd be no sound, there'd

be no notion of sight.

So even if you could get around this weird

idea of shrinking yourself, it wouldn't be

a place to experience.

And then inside a black hole, every

direction points down and you'd be

spaghettified.

So it's a bad idea.

That'd be a problem.

Yeah.

I mean, I love that statement.

So let's go to the alien planet.

That's a technical term, actually.

Yeah, yeah, yeah.

Spaghettification.

Yeah, yeah, yeah.

And yeah, I mean, I'm shocked by the

revelation you just made on this podcast

that Ant-Man is not a documentary.

That's just, I'm just shocked.

So I think it's time to stop the podcast.

First of all, because I don't have any

more light and second, because well, I've

taken a lot of time from you.

Thanks a lot, Chris.

That was really awesome.