YouSaid · the spoken record

Dawn Song

lines on the record: 146
first: 2020-05-12
most recent: 2020-05-12
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“Oh, let me just add one more thing. So it's interesting. So sometimes, yes, it can help you to focus. So when I shifted my focus more from security to AI and machine learning, at the time actually one of the main reasons that I did that was because at the time I thought the meaning of my life and the purpose of my life is to build intelligent machines.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“It's a question we can say, right? Like whether it's a well-defined question. And on the other hand, given that you get to answer it yourself, you can define it yourself, then sure, that I can just give it an answer. And in that sense, yes, it can help. like we discussed if you say oh then my meaning of life is to create or to grow then then yes then i think they can help But how do you know that that is really the meaning of life or the meaning of your life? There's no way for you to really answer the question”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean yes and no in a sense that I think for people who really dedicate time to search for the answer to ask the question what is the meaning of life it does not necessarily bring you happiness”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, and for me, I think certainly we do share a lot of similarity here. Like, so creation is also really important for me, even from the things I've already talked about, even like, you know, writing papers, and these are all creations as well. And I have not quite thought whether that has really the meaning of my life. Like in a sense, also that maybe what kind of things should you create? There are so many different. Things that you could create. And also you can say another view is maybe growth is related but different from experience. Growth is also maybe type of meaning of life. It's just you try to grow every day, try to be a better self every day. And also, ultimately, we are here as part of the overall evolution. The world is evolving again.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Some people they can, I think they may say it's experience, right? Like their meaning of life, they just want to experience to the richest and fullest they can. And a lot of people do take that path.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, and also you can see it's deeper, but you can also say it's shallower, depending on how people want to define the meaning of their life. So for example, most people don't even think about this question. Then the meaning of life to them doesn't really matter that much. And also whether knowing the meaning of life, whether it actually helps your life to be better or whether helps your life to be happier. These actually are often questions. It's not most questions are open.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“And another question is like, what does it really mean by the meaning of life? Right. And also whether the question even makes sense.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, okay, so for that, I have an answer. And through the long period of time of thinking and searching, even searching through outside voices or factors outside of me. So that I have, and I've come to the conclusion and realization that it's you yourself that defines the meaning of life.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, yeah. So in my own case, I didn't need to face mortality To try to ask that question. And I think there are a couple things. So one is who should be defining the meaning of your life. Is there some kind of even greater things than you who should define the meaning of your life? So for example, when people say that the searching the meaning for your life is, is there some outside voice or is there something outside of you who actually tells you so people talk about, oh, this is what you have been born to do. Right, like this is your destiny. So who, right? So that's one question, like, who gets to define the meaning of your life? Should you be finding some other thing, some other factor to define this for you? Or is it something actually, it's just entirely what you define yourself and it can be very arbitrary.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“It's interesting that you ask this question. Maybe this question is probably the question that has followed me and followed my life the most.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Remember I mentioned one of the jobs for me to computer science is how easy it is to realize your ideas. So once I read a book, I taught myself how to programming C, immediately what did I do? I programmed two games. One is just simple, like it's a go game. Like it's a board, you can move the stones and so on. And the other one actually programmed the game that's like a 3D tetris. It turned out to be a super hard game to play. Yourself just standard two detachers is actually a 3D thing But I realized, wow, you know, I just had these ideas to try it out.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So maybe as I mentioned actually in college one summer I just taught myself programming C. You just read a book and then you.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so this is the other point I was going to mention is that especially in academic research, everything is public. Like we write papers, we open source codes and all this is in the public domain. It doesn't matter whether the person is in the US, in China, or some other parts of the world. They can go on archive and look at the latest research and results.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“I believe so. I think it's science that has no border. And the advancement of the technology helps everyone, helps the whole world. And so I certainly hope that the two countries will collaborate. And I certainly believe so.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“It was a very different time. At the time We didn't even have easy access to email. Not to mention about the Remember, I had to go to specific privileged civil rooms to use email. And hence at the time we had much less knowledge about the Western world. And actually at the time I didn't know actually in the US the west coast whether it's much better than the East Coast. Yeah, things like that actually. But now it's so different at the time. I would say there's also a bigger cultural difference because there was so much less opportunity for shared information. So it's such a different time and world.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So yes, I think especially back then, it's very different from now. So, you know, now actually I see students coming from China and even undergrads, actually they speak fluent English. It was just, you know, like amazing. And they have already understood so much of the culture in the US and so on.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“It's not quite the same. You don't derive the computer systems with just a few simple laws. You actually have to see there is historical reasons why a system is built and designed one way versus the other.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So I can start to switch to computer science. And one thing I think maybe people have realized is that for people who studied physics, actually, it's very easy for physicists to change to do something else. I think physics provides a really good training. And yeah, so actually it was fairly easy to switch to computer science. But one thing back to your earlier question. So one thing I actually did realize, so there is a big difference between computer science and physics where physics you can derive the whole universe from just a few simple laws. And computer science, given that a lot of it is defined by humans, systems that define by humans and artificial.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Bring it to life. We're seeing physics if you have a good theory, you have to wait for the experimentalist to do the experiments and to confirm the theory and things just take so much longer. And also the reason in physics I decided to do The writing of physics was because I had my experience with experimental physics. First, you have to fix the equipment.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Anyway, so then I realized instead of just doing programming for doing simulations and so on, then I may as well just change to computer science. And also one thing I really like that's a key difference between the two is in computer science, it's so much easier to realize your ideas. If you have an idea, you write it down, you code it up, and then you can see it actually. Exactly. Running and you can see it.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Actually, it's interesting, you know, in physics at the time, I think now the program private has changed. But at the time, really the only class we had related to computer science education was introduction to, I forgot, to computer science or computing and Fortune 77th.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“And also, at the time from talking with the senior students in the program, I realized many of the students actually were going off to Wall Street and so on. And I've always been interested in computer science and actually essentially taught myself C programming.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So that's very interesting. So that gets to the transition from physics to computer science It's quite different for physics in grad school actually things changed. So one is I started to realize that when I started doing research in physics, at the time I was doing theoretical physics. And a lot of it, you still have the beauty, but it's very different. So I had to actually do a lot of simulation. So essentially, I was actually writing in some cases writing Fortune code.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“But anyway, so when I studied physics, I was, I think I was really attracted to physics. It's really beautiful. And I actually, physics is a language of nature. And I actually clearly remember one moment in my undergrads, like I did my undergrad in Tsinghua and I used to study in the library. And I clearly remember, like one day I was sitting in the library and I was like writing on my notes and so on and I got so excited that I realized that really just from a few simple axioms a few simple laws, I can derive so much. It's almost like I can derive the rest of the world.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So when I first came to the United States, I was actually in the physics PhD program at Cornell. I was there for one year and then I switched to computer science, and then I was in the PG program at Kennedy Malone. So, okay, so the reasons for switching. So, one thing, so that's why I also mentioned that about this difference in backgrounds about having studied physics. First, in undergrad. I actually really did enjoy my undergrad time and education in physics. I think that actually really helped me in my future work in computer science. Actually, even for machine learning, a lot of machine learning stuff, the core machine learning methods, many of them actually came from physics.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“That's very possible, some of my undergrad classmates then they later on studied physics got their PhD in physics from these schools from top. Physics programs.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Because of that time in you, actually, it's interesting. I think even more so, maybe something that's Even be more different from my experience than a lot of computer science researchers and practitioners is that, so for my undergrad, I actually studied physics.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a good question. I think, so I studied in China for my undergraduate and that was more than 20 years ago. It's been a long time.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, exactly. And I think that's a particular domain that as a community, we need to put more emphasis on. And I hope that we can make more progress there as well.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“And just like in deep enforcement, we don't want to just train agents to play a particular game. Either it's atari or its goal or whatever, we want to train these agents that can essentially extract knowledge from the past learning experience to be able to adapt to new tasks and solve new tasks. And I think this is particularly important for program synthesis.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it's not just for programming synthesis, it's also cutting across other fields in machine learning and also including deeper enforcement learning in particular is that This adaptation is that we want to be able to learn from the past and tasks and training and so on to be able to solve new tasks. So for example, in program synthesis today, we still are working in the setting where given particular task, we train the model and to solve this particular task. But that's not how humans work. The whole point is we train a human and you can then program to solve new tasks.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So to be able to generalize to previously unseen inputs. And so some of the work we did earlier, learning recursive neural programs actually showed that recursion actually is important to learn. And if we have recursion, then for certain set of tasks, we can actually show that you can actually have perfect generalization. So one of the best paper awards at iClear earlier. So that's one example of we want to learn these neural programs that can generalize better, but that works for a certain task, certain domains, and there's question how we can essentially develop more techniques that can have generalization for a wider set of domains and so on. So that's another area. And then the third challenge.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Generalization like one way train, I want to learn program synthesizer in this case, a neural program to synthesize programs, then you wanted to generalize.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, for example, initially our first work in programming synthesis was to translate natural language description into really simple programs called iftt, if the standards. So given the trigger condition, what is the action you should take? So that program is a super simple. You just identify the trigger conditions and the action. And then they say, oh, with SQL queries, it gets more complex. And then also we started to synthesize programs with loops and.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“See the complex Meaning, we want to be able to synthesize more and more complex programs, bigger and bigger programs. So we want to see.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“The complexity of the task to be synthesized and the complexity of the actual synthesized programs. So, the lines of code, even for example.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“And also, I think in terms of you asked about open challenges, I think the domain is full of challenges. And in particular also, we want to see how we should measure the progress in the space. And I would say mainly. Three main, I'll say, metrics. So one is the complexity of the program that we can synthesize. And that will actually have clear measures and just look at the past publications. And even like, for example, I was at the recent NeuroRibs conference, now there is actually fairly sizable session dedicated to programming synthesis, which is.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Again, in limited domains, actually, it can work pretty well. And now this is also a very active domain of research. At the time, I think when he saw our paper at the time, we were the state of the arts. On that task. And since then, actually, now there has been more work and with even more sophisticated data sets. But I think I wouldn't be surprised that more of this type of technology really gets into the real world. That's exciting in the near term.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Actually, so I give another talk at the previous rework conference in deeper enforcement learning. And then I actually met someone from a startup, the CEO of the startup. And when he saw my name, he recognized it. And he actually said one of our papers actually have put had actually become a key product. And that was programmed since in that particular case was natural language translation translating natural language description into sequel queries.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, very good questions. We are still at an early stage, but already I think we have seen a lot of progress. I mean, definitely we have existence proof, just like humans can write programs. So there's no reason why computers cannot write programs. So, I think that's definitely an achievable goal. It's just how long it takes. And then, and even today, we actually have the program synthesis community, especially the programming synthesis via learning, how we call it, neuroprogram synthesis community, is still very small. But the community has been growing and we have seen a lot of progress. And in limited domains, I think actually program synthesis is ripe for real world applications. So actually it was quite amazing. I was giving a talk earlier. So here is a rework conference.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, the reason for that is actually when I shift my focus from security into AI machine learning. Actually, one of our main motivation at the time is that even though I have been doing a lot of work in security and privacy, but I have always been fascinated about building intelligent machines. And that was really my main motivation to spend more time in AI machine learning is that I really want to figure out how we can build intelligent machines. And to help us towards that goal, program synthesis is really one of, I would say, the best domain to work on. I actually call it like a program synthesis. It's like the perfect playground for building intelligent machines and for Artificial generating intelligence.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So yeah, and also for me actually. When I shifted from security to more AI machine learning, program synthesis adversarial machine learning, these are the two fields that I particularly focus on. Like program synthesis is one of the first questions that I actually started investigating.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, program synthesis is about teaching computers to write code. Program. And I think that's one of our ultimate dreams or goals. I think Andreessen talked about software eating the world So I say once we teach computers to write software, how to write programs, then Guess computers would be eating the world by sensitivity”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Enabling ownership of data and privacy of data and so on. So at OECD Labs, we're actually building what we call a platform for responsible data economy to actually combine these different technologies together to enable secure and privacy preserving computation and also using the ledger to help provide immutable log of users' ownership to their data and the policies they want the data to adhere to the usage of the data to adhere to and also how the data has been utilized. So all this together can build what we call a distributed secure computing fabric that helps to enable a more responsible data economy. Saturday things toget”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“So, in this case, for example, you want to enable confidential transactions. So there are different essentially types of data that you want to keep private confidential. And you can utilize different technologies, including zero knowledge proofs, and also secure computing techniques to hide either the who is making the transactions to whom and the transaction amount. And in our case also, we can enable like confidential smart contracts so that you don't know the data and the execution of the smart contract and so on. And we actually are combining these different technologies to going back to the earlier discussion we had.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so actually, in general, on a public ledger in this public decentralized systems, actually nothing is private. So all the transactions poses on the ledger anybody can see. So in that sense, there's no confidentiality. So usually what you can do is then other mechanisms that you can build in to enable confidentiality, privacy of the transactions and the data and so on. That's also some of the work that both my group and also my startup does as well.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“I see. So, in general, for each consensus mechanism, you can actually show theoretically what is needed to be able to attack the system. Of course, there can be different types of attacks as we discuss at the beginning so that it's difficult to give a complete estimate, like really how much is needed to compromise the system. But in general, right, so there are ways to say what percentage of the nodes you need to compromise and so on.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“And what is needed, what amount of resources needed to be able to attack the system? Like, for example, what percentage of the nodes do you need to control or compromise in order to change the log?”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, right. And then that very much depends on the consensus mechanism, how the system is built, and all that. So there are different ways to build these decentralized systems. People may have heard about the terms called proof of work, proof of stake, these different mechanisms. And it really depends on how the system has been built and also how much resources how much work has gone into the network to actually say how secure it is. So for example, people talk about like in Bitcoin is profile work system, so much electricity has been burnt.”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source
“As about security and privacy. So again, as I mentioned earlier, in security, we actually talk about two main properties. The integrity and confidentiality. So there's another one for availability. You want the system to be available. But here, for the question you asked, let's just focus. Integrity and confidentiality. So, for integrity of this distribution, essentially, as we discussed, we want to ensure that the different nodes, so they have this consistent view, usually it's down through what we call a consensus protocol. That's the establish this shared view on this ledger that you can go back and change is immutable, and so on. So in this case, then the security often refers to this integrity property. And essentially you're asking the question, how much work? How can you attack the system?”
2020-05-12 · Lex Fridman Podcast · #95 – Dawn Song: Adversarial Machine Learning and Computer Security · IDENTIFIED FROM THE TRANSCRIPT · source