Real Astronomer v Virtual Astronomer - Sixty Symbols

0:00 We're looking at my retirement here.

0:02 What is this?

0:02 What are these?

0:03 This is a little device that I created.

0:07 Um, so one of the things I got

0:08 really interested in when I retired is digital electronics.

0:11 It's not something I've ever done before,

0:13 but I just randomly kind of fell into it and turns out it's it's a lot of fun.

0:17 You basically so it's a combination of hardware,

0:21 you know, putting together pieces of electronics,

0:22 but actually coding as well because you then write code for it

0:25 to make it do whatever it is you want it to do.

0:27 Neither are things that I'm particularly good at.

0:29 I obviously I used to code quite a bit

0:30 in the past but I haven't actually written any code

0:32 myself in many years and actually these things get programmed

0:34 in C which isn't a language I know at all.

0:37 Um on the electronic side I last used the soldering

0:40 iron probably when I was about 16 years old.

0:42 So that was again a bit of a learning curve

0:44 for me but I have made a digital doppelganger of myself.

0:48 So what it does is it talks to chat GPT or rather you talk to it,

0:53 it talks to Jack GPT.

0:54 Chat GPT talks back to it and then it says things and I

0:58 basically went out of my way to try and make it behave like me.

1:02 So the in terms of the content there's this thing called a rag layer

1:06 and the rag layer basically injects extra

1:08 information because of course chat GPT doesn't know

1:10 anything about me but what this layer does is it searches for keywords when

1:14 you say certain things and it injects

1:16 some biographical information into the query you send

1:19 to chat GPT say you know so if you were to ask how old

1:22 are you if I had put in that rag layer if you were asked how

1:25 old you are you you should know that you're 60 years old and that would

1:29 then pass the chat GPT so that when it answered the question and said,

1:32 "Oh, I'm 60 years old." So that it actually knows those things.

1:36 So that's part of what it does.

1:38 I also use my voice, which actually I lifted off your videos uh because

1:42 it needs a long decent sized sample of my voice.

1:44 So I just lifted a whole bunch of my voice

1:47 from your videos to actually train it on my voice.

1:51 So the point of this paper,

1:53 so one of the things you can do with chat GPT is you can fine-tune the model.

1:57 You can make it behave in particular ways.

1:59 So I actually tried using we did an interview

2:01 ages ago where you asked me about my life.

2:03 So I used that as a way to try to uh to finetune Jack GPT.

2:08 Turns out that turned chat GPT into a psychopath which is

2:11 a bit bit alarming in that if basically whatever questions you asked it,

2:15 it would just laugh maniacally in response.

2:17 Um so um uh turns out it's it's you know

2:21 there are some subtleties involved here but uh uh basically

2:24 yeah I sort of tweaked around with chat GPT

2:26 to try and make it behave a bit more like me.

2:28 Will its answers be a little bit more mic

2:31 than if I use chat GPT myself on my phone?

2:34 A little bit because the version of chat GPT I'm using is fine-tuned.

2:37 So it's not so I tried to fine tune it turns out.

2:40 So there are limitations to what you can do

2:42 with fine-tuning for example and the the one I

2:44 ran up right up against is what one obvious

2:48 question is where did you go to university right?

2:50 If and in the untuned version if you say where

2:52 did you go to university it says I went to Cambridge.

2:55 I never went to Cambridge, but it knows I'm a scientist and it somewhere deep

3:00 in its mind thinks scientist must have gone to Cambridge.

3:03 And I fine-tuned it and one of the way

3:05 you fine-tune it is by queries and responses, right?

3:07 And so I would query where did you go to university?

3:10 I went to Oxford University.

3:11 And I would ask that 15 different times.

3:14 Feed that into the fine tuning.

3:16 Then you you ask chat GPT where did you go to university?

3:19 Oh, I went to Cambridge.

3:21 So for some reason it's very hardwired into it some pieces of information.

3:26 So no amount of fine tuning and that's where I

3:28 ended up turning it into a psychopath in I kept doing

3:30 the fine more and more fine tuning to try and get

3:32 it to answer that question right and it never got there.

3:35 It just went completely dally.

3:37 Have you fine-tuned it much with your just like

3:40 your opinions and your beliefs and things like that?

3:43 Not much only a bit things like you know

3:45 what's your favorite food and that kind of thing.

3:47 So the the the not but that's not the so that was the other bit right

3:50 this the fine-tuning is trying to make it

3:52 behave in particular ways then there's this other

3:54 thing called I really ought to know what

3:55 rag stands for anyway this thing called a rag

3:57 layer which sits on top of it which

3:59 feeds in that biographical information and the reason

4:01 I implemented that rag layer was basically

4:04 to try and overcome this problem so now it

4:06 knows so one of the things in that rag layer is where did you go to university

4:09 Oxford so now it knows that as a piece of biographical fact that it it will

4:13 get right all right well I want to do

4:14 an interview with you I've written some questions.

4:18 Yeah.

4:18 And I've written and I want to I want to ask

4:20 you the questions and I want to ask your doppelganger the questions.

4:24 You've got two there.

4:25 You said like that's V1 and V2 there.

4:28 So this is so this is the latest incarnation which isn't working terribly

4:31 well for some reason that I haven't quite got to the bottom of.

4:33 Um but it's just I just made a pretty version cuz I put it on I got

4:36 a a printed circuit board made to put it on to make it as small as possible.

4:41 I I 3D printed a box for it.

4:43 So this is the box I printed for it and I put an external

4:46 antenna on it and a nice little cover for the microphone and things.

4:49 So this is the the finished product, but this is kind of this was the working

4:52 version that I actually first tried it all on.

4:55 So I can show you what the bits are if you like.

4:56 So it's sitting on one of these things called a breadboard,

4:58 which is just a way of kind of wiring together circuits.

5:01 This is the brains of the operation.

5:03 This is the the kind of the the little microprocessor that controls

5:07 the whole thing with its various outputs and inputs to it.

5:10 Uh and it's got an antenna attached to it.

5:12 So, this is an antenna for Wi-Fi.

5:14 This is a little amplifier that plays

5:16 the the voice coming out to a speaker here.

5:19 And this is the microphone.

5:20 And you can see there just basically wiring that joins

5:22 the the microcontroller up to the amplifier in the speaker.

5:26 Let's do it.

5:26 Okay.

5:27 You want me first?

5:30 What is the Messier catalog and how important is it to modern astronomy?

5:35 So, it's a collection of a hundred or so objects collected by Charles Messier.

5:39 And actually, some of them he observed himself,

5:41 some of them were observed by other people that he put together uh

5:45 that were things that are not comets

5:47 because he was actually interested in finding comets.

5:49 And so, they're fuzzy things um that might be confused

5:51 for comets that he didn't want to be confused by.

5:54 It's a kind of fairly eclectic mix of things.

5:57 some clusters of stars, some nebula,

6:00 some galaxies um that are kind of make nice targets for amateur astronomers.

6:04 But in terms of for mainstream astronomy, it's not that important really.

6:08 The Messia catalog is a list of astronomical objects compiled

6:11 by the French astronomer Charles Messier in the 18th century.

6:15 It includes nebula, star clusters,

6:17 and galaxies primarily to help distinguish these objects from comets.

6:21 There are 110 entries in total.

6:24 Its importance to modern astronomy lies in its role

6:26 as a reference for amateur and professional astronomers alike,

6:29 serving as a guide to some

6:30 of the most prominent and accessible deep sky objects.

6:33 It also laid the groundwork for further

6:35 exploration and classification of celestial bodies.

6:39 How is being a professional astronomer different today to what it

6:43 was like when you were doing the job in the 1990s?

6:47 I think probably the biggest difference is the amount of data we have.

6:50 In in the 1990s, we were incredibly data starve.

6:54 We fought for every photon.

6:55 We over interterpreted every single result that we got.

6:58 We really analyzed the each individual data set.

7:00 Now there are these huge data sets being generated and you mine

7:04 in a completely different way from the way we were doing science then.

7:08 Being a professional astronomer now is quite different from the 1990s

7:11 largely due to advancements in technology and data analysis.

7:15 In the past, astronomers relied heavily

7:17 on photographic plates and manual measurements.

7:19 While today we have sophisticated digital

7:21 imaging and powerful software for data processing,

7:24 the internet has also transformed collaboration allowing for real-time

7:28 communication and sharing of research across the globe.

7:31 Furthermore, the availability of large astronomical surveys

7:34 and databases has changed how we conduct research,

7:36 making it easier to access vast amounts of information.

7:39 The field is more interdicciplinary now,

7:41 blending techniques from computer science and engineering into astronomy.

7:45 What are the three most beautiful objects in space

7:49 and why are they beautiful other than my wife?

7:51 No, she's not in space.

7:52 Um, the three most beautiful objects and why are they beautiful?

7:57 I guess probably mostly although I study galaxies mostly

8:01 I'd probably pick planetary nebula just because they're gorgeous things.

8:04 You get these incredibly intricate structures forming when these stars explode.

8:07 So some of the planetary nebula out there are probably very beautiful.

8:11 I'd have to pick a galaxy like Messier 31, the Andromeda galaxy,

8:14 just because I've studied it a lot and it is rather a pretty galaxy.

8:17 Although actually probably Messier 51 is a prettier

8:19 galaxy because it's a beautiful spiral structure.

8:21 So there we go.

8:22 That's three.

8:23 Okay, I'll give you that.

8:25 Beauty in space is quite subjective,

8:27 but three objects often mentioned are the Orion Nebula,

8:29 the Andromeda Galaxy, and the Ring Nebula.

8:32 And the Orion Nebula is stunning due to its vibrant

8:35 colors and intricate structures showcasing the process of star formation.

8:39 The Andromeda Galaxy, our nearest spiral galaxy,

8:42 captivates with its majestic spiral arms

8:45 and the sheer scale of its millions of stars.

8:48 Finally, the Ring Nebula is beautiful for its striking appearance,

8:51 resembling a cosmic smoke ring,

8:53 and it's a fascinating example of a star at the end of its life,

8:56 shedding its outer layers.

8:57 Each of these objects offers a unique glimpse into the wonders of the universe.

9:01 What is the biggest unanswered question in astronomy,

9:05 and how and when is it likely to be answered?

9:09 I guess it's probably one of these things to do with the nature of dark matter,

9:12 the nature of dark energy.

9:13 That's kind of a very big picture question where we

9:15 really still don't have very much by way of a clue.

9:18 I don't know when it's going to be answered to be honest,

9:20 but because we don't really have that much of a clue,

9:22 but there's lots of people working on it.

9:23 One of the biggest unanswered questions in astronomy

9:26 is the nature of dark matter and dark energy.

9:29 We know they make up about 95% of the universe,

9:32 yet we still don't fully understand what they are.

9:34 Current efforts like the Large Hadron Collider and various

9:37 astronomical surveys aim to shed light on these mysteries.

9:40 It's hard to pinpoint exactly when we might have answers,

9:43 but advancements in technology and observational

9:45 techniques over the next couple of decades

9:47 could bring us closer to understanding

9:49 these fundamental components of our universe.

9:52 If you were given a week of observation time on the telescope of your choice,

9:58 what telescope would you choose and how would you use it?

10:02 It will be the James Web Space Telescope.

10:04 Have to be these days because it is the premier instrument out there.

10:07 And honestly, I'd probably use it to search for life on exoplanets.

10:11 So, I'd try and come up with some clever

10:12 way of analyzing the atmospheres of them to search

10:14 for those bio signatures that would tell you there's

10:16 life there cuz that'll get me a Nobel Prize.

10:20 Would you like to win the Nobel Prize?

10:22 I think everyone wants to win a Nobel Prize, don't they?

10:24 If I had a week of observing time, I'd choose the Extremely Large Telescope.

10:27 With its incredible light gathering power and advanced instrumentation,

10:31 I'd focus on studying distant galaxies and their dynamics.

10:35 It would be fascinating to explore

10:37 the interactions and formation processes of these galaxies,

10:40 potentially revealing insights into dark matter's role in their structure.

10:44 I'd also dedicate some time to public outreach,

10:46 sharing the experience and findings with enthusiasts and students,

10:50 making the most of the opportunity to inspire others in the field of astronomy.

10:53 Would you like to win the Nobel Prize?

10:56 Winning a Nobel Prize would certainly be an incredible

10:59 honor as it recognizes significant contributions to science.

11:04 However, the real joy comes from the pursuit

11:06 of knowledge and sharing discoveries with others.

11:08 Making a meaningful impact in the field and inspiring

11:11 the next generation of astronomers is what truly matters.

11:14 Who is the greatest astronomer ever and why?

11:20 Um, present company accepted of course.

11:23 uh greatest astronomer probably Edwin Hubble I guess probably is the person

11:28 who kind of revolutionized our view of the scale of the universe

11:31 and the nature of galaxies so really contributed in a massive

11:35 way to our understanding of the universe it's tough to single out

11:38 one astronomer as the greatest but many would argue for Johannes Kepler

11:42 his laws of planetary motion fundamentally

11:44 changed our understanding of the solar

11:46 system moving us away from the geocentric model Kepler's work laid

11:50 the groundwork for Newton's laws of motion

11:52 and universal gravitation shaping modern astronomy.

11:55 His blend of observation and mathematics was revolutionary

11:58 and his influence is still felt in the field today.

12:00 Will alien life be discovered or confirmed in the next 50 years?

12:06 Yes, there you go.

12:09 That's a very definite prediction.

12:11 Uh I don't know how, but I'm pretty confident we'll find it.

12:15 Predicting the discovery of alien life within the next 50 years is challenging,

12:19 but the prospects are intriguing.

12:20 With advancements in technology and missions

12:23 like the James Webb Space Telescope,

12:25 we're gaining unprecedented insights into exoplanets and their atmospheres.

12:29 The search for bio signatures is becoming more sophisticated,

12:32 and missions to Mars and the icy moons

12:34 of Jupiter and Saturn may yield promising results.

12:38 While we can't say for certain, the next few decades could bring us closer

12:41 to confirming whether we're alone in the universe.

12:44 That's right.

12:45 Yeah.

12:45 Yeah.

12:48 Thanks for watching.

12:49 I'll put links down below in all

12:50 the usual places to more videos with Mike Mirfield.

12:54 And why don't you head over to our computer science channel.

12:56 It's called Computer File, where we've done a similar experiment creating

13:00 a virtual version of our very own Mike Pound.

13:03 Of course, these are the computer scientists, so it's all a bit more advanced.

13:06 It's well worth a look.

13:07 I want you to please promote him straight to a full

13:09 professorship position and demote me back to a PhD student.

13:13 Uh, also I want you to divert all

13:15 of my grant money straight into his personal bank