Welcome to Episode 7 of law.mit.edu's idea flow, an opportunity to go deeper into the various facets of the emerging field of computational law. And today we're going to learn about, and maybe even in our own particular way, help to brainstorm about future directions for this new field known as computational antitrust. And who better to lead us in this discussion than Thibault Shrepple, who I think it's fair to say is the recognized global heavyweight thought leader in the area and who has organized the very successful recently launched Stanford Law School computational antitrust initiative. Which I hope that you'll tell us a little bit more about, especially the impressive list of governmental regulatory agencies and and other experts and stakeholders who have jumped right in in a very public way for this initiative. Thibault is an associate professor of law at VU Amsterdam and also faculty affiliated Stanford, among many other affiliations and he and I know each other. I think, you know, in a sense, I would say through legal hacking circles and adventures and I just couldn't be more thrilled than to have you join the MIT computational community today and to have I see brought some of your, your posse with you as well to help us understand this idea and co think it with you. So, I also want to signal that our own Camila from Brazil is also going to be have a more formal role today as what we call a discussant and that's because she is in her legal practice area. Got quite a good mix of experience with antitrust and competition law, as well as with computational law and technology law in general. And of course, she is the founder of San Pao legal hackers. And so with that, I'd like to hand the baton to you, Thibault, and with a warm welcome, I invite you to maybe start by making a few remarks to further introduce yourself. If you like and talk about the project, but especially introduce us all to this. What is this idea and what are the problems and prospects for the very idea of computational antitrust? Of course. Well, first of all, I'm delighted to to be amongst friends today. I like very much the words adventures. I think it characterizes exactly are the context of our meetings every time we had a discussion. It's always an adventure and we learn. I mean, I learn a lot from you. So I'm very much looking for our conversation today. The thing I wanted to say also is that I've been listening to the previous episodes. And so it feels a bit like being, you know, trapped in the box today because I'm on the other side of the screen, although I'm not too sure if it means anything nowadays with the digital era, but that's a different topic for a different day. I'm here to talk about indeed digital antitrust. And most of all, to hear from you and to gather your thoughts and see if we can make some progress together in just a few minutes, but I'm sure we can. So what we thought we will do is that that first I will give you a 10 minute ish presentation about what I think computational antitrust is, but feel free to disagree with me. You'll see I'll be asking you a question right after the start and then we can keep the conversation going. So for that, not so surprisingly, I do not need to share my screen, but hopefully you can see my screen. My video in full screen. What I will do is that I will use a presentation that I hope you can see right now. So as you see what I've decided to do is to actually open two different tracks and depending on the answer that you will give to the first question I'll be asking you, I will then take one track over the other. So this is, I hope, very much an interactive presentation. But so before we get started, I need to ask you the question that I want to ask you, which is the following.  And here in the context of computational antitrust what I mean is that, should we use computational tools, such as AI and I'm about to be a bit more specific than that to tackle for instance the tech giants. So for you to answer the question. You can take a picture of the QR codes that appears on the screen, or you can go to slido.com, and then on the front page they will be asking you for the even codes, and I've chosen the only even codes that I could choose today, does that. If you just enter that you will get to answer the question. I'm not going to wait for for you all to answer the question. As I speak, I just, I'm just leaving that on the screen for a minute or two. Hopefully at the time to take the picture of the QR code or the slides.com and the even code. In the meantime, what I want to mention is that the idea of computational law and the idea to be able to compute the law is not entirely new, of course, what is new, and it's the pace of technology and all the technologies that we are about to discuss. But going a bit back in time, you may be interested in the work of the Japanese, and in his opinion, and I pretty much have to confess, share the same view. It will be possible with the right tools to calculate legal outcome. Now, I don't think we have all the right tools to be able to calculate all legal outcomes, but potentially one day we will reach that. I mean, this is pretty much a philosophical believe so I'm not going to insist on that today. Something which is closer to the field of antitrust is Richard Posner, who in an article published already 20 years ago. Notice that the mismatch between the law time and the time for markets is troubling to say the least because indeed one goes much faster than the other. Of course, there is a question do we really want lawyers to go faster than markets, not necessarily, but potentially at the same speeds. That might be something that we may want to work upon. So, that is the context of my talk today, and being a bit more aligned with what's happening on today's markets. If you look at some empirical work, you see that we detect pretty much between 13 and 17% of antitrust infringements, which you could say is not too bad but it's also not too good. It means that 90% of the time, if you infringe antitrust you'll be fine, and your practice will go undetected so of course this is not optimal. And if you look at what's happening and what's coming, unfortunately there are reasons to be pessimistic, but hopefully today is a space for an optimist conversation or the realist. But what we see according to the OECD is that competition agencies are reactive, meaning that they wait for companies to go to them and to complain, when in fact, they potentially should be more proactive which is to go out there on the markets and detect practices on their own. This is the question as to the means we give to those agencies, the two agencies in the US would get a budget increase, but I don't believe that this is on the map for the European Commission and any other agencies all over the world so we do have a problem here the one of detection. As I mentioned already, it's unfortunately not about to become better. I mean, don't please don't care about the exact number that appears on the screen right now, those are predictions so it's certainly wrong, but the idea is very important in 2020 so this one you can trust. We've produced all over the world, 44 zettabytes of data, I had no idea what a zettabyte was to check it out, a zettabyte equals 1 trillion gigabytes which is a lot, which is already 40 times more bytes than there are stars in the universe just to give you a sense of what we are talking about here, but in five years we'll be producing 175 zettabytes of data, 600 and over 2000 in just 15 years from now. And that's if you don't have the right tools as an agency to be proactive, then your job will become increasingly complex and potentially this is not great news because we want agencies to be able to detect more practices. So that's issue number one and issue number two is the one after you have detected a potential practice. What do you do. You have the issue of the quantity of the data you need to analyze to give you some number in the Google shopping case, almost 2 billion I mean 1.7 billion search queries were analyzed by the European Commission. The CMA access to Google and being search queries for just one week and they ended up in between three and 4 billion data entries to analyze. So you can have lots of interns but it won't do the trick. Despite the quantity also the nature of data is something we may want to question. What do we analyze do we focus on static competition and just prices, something that we know how to analyze more or less, or do we want to take into account business open the firm black box of bits computer science behavioral insights, etc, etc. So those are a few of the questions that we have to discuss today and a few of the challenges in a bit of a proactive way. I would say we have two solutions we can give up if we give up we could say well you know what the market will take care of it, which is true most of the time but sometimes the market needs 50 or 40 years to take care of something so what do we do in the meantime that's a good question I think. Another one is to say well we regulate everything ex ante which is what's coming in Europe and in the US. But even though you may be doing that you still end up with potential infringement to ex ante regulation, and therefore the ability to detect that and to analyze the infringement comes comes back and so you haven't solved anything by just just working on on such regulation. So if you don't give up, you can work on computational antitrust, and so that's the subject of my talk today. So now looking at the answer that you that you give me gave me, and I'm here putting the answer on the screen so to show you I'm not lying and making the results myself. 75% of you answered that yes it's a good idea to fight fire with fire, and that's therefore computational antitrust is a good idea or at least an idea we should explore. So, going back to my presentation I'm going to explore the yes track. So first of all, thank you very much. As you can guess, I was a bit biased and I hoped that you will answer that it is indeed a good idea to explore computational antitrust. Two things I do want to mention though, it might be that you answered that to please me. That's something that we see a lot in behavioral science so I'm not going to take it for granted that you think computational antitrust is a good idea but I'm going to try my best to convince you even more and we do have 25% of you, thinking it potentially is not a good idea. So the question becomes, if indeed we should use fire, fight fire with fire, which type of fire do we need or to put it differently. If antitrust without computer science is like Sherlock without Watson. The question is, which Watson's do we need. And so here what I briefly want to do is to mention three fields of competition law and policy or antitrust. First being anti competitive practices. The second one being merger control and then antitrust policy to be very brief I mentioned already that we have a detection issue here to have the computational tools, which I will define as computer based problem methods that we could be using is to develop API's and I believe this is something that we may be discussing including with a DASA we juggle with the idea for quite some time that agencies and companies will create flows of data to be able to better understand the markets, something else that could work and is actually already used by some agencies and not to show if I can disclose the names, but is to use natural language processing or understanding. And you could do that on the basis of the documentation, every company as to publish, and there are quite a few of this documentation available as we speak. They do have to send information to financial agencies to data protection agencies, etc, etc. And we know, including from the work of Nicola Petit that using this financial information you can actually detect potential infringements to antitrust. So should you be able to analyze lots of those documents using natural language processing, you could potentially detect some infringements to antitrust and something else that I mentioned is the ability to compare millions of documents data entries, etc, etc. This ties with what I just discussed. A space where we know every antitrust agency can can could start with is with their own case law, because indeed, every antitrust agencies has access to at least its own case law. Regarding the subject Bill Kovacic the former chair of the FTC wrote a paper in which he argued that it will be a good idea that sometime we look at what happened in the past and try to better understand the practices of competition agencies and try to analyze if the decisions were the right call or if we potentially made a mistake. And so, on that idea, we published within the competition I title project the paper by two researchers from Europe, in which they trained a machine learning algorithm boost supervised and unsupervised on top of the FTC case law, especially in the farmer sector. And what they were able to do is to detect patterns of anti competitive practices, and to see that generally speaking, when companies implement one type of anti competitive practice, they also implement another type of anti competitive practice, which is something which was invisible to the UNI. So that's ID number one ID number two merger control. So here we don't have the detection issue. Most companies will notify the merger, but we do have the time factor, and also the fact that potentially agencies have to deal with the loss of data, and they have no choice but to take a decision within 90 days, most of the time. Agencies complain. Those are two of the screenshots that I took on the European Commission website. They complain because they say they don't have all the data companies send misleading information or incomplete databases. A solution could be to force companies to register some information onto private blockchain and ask access to those private blockchain knowing that's if the company wants to get rid of some information before notifying a merger. This will appear on the blockchain and at least the agency could ask why did you get rid of half of the database. So that's another solution that we may want to discuss. And something in here I do have to mention that I'm mentioning and putting on the screen several of the MIT researchers including several of the leading researchers in the MIT who published a paper for the Stanford project in which they argue that potentially we may want to analyze the technology when it comes to merger control instead of simply relying on thresholds and the size of the competitors, etc, etc. So that's another idea I wanted to put on the table. The final one is the one of policy. So here we could be discussing how to do risk-respection analysis or how to predict the future. But something I just want to show you is the use of agent-based modeling, not that I have the time to explain agent-based modeling, but let me just show you how it looks like. This is cellular automata. So the most basic type of agent-based modeling. Here you see that when agents forms a group of 15 agents, they go to the right. Similarly, you could design a simulation in which you would say that if the price of a product goes over the value of 10, then companies move to the right, which is they leave the markets. And of course you could be a bit more sophisticated and use AI and try to see if we implement certain policies, if we allow a merger, what could be the reaction of companies on the market. This won't be perfect, but it seems to me that it is better than relying on the idea of the average consumer, whatever that means, because I never met anyone average, and I'm sure you haven't as well. So those are the things that I wanted to discuss. But of course where I need your help and where agencies and scholars need your help is to address some of the limits of computational antitrust, which is why we have created this project at the Codex Center. So what we do in just 20 seconds is that we have gathered 55 as we speak competition agencies. They agree to receive our publication to exchange with us and receive lots of email from them, including from very small competition agencies, asking very specific question. And then we organize a annual conference which is coming in December where all agencies gather to discuss the advancements in the field of computational antitrust. So we publish one article every month, there is a podcast episodes and the annual workshop that I just told you about, knowing that after the workshop, agencies will send us a two pages report explaining the implementation they've been doing of the computational tools within the year. But as I mentioned, there are some limits. Limit number one, what, which fields of antitrust law can we compute. It might be easy when it is related to prices it might be, it could be much harder when it relates to privacy or the quality of a product. This is a question I know does I want to ask you challenge number two, which tools are we talking about. I've mentioned a few agent based modeling natural language processing, but potentially, we may want to explore all the tools. But of course designing the tool is not the only thing you need to do what you also need is the data to fit the tool. And so the question is, who should actually design those API is to to improve data flow etc etc. Challenge number three, what's the role of computational antitrust. Let me just draw a parallel with economic science in which George I can love Nobel Prize in economic theory, argued in a paper published last year that they are important topics that cannot be approached in a way, meaning with mathematical formula, and in a way which rely on the classical economy theory. Well the same is true for antitrust. Some things cannot be computed as we speak, it might be different in 500 years. But as we speak, some of the practices cannot be computed so what do we do with those practices what's the limits. The very last one is to know the limits. Of course there is no theory of everything, although I do personally believe that one day we will reach that but we'll see about that and I'll be dead for sure. But knowing that they are black swans and evens that we cannot predict, then what do we do, and if we have a computable results, what's the limit and what's the weight that we give to that result. Those are a few of the limitation. Something I do want to mention though is that the same is true for weather forecast. It's not perfect, there are limits. And yet, if you rely on it, then you might be able to predict when there is a storm coming and potentially move people away from the region and save lives. And in fact, if you look at empirical evidence, weather forecast is much better today than it was 40 years ago. So I imagine 40 years ago, it probably was a nightmare, knowing that it's not perfect as we speak, but still it is improving. And it seems to me that the same could be safe for computational antitrust. It would improve. And although it's not perfect, this is not a good reason enough not to use it. Because indeed what we see today is that some of the big tech companies are using advanced tools, while some agencies are not and it creates as Richard Posner was saying a mismatch which is troubling to say that if so potentially we may want to equip agencies with some sort of fires. But again, I need you to to discuss which type of fire that we want. If you are interested in the issue for after the talk, you could go to computational entitles.com you have all of our papers, podcasts, everything is open access, as it should be. So thank you very much and very much looking forward to our discussion. Here, thank you so much, Tebow for that tour de force on computational antitrust and especially for taking time to customize some of, you know, what are the really present bigger questions the conceptual breakthroughs that need to happen to get to the next level. And I wonder if you'd be willing to screen share again and just put up those questions so people can refresh their memory. Because we did take some time in advance of today to help to craft questions to for you, really. So usually what happens after a talk in a traditional academic, or, you know, whatever computer industry setting is that the sage on the stage, you know, says things and then the people and the people in the pulpit, or rather in the audience, ask questions. We want to flip that around today and to encourage idea flow, we have questions for you. And those questions are one more time, just to frame the dialogue. So you mean the four questions is alright. Exactly. And while you're doing that I'll just riff a little bit. I mean, what there's a theme here which is with the technologies we already have today, like if we don't assume new breakthroughs and blockchain or quantum computing or whatever. You know, where are the best fits to people think the the ones where there might be really good value, or where, where, where, where things are really ready to adopt. We already have data we already maybe know the API's or the this or the that. And if we just one little change, we could transform a field of antitrust like the cartels and conclusion and collusion stuff or the merger review has a certain kind of shape to it. And existing data or all the monopoly power and the, the price discrimination and the, you know, and the tying of products and stuff has a certain shape to it. So, I mean, we're, what's right for a breakthrough. Oh, and now we actually have the real questions. So do you want to just state the questions one more time and then and then with the help of Mila as our primary discuss and perhaps we can dive right in. Of course, I mean, I think you framed the question exactly how it should be framed so it's hard for me but no indeed the question is, I mean, if you've been involved in a field of antitrust you know that prices are easier to compute and we've been obsessed with prices, potentially, for good reasons but maybe now is the time that we leave prices aside a bit. And we also care about other metrics, such as the quality of a product or whether you know they are dark dark patterns and all of those new issues. And so the question is, if you can more easily compute practices which are prices related. Should you go this way because that's the easiest, or should you try to, should you develop more tools so that you are able to tackle other issues, which are more qualitative by nature. That's the core of the question. And I know we have some judges in the room so I'll be delighted to hear you know if not just your your feeling when hearing the presentation what do you, what do you think would make sense. Is there something you want to try within the courts or something that you've tried already because some judges have been experimenting a bit so this is the question. Hi, well since you've mentioned the judge in the room, I'll just jump right in. And I would actually love to see some artificial intelligence working on some nuclear terms, or maybe on the 10 areas of the antitrust questions and cases so that we could actually harvest this data on a more concentrated frame. And therefore, we could actually work these data a lot better, because sometimes we can think about price and we can think about collision but today we must must think as well as like data concentration and other aspects that aren't really focused on a specific area but can actually be very relevant to the market. So, I think that we should start maybe with some machine learning. And actually analyze the decisions and the criteria and the criteria used in the decisions to evaluate what was actually decided as an antitrust or anti-concernation practice. And after that, we could work with blockchain to have a very specific way of monitoring this information, not only the criteria but if the criteria has been actually applied from the decision on and I would actually start from that, just first extract the data, I wouldn't actually choose one area, I would just assert every area because when we evaluate the market, if we only look at the price sometimes you can have like not very complete analysis of actually what's going on so I think that we should have just as much information as possible and after that interpret and then we would go on from there. If I may ask you for a question then I'll leave the floor to Mila because I'm very curious to hear your thought but I mean first of all you mentioned the analysis of terms and concept that's a paper that we are about to publish on Monday, in which they analyzed whether when undertakings use the term gatekeeper or dominance whether they mean the same thing, and they found out that this is not the case depending on the size of the company they see concepts in a different way which is troubling, and very interesting but let me ask you this question. In the paper that we published, they tried to train a machine learning using FTC and DOJ decisions, but because it's the case law is, is so different, the machine got confused. And so they couldn't train actually the machine learning and they had to say well we're going to choose just the FTC because for now it doesn't work so let along you know using the European Commission case law. And that's something which was curious to me because I always thought well first we have to make the substance coherence, and then we can design the right tools but it might be the opposite, because if you want to make the tools function properly, then it would be more incentive so that the case flow is more substantial so my question for you is, do you think this is the type of arguments you could make within the court, you could say, we need the case law to be more coherent because I need to be able to train the machine learning in a way which is more consistent, or do you think this argument will never work because this is too geeky for for judges to to accept. Well, I think if if it's a very clear argument and a very in actually proposed in a very clear way, it can work out, but it would work out for me. So I can actually speak for my fellow colleagues and sometimes judges can be very different from each other and they have like, for instance, the whole data concentration may not be something that they will care for as long as maybe a horizontal market the case has to be very well exposed for the court, so that this substance can actually show what the case is actually about. Fascinating does the floor is yours. So I was just about the back channel with me a little bit. So what I'd like to suggest is that we let's get another idea on the table. So that we've got some, you know, some some things to play with and then bring meal in as our discussion to help us start to process process this with, you know, together. And that person who I think ought to be next is summit.  And maybe you can help us raise some questions which we haven't really been in focus yet, but how does this all look from the perspective of a consumer and how does this play out for like, what are the issues and the options and the opportunities and maybe the, again, the problems and the prospects from a consumer perspective. It seems like things here could be quite these some of these tools and approaches could be really transformative to achieve some of the aims I've heard you talk about with respect to antitrust from a consumer perspective. But again, when we start automating things, there's perils and, you know, potentially as well for consumers and I just wonder if you could say a few words from a consumer perspective to help us bring that into the conversation. Yeah, thanks. Thanks. So I'm summit. I'm an economist and I work for consumer reports in the advocacy division in DC Washington DC. And this has been a very interesting presentation table. Thanks. Thanks. Thanks for the presentation. And I have a couple itself from the consumer perspective, one of the, you know, the biggest challenges for us is to explain these issues to to consumers and to the average user. So I have some hesitancy in sort of fighting a black box with another black box. So I think the question of explaining when we are into wheeling in markets is important for us as a policy organization to get support to adopt some of these tools. I did like you mentioned the folks and prices and these other aspects of services like privacy and quality. I think they're usually important in some of the markets. We all know, you know, on Google and Facebook, these services are free. So if these tools could be used to analyze and produce concrete evidence on how privacy has changed with competition and how, you know, having just one monopoly provider or two or three providers affects privacy to an analysis of I'm not an expert in computer science, but you know, for analysis of various privacy policies and see how they've changed over time, etc. I think that would be great. Another thing is, I think, is there a possibility to use some of these tools to just provide to study what's happening in some of these markets today. You know, like prices on Amazon and price discrimination on Amazon. These are against I think that there's only questions I feel that these tools to be applied to before we go into enforcement. It would be very useful to have my final comment from the viewpoint of adopting some of these tools. It would be very useful to hear how some of these how computational antitrust would require fewer sources from the agencies. It's not easy to get resources for agency. So if he's saying let's adopt these new tools and this requires another $50 million, you know, that's that's not a good sell. But if we can say, from a policy perspective, just help you save money. Then I think we have a much better chance of increasing adoption. Thanks. If you could help us process some of those are three, you know, like we can do all day on any one of those three, but maybe get us started and then let's bring Mila in to help us process that. I would love to react to that because I mean, I've been a bit obsessed with those points. Not that I have a perfect answer far from that but I've been thinking about it. So, one thing I wanted to mention regarding the first point is the Google shopping decision, which I think is very interesting. And that's the same. The same history for all of the Google cases before the European Commission because it will be very hard to argue that all practices are pro consumer. You know, some of them you get feeling that this can't be good for consumers. And yet if you read those decision the European Commission does not explain how consumers are being hurt by those practices, which is very troubling. Well, let's say that we can actually come up with network analysis and show that the the layer that Google owns or any other company is actually necessary for businesses and and try to show the growth and the dynamism of the markets. In fact, in the earlier we could quantify not all of the consumer damage but part of it. And so it seems to me that the European Commission wanted to go this way. They didn't have the right to let the time and therefore try to say, less choice equal equals bad for consumer, which is a bit of a shortcut because sometimes you have less choice is actually good for consumer because it avoids choice overloads. And that is not as easy as the European Commission in my view, argue in the decision and yet the practices seems to be anti competitive so I just wanted to mention one concrete example but as you say I mean, can you measure privacy issues for instance so that for me reminds me of a study that that that was conducted two years ago by Princeton University researchers, they have analyzed. If I'm not mistaken, 9,000 different websites and identify dark patterns on those websites and of course what you will need to do is to conduct the same analysis all the time. And I've, I'm involved in a project right now where we try to do that, but website change the structure and they change where the information is located so of course you come up with all of those very practical day to day issues. But I do agree with you that it will be very interesting to see the change on the market and policy consideration but again it involves to conduct the study for for quite a long time. So that's the type of study that we are conducting regarding, and I won't give name but some of the shopping websites, try to see if we can come up with some some good results, and the very last point regarding the costs. That's the very first question that I asked in the very first episode of our podcast to the researchers, I said how much, and they said well it took us a year. And on top of doing the teaching and all that so it was quite lengthy for them to train the machine learning, but the cost they say we're zero, they were able to do it using the their MacBook. And so it seems that some agencies could actually start there again it seems to me that coding their own case law and by coding I mean just putting some labels and practices and industries is where they could start potentially just allocating two employees to the task and see if the results are indeed satisfying or not. It will be way more expensive and does that knows a lot about that when we talk about some other technologies, but there are places where we could start and try to see if it works, and we are working with some agencies to try to implement a few of those ideas. So that are again are just some initial thoughts but far from being complete, unfortunately. I'll just I'm going to put in one and then write to Mila but what one thought to vote in hopes that it's helpful is to think in terms of time span when we talk about the adoption and the applicability of new technologies to transform a field of law. And so, when you look at, you know, like moment of look at is like adoption curve of a new technology. And the questions differ depending on and what when in that cycle of time we're talking, maybe initially the question is, what is the suite of close to zero or incredibly low cost existing tools, just to kind of pluck the low hanging fruit of data we have and, you know, analytical models and other sorts of things that we could just do on a lot like on a laptop. And then that was a raise the question of, you know, like, what what might it look like for you know changing the back end systems and for more industry kinds of things and maybe registries and other stuff is now we're talking about a lot of new technology and new systems and integrations and then you can almost start to imagine but once we get past that hump and some of that hump will occur as industry and society and the economy transforms anyway that's happening with or without computational antitrust and things become, you know, digital first. And then what are the opportunities to do a little tweak or to add another call to an API, or to, you know, tweak a model where you can, you know, maybe get huge value for for achieving the aims of antitrust toward the end of the adoption curve but anyway I just want to throw out there the idea of thinking in terms of time when we address these questions. And with that, it's time for Mila. Well done. What a pleasure to be here. Thank you so much for the invite to go. This is long due right so many emails back and forth different initiative so it's a pleasure to be joining you on the floor. And also Hannah summit and everybody who is in here so I feel lucky enough to be the one to speak at this point in time because I was observing and something that really caught my attention was that first from a research slash administrative side of things we have to both saying, should we wonder about like how does competition take place. And then we have another, like from the judicial side of things and saying, Okay, we may be able within the case law or the institution to rethink the way competition takes place. And then we have some it and the first thing that it says is that also from a consumer perspective, what's needed to be done is to understand how the competition takes place. We are in the fourth industrial revolution, we are facing the web 3.0 like effects and how things reorganize. So there's a question there's comment to everybody who is in this like, you know, conversation and I can put my head lawyer on for a second, and you know, maybe of course whenever a new merger control opportunity shows up, or like an antitrust like analysis case, it comes to a law firm we always wonder like how flexible the judiciary or the administrative bodies would be like to take a look on that so it drives us to a very like a common point of action but then extrapolating that and trying to think about this common field but place it in time in a time of action. I would say that when people was a very, you know, a detailed when he pointed out okay there are three areas of competition law that we could think about like doing this innovations which is merger filings infringements as a whole right policies. So if we look at the problem that was stated as the most relevant product problem I would say that the place to look for is data driven policy, because if we have data and data driven policy that means that we understand that we break that riddle of being like a proactive or reactive that has been joining and accompanying like competition and antitrust for like ages and forever. We break that paradigm for the first time in history, and we are also able to learn to understand why we are doing this and also have like transparency, transparency to like also showcase that to the consumers. So I would say okay we found the holy and the golden grail but from a technology implementation standpoint, and base of like by what I learned from that not only for today but I'm lucky enough to be pursuing the guy for the past three or four years is that this kind of things because we're talking about like different, you know, databases and so many different, you know, competition areas, sorry, and industries. This is like a ginormous problem to handle so what if we look at the other spectrum of this angle and to the low hanging fruit and think about like merger analysis. I consider that today, the whole world would need to talk to an antitrust agency needs to type in a form. This form is typed and like most of the countries, and it's just like a simple word document in which questions they're very similar sometimes are posed with very different like ways or shapes or forms. There are some countries in the United States, I don't know, like Europe. Have you seen a form CD is just like the questions that you asked in a, in a filing form in Brazil so isn't it such a low hanging fruit to consider that the same structure should or could, you know, be put in place by the authorities when they're requesting information by the players. So I'm not talking about like gigantic like AI analyzing transparent markets or not in public domains I'm saying the companies are subject to do it and they need to do it and they pay to do it they pay huge fees. So going to the question on who is going to pay for that well the company's pay already. So what if there's a simple math that says okay the cost for doing a computational filing forum is X. The filing costs are X, Y and Z and the different countries let's all pay like a small fraction of it and boom, you have your computational global system with privacy in places and respecting like country sovereignty is one very like easy way to address a problem. I would like to stay more in here but since I've talked a lot I just wanted to make time for like a second very small thing so the place where you have the same type of transparent database and you can see the dynamics of price fluctuation privacy and quality and ease of access and the competition is called blockchain. The APIs they are there you just need to scrape information and start to understand how that you know organizes and with this defy initiatives. It may be even easier you know for us to understand how consumers relate to two fundamental questions of antitrust, which are price and quality. The other point that you both brought to this conversation was privacy and it's a much more modern approach, but when we talk about classical antitrust analysis please master correct me if I'm wrong. We're talking about like price and quality, and then we have this add up of like privacy perhaps or not. We're talking about that and we want to do something like very quick. We also have a way using public data and API so this is kind of what I was looking for. And thinking while hearing you speaking like, okay, now that we see what the golden grail is, what are the two quick things that perhaps we could do together to have a little bit more visibility into computational law in the future. There's a lot there. So Tbo, any reactions. Sure. I mean, I'm not sure if we've discussed that together Mila but I very much agree with you that merger control might be the first place where to start. So I didn't want to say that in a way that was too obvious in my presentation, but I'm glad we agree on this one. So again, I mean it depends on which level you're talking about, but it seems that the forum and indeed the basic analysis that we do is something that I have to teach every year to my students doing the same analysis showing them that it's not complex, although there is a bit of mathematics but come on this is quite easy. And the computer could compute all that in a way, which is way more efficient but of course, if you then try to discuss whether we should keep on relying on neoclassical theory and the idea that there are equilibrium in the market when there are not or very often no equilibrium for a long lasting basis, and try to see how to use complexity theory and agent based modeling you talk about something which is way more advanced, we could go step by step and indeed start there. So, in my personal view, if I may share I would say merger control defining forms and train machine learning algorithm on the case using the case law of competition agencies, maybe a third will be to use publicly available documentation to try to to to come up with an LP analysis and detect more practices. This could be done. Again, with just a laptop. So this was my my first reaction but again, I mean we could talk about that for ages but I'm more than happy to to leave the floor so I can hear your thoughts on that. To think sorry. Oh, pardon me, I didn't I was just saying that back to you but you were talking at the same time so least useful comment of the day so far. Um, I wish we had more time. I actually like to discuss this in advance. I know I probably went like all in my idea was just to like spark some, you know, opportunities and possibilities, and not that I see like a way, and I know how to push this forward, but putting I think one of the main roles here is to poke this type of intervention so I would be also glad to hear from the broad audience how does that resonate if they do also feel that there was like this link amongst like the different players as regard like I need to understand how competition takes place and then perhaps like leave the how to do it for like perhaps the next section together. I don't know. And if not, I could talk about blockchain for ages. So please don't get me started. Okay, so what I will throw something in there just to confound us a little bit and so this is in the spirit of speaking of hats. Okay, so let's get a little hacky and think about some topics that maybe or some technologies that exist, but they haven't been configured yet to plumb the value of them. Blockchain we must return to and part of the reason why it seemed like such a great match to have to go and Mila in in guest and discussant roles was because of your thought leadership for and blockchain and antitrust. But I want to, but you know, there's there needs to be a fuel for computational methods, whether those methods and mechanisms be expressed through the technology of blockchain or machine learning or, you know, automation type stuff or other stuff, which is, which is the data, you know, just like where's the where's the data that is the, the, you know, the inputs for for this, for these tools, where is it, where's it created, where does it reside how can it be accessed. How can it be used, and the raises a whole, you know, legal layer of ownership and control and whole bunch of other stuff and a lot of technical questions about the format and accessibility. But but so what but one thing that I feel is lurking just below the surface for all of this. We start with like the securities filings and and publicly reported data of companies and market data. But if we just kind of tipping the creative had back towards summit for a moment. A lot of it really does have to do with the with consumers and and people that operate within the markets, you know, and, and they we have data. And so I guess one thing I wanted to throw in the mix also is what if what happens when not even if at this point, people start availing themselves of their rights under GDPR and California Consumer Privacy Act in China, just enacted GDPR CCPA like act that gives the thing these things all have in common is people have a right to get a copy of their data from wherever it resides in the market from all of these same not coincidentally companies that we're trying to understand and get data about what they're doing. It is places like well, well, consumer reports would be one example of an organization that is seeking to play more of an intermediary role on behalf of and at the behest of consumers to help them exercise their rights. That's a project that summit and I have been talking about a little bit in the past and there's many other organizations around the world that are helping people get there. Let's just look at get my data and put it in a data store of some kind. So I have the health data, the financial data, my, my commercial data, my location data, like we have rights to this data as we start to put them into protected markets. Are there opportunities in a permission based way in a legitimate way to look across that data almost like epidemiology, but for markets to see things like. Well, that's this is where I don't know enough about antitrust to say exactly what but you know price is the obvious thing that I think about but other other trends like opportunities that I had or, or, you know, or like, you know, patterns in markets or who knows what insights we might get from that vantage point of data so I just wanted to mix things up a little bit by throwing that out into the mix as well. Floor is open. All right, I'll take a chance. First of all, and job is that only have one hat today, because you have so many so that's something I need to think about for the future. We're going to get law.mit.edu hats for our inner team and our collaborators soon so stand by because you have been. So we're going to get to that hat my friend but go on. That's great. Can't wait. Yeah. Thank you very much that's wonderful. But I mean, of course the question of data is is central sometime I think it's not so central by the way. Here it is central so a few just like to make a distinction between three different sub topics. First of all, when it comes to merger control, the idea that I mentioned that you could say of course it's not. It's probably not for today because you can't really say to a startup you should store all of your market shares in a private blockchain it might be a bit too complex for them but potentially in the future this might be a possibility. And here I'm not talking about studying late ledgers across across an entire market but just one at a time when a company wants to merge. You can imagine that this company will have to send or give access to the private blockchain, which which is non visible to the investors in a way to allow the agency to to see which data is available to make sure that it is not being taken away before sending the data set to to the anti justice agencies, because again, that is a common issue and the European Commission will complain about that every three or four months and will sanction the company, realizing that the data set was not complete at the time when the company sent it so that's number one so where is the data coming from here coming from the company, something else, which is a bit difference, but I've written the paper on that is how companies could use smart contracts to implement anti competitive practices. So here, the issue is much harder, potentially, knowing that the bite code of a smart contract without wanting to be too technical is available, but should you try to translate the bite code of a smart contract into the original source code. It's not actually perfect and potentially, this is not good enough for an agency to understand what's what the smart contract is all about so this might be something we may want to investigate. But if you start investigating that you quickly end up with one solution which I'm not too sure is exactly perfect, which is to create templates for companies to use every time they design a smart contracts. And I fear that this might be a way for agencies, even with the best intention in the world to interfere with the conduct of business activities so there is potentially a meal of ground but again I don't have perfect solutions as we speak and the very last points that you mentioned to to study data across the markets. So there are some patterns that indeed you could, you could try to to detect prices at one. You could say the sharing of markets you could, you could see that a company is selling product in Germany and France and the US and suddenly the company is not setting the same product in Germany, and a competitor is setting all of its product in Germany so there are a few patterns that you may want to detect. The beauty of unsupervised machine learning is that you only give the inputs, but the outputs is for the machine to find out so potentially you will detect outputs that where unthinkable for the human brain so that's the beauty of it and that's why I think it's very exciting, but just one, one thing in this regard. If you do and if you ever experimented with using unsupervised machine learning, you may want to say well I want you to cluster the data into five clusters or 10 clusters. And if you run the same analysis over and over again you will find indeed different number of clusters, and it might be that clustering the data into three clusters gives you certain types of clusters which are convenient as an agency or as a company. If you run the same analysis with seven clusters instead of three, then the results are not at all convenient for the sake of your analysis. So that's where human being are behind the machine, and that's where potentially we should be able to come up with some sort of procedural fairness, because thinking that with the machine you can solve it all, I think is is a big mistake, but pretty much no one thinks that nowadays so that's the good news I wanted to leave on the positive notes. That is good news and so I understand people are needing to drop off now because it's the end of the hour, however, for those of you in the land of YouTube we did get started a couple of minutes late so we'll end a couple of minutes late. Mostly to make sure that we have an opportunity to thank Tebow and to thank Mila so very much for helping us to sculpt the conversation and make it accessible for everyone to contribute. People didn't get a chance to contribute enough because we just didn't have enough time. And so I'd like to ask Tebow, without imposing too much on your time if you'd be willing to come back later in the year, or possibly until next year to do a kind of part two and take a look at some of these ideas, maybe after your summit that you're doing in December, and to maybe you know further sculpt them in some way we would very much like that opportunity if you're up for it. So, I only have one condition, I need to have beautiful law that MIT.edu hats. And if so, I will be delighted of course to come back to to continue the conversation. I'm going to count on it and speaking of wearing different hats. We also have to say a heartfelt, not goodbye but farewell to our own TMA, Rogier, who's been with us since the start of the, of the MIT computational law report and before that in our MIT computational law course and TMA. Come on, come on out. And she is, why is she leaving? Well, she's beginning her ascension to the law itself starting next week at University of Chicago Law School. She's going to, we're about to have a newly hatched attorney of computational law. Hey TMA, we're going to miss you.  I'll pop in here and there, I'm sure. Yeah, thank you Timo by the way for such an awesome discussion. I feel like we're going to be talking about anti-trust a lot during my 1L year so. Oh yes. Oh yes. Yeah, and how perfect it is that you'll be at University of Chicago so you can really, really get the foundations of the economics of this whole thing because obviously it is essential to understand it and to successfully transform. So with that, I want to thank everybody for engaging today in another idea flow and we look forward to continuing the collaboration with you next month on the last Friday from 12pm to 1pm Eastern.


Hey there, Chad Bonser here for High University Libraries. If you're comparing companies in the wine market, you'll want to compare company financials, operating revenues, net income, things like that across all the companies that you possibly can. Mergent Online is a database that will allow you to compare U.S. companies and companies abroad in international markets in a variety of ways. This video shows you how to find those companies and how to compare them with Mergent Online, so here you go. So let's say you've done some Googling and you've found this big company that's Williamette Valley Vineyard Incorporated out of Oregon in the United States, and you've done as your friendly librarian has said to do and say, go look for company information in Mergent Online for that company. So you've done that, you've gone and found this company, and what you find here is lots of good information, business summary, financials, all this kind of good stuff. And you say, well I actually want to look at competitors for this company, so you click on competitors here. Now what this will give you is a list of competitors according to the database, and you'll see it there's some things in here like Boston Beer Company, there's some of these are like warehouses and things like that, so this isn't really a great competitor list. So what you can do to create your own list of competitors if you're not satisfied with this list is to go up here and use these industry codes here. And so I want to choose this NAICS code with this 312-130. I'm just going to copy that guy right there. And we're going to go back and do a search here in Mergent Online. Okay, so what you're able to do is go over here and search for primary NAICS code. And we can plug that NAICS code right in there, and we'll just leave it because I'm looking for global companies, so I'm not going to choose a country or an exchange or an index or anything like that. And we're going to do search. Now the problem with this, this way of searching is that it finds a whole lot of companies. Here we have 110 public companies, so we're like cool, let's look at that.  I really don't want those inactive companies, okay? So what we have to do instead is go back to our search screen here, and instead of using this search, we're going to use the advanced search. Now what this will allow us to do is basically to deselect this inactive company database here and only get active companies. So we're going to do that, and then we're going to click on industry codes here. And we're going to do primary NAICS code. You can do any NAICS, but that might be if there's a holding company who has holdings in wine, they might have a NAICS code for that. I want to get companies who are primarily engaged in wine production. So that's what we're doing primary NAICS code. So we'll do that, add our NAICS code, click submit here, and see now it finds 69 companies, which is a lot better than 110.  So we click over here and click view, and it's going to go give us our list of companies here. Okay? So what we can do now is there's this thing over here under emergent tools called a company analysis list. And you'll see there's nothing there right now, but what we can do is up here in the top left, we can add all companies to our company analysis list. And when we do that, we have 69 companies over here. And so now we can click on this company analysis list. And this gives us a couple of options here. Let me shrink this down so I'll actually fit on our page here. So this gives us a couple options. The default selection is this multiple company report. Now if we select that, it's going to give us a big long PDF of all these companies. And I don't really want that I want tables comparing the companies. And so to do that, we're going to do this company comparison report right here. So we click that. And what countries we want or companies we want over there, we just click the add button here. And we scroll down and let's say we want things like Oh, let's say we want to know how big the company is, we'll do a number of employees, we'll add that guy over there. And then we'll scroll down, let's do some financial information here. Now because we're dealing a lot with international companies, we may not have all the same information available, depending on what's reported there. So we'll just do a few items here to see what what actually we can find. And we will do total revenue there. Okay, and then we can go into ratios and maybe do let's do net profit margin. Okay. Now before we click, I create report down here, we can choose the years we want. If you wanted to, you can hold the select button down or the shift key down and actually click and get all the available data that's here. I'm just going to do the latest and I'm also included an average which will give us an average of all the companies there in the header for us. So now we can go down and choose select a format. I'm just going to do HTML if you want to you can download to excel if you like. So we'll do HTML. And then we'll create a report. So for the companies we selected, here is the list of information that we have for for a number of employees, the advertising spent, you can see probably mostly are just US brands are reporting that net income. And you'll notice this is actually all results are stated in US dollars. So you are comparing apples to apples here, we get net profit margin, things like that. So a great way to kind of compare you can also sort this you want to see, you know, who's the let's do the other way, who's on top as far as the largest companies in the world who produce wine, and that sort of thing. So a great way to get good international and US market information for companies in the wine and wine, winery industry. Hopefully this video helps you understand how to use merchant online to compare companies in the wine market. Should you need more help, look for the contact link on the business blog, be glad to help you anyway can take care and have a great day.


All right, Lady Ada, what is this? Hey everybody. Hi, and welcome to Show and Tell. Thank you. Last week was it Liz that ran Show and Tell? Or JP, sorry, I don't remember who. Whoever it was, thank you so much for running Show and Tell. But we're back. It's me, Lady Ada, with me, Mr. Lady Ada. But it's not about us. It's about all the makers and community members that are going to come by and show off what they're making in crafting and 3D printing and robotting and blowing bubbles. Oh, that's exciting stuff going on here. We're first going to kick it to Jay. Jay, what is going on? How are your robots doing? Did you keep your bottoms on? Good. I have another Aussie. This one actually has Fisher recognition. And I kind of just recorded a small thing, because I noticed it was looking at both of you guys. It kept lighting up and then going back and forth. I was like, oh, that's cool. Let me just record that really quickly. Oh, because he's looking at the video. We just had a kid in one of the first things. Initially, he was like, oh, she's looking at both of us now. So it's like a lot of folks said, oh, when you're doing AI and robotics, there's a very like, oh, I'm teaching it in its learning. And now it's reacting to something. It's a very, you know, we have that make robot friend, not robot enemy. And I think I trust your robots more than others. Well, it's funny. So this is the second one, because the first one is all remote controlled. So I have two of them now. One can be controlled by remote control for people who want to play with robots. One, I can easily just wear. And then you can do the AI thing and tilt. Easy facial recognition. This one's all AI. This one's all for play. How'd you do it?  OpenMV. Me and my friend, Sean, Sean, I'm sorry. Sean, I always mess up your last name. If you see this, Sean, I am sorry. But we use the OpenMV. We roll a code, and we use the OpenMV. I have one. You can get one, as well, if you start. We wrote the code for this a while ago, and I've been improving on it and just adding a little bit. Each time I do it, this one is the most recent upgrade where I mess around with some of the numbers. And now it has a bigger range of motion. And it's a bit faster when tracking people. And I also put a limit on it, too, because the other one just stares at people. But this one will take a quick glance. You have to write the creeper. The creeper, after so many seconds, is like, oh, it's doing creeper. After a small minute, it just looks away. I find somebody else. They can't quietly judge. No. Yeah, I got really tired of people doing the whole, like, this thing when I'm out in the valley. They try to, like, see if it's following them. I'm like, yeah, stop it. When we first started learning how to do puppetry for our shows, one of the things that we learned was, if the puppet is always in motion, people, they think it's alive and it's breathing, especially young kids. But as soon as it stays completely still, it dies. It's like, oh, now it's an inanimate object. I don't like it. It's actually creepy. But as long as you're kind of doing stuff and it's always in motion, it's always blinking, it's always kind of doing something that's not just like, I'm a piece of plastic. It's a whole thing with human psychology. Because for some reason, we don't really notice this intentionally, but we notice things that are perfectly still. There's a whole bunch of fun sci-fi books where a robot's trying to be human, and they have to program small movements and itches and stuff. Because if they're completely still, people just unintentionally notice this person is like. Yeah, maybe lines and tigers just to be perfectly still before they ate us. So we're programmed like, oh, something's really still. I'm about to get eaten. Yeah, yeah, probably, probably actually. This is my guess. Yeah, I saw an article, and it's like, we found a cave full of skulls, and it has big cat teeth, saber-toothed teeth from eaten people. So I'm like, oh, no. So anyways, robots should not stay still. The fifth law of robotics. We need to rewrite that whole system anyway. I'm not a fan of both rules. Yeah. I think robot friend, not robot enemy, is what we've been doing. We keep saying whatever we put into these robots is what we're going to get out. So we should put good stuff in. And I think that's why a lot of folks are freaked out about AI. Not because of the AI. I think subconsciously they know there's some crummy people doing crummy things with technology. And so it's actually now about to introduce itself to us. So I think you should be in charge of all robotics. I mean, as anyone can learn from any sci-fi movie, the easiest way is to stay friends with the robots. It'd just be nice to the robot. We've learned this so many times. I've seen so many movies. Don't case the robot. Yeah. Yeah, it's not that hard. Just do some basic human decency. Science fiction has paved the way. It's like, don't do certain things. And then the robots will be your friend. They'll totally be your friend. You know what I'm saying? With games like, can you pet the dog? They should have it be like, can you kick the robot? Because you can kick the robot.  Yeah, I'll kick the robot. Yeah, I agree with that. All right. Well, keep coming back with your robot friends. They're delightful. Before we started the show in Tel Aviv, I have to look at a lot of things in the world every day on my internet computer. And I save your stuff as a treat after I get through this stuff that's not so fun. Because it's always delightful. And it's always whimsical. And it always makes me feel good about technology. Oh, flat. Yeah. All right. Well, thanks so much, Shane. Thanks, Jay. All right. Speaking of great things and great people in technology, Jeff, what you get going on? Oh, I figured you'd bring somebody else up. Yeah, so this is a pie portal, perfectly normal. But I've connected it to OpenAI. And I wanted to do a little interactive game. This is a good invisible AI, by the way. I hope so. This is a wholesome good use. Yeah, so my inspiration is the good old Zork games. And each time you start it, you get a different prompt. And just by touching the touchscreen, you can make a choice. So what should we do? Look around. Look around. All right. That's always a safe move. And so now this device here is connecting on the internet, talking to OpenAI, hopefully getting back to completion. Here we go. Let's see. The grounds are overgrown. The gates are rusted. Shuts. I always very good. The descriptive text is so similar. OK. Also for another entrance.  I have actually had the game announced that I won. But it's intended to kind of be unlimited, so. OK. Well, look for a light switch. Look for a light switch. So anyway, this will. I don't keep picking two. I don't know why two can is always the one. Yeah. I'm working on a guide about this, because we want to kind of show how you can do AI with a circuit Python and with Wi-Fi. So this will be one of them. And then we're talking about doing one with the PicoW as well. OK, look around. It's like, what's going to happen next? You're just going to have to find a way. It's also one of things with ChatGPTs. It takes a little bit of time between every query, but it kind of works well, because it's got this heightened sense of anticipation. I feel like it's like the right tool for the right job, because the AI right now that everyone's starting to play with is a very confident liar. But that's exactly what you want for a game. You want somebody who's just going to go with whatever the idea is. I want a dungeon master that I have unlimited access to for gaming and fun. I don't want this to decide if I get a mortgage or not.  She's a slave, and she has to tell a story to the master, and he's going to kill her unless she comes up with a good story every day. So I don't know why it has this feel of ChatGPTs probably has this anxiety of like, I have to be connected. It has to impress us, otherwise the plug is told. Could be. I think they're most curious. All right, this is super cool. So this will be on the learning system soon? Yeah, yeah, probably on the next week or so. So keep an eye out. I'll mention one thing. I don't know if I'll have time to do this. I might have to get a crew, a team of people. One of the things I wanted to do is put in all of the old Teddy Ruxpin things, if everyone remembers with that one. I kind of missed Teddy Ruxpin. I know it was out there, but I was a little sad. Yeah, so Teddy Ruxpin was a little animatronic toy. It would talk to kids and everything. A million years ago, I worked on this thing, the Sony Securio robot, and it would read to kids, but it was like a humanoid robot. But what I would like to do is get all of these positive good things that someone wrote up for kids, put it in, and use that as the training stuff, not the entire internet, and then have it start to build off of that and make kind of a more modern animatronic Teddy bear. If folks have seen the movie AI, I think Teddy was one of the little bear that could walk around. I have one from the movie, but you just press a button and just talk. So this would actually be something that would speak and do some more things. But I like the idea of a smaller training set to not worry about like, uh-oh, like I wish you didn't go to a four-champion. Right. Learn from that, so. Okay. Come on. Well anyway, yeah, it's cool stuff. For folks that are playing around with this, you can get browser extensions, be careful about which ones, but there's ones that will speak whatever text comes back and it'll also, you know, you can use your modern computer to do voice recognition. So you can say like, climb the stairs and it would repeat it back to you, but you can do it with audio as well. So it does text a voice, just kind of neat. Anyways, make your own Alexa. All right. Hi there. You're playing out there. Good night. Bye, Jepler.  Hey, first of all, from earlier, I was excited to learn that the way to keep Lars from being creepy is to keep him moving. Yeah. Oh no. That's totally not creepy. You know, I don't know what that means. Hi, how are you so lovable? Hi. Hi. Yeah. So it's a Meowzik central over here and I've taken the previous Meowzik project was to get a use the onboard synthesis and just put a line out so that we could go into guitar effects pedals. The new thing though is this one, which is my fiber cat. So this is a Meowzik, which I've turned into a MIDI controller. So it doesn't sound anymore, but it sends either USB MIDI or classic over TRS MIDI to hardware sense, software sense. We've got the 28 keys. The nose does MIDI panic, which is a standard MIDI thing to send off to all notes in case some get hung. I've made this a hold. I've made this a sort of temporary CC that can change formats. We can pick different patches and patches over here. These can pick different CCs, which is like knobs that get twirled when we move the accelerometer that's in the ice cream cone. This will start in our peggiator and then I've got octaves up and down and pitch bends. So I'll demo a couple of those things. Yeah, definitely. Won't do it exhaustively, but so let's see what I've got. I don't know if it's smart, and if I hit play here, it'll just let it act as a regular keyboard. If I turn on the ice cream cone action, wait, does that one not do anything? It might not on this patch. Let me pick it from patch. Oh yeah, it's not noticing that at all. Ice cream cone is broken. Forget it. I'll say the hold function is kind of cool. So if I turn off the arpeggio, now when I let go, it's just going to keep notes held and I can go change octaves. Build up these big pads and then I can do the pitch bend and this is my little furry formance. What happened to the ice cream cone that's so sad? The ice cream cone was the coolest part. I feel like you're creating a soundscape. Come back next week and show the ice cream cone. I will. Okay, that's the tease. I'm in a little bit of a project dilemma. I was going to actually email you about it. So there's some of the kids toys that we're taking apart for our kid and we're putting new electronics in, but I want to paint them black, of course, baby. So there's no, you can't get kids toys in black. This is why I'm just like, oh my God, this is really neat. If you know, maybe I'll talk to you later. If you know any really good way to food safe paint something, because kids put stuff in their mouth, I'm probably not going to do it. I'm probably not going to do it because I can't think of a really great for sure way to do it, but I would like to paint all of our toys black. I'm curious about the, oh, now it's, just like temporary paint, which is made out of eggs, literally. What's the stuff? The plaster dip. You can get spray plaster dip. So it is peel off later, but it's essentially like a rubberized stuff. I'd be curious if that's, some of the choking hazard. Yeah, I used a matte paint and then I also used some sealant, some sort of glossy sealant on a couple of the items, which gave it color. Yeah, that's so good. And then this was actually not in the guide.  I think desert desert. I couldn't really mask it well enough. So I just painted it over black and figured if I came in with an exacto knife, I might be able to get some sliddy eyes. Looks like an Xbox controller designed by a cat. Yeah, love that slime green. All right, we'll come back next week and share the ice cream cone. Ice cream cone next week. Thanks. Okay. All right, next up. Liz, what you got going on? Hello. So this is a robot liar that I've been working on. And what is it? It has a feather. It has a feather RP2040 and running circuit Python. And then it has a servo driver connected over I squared C that can drive 16 servo motors. They're measured here and it's being controlled over MIDI. So we've got this MIDI controller here and a cat in the back. And let me know if you can hear the strings or I can move the mic. Okay, here we go. Yeah, I heard straight. Yeah, it should sound a little, but I don't have it fully pinned down yet. So I'm just going to quickly adjust it. Okay. I'm going to make sure the lies are lined up. Okay. All right. There we go. Yeah. I need to, it has like little risers underneath. So I need to hot glue those, but I can try to get the a peggiator going. Oh, cool. Yeah. Yeah. So it's really responsive, which is what I was like most worried about. So I just need to secure this down and then it'll be good. And then the aluminum extrusion doubles as counterbalancing the weight because all these servos are really heavy. So once it's secured down, then should be good for some really nice demos. All right. All right. Well, I'm looking forward to this. This is a really cool instrument. And yeah, that's how it reminds me of, of Renfairs and like, it's like a spa. Yeah. I feel, I feel very nice. Great. Thanks so much. All right. We're going to go to Aaron, then Scott and then Delta, we all know who is up next. Aaron. Hello. Oh no, Aaron, you're not on her audio. Let's see here. We will, I'll give you a second. I might go to Scott and then come back to you. If you want to do, we're going to be showing this project tonight on ask an engineer too. So I'm not too worried about it. Aaron, I'm going to come back to you and see how you're doing. Okay. Can you hear me? Uh-oh. Can you hear me? All right. Well, but you know what, maybe we'll just do maker charades. So this is a, I guess. It's an infinity mirror bubble table. Right. I was going to say, like how would you describe this? Exactly how I described it. Yeah. It's Aaron's latest guide. So we've seen infinity mirrors before. She's friends with like a bubble maker guys. It's got battery. It's got like a half silver plastic mirror. It's got a feather. And it, the really cool thing is it's using circuit Python and infrared receiver with the LED animations library and Dan Halbert and her work together to make it. So you can like send the remote signals and it'll change displays. And then she's got a really good video with the smoke that you can put in and stuff like that. Yeah. I was saying, I imagine every day you go to Aaron's house and there's just like some circus person there just doing flips or swallowing swords in the kitchen like, Hey, I was going to use that to get the bread.  I just imagine it's super fun over at Aaron's house. And so she's got somebody who blows bubbles. All right. Well, I think you did a really good job on maker charade. Hopefully. And thank you so much. We're going to play the video. But it's no storm. So it could be here. Yeah. You can tell by the, the winter, the winter gear when we were in our meeting, I said Aaron wins the code of the day. I know. Aaron's cool Viking cosplay videos as well. She's got a whole bunch of them with like runes and stuff. And I think that will outfit is kind of reminiscent of that, the Viking cosplay stuff. So what was, we, she had a good, we were talking about how cold it was in California. Yeah. And the joke was how cold is inside of a Tom Tom, you know, the things that it was an empire strikes back. I don't know. How cold, how warm is it in a Tom Tom? Look warm. This is the joke that we had in our, in our other meetings. And this is why we stick to, yeah. All right. Thanks. That's a good dead joke. Some of that. Okay. Let's go to Scott. Hey, just got some pretty good. I'm enjoying the dad jokes. The same club as me now. You've always loved them. They've always been there. And I just have an excuse to laugh a lot. Okay. Okay so I've been working on the IMX RT for folks who don't know it's a new chip that we've got on a new metro and the cool thing about it is that it runs at 500 megahertz which is kind of a lot but one of the challenges is that your codes lives on flash by default and this is true for ESP as well but basically you have levels of caches above that flash to make everything go hopefully fast. So I've been looking into how to make CircuitPython run faster and I'm running the performance benchmark and what I got here is it's full function tracing there is a bug so it's a little weird but this is a cool viewer you can get on the internet and so what I can do is I can see that like mp call function and key w called type call and then instance make new and blah blah blah and I've annotated these with r for ram or f for flash in front of them so that I can see kind of what is going on and is it in ram or is it in flash and there's actually it turns out there's a cost to going from one to the other as well even if you have a cache because arm has this thing where if they're like the functions are so far away you have to do this like trampolining thing so even if we're hitting the cache we're still doing these trampoline functions so I've been digging into this and basically moving more and more stuff to ram to try to make it run faster and might your handcrafted moving of speed optimizations yeah yeah whether that scales or not is a separate question but one of the interesting things is that there's two types of ram and like there's a generic cache that the cpu has and it will cache both flash and regular ram but then there's also this like tightly coupled ram that doesn't get cached because it operates at the speed of the cpu and so for things that you know you're always going to run you kind of want them in that special ram because then you can have more of this like versatile flash or this versatile cache for everything else that like we may not always run so yeah I'm digging into this and and we'll see how much I can I'm not I'm not no pressure but one of the things that when you did your deep dives I really like watching was there's so much what goes into building a platform that you never see ever you'll never like there's someone like an apple that's messing around with like an m2 we'll never see that it'll never know never and so this is really neat to get a glimpse of what it's like to get down to the the parametral um right as as folks say so if you ever were to do like a screen capture and put on our youtube or anything like that that'd be like kind of like you know I actually haven't been on top of this but foamy guys out this week so I was thinking about streaming in my well this would be neat just to like watch him up around with this even if it was just like put on some yeah put on some non copyright infringing tunes and um well you know I can talk for two hours it's fine yeah I won't do two hours because yeah but it would be we were thinking of doing that with like the more doing stuff in eaglecatter and key cat because we're doing a key cat thing same where it was just like we just do a screen capture and like maybe have a voice over only yeah so I'll I'll try to do that if folks want to um two o'clock pacific definitely okay I won't do the full two hours like I used to but um yeah I'll be I'll be there too ish okay all right well my setup still works and I have been thinking about trying to find a slot during the week that I can start regularly streaming again yeah well as as someone who has their ideas for that a similar situation maybe a little bit like you are we've been doing some pre-record segments for our shows when we know that we can get away with it because yeah I don't know so okay all right Scott thank you I'm not I'm not terse I'm very long winded well that's why I might be yeah the challenge is how to get to the point what's the phrase that people always say it's like I would have written you something I would have written a short note but I I don't know I'm ruining that quote I know you're talking but it but it's very true like I don't have to prepare very much for a two hour stream but if I'm preparing for a 10 minute stream I have a lot of preparation yeah yeah because you gotta get to it yeah exactly okay all right thanks oh if I have more time I've written you short a shorter letter thank you Mr. yeah that's a phrase see like I would have I talked more about it than the sentence okay okay bye look forward to see you Friday maybe all right last but not these Delcey hello how are you hello I think I owe you a thank you for a gift that arrived I believe you get it then hozzah we did we got a pile of stuff when we had kiddo and then we had to go through mail so thank you so much very much appreciated cheers what you got well on the right is the uh pie portal disc uh usb thumb drive from last week I got the parts and I built it that's cool it is so neat to see um the future and the past and the present all in one project this has been a fun one people have really been making some cool stuff with it I have some seriously fun plans for this in the near future I got two of them and I'm already working on the second one turning into a little more than just a thumb drive to show slides and to do other things so hopefully I'll have that we're making one and we're going to give it as a gift so I don't think I'm going to spoil the gift for this person but um anneal dash let us borrow the prince floppy and we got the content off the prince floppy when prince changed his game to the artist firmly knows the prince as a symbol and he let us like you know use it get it we put it on archive.org and then um what I'm going to do is I'm going to put all the contents on a floppy so the prince font symbols on there and give it oh yeah no one tell him but anyway that's what that's what I'm going to do I thought that would be neat for people are in the retro you can do little gifts like that definitely all right so what else you got there you got a robot on the left there is my first stack-chan robot it's uh it's a Japanese based like fan club thing uh some folks came together and made some 3D prints and it's using an ESP32 M5 stack and it's like a personal companion robot this is like the very baseline one it uses two servos and the M5 stack and I've changed the code a little bit and then based on this I built a second one which is actually a little bigger but unfortunately that one's having some servo problems so it's uh not in view at the moment that it's basically a companion robot uh I've programmed it to talk to my web server my home web server so it will grab information like how many days are left till DEF CON or somebody just sent you a tweet that says this and otherwise it'll just sit there and look around and blink at you and say hello which it's doing right now it's really neat it looks like a little pet that's just like kind of quietly hanging out chilling like a cat with cute little lego feet I've got four of them now and like different places in my apartment so that they're all like he's always kind of sort of there yeah it's cute that is super cute now I like I like the little blinky this is what we were talking about in the beginning of the show like as long as like the robots are moving and things like the eyes are constantly like this is peace.com this is my robot friend everything's okay well it's funny you say that because Jay was one of the people who inspired me to actually get up and do this and yes I can and you know he gave me some tips in on the servo so he was a really big help getting me started yeah I I like saying that a lot of the show and tells and the thing that we do in the maker community is like skateboarding it's not competitive it's more like oh I see that you did any trick I can't do that trick and then people help each other and then you really yes and then you keep building on top of each other's projects and I used to be a skateboarder I remember thinking like wow it wasn't a competitive thing it was more like a team sport that you get to play forever around the world where you just push each other in good ways and I think that's why a lot of these projects are fun it's very different than like one-on-one sports or you know business and other stuff so thanks for thanks for skateboarding this week my third project isn't ready yet I hope to have it ready for you for next week I unveiled an early copy of it at Defconn it's called Rolling Thunder and it's a heavily modified jazzy 1450 motorized wheelchair it comes complete with a light package a 200 watt stereo a raspberry pie that plays movies and it has a 14 inch monitor on the back of it nice and a nebula projector a little spaceman nebula projector it's not ready yet it's not fully ready to show off but I hope by next week it'll be ready to go awesome those projectors are really nice the nebula ones um one of the things I want to do is play around with you know the projection mapping that you can do where it looks at an object and then it projects yes yeah that'd be kind of cool anyways this is this is the cheesier version of that it's still a little five volt you know star field nebula projector very full projector I tried to do but the power consumption even with like a laser instead of a bulb yeah it was still a lot of power and my jackery only has so many watts in it per day there is a tube based projector that has a battery in it that's usb chargeable you remember send me an email send me a link to it they're not they're not they're also not super expensive that might be anything you'll get one of the things about that is that when you're securing something to a power wheelchair you know you take a lot of jumps and bolts and knockarounds and things tend to fall off I've become a master of zip tying it's like it's like an art you're like like origami but with zip ties to make sure that things don't fall I originally my monitor used to can't you know one way or the other and I had to really knock down on that and then everything is based on a PVC pipe frame that I built on the back of the chair and a lot of audio equipment has a what is it one inch pipe fitting in the bottom of it so it dogs down on that and then getting the power because I don't want to take power away from the chair so I've got an external jackery battery that does that handles that and I've got it tuned to the point where I can get about nine hours out of the battery before it dies well come back next week and show the uh the third project yeah you know whatever you get it yes next week hopefully I will have it done by then once again thank you for the wonderful nice thoughtful gift cheers all right everybody that is our show until this week that was super fun it's so good to be back meeting and sharing it with folks we'll see everybody on ask an engineer in just a minute or so we're here every single week some 30 p.m. Eastern time we'll see y'all next week see you in a few minutes bye bye


I lit my cigarette, my eyes focused on the dark road in front of me. It was one in the morning, and I was really tired. I'd been driving for hours and was in the middle of nowhere.  My stomach growled menacingly. I glanced in my rear view, trying to recall how long it had been since I'd eaten last dinner last night. I decided to pull in at the next fast food place that I saw. A break would do me good, and if I still felt this tired by the time that I'd eaten, then perhaps a quick nap in the car before continuing on wouldn't be such a bad call either. I blew smoke out of the window, trying to ignore the hunger pangs in my stomach. I was always being reminded to eat. I turned the music up louder. I wasn't going to think about that. It was about 20 minutes before the golden arches came into view. Thank God I muttered as I pulled off of the highway. I threw my cigarette butt out of the window, and used my car into the McDonald's parking lot. The place was brightly lit, and was as inviting as any McDonald's could be, though I couldn't see anyone inside. There were no cars in the drive-through, or even in the parking lot for that matter. Not that I had really been expecting anyone. The highway itself had been pretty much deserted for miles. It struck me as a little odd that there were no cars at all in the parking lot, though. Turning my music right down, I crawled toward the menu board.  The speaker next to the board crackled to life, and a man's voice came through. Welcome to McDonald's. May I take your order? I gave a small sigh of relief. There was someone here. Uh, hi. Could you give me a minute, please? Certainly, sir. Just let me know when you're ready. Thank you.  I was his sole customer, and probably had been for quite some time, if the roads were anything to go by. All the same, I hated it when people had to wait on me. The speaker was still on, and I could tell that he was waiting on my order. I hurriedly decided between a couple of options, and then spoke out toward the speaker rapidly. Uh, right. I'll take a double quarter pounder combo, and, uh, no, wait. A quarter pounder deluxe combo, actually. Quarter pounder deluxe? Yes, please. And for the drink I'll have. I'm sorry, sir. Could you hold on for just a moment, please? Uh, yeah, sure. Thank you. I'll be right with you shortly. No problem. The speaker shut off, and I gazed up at the board, double-checking my decision. Once I was absolutely sure of what I wanted, I finally looked away and gazed ahead at the empty drive-through. I rolled my head a little, trying to relieve some of the tension in my neck. The bright restaurant windows flooded the drive-through road with light. My heavy eyes focused on the golden pool closest to me, and I started to zone out. God, what I would have given for a nice full stomach in a comfortable bed right now. Suddenly my eyes snapped up. The light in the first window had gone out, and the first half of the drive-through had been plunged into darkness. I instinctively turned to face the speaker, waiting for it to crackle on again. Nothing. The lights in the second window suddenly shut out, plunging the remainder of road into darkness. I sat up straight. I tried to relax. Sure, it felt a little eerie, but it was only a drive-through for God's sake. The speaker crackled again once more, and I jumped. My apologies, sir. May I resume taking your order? Uh, yeah, yeah. So it was a quarter-pounder deluxe combo. Large fries, please. Large fries? All right. And for your drink? I'll just take a chocolate milkshake. Chocolate shake? Sure. Anything else?  I grit my teeth, trying not to let my hunger and tiredness get the better of me. What was it going to take just for one thing to go right today without any hassle? I sat for a couple of minutes, waiting for him to return. Nothing. Screw this.  Before I could do so, however, the speaker once again crackled back to life. My apologies for that, sir. Slight glitch in the system. It's fine. So that's a quarter-pounder deluxe combo with large fries and a chocolate shake. Will that be all for you today? Yes. Thank you. All right. If you could just make your way to the first window, please. Sure. The speaker cut out, and I crawled forward into the dark. I was vexed. I just wanted to get the hell out of there. Everything was a damn roadblock today. I rolled up to the first window and looked in. The place was in darkness. A man's form appeared, and he slid the window open. I couldn't really see him that well, but I could tell from his voice that he was the same man that had taken my order. I felt instantly on edge as he greeted me in the dark and took my card. Was this some kind of joke? He handed it back. Thank you, sir. Window number two. Uh, thanks. Before I could drive forward, the lights in window two suddenly flooded back on. Card between my teeth. I eased forward gently toward the window and came to a halt. My blood froze. The same man stood there, clutching my bag of food. On any other occasion, this would have been a complete normality, except that he was absolutely covered in blood. His face, his hands, his clothing, even his hair and lips.  The entire bottom was soaked. I felt sick. Here you go, sir. He smiled, holding the bag out to me. Enjoy your meal. Shock and terror had risen up like bile from my stomach. My face was on fire. I could feel my quickened pulse pounding fiercely. I knew that I should speed away. I knew that.  I stared at him in horror and he smiled. After a moment, he slowly slid the window shut. My hand was still gripping the sopping bag, now dripping onto my legs. He stood there silently, staring at me from behind the glass. Out of nowhere, my senses kicked in and I sped off, flooring it right over a grassy mound. I didn't care. I was desperate to get to the highway. As I sped along, I fought back the urge to be sick.  I never knew what the contents of that bag had been, and I didn't want to know.


All right, so you want to go into the actual page where the link is and you'll want to click on it Then of course you want to make sure you're in edit mode You want to scroll down to where there is a link such as this one. You'll want to highlight it So highlight the link come up here to the little link icon and on this page You want to make sure the link is there and then you want to choose new window And then you want to hit update Then you'll want to submit it and then turn edit mode off and we can go and check the link Come down here take a look at the link We'll see that it took us to the right page So that's all you got to do and you just want to make sure that All the links that you have do that so that when say you're done with this page You can close the tab and you're still back in the course. All right. Hope this helps