by Y Combinator7/6/2018
Fermat’s Library is a platform for annotating papers. Each week they send out a paper annotated by their community. Some recent papers were Birds and Frogs by Freeman Dyson and Von Neumann’s First Computer Program by Donald Knuth.
They’ve also built a Chrome Extension call Librarian for the arXiv which allows you to get direct links to references, do BibTeX extraction and make comments on papers.
You can find them at FermatsLibrary.com
Craig Cannon [00:00:00] – Hey how is it going? This is Craig Cannon and you’re listening to Y Combinator’s podcast. Today’s episode is with João Batalha and Luís Batalha, co-founders of Fermat’s Library. Fermat’s Library is a platform for annotating papers. Each week, they send out a paper annotated by their community. Some recent ones include Birds and Frogs by Freeman Dyson and Von Neumann’s First Computer Program by Donald Knuth. They’ve also built a Chrome extension for the arXiv called Librarian which allows you to get direct links to references, do BibTeX extraction and make comments on papers. You can find them at fermatslibrary.com. All right, here we go. You guys are brothers, right?
João Batalha [00:00:40] – Yeah he’s the older one. I’m two years younger.
Craig Cannon [00:00:42] – Okay, and what made you want to start Fermat’s Library?
João Batalha [00:00:46] – Just for the people who don’t know what it is. Fermat is a platform for annotating papers. If you want to think about it, you imagine a PDF view in your browser and then you have annotation on the side that support LaTeX and markdown. You can add an annotations in parts of paper that you figure particularly tough to understand or where you think there you can add more content there. But there is something that we’ve done… The four of us that started Fermat’s, we all have a technical background. After college, we kept on reading papers and every once in a while, we had this internal journal club. Where we would read a paper and present it to the others, so I remember for instance presenting few years back presenting the Bitcoin paper. To Luís and Micael which don’t have a CS background. You have to go into first instance for the Bitcoin. You might have to go into, “Okay what’s an hash function? What’s public key encryption?” We are already doing this and we knew that they also have this behavior offline in places like universities. We wanted to take that experience and bring it online. We thought there is a lot of content that you end up producing while you’re trying to read a paper, which can be the most dense piece of content that humans can read sometimes. The language can be incredible spartan and sometimes there is a step in some paper to say that this should be obvious. But then you look at it and so okay I don’t get it. We knew there was a lot of content there
João Batalha [00:02:26] – that you end up producing while trying understand a paper, we wanted to bring that online.
Craig Cannon [00:02:33] – ‘Luís, you were in physic before?
Luís Batalha [00:02:35] – Yeah, I studied physics together with Micael. And João and Tymor went to MIT. Tymor studied economics, and you studied CS. A lot of the papers are around physics, maths, economics, biology, CS.
Craig Cannon [00:02:52] – Beccause you solved the cold start by just annotating yourself.
Luís Batalha [00:02:57] – Exactly.
Craig Cannon [00:02:58] – Now it is like more getting the author in there.
João Batalha [00:03:00] – Exactly, that was the growth hack. Our first paper work was the Bitcoin paper.
Craig Cannon [00:03:05] – Yep and still the most commented.
João Batalha [00:03:07] – Yeah, that one has a good number of comments, it has been there for the longest and it is was quoted. Just they are a bunch of news sites that have pointed back to it. And okay if you want to read it, go to the annotated version. We had a few cool people out there.
Luís Batalha [00:03:26] – Lawrence Lessig. Commented on the Bitcoin paper. A bunch of people from the Bitcoin communities had comment there.
João Batalha [00:03:28] – A bunch of people from the Bitcoin communities had comment there. The larger goal with Fermat is to try to move things in the right direction meaning move science towards what people call open science. Thatvencompasses a number of things from open data, which meana just sharing the data that have used for publishing or whatever research you might publishing and you want to share that. Make that easy and accessible to people so if they want to replicate the results that you got or use it in their own research, they have an easy time doing that so that’s open data. You also have just publishing the code that we use or the algorithms that have used and making those more easily available to people. There’s also open publishing which means just publishing and papers that not behind or in journals that are not behind pay walls. There’s a lot of things that are within open science. All of those and then there’s also, we want to push things in that direction and also try to build a platform that make it easier for people to collaborate. And we think that there’s a lot of things
João Batalha [00:04:42] – that can be happening nowadays where scientists could be collaborating remotely a lot more than they are or that’s at least the way we think, but it’s starting change where we’ve had the paper there those.
Luís Batalha [00:05:01] – This is actually a trend. We’re seeing more and more people collaborating online or on papers. So for instance, there is these famous example, around the problem call the Erdős Discrepancy. This problem is a famous problem that was posed by Paul Erdős which is a famous mathematician, 80s years ago. Terence Tao, the Fields Medalist was trying to solve the problem. He put it on his blog that he was trying to get the search and approach to solve the problem. Then this guy from Germany that just wrote a comment there like the size of a tweet. He said that the Erdős problem had the Sudoku like flavor. That some of the machinery that they were using to solve the Sudoku problem could be used there. That was actually the key to crack the problem and they ended up publishing a solution to the Erdős Discrepancy problem, which was probably one of the biggest milestones in number theory in 2016. That was all thanks to a comment on these blog and to the fact that they were collaborating online, around solving there problem.
Luís Batalha [00:06:10] – Which is also was also polymath problem. The Polymath Project was a project started by these other Fields Medalists called Timothy Gowers. It was actually a social experiment to see if it was possible to solve a math problems online collaborating on your own math problems online and yeah and they were able to solve it, thanks to that comment.
João Batalha [00:06:34] – You look at GitHub and then you think of the impact that GitHub has had for open source. Open source of course existed much before GitHub but it had really allowed a lot more people to come in on be able to get into open source, and start contributing And there are a number of other really interesting platforms. We do have Wikipedia just for more general knowledge or you have Stack Overflow which is programmers helping each other. We think that they could be something similar to that but for science in general.
Craig Cannon [00:07:09] – Did you listen to the Rogan with Peter Aattia?
João Batalha [00:07:13] – Parts of it.
Luís Batalha [00:07:14] – Micael listened to that.
Craig Cannon [00:07:16] – It was a really good one and he talks about, I don’t know if they’re talking about the arXiv in particular around publishing papers, but he talks about having full time staff just scrubbing the data looking for interesting information coming out. Again in the context of Stack Overflow, that’s the place where programmers find specific answers to problems.
João Batalha [00:07:40] – Exactly.
Craig Cannon [00:07:41] – Whereas with the arXiv like good luck. Good luck finding that stuff. Have you guys thought about addressing just discoverability in the context of particular fields?
João Batalha [00:07:54] – It’s really tough problem. For instance paper recommendations. It’s really hard to….
Craig Cannon [00:08:01] – Because you’re just doing one week right now. In addition to the browser extension.
João Batalha [00:08:05] – We also have our tool that is used internally at universities and research groups for people that they are reading papers together, and they add annotation. But for now, we have the Weekly Journal. We release the paper every week that we select and we annotate it or somebody in the community annotates it. Then we have our arXiv extension that adds a bunch of features on top of arXiv like BibTeX extraction, reference extraction and comments and it eventually definitely like recommendation. A recommendation engine and making it easier to discover papers that are relevant to you. That’s something we definitely want to add onto our arXiv extension, but it’s a tough problem.
Luís Batalha [00:08:54] – Initially, we started Fermat’s as João said as a Journal Club and then we saw that people like the interface. The commenting interface and liked reading the annotations, so now we are starting to expand and turn Fermat’s into more of a platform qnd that’s why we decided to do the arXiv Chrome extension. Because arXiv for people that don’t know what it is, it’s basically a place where papers live before they go to journals in the form of pre-prints. They are like drafts before they go to journals. What we did is build the Chrome extension that basically allows people to see all the commenting interface on arXiv papers. You don’t have to go another website, you’re just reading arXiv papers and you see the comments on the side if you have the Chrome extension installed.
Craig Cannon [00:09:48] – Well in a lot these papers, don’t even have comments.
Luís Batalha [00:09:50] – They don’t.
Craig Cannon [00:09:51] – Best case you’re emailing the author.
Luís Batalha [00:09:56] – So what arXiv does is basically they just host papers. That’s the core functionality of arXiv. One of the things that we noticed is that especially for areas like machine learning and deep learning, arXiv is super important because the new papers are coming out at such a high rate that people don’t wait before the papers go to journals before they start working on top of it and using the stuff that other people discovered. All the papers are published on arXiv, and so you need a way to distinguish good quality work from bad work if you are reading a paper on arXiv that hasn’t been peer reviewed or something about machine learning, and I think that’s why the Librarian’s extension is so important such as machine learning.
Craig Cannon [00:10:49] – Does the Librarian extension have a rating mechanism as well? How do you distinguish good from bad work?
Luís Batalha [00:10:55] – Right now, it’s only through the comments. But we are actually thinking about implementing some rating system for papers.
João Batalha [00:11:04] – We’ve been thinking about that for a while now, and we’re probably going to run a few surveys to our audience because you could do it in a number of ways. Like rating a paper, you could do it. Obviously there’s likes or dislikes or uploads and downloads. You can have just an implicit rating for the whole paper. You can also imagine the rating it a number of different aspects of the paper. It could be about how big their dataset if they’re using some dataset or what do you think about their methods. So you could have a more complex rating system and so we’ve been thinking about that a lot and we’re just trying to figure out what makes the most sense there. But that’s also definitely, we would love to add that to arXiv or to our Chrome extension program.
Craig Cannon [00:11:55] – How do you think the collaboration plays out then? Because I understand how say for instance you’re a physicist. You start commenting on someone else’s paper. You start a discussion that creates a new project. Do you think you’ll go further than there? Are you talking about forking and that stuff?
João Batalha [00:12:15] – There’s a lot of things that you could do once you have a platform that has more people in it, and that they’re doing more stuff in it. That’s why the way, we’ve been growing Fermat is with a goal far in the future where we are a much broader platform. Right now, we are focused mostly on solving problems that people have nowadays. Actually we were largely inspired for our arXiv extension by the survey that the arXiv guys did where they had, I don’t know how many people but they surveyed the people that used arXiv and then published a paper where they described the problems that those people reported while using arXiv and the things that they most wanted to see. The features that they most wanted to see, and then the arXivs folks just said. Hey we’re just going to be the platform to build upon and we’re not going to do all these things that people want, would like us to do. But we here it is, this is what people want to see. If there’s anybody else that wants to work on this, here are the results of the survey. Since then they’ve actually done a pretty great job of building an API and wanting to become more of a platform. There’s a lot of ways that we envisioned that we could have collaboration around science, and so forking a paper or forking some type of research.
Luís Batalha [00:13:48] – Or data.
João Batalha [00:13:49] – Exactly or data, there’s a lot of things that it could do there. It’s not something that we’re focused on right now. Right now, we’re just trying to solve these problems that people have pointed out and created a place where people can just post comments, and discuss around a paper.
Luís Batalha [00:14:05] – An example of the problems that people mentioned was for instance reference extraction. If you go to a PDF, at the bottom of the paper. You have the references that they used. And most of the times when people want to search the references, they have to copy the text in the PDF. Put it on Google and try to find the link to the paper. One of the things that we did with our Chrome extension is we allowed that. They just click on the button in the Chrome extension and then they see a list of references with links to the paper. It was one of the features that was most requested by the arXiv users. Our idea was initially we wanted really to convince people to install the Chrome extension. And so let’s solve the hair on fire problems that they are describing here. And then once we have people using the Chrome extension then we can expand into open collaboration around papers since they are already there, so that was that.
Craig Cannon [00:14:59] – Do you guys know of anyone working on publishing negative results? This is something I’ve been fascinated with. Basically the problem is as an academic, you’re not incentivized to publish negative results because you want to publish things that have high impact so you can get a job or attend your position, or just get people to even care about your work, right? So they don’t publish. Do you know anyone working on that?
João Batalha [00:15:26] – I know of researchers that are studying that field a lot. But unfortunately, for some of these things. That’s a very large problem, and people are becoming more aware of that. And with that you get negative results but you also people doing a lot of research into the P value of hacking.
Craig Cannon [00:15:46] – Yeah, you should explain that.
João Batalha [00:15:48] – Yes, so P value, it’s essentially a standard that people use in order to know if the results that you have obtained out of some experiment that you’ve run are worthy of being published. That has worked for the most part that has worked fine until now. But we’re running the target but people are looking into it and thinking, okay should we do things differently and should we be much more stricter with what’s considered the golden standard to publishing. We’ve thought of doing things there with Fermat early. Just so that if you’re looking at a paper to have an idea. Okay, how relevant is this paper? This is more specific for a certain areas like if your talking about medicine or biology where that is really important. The statistical significance of the results that you are presenting. That’s all, that’s the most important thing. We’ve thought of doing something with Fermat there. Either via some API where you could send us the DOI (Digital Object Identifier) for a paper and we would send you some information regarding the P value or something. Or with a a Chrome extension where you would see that information displayed very prominently. Saying hey, there might be some P value hack in here or this is very solid research because that is a very big problem and people are realizing how prevalent it is especially in things like economics and–
Luís Batalha [00:17:25] – Biology.
João Batalha [00:17:25] – Biology.
Luís Batalha [00:17:27] – Nutrition.
Craig Cannon [00:17:27] – Nutrition. It came about, I was just talking to a friend who’s doing a PhD at Cambridge in Bio.
João Batalha [00:17:33] – That’s a big thing.
Craig Cannon [00:17:34] – Yeah and only by attending a conference in the states that he realize that there were someone in Australia working on the exact same problem as him concurrently. They’re failing at the same types of experiments but because they don’t publish them, no one knows the results, no one knows the methods and essentially these traveling salesman type problems that people are so excited about quantum for. Trying all those permutations are happening at a smaller scale but no one’s publishing anything. So the progress isn’t happening.
João Batalha [00:18:08] – Yeah, and part of it is just the way research is done and you come into it and you’re trying to find some correlation. You will be trying to find some trends in the data. You are going to usually have that bias. You’re trying to find some correlation in publishing that so yeah, you might need to change things dramatically in order to get people to start publishing negative results which could be incredibly useful for other researchers. But there are much people working on that. There’s this researcher at Stanford. I’m forgetting his name. It’s John, I forgot his last name, but he actually just went on this podcast EconTalk.
Craig Cannon [00:18:57] – I love EconTalk.
João Batalha [00:18:58] – Yeah, so you should listen to that podcast and actually Tymor has been talking to the professor. I think it’s the professor at Stanford and he has analyzed more this subject but it more relating to the economics I believe. He’s found a lot of the things we’re talking about here. They’re prevalent also in economics.
Craig Cannon [00:19:21] – Cool, let’s go into the Twitter questions. We’ve got a ton of questions. You guys are very popular on Twitter. Congrats on your great following, let’s see, let’s start with something broad. Tanner Gobblenstein asks what are the most interesting papers you read in the past couple of years that are not widely known?
João Batalha [00:19:44] – That’s interesting. I ended up reading all sorts of papers from different areas.
Craig Cannon [00:19:52] – How do you get the papers actually?
João Batalha [00:19:54] – It’s like random walking people.
Craig Cannon [00:19:58] – Really?
João Batalha [00:19:58] – It could be random walk, it’s funny. Or sometimes you will think for instance. A few months ago, I got a Fitbit to track my sleep and so I wanted to read papers about sleep. And so that just got me into a random walk around. Let me search around sleep and then I found a bunch of interesting things. I ended up annotation a paper about a big study in Finland that was done regards to the association between sleep and mortality. There are a bunch of really interesting things that I learned from there. For instance, that if you sleep less than seven hours, that’s associated with higher mortality. You should sleep more than eights hours that is also associated with higher mortality.
Craig Cannon [00:20:47] – Have you changed your life based on that?
João Batalha [00:20:48] – I was usually more on the end of not sleeping enough but there is also another thing from that research that currently sleep quality doesn’t matter as much, at least for mortality, which is counter intuitive but it seems that just sleep quality is very closely related to the amount of sleep that you’re getting. Seven hours of okay sleep verses seven hours of great sleep. That’s hard to distinguish.
Craig Cannon [00:21:18] – You sleep on airplanes your whole life and live as long.
João Batalha [00:21:22] – Yeah, yeah apparently. Maybe your life will be a little bit more miserable but it’s hard sometimes to pick the favorites but there is one that is random. But it’s a paper published in the 90s about the Simpson’s paradox and the hot hand phenomenon in basketball. The hot hand phenomenon in basketball is you think that okay because they just made a few goals, the next one, they have a higher chance of making it. There is this researcher that in the 90s looked at a dataset from the Celtics to see if for free throws if that was true. Before they had asked students at Stanford and Cornell like a hundred students. If they just made the first free throw is it before the second one? Are they higher? Do they have a higher chance of making it or not? And there was something like 68 of the 100 students that were asked that agreed and they thought that was true. And it’s people from Stanford and Cornell, and so then they looked at this and what they found back in the 90s. What they found was that actually, that seemed not to be the case. Your second free throw, you’re not more likely to make it if you made the first one, but what they found is that you’re just more likely to make it on your second one.
Craig Cannon [00:22:58] – Objectively.
João Batalha [00:22:58] – Significantly. Yeah, and so this was done in the 90s with I don’t know how many free throws. Maybe 5000, they looked at some data from the Celtics.
Craig Cannon [00:23:07] – Just across the Celtics?
João Batalha [00:23:09] – And then I went and got a dataset from Kaggle with 600,000 free throws.
Craig Cannon [00:23:15] – Free throw shots?
João Batalha [00:23:16] – And I reran the same rhythms that they ran for the study in the 90s, and then looked at what the results were. The pattern is pretty clear that just under second free throw, they’re just much better at it significantly regardless of their first one. And it doesn’t matter if they made their first one or if they missed. That paper then tried to explain why people think that there is a hot hand phenomenon and that is related to the Simpson’s paradox. For people that don’t know what the Simpson’s paradox is… It’s also a really changed my world view a little bit once I learned more about the Simpson’s paradox. But it’s basically what it says is that you can get two valid conclusions out of the same data depending on how split it. An example is for instance between 2013, the median wage for high school dropouts in the U.S. has dropped for high school graduates. It also dropped for people with an undergrad degree, it dropped and for people with a graduate degree or higher, it also dropped. Across the board for all of those segments the median wage dropped, but in aggregates it went up. You look at it and it’s like what’s going on here. And it turns out is that what happens is that a lot more people got a degree. So they just shifted towards higher education and so that’s why you get on average it going up,
João Batalha [00:25:12] – and then for each one of these segments, it goes down. The Simpson’s paradox is that depending on how you cut the data, you might get different results. But in this case it’s pretty easy to understand that you should be like what’s the right way to look at this data but in some of other cases it’s not clear whether or not you should include this variable or cut the data in some different way. Relating it back for this basketball issue, what it was is that if you looked. The results were different whether you looked on a player by player or if you looked at the aggregate. Once you collapse it all into the same table, you get different results rather than when you looked at it player by player and so yeah. If you collapse it, I forget exactly the way it went but if you collapse it might have been that you indeed saw. You didn’t see the hot hand phenomenon but if you looked at it player by player, you saw it. They’re arguing that that’s why people had the idea that’s why you get 68 students out of 100 saying that they believe in the hot hand phenomenon.
João Batalha [00:26:19] – And so some of the paper is really random..
Craig Cannon [00:26:29] – Has it been relevant to you in terms of physics? You’re working on software now, right?
Luís Batalha [00:26:34] – Yeah, I also end up discovering really cool physics paper. So for instance my two favorite papers were actually written by Freeman Dyson. One of them is when he proposed the concept of a Dyson sphere. It’s just one page and he basically explained how an advanced civilization would need more energy than the energy that we can generate on Earth. We would have to go to a star and build a cap around the star to extract the energy of the star, but it’s funny because it’s really simple maths and physics equations. He was able to derive, okay is this a sphere’s table. Is it going to eat indefinitely and so it’s a really interesting paper. And the other one that I really like is one about Feynman’s derivation of Schrödinger’s equation, and also written by Freeman Dyson. It just shows Feynman’s intuition about quantum mechanics and it’s also really simple and easy to read even if you don’t have a physics background. But one of the things that I notice from trying to find papers and annotating all these papers was that in the 60s and all the way through the 20th century. All these discoveries and all these papers were mostly like one, two pages. And it’s so funny, and also fairly simple to read but the discovery of the neutron is maybe one column just the discovery of the positron. The Dyson’s sphere of paper. They’re really, really short papers and fairly accessible.
Craig Cannon [00:28:24] – Why do you think they’ve gotten so long? Is it like David Foster Wallace hiding a million things because he doesn’t have confidence?
Luís Batalha [00:28:31] – I think it’s also consequence of a field developing. You will just have more complex questions and so it’s harder to write.
João Batalha [00:28:43] – They’re also a little bit more detailed as to the methodology and the format of papers has gone a little bit more formal in that sense where people follow us. The very specific format and I think that has added onto but yeah nowadays they tend. Like the gravitational wave that we annotated. That’s relative. That’s what, like 15 pages?
Luís Batalha [00:29:06] – Maybe, it would be interesting to analyze the constraints in terms of size that the journals we’re imposing like 50 or 60 years ago compared to what they’re doing now is they were forcing people to write shorter papers back then. Not sure but I if the discovery of the positron paper was published today. I bet it wouldn’t just be a single column.
Craig Cannon [00:29:36] – Well are they intended to be more reproduceable now?
Luís Batalha [00:29:39] – Good question, maybe. Yeah or maybe it’s just more complex problems that they are tackling now. It might be the case.
João Batalha [00:29:53] – It’s definitely not going back it seems. You don’t really see a trend anywhere. The shorter papers but it’s interesting. You go back to the 50s and 60s and then it was pretty nice.
Craig Cannon [00:30:07] – All right cool, so let’s go to another question. Polaris seven asks what are the necessary ingredients in a good and impactful science writing?
Luís Batalha [00:30:18] – This is also a good question. I don’t think that I’m qualified to, I haven’t published that many papers to know that but one of the things that we noticed or that at least I noticed from reading papers is that sometimes it’s not like the discovery paper that is the most impactful paper. For instance, I just remembered when Quantum Electrodynamics was discovered, there were three guy working on that problem. So Feynman, Schrödinger, and … and they were working independently on that problem. And publishing papers on Quantum Electrodynamics. The most impactful paper was actually published by Freeman Dyson, who at the time, took the time to analyze all the work and unified the work refinement of … and Schrödinger wrote a paper that helped modern researchers understand what Quantum Electrodynamics was back then. And helped really spread their work, so it was actually most impactful paper.
Craig Cannon [00:31:35] – In other words, they had clear writing?
Luís Batalha [00:31:37] – Exactly yeah, clear writing.
João Batalha [00:31:40] – It’s also the question here is impactful scientific writing. And so you have of course writing papers and then you also have just scientific writing in the sense of makings some concepts more explaining that to a more general audience. It’s also the same where you want to make it clear and you want to make it accessible. But for instance even something like the Bitcoin paper. I studied cyrptography in college and it took me a few reads through it to actually get it. And it’s a beautiful paper but it’s definitely not. It’s very spartan language, and you want to read every sentence. It can be very challenging to approach it and I think definitely you always benefit if you can make it as clear and accessible as possible. Because you never know the audience that is going to end up reading your paper. You of course, you can expect other people in your field are going to read it but sometimes things can be useful especially for interactions between maths and physics. It’s going to be useful in different fields and so I think it’s always beneficial for science if you try to make it as accessible as possible. What does impact mean? It mean number of–
Craig Cannon [00:33:03] – Well that’s a question as well. Did you see that one from Adam, Adam Baeba asks basically the metrics for value add?
Luís Batalha [00:33:12] – Yeah, I can see that. What does the impact mean if it’s the number of citations that you get or just a number of people that learn about a certain subject because of a paper. In that way, a review paper can have a really big impact compared to a discovery paper. It’s one of the problems that we also think about a lot. This metrics and what are the incentives in science and what makes people want to publish a paper or why should people worry about clarifying a paper and making it understandable to as many people as possible. Do they have the incentives to do that? How can you create incentives to do that? And then sometimes if the metric is just the number of citations. Sometimes it’s not aligned to making the paper understandable and comprehensible to a large audience.
Craig Cannon [00:34:11] – Is that a question that you guys have to tackle? Because on one hand, you want to illuminate these papers that people could potentially learn from. Then on the other hand, you’re running a site with content and you want things that are going to capture attention. I saw you have the Charlie Munger post on there, right?
Luís Batalha [00:34:30] – Micael annotated the Charlie Munger paper. Our other co-founder.
Craig Cannon [00:34:35] – Yeah, yeah so it’s squarely non-technical paper, but Charlie Munger has millions of fans across the world.
Luís Batalha [00:34:41] – Exactly.
Craig Cannon [00:34:42] – Right, so you have to balance those two things.
João Batalha [00:34:44] – It’s not easy, and citations are definitely a proxy. If the paper is getting studied a lot. It has some importance but it’s definitely not perfect. And is you look at the most cited papers in these different fields, you might be surprised that they’re might not be the ones that you expect it to be. I certainly remember looking at most cited papers in computer science, and there are definitely very impactful. But some of them, I remember reading through those 10 and some of them I’ve never heard about before. Sometimes it’s very important, well this is more specific for certain fields. Very important concepts or discoveries never really get published in one paper that then gets a ton of citations. The knowledge gets spread in some other way. Citations are not perfect but I wouldn’t say that we have a great answer for that. What’s a better proxy and how you should go about it? I don’t think anybody really right now has a better answer or not that we’ve heard about. It’s an interesting problem. We’ll see what people started using in the future. Because you could measure impacts. How many people are talking about it on social media?
Luís Batalha [00:36:11] – You see a blog post star rating about this paper or if you have code, and if you have a public repo. How many forks do you have on your repo?
João Batalha [00:36:22] – Then it depends on field by field so if you take bio then bio papers can be used very directly say in industry. You can publish a paper about a drug, and then that can be used worldwide and save lives. For that field, maybe you can, there are a bunch of other metrics that you could use there to calculate the impact of the paper. But for the more traditional science like physics and math, it’s hard.
Craig Cannon [00:36:59] – Okay, question up top. Arselon Yarvisee asks, it’s basically about working in public and the speed of publishing. They say since scientific papers usually go through scrutiny and evaluation before getting published. How do you cope with not being always up dated and up to speed in a world with daily news and contributions? It relates to what we were talking about before in relations to people publishing to the arXiv before they really test it out. Where do you guys fall in that dynamic of publishing as soon as possible with something like machine learning where things are just getting put out all the time verses going through a peer review before getting something up?
João Batalha [00:37:46] – This loops into peer review, which is a whole world unto itself that people are talking a lot about. For us generally or for our weekly journal, we generally are not publishing the most recent research. There is definitely sometimes there’s a lot of us having to catch up to even, I remember annotating a paper about this machine learning algorithm to play one-on-one poker. And this was out of my league. I actually go spend a good amount of time there researching it and also figuring out okay, how relevant is this. I also don’t because I’m not in the field so it’s hard for me to gauge what’s the impact of this paper. Sometimes it takes us a lot reading up before we can actually say okay, this is worth publicizing and having our audience. In short our stamp of approval and saying hey, you should read this. I think you’ll like it. It could take a while sometimes, but in the future looping back to peer review. That’s also something that the system nowadays does not seem to be perfect the way things work now a days, and we would love to see other either via Fermat or some other platform to try to tackle that and try to do something to make the peer review a better system or to change it significantly. I think there is a lot of work left to be done there. Which can have a very significant impact of science. That’s part of the most important aspects of science is just having a very skeptical mindset looking at it.
João Batalha [00:39:43] – With a very critical eye and seeing okay is this something that we can build upon? This is something that we’re going to add to over foundations to build more science upon this and so that’s a very important aspect of science and it’s not perfect and could be better.
Craig Cannon [00:40:02] – Anvil Rotterdam asks, have you ever thought of building a tool for annotating books? Something like what Patrick Collison was talking about in his tread. Where he basically says, “I’d pay a lot more for books if I could see the highlights annotations and marginalia of friends or people I follow.”
Luís Batalha [00:40:19] – It’s actually really a good question and we have a friend, Jess Riddle from the Prematory Institute. He’s a researcher there that writes about this on his blog. Besides annotating academic papers, it also makes total sense to annotate books, and especially introductory books about science. He gives his example of a book that is used by thousands of students to learn classical mechanics called Goldstein. There is a section on that book where they talk about this transformation called the Legendre transform. He does a bad job of explaining what it is, apart from that section, the rest of the book is awesome. It’s really nice if you want to learn classical mechanics but if I want to write a book that does a better job at explaining the Legendre transformation. It has to be net better than the Goldstein book so that anyone will adopt it. Otherwise people will just keep using the Goldstein books so it would make sense for books to be annotated and also be open source, so that in that sense, you would just commit a new chapter. A new explanation for that and keep all the other chapters and just change that bit. Instead of having to write a new book, and then convince people to adopt your book.
Luís Batalha [00:41:57] – Just because of that. It makes total sense to do that more…
João Batalha [00:42:02] – We’ve thought about that though. The type of things that he could do. If you had some platform where you could have books that kept being updated. Okay, this is the standard for learning calculus this is constantly being up to day. You were adding exercises to it. People are forking in, if you need more information about this, you’re not understanding it. You could deep dive into it and you have a bunch of additional content that is attached to it. Really feels like something that should exist and we’ve thought about it. About doing something with Fermat for that. Just so many things.
Craig Cannon [00:42:46] – In terms of copyright, are there massive issues there or is that possible?
João Batalha [00:42:52] – I think we might be facing some of the same challenges that Wikipedia is facing to an extent. It would depend a lot on the format that is used. I do think there’s, for something like this, you probably benefit from having some editor or a team of editors to curate and to see okay. Should we add this? Should we not to an extent to be a curating voice. In terms of copyright, you can run into some issues there. Well some of these especially the classical books on electromagnet is more like–
Craig Cannon [00:43:34] – They’re out of copyright. My impression was that these are maybe current books coming out. Popular fiction even, as annotated by X famous person, maybe if the gave away their notes for free and they were just a layer on top then you’re good. But if you wanted to resell your own version of the book.
João Batalha [00:43:58] – Yeah, that’s interesting. There is some legislation, well there’s fair use. You can use a piece of content if you’re adding onto it or this is why you can have a video on YouTube with a snippet from the movie if you’re revealing it. There’s some precedent there for doing this type of thing. But for more general books, I also agree that it would be amazing. We were just talking about this. We’ve talked about this for a awhile now because you read the book and the purpose of that book is not only for you to absorb all the knowledge that is there but it’s also to get you thinking about what’s being talked about in the book. Then you might reach some other conclusion. You might go on a tangent, and when you’re reading it that knowledge might never be shared with anybody else. You might just read it yourself, and you think, okay this just made me think about something else. And there’s a lot of knowledge that is being lost. And it would be great if you could capture it in some way.
Craig Cannon [00:45:11] – The Amazon Kindle highlights site is one of the saddest things you’ve ever seen. Have you ever done that?
João Batalha [00:45:16] – We have Kindles but we haven’t explore them.
Craig Cannon [00:45:18] – Oh yeah, so there is a whole web interface for looking at all of your highlights across all of your Kindle books. It’s not good.
João Batalha [00:45:26] – So do you use it for anything?
Craig Cannon [00:45:27] – Sometimes I go back, so the best way that I found for me personally to retain is to buy the audiobook and go through a book a couple times. Then my retention goes way up, but occasionally I’ll be just like, what is that passage in whatever book. And I’ll go back onto Amazon and you can–
João Batalha [00:45:46] – It’s from Amazon.
Craig Cannon [00:45:47] – Yeah, you can dig through your highlights from your Kindle.
Luís Batalha [00:45:50] – I think I’ve seen the startup that does it in a bad where they pulls your highlights and organizes them on the key note aisles.
João Batalha [00:45:59] – I remember looking into this what I’ve started doing is I also use Kindle and so that I don’t usually don’t write annotations via Kindle. Someone you were highlighting unusually, don’t use it for that. But if I’m reading a physical book, whereas before I’d never write anything. Now I try to write a lot more there and then at some point if I have time to try to go through the books see where I wrote things and then write that in some notebook. Because there is just going through that exercise of looking at what you highlighted can be very helpful.
Craig Cannon [00:46:43] – I was an English major in college, so I’ve forgotten more books than a lot of people have to read in college. And one of my professors actually recommended this which is basically take a 5×7 index card, and as you’re reading the book, you’re making little notes. You’re like all right, this character does this. This is an important point, and then at the end you basically write a paragraph to your future self describing your memories of the book and what happened and important ideas and that can really trigger it for you to retain, to pass that level.
João Batalha [00:47:18] – But I remembered in school or back in Portugal. We all have to read this epic poem that is called the Os Lusíadas. It was written by a poet back in the day. It’s about the Portuguese going from Portugal all the way from Portugal all the way to India. The Portuguese discoveries and so remember we had a version. You had the original version which is pretty thick and then we also have the version that had annotations on the side for each verse. Not for all of them but for a lot of them, and that made such a big difference because you’re reading in old Portuguese, which by itself is already hard to tell. He’s making references that he has no clue about so much historical context in every word, almost. India was not called India, everything is different and you’re reading it through the first time you go, it sounds great, it rhymes. But you don’t understand a lot of the context behind it, and if you go through it and you read through it and then on the side, you have all this rich content that really only adds onto your experience and makes it much more memorable. You can map it out in your mind, and create much more connections. It really enriches your experience. And of course, you have this because in this case, this is an epic poem that everybody has to read and so there is a large incentive to publishing the annotative version of this book that is no longer under copyright. There you can have those types of things. But for a lot more recent books, I think you can benefit a lot from having that to some extent if you’re reading through these few pages,
João Batalha [00:49:09] – and you love what the author is talking about here. You want to dig deeper into this topic that he’s talking about right now. There should be some place where you could do that but yeah, just nobody has actually built this.
Craig Cannon [00:49:22] – I think that defaults towards the blog-o-sphere for most people. People summarize books and write Amazon reviews.
João Batalha [00:49:32] – But then the thing there is that and sometimes that content does exists but being able to find it easily. Having that in your fingertips can make a whole difference. All right, you could spend a minute searching on Google and you’ll find the kind of content there you’re looking for but it feels right there. You could click and it would pop up, and you’d see it then. It would be much more likely that you would end up reading that content. Those type of things make a big difference being right there.
Craig Cannon [00:50:04] – Do you find that annotations sometimes are best done by someone who is not the author of a paper?
João Batalha [00:50:12] – What’s interesting is that the authors of the paper sometimes they are not going to know where people are going to know where people are going to struggle understanding the paper often times. I remember when I was annotating the Ethereum white paper written by Vitalik. I went through it and then I emailed him and he’ super quick to reply. And he replied back with some of the questions that he gets the most about Ethereum. Make sense. But when you’re writing it, you have no clue. You’ve worked it out in your minds, some steps you might skip ’cause you have internalize them by so much. You only know where people are going to struggle once you put it out there and you start getting questions. And so sometimes the authors are not the best.
Luís Batalha [00:51:06] – Every time we talk with an author, I think it’s easier for them to answer questions about their papers than to annotate the paper. But then if you have another person annotating the paper, I think it’s easier for them because with the authors we see that a lot. Just ask me questions, I will answer them, but sometimes I don’t know how to enhance or add content to my own paper.
Craig Cannon [00:51:30] – Yeah, you guys can provide those services for sure. You give reverse engineer clear papers. It’s worth noting that this is a side project for you guys. I have so many questions about how you go about building this thing that’s definitely consuming a lot of your time. It has to between finding reading papers, making all those graphics and tweets and stuff that you guys do. How do you find that balance? What’s your whole philosophy around this?
Luís Batalha [00:52:06] – Yeah, it definitely takes its time. It is something that we actively try to do after college, and before doing Fermat. Reading papers and staying up to date is something that we try to do anyway. We were already looking into research before it was just something that we would enjoy and then we found it good to have some peer pressure amongst ourselves to present papers to each other. Because that really forces you to understand something well. I think it was fine, he had some quote where you don’t understand something until you can explain it–
Craig Cannon [00:52:49] – I’m a five year old.
Luís Batalha [00:52:50] – A freshman in college. And so that’s very true, and so we tried to do that amongst each other. And so then we got to Fermat and we thought, okay, maybe we can bring this online. And so, we are already spending an healthy amount of time doing this type of stuff. But it is, well Fermat you have two. The first version of Fermat, we build it over the weekend and we tried to just put it out there as fast as possible. And then it’s mostly late at night, I’ll be trying to fix bugs. People in Hacker News don’t seem to think that it is a side project.
Craig Cannon [00:53:32] – It doesn’t matter.
Luís Batalha [00:53:33] – And everybody harsh on it, so there’s definitely bugs, sorry about that. We’ll try to fix them when we have time Yeah, but it definitely takes its time.
João Batalha [00:53:44] – It’s also something that all of us really like doing and I start looking at Wikipedia articles about Quantum computing. And then I spend three hours tweaking on articles and articles, and then I found five papers to annotate. And I’ve produced 10 or 15 tweets, so it’s something that we really enjoy doing. Yeah, and so it’s– I think that’s the real genius of it. It’s basically figuring out a way to turn your, if you have the desire. What would be your hobby anyway. Exactly, and having a forcing function because this type of thing is really easy to let go. Because sometimes you might not feel like understanding a paper to the point where you could annotate it. It takes a while to get a good grip especially if it’s not an area that you are super familiar with.
Craig Cannon [00:54:40] – Of course.
João Batalha [00:54:41] – And so that’s definitely not the type of effort that you do on a Saturday night unless you had a foreseen function that you know that within a couple weeks you’re going to be putting this to a lot of people.
Craig Cannon [00:54:55] – That’s my favorite part of the podcast. With the software stuff, it’s pretty easy for me to. It could be anyone in the room, and we can do a podcast. But when we do physics ones or math or something. I’m just like, “Oh my God.” I had to take a couple days just reading. Obviously I couldn’t even become an expert if I dedicated a week to it but I want to be conversant to a certain extent, and that part is fun.
João Batalha [00:55:17] – Yeah, same with us. You definitely feel the pressure when you’re writing these annotations. And people call you up, and they’ll be okay, this is wrong or you missed this. And so when you’re writing, you want to be really careful. Make sure that what you’re saying is correct and you know that you might have somebody that actually, a college kid or whoever that is reading through that paper and then is going to use your annotation to help them understand. And so you have the responsibility. We feel that responsibility towards those people to do a good job at it. And to when we put an ambition, we want to stand by it and we want it to be of quality.
Luís Batalha [00:56:02] – And it’s funny, the more you annotate a paper, it’s like a circle. The more you annotate a paper, the more people there are at the edge of starting to understand what the paper is about. You start getting more and more questions because the circle expands, and then you just have more people that are starting to understand this topic about number theory or physics or whatever. You get more and more questions about the paper. And then when do stop explaining a certain concept? You want to annotate a paper about number theory. Okay, do you have to explain what a prime number is for instance or do I have to explain what a rational number is? So it’s really interesting once you start thinking about that. How deep do you go.
Craig Cannon [00:56:50] – But you got to be careful about those YouTube videos then because if you get discovered on YouTube as an explainer series, good luck.
Luís Batalha [00:57:02] – We’ve annotated a paper that it was a proof of the rationality of the square root of two. And then there was this, I think was 14 year old kid from Russia that because of that paper, he came out with an alternative proof for that. And he sent us that proof, and I read the proof and it was apparently…
Craig Cannon [00:57:28] – It was legit?
Luís Batalha [00:57:29] – Yeah, and I told him to submit that to a math journal, and I think he did it. I haven’t heard back from him, but we should reach out to him to see if he was actually able to publish it. So it’s also nice to see how we can inspire people sometimes to do this types of things. I also think especially with Twitter, one of the things that we learn is that learning something, learning a concept or learning a fact is really, really addictive. And we see that on Twitter almost everyday. People come back and we have hundreds of thousands of users that read our tweets. That’s why people really like when they have a good teacher, and when they can go to a class and really learn something. The problem is that usually that requires a lot of effort from people. You either have to go to a class or you have to read a book to learn something. I think what we’re able to do with our Twitter account was to provide that same feeling that acquiring the quantum of knowledge but at the cost of reading the tweet, which is really easy for the reader. Sometimes it’s really hard to make those tweets. It requires a lot of reading and thinking how can you explain something with just these characters and an image maybe. But once you get to that, and once you’re able to teach someone a fact or something, people really like that. I think it’s something that there should be more people exploring that on Twitter. It’s a very particular medium.
João Batalha [00:59:14] – But there’s a lot of people that are attracted by that. You might not, a few years ago, I would have been very surprised but now you have all these scientific explainers. But you have people that have millions of followers and what they’re following for is for scientific content. They just want to learn and so that’s something very uplifting that we’ve learnt. That there’s a lot of people out there that want to learn.
Craig Cannon [00:59:42] – It’s too easy to get down on these people. They’re just like, oh this is base. It’s fun facts or whatever. I’m like at the end of the day, that’s good. People are excited to learn. They want to learn, and then you extrapolate it out a little bit more and you look at someone like Dan Carlin, doing the Hardcore History podcast. I think if you would have objectively written that down. All right, I’m going to produce 25 hours of content about the Khans and people are going to be into it. I would have told you no fucking way, and then you look at it and it’s like millions and millions and millions of downloads. That’s pretty cool.
Luís Batalha [01:00:16] – There’s some things that you look at and it really catches you by surprise. This is parallel but it’s, Wikipedia for instance. If somebody had pitched Wikipedia to me before Wikipedia existed, I would have never guessed that would be possible. Because rightly, how are you going to do this? No incentive, people are going out of goodwill. They’re going to add content to it, and it’s going to be good content, reliable. Things that you can use to learn, and that’s just not something that you would initially think would fit with human nature. But people surprise you positively and the same goes for Stack Overflow. People just out of goodwill, they will go out and explain or try to help you solve your problems. There is something to be said that humans have some untapped fountains of goodwill that we might not be leveraging as much as we could.
Luís Batalha [01:01:21] – You see it, bright spots here and there and like Wikipedia or Stack Overflow. Some projects if you pitch them to me before they existed, I would be very skeptical that they would be able to get to the point that they are today.
João Batalha [01:01:34] – Of all the parallel universes, we are in the universe where Wikipedia exists.
Luís Batalha [01:01:38] – Exactly, there’s got to be a lot of parallel universes where Wikipedia doesn’t.
João Batalha [01:01:43] – Didn’t survive.
Craig Cannon [01:01:44] – Yeah, it’s like when you talk about you guys expanding. You almost don’t have to over engineer the incentive mechanism if you believe that it’s true. Right, like annotating more papers as objectively interesting to people.
Luís Batalha [01:01:59] – Exactly. We will always have people that are going to be interested in consuming the content and reading, then you have the other side. How do you create incentives for people to annotate the papers?
Craig Cannon [01:02:14] – Right.
João Batalha [01:02:15] – Some things is just that it takes some time and when we started this, we knew that it would take time and it took people to care at all about what you’re doing. And then it takes even more time to make any impact on the issues that we care about. But for a lot of these things, even say if you look at arXiv. It was started, splits my age. It started August 1991, and it has taken a long time to get to where it is today. And if you look at the graph of submissions for arXiv. It’s completely almost linear. There is no start up exponential growth. It’s completely linear but it’s arguably one of the things that has impacted the makings of science or the distribution of science to most but it just took a while to grow. And seems like it’s just going to keep growing linearly but sometimes that’s what you need. We are totally mindful of that, and we know that this might take a really long time until you can get to do what our ultimate vision is to build that out. But some things, they just take some time.
Craig Cannon [01:03:32] – Do you feel pressured to achieve profitability or even sustainability in the business?
Luís Batalha [01:03:40] – No, not at all.
João Batalha [01:03:41] – We never really thought about that and also probably because this is a side project. We never really thought about monetizing or achieving profitability. It is for some of these communities, like Stack Overflow, it’s a for profit company, and I think it does a great job at what it does, and I am probably happy that it is a for profit company because they’re just more independent than if they have good leadership that takes it in the right direction. It’s great because they don’t need to ask for donations to keep going. Wikipedia is a non-profit, and they’re been doing great. So it’s possible to do it both ways. Because we have very limited resources. We try to focus all of our attention in the areas that are the most important into what we’re trying to achieve. That means we have to prioritize. So meaning our next step is going to be building the chrome extension for arXiv verses doing anything else because we think that’s what has the biggest impact. That’s why we never delve into profitability and we just paid the costs ourselves. It’s just server cost. We do all the work, so it’s never something that has been in our minds a lot, and we think we could build these types of platforms either for profit or non-profit. Just something we’ll defer further down into the future. That’s a question for instance, could arXiv survive if they were a start up for instance?
João Batalha [01:05:22] – Right if they were for profit.
Luís Batalha [01:05:24] – Yeah, could they raise money with that linear growth, if they were not inside a university? Yeah, that’s a good question.
Craig Cannon [01:05:33] – Yeah, plenty of companies without startup growth raise money and become profitable or sustainable. What are you going to charge for people who care because arXiv is great because it’s open. And so many other journals maybe dying out because they are not.
Luís Batalha [01:05:51] – Yeah, absolutely. Of the trends that we’ve also noticed is a lot of people building journals on top of arXiv. And we are even collaborating with a few journals. One of them being the Quantum journal which is an overlay journal and top of arXiv on the quantum physics category. What they do is basically, so what is a journal is just a list of links to papers and so they don’t have any hosting costs. They just have a page where they just have the links to all the papers that they decided to publish, and all the papers are on arXiv, so it’s completely open. What our partnership with them is basically all the papers have the Fermat’s Library commenting interface. But we are seeing more and more of these journals popping up, so for instance the Erdős Discrepancy solution was published on one of these open journals called Discreet Analysis. It’s totally possible that these open journals get to a point where they have a reputation like Science or Nature. As long as you convince people to publish their papers on these journals. There’s nothing about Science or Nature that is unique to them and prevents these open journals to get to that point. Of course it’s also going to take time but I think it’s totally possible.
João Batalha [01:07:24] – Yeah, exactly. A lot of people talk about this where you have journals that put content behind paywalls and that might have been funded with public funds. There is the whole discussion about that and it is a tricky system to get out of because it is in a stable equilibrium to a sense. Because if you are a researcher, you need the publication and Nature or whatever to get your post doc position in a renown university and so you have incentives for the status quo to persist. But there are a few ways that you could get out of it. Right as Luís was mentioning, one way is for these open journals to start gaining more reputation. So that if getting published in Discreet Analysis, it’s a big deal and it has a lot of reputation attached to it. And once that starts to happen, you get more and more people just putting it all out there on arXiv and publishing it all in open journals. The other ways that you could get out of the system for specific fields like what we were talking about machine learning where you have an incentive to publish as fast as possible because the field is just moving so quickly. And nowadays journals or big conferences might take time. A lot of time for submitting it until it actually gets out there. If you’re submitting to NIPS or whatever for machine learning. It takes a long time for it to actually be officially published and so you also have that incentive that if it’s open publication, you can move much faster. And so it is a tricky equilibrium to get out of and that’s why these companies
João Batalha [01:09:19] – make billions of dollars in revenue.
Luís Batalha [01:09:22] – One of the ways that they are probably the way to get these open journals to be as popular as nature or science is to convince people that already have a tenure. A really famous scientist to publish on those journals. You already have your position, you already have your Fields Medal, your Nobel prize, just publish on an open journal. And that’s what Terence Tao did with the other discrepancy and that’s what other people are doing. Tim Gowers which is a field medalist also, it’s mathematician which founded the Discreet Analysis open journal and he wrote a blog post a while ago. His mission was to convince famous mathematicians and people in this situations to publish on open journals.
João Batalha [01:10:21] – Because for the young researcher that is trying to get a position in a uber competitive field. Then you need right because if you want to get your post doc in a renown university, you need to have that. That’s what’s keeping alive… So these big names endorsing the open journals.
Luís Batalha [01:10:39] – That need to be the grow effect to increase the reputation of these open journals.
João Batalha [01:10:45] – Absolutely, and what is interesting because it is a problem and we definitely believe that’s the right direction. And while you’re in the U.S., while I was studying at MIT. You don’t really realize it because if you’re within the MIT network everything is open. You’re accessing it and when I was in undergrad, I didn’t even realize.
Craig Cannon [01:11:05] – In other words if you’re literally on the MIT WiFi, you have access to these journals and it’s not paywalled.
João Batalha [01:11:10] – And you don’t even see okay, this would be $30 if I was five blocks down that way. But Luís was studying in Portugal and so we would talk and then we would compare. Even in Portugal where you have well funded universities but the research groups might not be able to afford all the journals and so you just sometimes you just have a lot of trouble accessing research and so this is not in the U.S. It is big institutions have access to it, but in a lot of other parts of the world, the fact that a lot of research is being published in non open journals has a significant impact.
Craig Cannon [01:11:50] – Especially when legit CS papers are written by people who aren’t associated with any university. They’re just hobbyists writing things. Why would they have a hundred journal subscriptions?
Luís Batalha [01:12:04] – I remember even like other researchers in my research group. Sometimes they would have to go through CERN to get VPN through CERN to get access to these papers or I would have to email you and ask you to send the PDFs.
Craig Cannon [01:12:23] – You’re a good brother.
João Batalha [01:12:24] – I contributed.
Craig Cannon [01:12:26] – Five bucks If someone wants to contribute or help out, what can do they to help you guys?
João Batalha [01:12:33] – There are a few ways that you can help us out. You can annotate a paper on Fermat’s Library.
Luís Batalha [01:12:39] – Also email us at team@fermatslibrary.
João Batalha [01:12:42] – Exactly if you want to annotate a paper there.
Luís Batalha [01:12:46] – Spread the word and if you’re at a university then–
João Batalha [01:12:51] – If you have a journal club. If you have a research group and you want to annotate papers and share them among your peers.
Luís Batalha [01:13:00] – When you created an account in Fermat, now you can also upload your own papers. You have that option and then you can share it with whoever and you can create your own lists and so we have people at universities that use this already. Be it for classes and students have to read papers and so they will post annotations on Fermat or just within research groups and they all decide to read a paper. And so if you’re at university and if you want to use this, it’s completely free so you just need to sign up.
João Batalha [01:13:32] – Those are the two main ways that you can help us out. We’re also taking cryptocurrency donations. But really most of our costs are just server costs so we don’t have to pay salaries to anybody. So yeah, that’s about it.
Luís Batalha [01:13:52] – That’s the way to help us.
Craig Cannon [01:13:54] – Cool all right, thanks guys.
João Batalha [01:13:55] – Thank you for having us.
Craig Cannon [01:13:57] – All right, thanks for listening. As always you can find a transcript and video at blog.ycombinator.com, and if you have a second. It would be awesome to give us a rating and review where ever you find your podcasts. See you next time.
Y Combinator created a new model for funding early stage startups. Twice a year we invest a small amount of money ($150k) in a large number of startups (recently 200). The startups move to Silicon