. So please enjoy it. We'll be back here at 1 p.m. with the paper presentations, so don't miss them. Until then, enjoy lunch. Thank you. Check one, two. Check one, two. Check, check. Check, check. Hey, hey, one, two. Check one, two. Check, check, one, two. Check one, two. It's a great view here. It's hard to speak in front of this view. To stay one day out. It's hard to speak in front of this view. Yeah, it's amazing. Okay, thank you so much for your attention. And stay here for the first talk in this session. So my name is Fabio Petrioli. I'm an associate professor at UCCAC, University of Quebec at Chico Timi. And we started work with my new PhD students, especially Marcella, did his master in robotics and moved to Canada to work with me in software engineering and robotics. And you say, oh, there is a great symposium about blockchain and robotics. Maybe you can share something and you prepare this work to share with you today. Just to say it's a really preliminary work yet in progress. But you have some insights that you would like to share, okay? So just to present, Quebec is a huge province in Canada. You run so far in the north. It's a good place to visit. You have the opportunity to visit. Take a flight. There is an airport. It's far, but there are not just bears there. There are flies also to come. So it's a beautiful place. It comes from small campus, but so kind. I do say. And you are trying to organize a team, a research team around software, software engineering in general. You do an acronym, smart seeds. Software is my art. Say software is more art than technology sometimes. And because it's hard to understand this phenomenon, you try to do it together. Try to organize this stuff. So finally, we start to discuss and say why people in Marcella start to discuss and why people... It's hard to use robots yet because industrial, traditional robotics is everywhere in the industry, traditional. But it is cost-efficient. Why is not everywhere yet? And you can say in the discussion because the safety, okay, in general, is not the safety to share. So there is the point that you have discussed that safety is something that you have to improve to put robotics everywhere. So one discussion, one option to improve the reliability in the safety maybe is blockchain. That's a discussion that you are trying to motivate this work. So what's our goal to try to identify and so the state of art on blockchain and robotics, okay? A little bit of point of view of the distributed systems and software. So our goal is try to identify, classify, evaluate the work on this topic. So how you did that, you do a systematic review. Yes, we read a lot and try to find the papers following traditional guidelines in systematic review in software engineering, okay? That's in the use of, you organize research questions and such strategy and blah, blah, blah, that you know probably and you try to show you some research questions as what are the main challenges that you can discuss, the main approach in blockchain, benefits and limitations, okay? So what you did, you propose a research string, search string in traditional libraries, okay, as ACM, IEEE Scopus, and you compose 89 papers and automatic search on blockchain and robotics, okay? That's you put these keywords and there is 89 papers and also we put together the papers manually from the first symposium, okay? First version of the symposium to try to collect more papers and after filtering the criteria seriously there is able to answer our research questions, you select 14 papers to analyze, okay? So I can show you and that's our first, maybe small but in progress contribution, a catalog of papers on this topic so that you can continue and use this work. And one important for me is it's really, really extremely new topic, okay? It's 80, 26, 27 and 19, okay? It's really, really, really recent topic. So you are in the trend, that's you can say. There's not a lot of but in progress there's a couple starting to come and different people are probably here working on. So what's the opportunity that you started to make mapping on this and you analyze these challenges and so it's not a surprise the majority of papers discuss about the challenges on communication, okay? How to robots work together and how communicate and a couple of seven from 14 papers work on collective decision. It's another important challenge discussed in this topic. So communication but also communication every time in point of security. This is the main point that you can realize and the distributed decision making algorithms is something really pervasive I can say in this work, okay? And we try to show you some quotations in really new paper. The usage of blockchain paradigm on embedded systems for distributed multi-agent robotics is still uncommon. This is important for me when I see the announcement for this event here say, wow, it's great blockchain and robotics. And first time is no meaning because blockchain is something for no real time system if you can think. But in fact, people starting to use this technology to improve the systems as robotics and however the limitations of embedded hardware is yet an issue to support this topic because as you probably know, blockchain is an intense proof of work. So this is an issue that you can work together to use blockchain in robotics systems. Okay? So also the discussion of using blockchains to intrusion detection this is one topic to discuss what's the main approach for what's the people are trying to use blockchain technology in robotics. Not surprised to is the smart contracts that you have an example in the first last presentation here uses smart contracts to organize the tasks in blockchain context. Okay? But the majority of approaches is smart contracts that is the point that people are focused on in blockchain. Okay? So blockchain approach has a potential enabling to build security and scalable distributed control systems device such as a robot in IoT environment. Okay? Some people are trying to focus and say it's a path. There's a potential to use. So the use of blockchains allow providing mechanisms for ensuring the truth, durability to storage and no repudiation from the information. Okay? There's new papers that can share this kind of discussion. Okay? Here talking about also this couple of work discussing about Lego Lego and safety regulations also in blockchain. Okay? Especially in swarm operation. However you can also discuss some traditional issues in blockchain and especially in robotics. And latency is the most important one Okay? It's a traditional problem that become probably the most significant one of the most important issue that in literature identify to use this technology in robotics systems. Okay? So with this consequence of the communication and swarm and large quantity of robots or to deploy this network this is not a simple task too. So this is another quotation about communication that you know. Okay? So just to finish some a couple of discussions that you prepared and to highlight. So regarding analysis studies mobile robotic systems more specifically swarm robotics is a predominant robotic to use a blockchain technology. Okay? And the integration of blockchain and robotic systems could be in fact a key series progress in the field of robotics. Okay? People are trying to observe that and you are here just to put together this idea probably. Okay? It is probably a huge impact in the economy that you discuss and it is clear in the literature to confirm that. So just to share some maybe points or recommendations that you can discuss maybe to create some metrics, parameters, parameters to evaluate this practice especially the point of view is security. Okay? Methods to compare blockchain and other different methods in distributed systems. Okay? And also requirements specifically requirements to put together robotics and blockchain. It is work to do it's something that you imagine that in the progress. Okay? So that's it. Some kinds of attributes in distributed systems for robotics. Also maybe is a kind of my research on software engineering how to put some software engineer aspects around blockchain and robotics. Okay? So I really appreciate your attention. I hope this as I said is a work in progress. You will continue to improve to the next version and work hard to publish a really good paper. And thank you so much for your attention. Okay? My name is Renita Moremi and I am associate professor at the University of Dallas. Today I'm going to talk about my research on a blockchain framework that's used for social robots and the means for analyzing this framework will be a mathematical concept called shift theory. So I apologize that I'm using 3D or motion graphics. It's mostly mathematical work and due to time constraints I've skipped the mathematical equations as much as I can and just simple visuals to show how shift theory really works. Before I go into the framework for social robots, I want to speak a little bit about the motivation for this problem. So the well start as a traditional conundrum in decision making. We all know of decisions we have to make in our lives, personal and professional, trivial and non-trivial. And one of the biggest hindrances is imperfect information. We often do not have all the information we need and that could relate to games, it could relate to where do you apply for college or how do you put in a job application, we simply do not have all the information we need. And in the absence of perfect information or rather in the presence of imperfect information we adopt an action and that action might have, may or may not have suboptimal outcomes for us. And these effects are compounded when we're working now not as an individual player but as a group. So there's this swarming behavior, this collective behavior where a bunch of people like us all make suboptimal decisions based on the imperfect information that we all have. The second impediment to good decision making is irrationality. Decades ago Kahneman and Tversky studied how people did not always do the right thing, especially when talking about outcomes of a game. So if you have the choice between getting $10 and $50 over a series of studies in various domains they found that people were consistently choosing the $10 outcome. And that's because they simply did not understand the mechanics of the game or rather their perceptions of the utility from the game seemed to be that choosing the $10 would be more profitable when in fact it was not. And so at Kahneman and Tversky did is they turned the traditional model of utility rising from economic games over and they said humans are not always rational. We have here an irrational actor who does not have good information who is behaving in such a way that the outcomes are suboptimal and often what plays into our decisions is biases when we do not have good information about a circumstance we rely on patterns that have worked well for us in the past or have worked well for others. And so we rely on these biases which are really shortcuts to making good decisions. Now I'll move on to the current conundrum in decision making. So for the past few minutes I spoke about the traditional conundrum. The current conundrum is that we have enabler technologies this trifecta of artificial intelligence machine learning and massive data sets and really good algorithms that parse through these data sets and these have tilted the scale of rationality in favor of the machine. We are all aware of recent advances where the robotic version of jeopardy or chess or alpha go defeated the world champions in those games when those games were played and they continue to improve. And what has happened is at the heart of this we have a game between two unevenly skilled players. On the one hand we have a robot a robotic version of the software that can perform one thing really well. So the alpha go robot just plays alpha go really well and you would not expect it to pick up a block. On the other hand we have a human who has imperfect information in a range of applications. So not perfect information in alpha go but a range of applications. And these things fairly well in many different domains. And it really because the scale has tilted in favor of the machine that is because the human has usually limited recall of the past is short-sighted in the future and even the current we are plagued with imperfect information. So what works for these robots? And why do they usually have the upper hand in these complex environments? It's because they do two things well. They reduce imperfect information because they can store everything in the cloud and they have access to these large data sets which we humans cannot. It's beyond the range of normal human cognition. And they're also usually not irrational. Given appropriate code it will always choose the best outcome which cannot be said for human beings all the time. And these algorithms are not just gaming versions. We see them combing through data sets of demographic information, voting polls, SAT results and they're working well. It helps when these algorithms help detect cancer faster. They help us correlate income to majors and in general they're able to predict the future well. Let's say stock prices, medical trajectory of certain illnesses. But the problem comes when we think of these devices or these robots as not just our helpers but their co-equals with us. And through this morning we heard various talks about robots working with humans becoming agents to interact with nature. So we're moving in that direction. And this is not really any more in the realm of a sci-fi future. We already have smartphones that are talking assistants and they keep the company of our elders. They entertain my children for sure. And when I was here last year I learned about a drone that has its own social media page. It orchestrates pickups and drop-offs. So we're looking at a future where we have a society that is inhabited co-equally with robots and humans in both virtual and physical spaces. And in such a scenario it is a problem when the robot always has the upper hand. If you're thinking of a robot as a co-equal member of society it's hardly that it knows everything in all situations. Who would want to play a game with an entity that always wins? Or to socialize with a robot that knows the answer to every question. I mean at least speaking for myself we all have these memories of conversations or quarrels with a friend that passes significant others. We're ten years down the lane and everything was said and there's no perfect information about who said what and we just let it slide. But that is not the case with the robot. The robot just knows what was it who said it along with the time stamp. So the work that we're proposing for social robots is to make them more social. It's not just in the form of aesthetics. There is a lot of fantastic work then around robot skins and appearances texture but the work around human empathy. I mean much of human society is made up of these glues of empathy where like-minded likely able individuals bond over common goals concerns challenges. So to make the robot more human in that sense. Now I'm not advocating for a robot who behaves with imperfect information and is irrational all the time. And that's where we bring in the concept of smart contracts. So I proposed framework and there's three things. The first is to have these tunable parameters both for imperfect information and irrationality. So for example a robot that's talking to a child or playing with a child has a certain level of imperfect information and irrationality and then when the same robot is used in a different application it has better information and exhibits a more serious demeanor if you will. And these classes are then embedded in smart contracts. Now smart contracts work well on the blockchain and that's not the only reason we pull the blockchain in here. It's distributed it's trusted and it's immutable. Now for analysis of all this. A common concern that was raised in this morning's talks was that the blockchain is limited in how much it can do. We have all this data that's coming up and analysis of these data sets is hard with attributes that maybe have different features. It's easy to represent an interaction or a transaction between entities up to three dimensional space that's good for us humans with algorithms we can go up a few more dimensions but imagine a transaction where you're recording I use the word transaction to record any interaction. So if there is a transaction between a robot and a child you're going to decipher sentiment emotion, facial expressions the content of the text being spoken all these features quickly add up and if I were to represent this as individual points it looks like a very dense point cloud and what happens in dense point clouds is you miss important features you miss components such as tunnels or voids in the graph you miss features about clusters and anomalies because it's just a very dense point cloud and analysis is difficult and that's where a fairly new mathematical concept developed around the turn of the 19th century called shift theory comes in shift theory actually has its root in algebraic topology and applied category theory. So this is the contribution of this work unifying framework for social robots analyzing shift theory and made more social or less social based on certain tunable parameters stored in smart contracts. This is the premise for sheaves on the left you have a line an edge which is a one simplex a simplex is a building block and then I have a two simplex the three simplex is the tetrahedron and n simplex in general is a convex hull and this is the extent of all the math that I will put up in the slides there is more in the paper than in free to talk with anyone interested about the details of this but algebraic topology really looks at the shape of spaces and what it does well is it understands patterns and the structure of spaces when it comes to things like graphs and by visualizing the block chain as a structure like this it becomes easy for us to find patterns faster. More and more applications are envisioned to use block chain there are some really nice visuals in the talks this morning but one example that I put up is that of fraud detection fraud detection usually depends on a range of characteristics patterns in location buying behavior the amount of the transaction and envisioning this as a blockchain of sheaves makes it easier to find out anomalies a sheave is simply a gluing of structures that has certain local properties and global properties and those local properties are enough to determine the global properties and that's where the power of faster computation comes in. Some more motivation for using algebraic topology last year at this symposium I proposed this framework for storing social network data on the blockchain and that also is massive amount of information lots of statistics online about how many tweets post shares that are generated every day and all this information and studying this with traditional graph theoretic tools becomes cumbersome so the default approach now is just to collect, harvest all the data and store it and analysis comes at a later time so one might argue that why do we use sheave theory there are some tools like principle component analysis that can help us study the structure of these interactions and use a limited they do not work well on manifold or curved spaces but sheave theory does really well on end dimensions which is harder for us humans to visualize but it's very forthcoming and very powerful using sheaves blockchain transactions have there is one other paper that I'm aware of that studies the blockchain using sheave theory to do work concerning distributed consensus protocols regardless there is other work purely from the field of mathematics that looks at sheaves and they study things like eccentricity and verdict significance simply put they're studying how well a node is integrated in the graph or how isolated it is how does that translate for us it helps us find anomalies and outliers and hubs and clusters there are tons of interesting things about transactions again transactions is a term I use loosely for interactions smart contracts usually smart contracts have underlined clauses just like contracts in a non-blockchain world where upon the fulfillment of certain clauses an action takes place so in terms of a graph you can depict it this way but when these conditions are executed another edge is formed so these smart contracts have the potential to balloon very fast because all these smart contracts lead to more actions which probably have more smart contracts embedded in them and so very quickly we're looking at very dense point clouds which are difficult to analyze in traditional tools and this scenario is further complicated by the use of IoT devices these devices latest statistics say 20 billion 22 billion by the end of next year so if these devices and various virtual agents are on the blockchain that results in computationally intractable techniques for analyzing the data produced by those devices this is an analogy of sheeps think of it as a sheaf of wheat a sheaf is made up of stocks what I have is a stock the power of sheaf theory comes in because it's so versatile it's applied to categories of objects and these objects can be heterogeneous these objects are also modular and the categories are modular so those of you in the audience who are familiar with object oriented programming might get that concept a little you might find it a little more relevant you can have objects of various elements so right now I have a stock of blocks and the common spine can be depicted as the spine inside that stock each of those blocks are analogous to the seeds inside or the germ inside every stock if we put together a bunch of these stocks and bind them with a smart contract then we have a sheaf this is another example on the left I have a single block depicted as a stock on the right I have an entire blockchain depicted as a stock so immediately you see the versatility it's not limited to a single kind of object to be linked within a stock and the individual blue circles they represent nodes each of these nodes can be transactions with those green circles are features so features recorded about a transaction these could be sensors that are monitoring various data points and then whatever is the common linking point usually is the hash that links them that comprises the stock in these diagrams here are some applications the one on the left is a blockchain stock for logistics and tracking you see now the structure of a sheaf where you have multiple stocks bound together these these are bound by smart contracts which are a function of the imperfect information and irrationality these can be tuned on the right we have a blockchain invasion for a pursuit invasion game where we have maybe a dominant robot and a slightly less skilled robot so heterogeneous robotic applications and on the bottom we have something like a swarm robotics behavior where multiple robots are measuring different things and they are all bound by the smart contract the applications as we mentioned in swarm robotics in smart social robots also in consensus applications consensus applications could be related to voting mechanisms and crypto wallets and exchanges can also be analyzed very well using sheaf theory we have central nodes that are behaving in different ways all of this information can be captured and analyzed very fast using sheaves and then stored on the blockchain and certain challenges and limitations that are not just unique to our framework they are the result of bringing together disparate disciplines one is quantum computing it helps and it hinders once the technology can be embedded in regular robots it of course leads to a very fast robot and therefore a very slow human but on the other side all of this if it's on the blockchain key management is a big issue and quantum cryptography can lead to issues in the provenance of the key and how strong it is how fast it can be broken so that is one challenge that affects such frameworks that is currently work done in post quantum computing that work is still emerging that produces ledgers that are resistant to quantum algorithms and so those will help this challenge the second one is that of regulation at its core blockchain has the concept of distributed computing so no one really owns who goes first how the consensus is formed it's a natural organic way based on mathematical constructs but in social robots or in smart contracts it might be necessary to have some kind of oversight for example if a robot is deployed to understand the prognosis of a patient it's helpful to decipher intent and emotion and these when not done well might lead to catastrophic consequences especially when things are not very black and white for medical conditions another common challenge is that of diverse blockchain environments there are so many environments used across so many applications and it becomes a challenge when we want a seamless way to interact with all our devices so that is another limitation and information overload blockchain in itself does not stood a lot and therefore tools such as sheaf theory are critical in reducing the amount of information that we gather and storing that on the blockchain so in conclusion this work brings together smart contracts that are tunable that behave differently in different environments and these smart contracts are created with the sole purpose of making these social robots more social or human imperfect information and irrationality will be the tunable parameters here and the analysis of all these interactions is done using sheaf theory which is a computationally efficient tool to analyze large volumes of data and finally storing all of these on the blockchain not just because of smart contracts but also because of the inner and trusted distributed nature of the blockchain for future work we are looking at elements of how AI technologies specifically the Boltzmann algorithm can help in looking at sheaf theoretic implications for analysis and a broader work is social justice through algorithms which we haven't hashed out yet but we are still in the initial stages so that is it for my talk and we have questions good afternoon my name is Jorge Peña Geralta and I'm here with Tommy Versterlund we are coming from University of Turku in Finland and I'm going to be talking about utilizing blockchain technology for managing collaboration in heterogeneous robotics swarms but before that just a brief introduction to what our research is about in this area we are working somehow in the intersection between robotics and blockchain technology and we are working in the intersection between robotics, cloud computing so IoT domain and in this direction our research call is to design methods that enable truly autonomous reconfigurable robotic swarms and we think about this from the point of view of how it works with cloud computing you can take someone else's application and without knowing exactly how it is implemented you can deploy it in a set of servers even to some extent in a distributed way so what if we could do the same with large robotic swarms heterogeneous what if you could take a set of robots with potential different capabilities and you could take an application that somehow is coded in a way that is abstracting these capabilities so doesn't necessarily know about the specific hardware or specific sensing capabilities of these robots and you could just deploy it and there could be a distributed consensus system that could take into account energy constraints that could take into account how to distribute the computation and how to distribute the tasks so that this is not given to the developer of the application this is a long-term goal and before explaining how or what can be the role of the blockchain in this idea I want to say or let me set the specific research questions that we want to answer in this paper and specific problem settings so I have said that we are talking about heterogeneous robotic swarms but what does heterogeneous mean so for us heterogeneous in this setting first means variable operational parameters so it means robots that interact with environment in different ways robots that can operate in the air, drones, robots in the ground, cars or why not robots in the water autonomous boats and by robots we mean in general any sort of autonomous agent in this context but it's also second variable and we have different sensing capabilities so robots that understand the environment or agents that understand the environment in different ways with different sensors they can have a geometric understanding they can have a semantic understanding or any kind of sensor suit and last they have variable processing power so how can we take this into account robots we can have an autonomous car with almost a super computer on it but drones have heavy load limitations so we cannot put a big a lot of processors in there there's that limit and just from a conceptual point of view so where would this be this image only shows cars and one track but in general we could think about a smart city of the future maybe even the near future where we have self driving cars we have autonomous delivery robots which are smaller we have also delivery drones or we have automated trucks or logistics industry and what we want to answer or what we are trying to discuss about in this paper is how can we achieve consensus in a collaborative heterogeneous multi-robot system but potentially ad hoc so we don't need a priori what are these robots and by achieving consensus we mean achieve consensus in the collaborative effort so now we are reducing to the fact that we have multiple robots and they want to share data they want to share data to improve their situational awareness to raise their degree of intelligence or level of autonomy and to do this we have to promote high quality data so we have constraints in terms of for example bandwidth in the network so what data is to be shared which robot is going to send which data to whom and when we think about data is not only about the quality of data or a specific characteristics of data but it's also about the amount so what size of data are we sharing and this is not only in terms of the network limitations but it's also in terms of processing limitations of who is receiving the data so how can we take this into account in this collaborative or distributed consensus system and we believe that maybe not the whole answer but part of the answer might be or can be in blockchain technology so in this paper we are tackling the idea of modeling to some extent sensing capabilities and processing power of different robots with blockchain or with technology that is part of the blockchain stack and specifically we are proposing the utilization of proof of work or cryptographic proof algorithms in order to model computing power this is maybe something relatively new in robotics but this has already been used to some extent in mining pools for example in the Bitcoin network and this can be utilized also in robots with limited computational power because we don't require full proof of work we don't require robots to solve the whole to find the proper hash we can utilize partial proofs of work so we can have to some extent an estimation of the processing power of the different robots without being aware of what hardware they have just by knowing how much of this proof of work they can solve within a certain time and then in terms of data we can somehow utilize the blockchain to characterize and rank data to try to promote this higher quality data so in this sense we can leverage the immutability and the data integrity properties of a blockchain in order to have a history of data samples provided by different robots and one thing that I have to say at this point is that as it has been mentioned blockchain in the current state of the art is not ready for low latency high throughput real time systems and data exchanges so we are not proposing that all data is shared through the blockchain but we are proposing that robots are requested to share a sample of that data and store it in the blockchain these samples have to be significant enough so that other robots either at the same time or later operating in the same environment are able to find the same features so it could be features that are using in SLAM algorithms for example it can be a corner of a building or something that another robot can find and this data which we call SLAMs that are stored in the blockchain can be utilized and be compared when submitted by multiple robots so of course these takes times is not trivial is initial research so it's still ongoing but it has a lot of potential and this can be used not only to rank the data and to choose what is the best source of data but also to characterize it so it can be images it can be data it can also be thermal data so it's just a sample from any kind of sensors it can be only geometric data from example from a laser scanner so just points in space and from these all robots that have access to the blockchain they can get an idea of who is able to produce what kind of data what is the quality in terms for example if it's images you can think of pixels inside each of those buildings windows in the building or if it's geometric data about how many points within a certain area defining a corner or defining a window as well but this all sounds very nice how to deploy it so it's not trivial either or it's not clear and here we are putting two main questions which are from the point of view of deployment are we talking about when anonymous blockchain permission less where everyone can join this can raise a lot of issues from the point of view of accountability and trustability because we are talking about potentially safety critical situations these are autonomous cars autonomous robots that might be operating in the same place than people so having anonymous agents in this setting might not be ideal however we are talking about having a permission to blockchain which is managed by a trusted authority for example public infrastructure in a smart city or mobile network infrastructure so this kind of blockchain not only allows to manage identities and we have a set of parties that are maintaining even in the case of network loss that is something that has been commented by the public and the public and the public and if suddenly only very few robots are cooperating so here there's a problem there's a higher chance of attack there's a lot of security risks but if we have some public infrastructure or trusted parties and large enough number maintaining the blockchain that might be a solution for how to define this in the case of trusted infrastructure yes it can be started by these public authorities and it can be maintained by them and we can have a single blockchain but what to do in the case of ad hoc blockchains one option that we propose in the paper is that these might be used by private parties for example think of Tesla, Audi or any car manufacturer that might be doing this within their own fleet so it's a private blockchain but it's not a single one it's just generated whenever there is a high enough number of cars in a certain area so within some distance or in the same environment then one of them could automatically start this blockchain and they could start automatically collaborating without the drivers being even aware of that so it could be from a private private point of view and just to finish some discussion and conclusion so there's a lot of challenges in this sense we believe that there's also a lot of opportunities but there's been a lot of talk today about scalability about real-time computing about security and what happens even in these cases of safety critical situations if we have a 51% attack or if we have civil attacks then we also have the problem of identity management and accountability and especially because we are talking about autonomous robots that are operating with people so how do we make them accountable or who is accountable of what or how do we make sure that we know who did what or what was done wrong and in general data integrity the blockchain in this setting is not used as a cryptocurrency so the value of the cryptocurrency is mainly used to transactions but what would happen for example if a set of malicious robots are the only ones operating in a certain environment providing fake data and validating between themselves there are strategies or there should be strategies to find these outliers based on for example some words that have been presented today but it's not clear and we need to do more work in that direction and just to conclude so what we are proposing here is that blockchain could be a good fit and a good tool towards consensus in robotic systems this has been said a lot today as well we can use the immutability and that integrity of these distributed ledgers to manage and to classify the data provided by different robots but we can also utilize part of this technology to abstract the different resources that in robots we don't usually a robotic developer just knows what hardware or what software it's using but if we want to open these robotic swarms to a wider array of applications we need to be able to abstract these resources and generate new ways of interacting and controlling swarms of robots so Eduardo has said very well this morning we have to go beyond human-robot interaction and start thinking how to do human-swarm interaction and control and that's all, thank you very much any question? so good afternoon colleagues my name is Vitzali today that in the morning in the beginning of our symposium Eduardo mentioned the need for new business models on robotics market so that's what I'm going to talk today but first of all let me ask you a question how many of you have used an Uber in the past month? by show hands most of you did so sharing economy became really common concept in our everyday life in our economy and I think that the same way that these technologies has led to this uberization of relations between the customer and the service provider the advent of cyber-physical systems paves their way for a completely new business on robotics market and these business models are not just about fully automatic production lines in the enterprise I'm talking about universal access to robotics capabilities for small and medium businesses and thankfully researchers have already started to think of these new concepts and one of the most famous ideas is robot as a service model and the idea there is that it's service oriented architecture that integrates different types of robotic devices and the hallmark of this concept is that people refuse to buy the software hardware directly and instead they use the service this allows to reduce significantly the cost of adoption robotics and also the cost of operating the robots and let's go deeper into robot as a service research first the robot as a service platform consists of basic services that describe the functionality of the robot some user services that can be added standardized communication protocols like HTTP and the final is computing environment and database and the publications that we researched most scientists actually discussed that in the context of cloud computing so publications about robot as a service widely represented by Yeong Chang and his colleagues from Arizona State University they actually published the most cited publication on the topic and it was one of the first to use the term robot as a service and in the first publication they say that in robot as a service there should be the same functions as in service oriented architecture which are robot as a service unit for which this functionality is described the service which is the cloud provider and then the broker is an interactive shell that gives access to those functions in the cloud and then in the next research those same authors expanded their research and they identified a few narrow points of using centralized approaches for robot as a service platforms and they proposed to solve them by using standardization and redundancy and even though they discussed the disadvantages of decentralized systems they actually state that some decentralized elements are required to improve the reliability of centralized systems and then in their last publication they presented an architectural scheme for their solution with multiple levels and we thought that the most interesting was a presence of business layer which not only manages the fees for the services but also it looks for new business opportunities to improve the whole system in the long run and some other research on the topic were published which is robot web and we found it interesting because it was one of the first to use robot operating system and it gives us a lot of opportunities to integrate different types of robot and then in this publication they focused really on robot as a service application for emergency response use cases and the interaction interface they present here is really similar to publish a subscriber system in ROS so we found it also interesting so basically as you can see in academic environments most research on robot as a service is focused on cloud computing and after reviewing these publications our team decided that well the future of robot as a service needs to be revised and that is why we need to propose new architecture and that's why we did actually practical implementation of that so here it is we offer broad decentralization of robotic devices and we offer giving them economic autonomy the first decentralization allows to actually reduce the computational burden on the agent management system and that allows to connect more robust system overall secondly even though some components of economic components were discussed we think that we need to propose a new way so every device need to be able to create transactions on its own in order to achieve fully automatic analytics system and that is basically the only way we can evaluate the performance of business processes and in our case we use organize the work of robots market mechanism and the robot sends the supply message to the special channel and same as the client sends the demand message and then we use interplanetary file system to do that to collect the demand and supply messages and after there is a match between supply and demand an economic transaction is created in the form of smart contract in one of distributed registers we started working with Ethereum a while back but now we have a lot of support and substrate and the use of smart contract technology allows us to guarantee the execution of robots code and basically improve the high and have the high level of protection against malfunction and hacking and in previous publications some methods of identifying faulty nodes were discussed but specific security issues for robot as a service were not raised and neither were transparency issues so the use of distributed registries allows us to have transparency of transactions and allows us to take some functionality of the cloud server to those independent software nodes so we have independent software nodes and independent robots and then finally all authors agree that there is a need for standardized communication protocol in robotics and on our opinion this standardized communication protocol is robot operating system and we pass the command to the robot using a rosback file which describes the functionality of the robot so this is our vision of how robot as a service should be organized and I'm happy to discuss business models on robotics market further and I'm happy to answer your questions thank you for your attention sure what do you think this is like something innovative compared to the other people that are working on something like this could you tell us more about that exactly so we think of liability as basically the robot that needs to deliver something to the client so basically whenever a client requests a service and pays for it the robot is liable and by using those peering technologies that we just described we can give this economic autonomy to the robot so it has its own identity has its own wallet and it's able to create contracts so now we can make sure that when this contract is executed the liability is transferred automatically and we can keep track of that thank you you might have kind of answered it through this previous answer but if you didn't use the smart contract would there be other ways to do it and why smart contract more advantageous to the other ways well in software architecture there are a lot of different ways of how you can do things but I think that it is really important to think of robots as independent economic agents and identity of wallet and ability to create contracts that's by having this smart contract smart contract is essentially a native contract for robots that's how I see that it basically is an instrument for us to create a contract with a robotic entity thank you so nowadays we have a lot of applications of multi UAV drone systems from surveillance problems to search and rescue exploration inspection missions and more but how can we improve these applications hello everyone my name is Mario Gabriel I came from Isai Supero in Toulouse France and today I'm going to talk about the implementation of the blockchain in the surveillance problem but first let's define what is the surveillance problem that we're talking about so a surveillance problem that I'm going to talk about basically consists in a set of UAVs completely autonomous they must patrol a certain number of points of interest or POIs but this patrolling must be according to these two criteria must be completely unpredictable so no external entity can actually predict which drone is going to visit each POI for security reasons and it must be efficient as well and efficient for us it means that each POI must be visited as many times as he can so in a perfect system a POI would be always visited by a drone but this is not possible so because we have limited number of drones but we want to maximize this number of visits but how to integrate the blockchain but the algorithms that are developed and the papers that are published to solve this kind of problems they usually they admit that this data is always available the communication is 100% secure instantaneous they don't take into account the communication process between the drones and they usually they rely on servers and they rely on non distributed products and so this is a problem because they are not resistant to single-point failure and it would be very nice as well to have anonymity and transparency because if you want to visit as a service for example I have a drone and I want to rent my drone to a company that runs a patrolling service so I want this every transaction to be transparent but how can we connect these four elements together and we think that a blockchain is the best answer so regarding the decision-making algorithm how to decide how a drone decides which POI to visit we have two options either we go with the classical optimization problem but unfortunately for implementing on a smart contract this is too complex and too resource intensive we are talking about drones we are talking about card computers very small very limited on power so the other solution is game theory game theory is great because game theory has high efficiency and low complexity so this can be easily implemented on a smart contract and the way we thought about this problem was using an utility function basically this function takes as input the position of all the points of interest in the system the position of every drone in that particular moment and also the idleness of every POI which means the time it took since the last drone visit to every POI and then by minimizing this utility function a drone can decide which POI to visit next but then there is a problem and that is why how the system is sure that a drone visits a certain POI so we brought two solutions a proof of visit or a proof of work the proof of visit is intended for smart devices intended for electronic devices devices have computational power for example a beacon that can communicate with a drone can see that the drone is there and they can actually they both sign a transaction and publish it to the blockchain the drone visits a certain POI but for example imagine that I want to navigate my drones around the forest around the tree how I'm sure that my drone visits a certain tree this is very simple to implement as well by using a proof of location the proof of location can be implemented by proof of location service based blockchains that are available right now I'm not going into very deep into this topic because it is out of the scope of my presentation but is a topic that is very well known and there are many services that provide this kind of proof of location already so talking about the smart contracts which smart contracts do we need to apply in order to make the system work first we need to have the system manager this is not a smart contract it's just the entity that is running the system it can be a company it can be an individual or it can be a foundation for the open source project but they need to run three smart contracts and the first one is a subscription if I have a house and I want to basically to rent a service to patrol my house I need to pay some tokens and these tokens are included in the subscription subscription smart contract and then there's the decision smart contract and this smart contract is basically the implementation of the algorithm that I told you before to make sure the drone computes the correct POI to visit after because the drones can be for example owned by a company or can be collected from individuals we need to make sure that the drones go to the optimal point of interest and why because in the end we have a reward smart contract basically is paying to the drones every time they visit the POI either by a fixed fare or by a fixed bonus of the POI and because we are paying tokens to the drones a malicious zone could just fly around the closest POIs just to collect as much tokens as it can so that's why it's important to have the decision smart contract as well and in order to embed everything in the drones as I told you we're embedding these in the small card computers in the drones itself so we want all the communication to be handled by the blockchain and you want every UAV to run a blockchain node and this is how the system looks like we have a control a control box basically just to handle the flight controller and we have the navigation the navigation is just to decide for example from this point of interest to the one the navigation basically it handles the path and the decision box actually decides which POI to visit this is the implementation of the smart contract that I told you in the slide before and then you have all the communication that is handled by the blockchain in order to select a blockchain that works with these multi these UAV heterogeneous devices and so on it's very hard to implement it with a blockchain like for example in Bitcoin a regular blockchain because this is very CPU intensive and we are dealing with very small cards these cards cannot compute the cryptographic puzzles that are proof of works that cannot mind blocks as a very large cluster so our approach was to go with IOTA and IOTA they propose a very different approach it's not a regular blockchain it's a Tangle it's a directed cyclic graph and this graph has many interesting properties one of them is that it doesn't require miners because the way it works every new transaction indirectly is attached to two transactions so it directly approves two other transactions and indirectly all the other transactions that are connected to these two and it's already non-cryptocurrency we can buy IOTA tokens right now and since we are trying to implement a service they handle payments and decision we can implement both the smart contracts and the payments on the same network so this is very very interesting and applies very well to this kind of project another advantage of IOTA is the way they handle the partitions for example on a regular blockchain if we split the blockchain we cannot reattach it without deleting one of the sub chains in Bitcoin for example the chain that lasts is the longest but in IOTA we can actually do a partition and the way it works and the way that we propose is for example when you launch a campaign we launch in one of these transactions and we there settle every parameter of the campaign and then the nodes which are built in the drones they will only process the transactions related with that campaign with that mission on a sub-tangle and in the end of the mission we reattach this tangle to the mainnet so that indirectly every other node will approve the campaign and we don't actually waste resources of the drones approving transactions from IOTA mainnet during the campaign and in order to see if it's possible to run an IOTA node on a small card computer we have Odroid XU4 it looks like a kind of Raspberry it's very similar it's a bit more powerful but it's quite similar in terms of characteristics and in the X-axis you can see the transactions per second TPS and Y-axis the CPU and RAM conceptions these were using the software that the IOTA foundation provides it won't be the final software but the IOTA node because it's still in development they plan to launch it in April next year but currently they have a test software that has a module, a spammer that we use in order to have these graphs so basically for every for example for the case of 30 transactions per second we're running for a long time and then we took the average and in the end we obtained this quite linear behavior and this can actually run both the control flight control and the blockchain in the same card we also ran tests on our algorithm the the game theory algorithm that I showed you before this is an image in our lab we run with three drones on the left side we can see the POIs they are the basically we divide in a grid of 5x5 with 25 points of interest and you can see in blue there are the areas that were recently visited and in red the areas that are visited they were not visited in a long time and the drones cover this was basically to validate that the drones will cover very efficiently they won't last they won't leave like an area for a very long time without a visit so finally I would like to thank you very much for your attention feel free to ask me every question that you may have wondering on the iota network given that it can split like that and then come back together what actually defines the main net as opposed to a peripheral net if you can have lots of these forks but you are saying that they can come back together and then be recombined and that how is the main net defined relative to these other net so basically the main net is where the majority of the devices are connected and is the network supported by the foundation where the iota tokens can value actual dollars in this image is just a small partition on the huge network so here exactly only after we are touching we can we can pay tokens to the drones and they will value some money because in the partition itself let's call it a sub-tangle they won't value any money because they are not connected to the main net I was just curious about your experience in terms of trying to implement the UIV with iota compared to with Ethereum I think that one of the I think one of the benefits of iota is that it is supposed to be more lightweight and you will be able to put the node onto more of a like a sensor or a single board computer much more like because of the lightweight of it I was just wondering whether you also have tried this with Ethereum as well in terms of Yes, currently in our lab we are doing work with Ethereum and with iota as well and what we notice is that it is very very the iota is very iota friendly and for example you can run the card that we are using is 32 bit card and if you try to run Ethereum the majority of libraries they are not compiled for 32 bits they are not compliant to the ARM architectures and so on iota is way easier to implement and for example in order to run a blockchain like Ethereum we would need to somehow decrease the complexity of the proof of work to be able to run in these small card computers but due to iota design in the way it doesn't need any miners we don't need to actually trade security for being able to run the network only on the small card computers One more follow up is have you tried running like a client node on the UAB instead of using it as a full node Yes, we tried but the whole purpose and this was a decision that we took in the beginning was to try to have a completely independent network of nodes basically they run a full node embedded in their software they don't need any external computer and external servers to connect to the network because for example if you want to control a forest and you have no internet connection since you're doing a partition of the network the drones they can communicate with each other and then in the end we attach their information to the mainnet so we don't actually need to have the internet connection at all time which makes the system more flexible and operate basically in every scenario Yes, you can use the ground station but in our case we it was just a design decision we decided to go just with basically drones we wanted to be sure that it was possible to implement and we didn't need to rely on ground stations or any other equipment Maybe one of the best ways to conclude this paper for example is to give this analysis for example he was just asking about how IOTA could be compared to Ethereum especially because the previous works are based on Ethereum and what are the pros and cons because I also know that for example IOTA hashing function has been criticized in the past so it's good to have this comparison and if the advantages are way over the disadvantages maybe you can claim that there is a new way of doing experiments in this field, right? So that would be really nice Thank you for your question actually we are currently working on it but when we wrote the paper we weren't really sure if we were actually doing the comparison but we are right now we implement the Ethereum and we're waiting for in order to implement the final version of IOTA but yes we plan to publish in the final paper the comparison between the two networks and we're not claiming that IOTA is better than Ethereum but just in this case, particular case we think we believe that IOTA is the best option Thank you I want to ask just a last question. Can you give a brief explanation about the costs of IOTA how much cost the transaction? Actually there's no fee associated with every transaction because the way it works is sorry I see these light gray blocks they're the tip blocks and when you want to append a new transaction you connect your transaction to two tip blocks at least usually it's all these two transactions directly connecting and approving these two transactions so there's no mining process because basically you do a small part of the work there's no need for external miners so you append, you approve two transactions then another transaction comes and approves yours and when the network has a high number of transactions the cumulative weight and we'll increase the trust in your transaction and that's the way it works, that's why it doesn't have miners and it doesn't rely it's very scalable actually the performance increases with a number of new transactions and there's no fee associated with the transaction Thank you Dear colleagues, my presentation is the last one about touching about the articles that were already started to talk about the robot painter and I will explain more details in this presentation what we did and why the new approach what we are promoting today like Robopreneurs the separate individual economical agents it's a really interesting topic not only from the technical sites but also for researchers and the future development and ideas how our world will look like just a short outline I will explain all the steps how we are making the work for robot painter and show the decentralized applications and details about the tractor planning painting drawing and so on and show the several experiments what we did some ideas about how we develop this project in the future actually the common workflow right now looks like this we are starting from the auction we are opening the auction on the decentralized application about who wants to buy this picture there is a picture the first picture is defined it's what translated from the hashtags from some social networks like twitter instagram and so on after that we are collecting such several of these auctions results and checking what the price was for every picture and use it for the future steps during the auction robots start to paint the picture and people can vote by the coins what the price is fair for that picture after finishing the auction as I showed previously the smart contracts also created and the rossback file put it inside and the owner of this picture put it also in the smart contract and when the smart contract is finalized that means the owner should get his product his picture how we synthesize this initial source for the picture for the hieroglyph would be drawn on the paper the first implementation we did the twitter search with the hashtag because it sounds crypto and after that we are creating the list of the words that's related with the hashtag in twitter and choose randomly the keyword for that set of the words and after that translate it the next step it's creating the picture based on the image of the hieroglyph we convert hieroglyph to image and the next step we skeletonize it we find the bounds of this picture trying to clusterize it maximize this with open cv applications and several additional libraries and after that we are getting the path what path should be for the robot which draw in this picture and when we have the trajectory when we have the path we can follow it using usual approach as direct the manipulator tasker so on here is the software and hardware what we used for drawing and communicating with the blockchain what's connected with the auction mechanism and here is we sensing what's happening on the picture on the that we look at the high with the death camera and getting the image from the usual camera and trying to get the information is it okay is it correct following the trajectory or not we used the real sense here the next thing the information from the sensor going to the main planning software to computer or control for the robot control and after selection and image processing it's starting the trajectory execution there is as usual local task planner and task execution and there is a we used the KUKA robot for that there is a special software they developed to connected with the robot operating system it's special interface and this interface can give the direct control to the drivers of this robot here you can see how looks like the interpretation of the hieroglyphs for robot this is the scheme of the auction we are starting from the initial point and painter send the transaction that he started the process of the painting and you can participate in auction to make a bit for this picture and we are collecting the bits during the one day 24 hours and when it's finished we are choosing the maximum price for this image and finalizing the smart contract for that deal just covering all the information with the smart contract and creating the new liability smart contract and finalize it this is an interface web interface how it looks like soon we will have more experiments and I hope we will ask you to join to participate in this process to collect more data because right now it looks sorry oh does the video work no oh okay yeah that's what to show and here I want to give just a more explanation about this is a robot this KUKA for it's created for soldering mainly but we equipped it for painting I think it's it's not a bad thing for this robot to be a painter not a solder and here is demonstrated how the initial information about the keywords from Twitter collected and after that we just translate this word to the hieroglyph and putting it searching here for the bounds of this picture and after that when we finish the search we just sending the trajectory for robot and here is the process of the painting how it's look like during the painting process of participants making the beats in decentralized applications and who will give the maximum beat will get this picture right now we are thinking about not just just taking the hashtag and draw it we want to add some right now we are on the way to adding some AI elements to this robot and our topic it's robotics and AI and here we start to work with the information from Instagram and the process will be look like this we are posting to Instagram some picture and collecting information about who likes this picture and when we collect the information about who likes we are checking the areas of interest and based on the information from the interest area we are synthesizing the new the new word the new data and after we know the area interests for participants we can this visualization of such things there is like purple it's not relevant not so relevant topics but yellow it's one of the hottest one of the closest topic what is really what is important for users who like this picture who like this follow this Instagram and using this data and combine it with the data about the price from the previous auctions we can synthesize in different proportion some new words right now it's a words but in the future I think I hope it will be like a full picture okay that's all thank you a lot any questions if no coffee break oh yep what is the price the highest price was just let me 0.7 efforts yeah for the picture it covers all the expenses for the I mean for the drawing process not for the robot of course okay any more questions yeah oh okay so what I find most interesting about this research is the fact of course that you have a new loop in which like you put like the robot not only in the labor part but also in the capital but also like what I think is very very interesting is the fact that you could have like some autonomous entities you know for example with only one robot as the employee right so as you have like entities for example trading in the stock exchange with an algorithm and that is an entity per se now you can have corporations in which the only real employer is a robot right so we have seen many cases in which especially artists are trying to think about what happens if you as an investor yeah can put some capital upfront in order like to set up the system but then is the robot through doing good and understanding what are the trends and getting more benefits out of the action to get some benefits that could pay back this initial investing effort right so once this initial effort is paid at some point in time the robot can buy itself out right and and is interesting you know what comes like there you know so for example people here at MIT are also thinking like about this one of them is called DASA is a guy that like will come at like a five like in order to oh 430 sorry in order to give out some ideas about computational law right and how this thing could go right but yeah it's interesting like food for thought maybe you have a question sir about three weeks ago the US patent and trademark law has issued a in the federal register a list of 13 questions looking for information about how to apply a trademark law to intellectual property like for instance your drawings that are generated by autonomous systems yeah you should all contribute yeah yeah yeah yeah maybe we should be talking to these people yeah so okay I think yeah the paper section is over so now we have like some coffee I think that the industry like session will start at 3pm so we have like 15 minutes you know so yeah let's let's get back here 15 minutes thank you okay hi everybody welcome back from the coffee break I like the coffee break because after lunch you usually have a glucose down and so I know because I teach a lot of people and I at 2 o'clock 3 o'clock they start to right after lunch I'm going to be talking about a specific topic called digital assets or digital investment assets and discussing where this whole piece is going and how it's converging with artificial intelligence and our blockchain there's no robot talk here I'm not talking about robots maybe at the end I will tie it in to some robotics and we'll see so a quick a little bit about myself I've spent over 20 years in technology I teach graduate level blockchain artificial intelligence and machine learning at a bunch of different schools in New York City we actually flew and me and my team flew in this morning from New York City at Columbia NYU and CUNY on these topics I run a company called Chain House we do blockchain AI advisory we're building some products in the space I'm a coder I spend time at night coding I've been doing that for over 20 years we do in terms of our services we do education on blockchain we do events I run one of the largest blockchain meetup groups in New York City I'm going to show you some of that and we have a division called Phytoscent which is decentralized finance and we're building some products in that space one of them is one of the things I'm going to be talking about today which is digital assets and we're looking for co-founders if anybody's interested please hit me up these are some of our customers that we deal with these are some of the people that we've educated companies that we taught blockchain and AI and we just wrapped up a project with the World Bank we did a project where we took Haiti we're still in the process of doing that and put mango farmers on the blockchain we helped design and architect that system and we're also involved with a company that came out of MIT that is building a blockchain and AI company that's building a mortgage platform on DLT and then we'll move to mortgage trading on the DLT which is effectively a digital asset so those are the things that I'm involved with I'm also writing a book on the core of blockchain for O'Reilly which should be out sometime in maybe January-February I have about 80% of the book done and I run this is the meetup group if you're ever in New York City I run a fairly large where over 5,000 people very active blockchain AI and data science group the benefit for me for doing this is I get a ton of market intel we learn a lot about what other people are doing we have a bunch of events coming up we actually have an event on AI in about two weeks so if you happen to be in New York City or if you are, I did see an art presentation if you'd like to talk about presenting please let me know so I want to talk about I'm going to set some up front baseline and then I'm going to talk about digital investment assets where it's heading and where there may be commercial opportunities for people that are looking for commercial opportunities first in the blockchain space there's a significant amount of noise you have people that are posting things like this this is Nouriel Rubini he's a professor at NYU he's one of the leading economists in the US he called the 2008 crisis he called it 2006 and 2007 and this is pinned to his twitter account so blockchain is a failure and to some degree there is some truth to what he's saying and then maybe there is a little bit of attention grabbing here and that right? on the flip side you have people who are advocating a different picture or thinking that there's going to be a different picture and somebody called the pump who believed at one point in time that bitcoin would hit $100,000 by the end of this year and obviously that hasn't happened and then he says the secret though is that the prices don't matter I don't know what that means I think that's all that matters that's my view so yeah but so all of this is happening me, I as a business and I as a teacher and educator and as a professor and all these kinds of things I do I try to avoid this stuff and I try to find the diamonds in the rough like where are the business opportunities right? so we work with a bunch of different companies and we start to see patterns and trends around where there is money to be made so there is a quiet storm where people are adopting blockchain where blockchain is moving forward it's not very sexy but it's occurring and that happens to be in the enterprises right now so if you look at some of the news articles that have come out just BC just came out with this article they are going to be tracking $20 billion worth of digital assets and they are going to be using certain blockchain technologies I want to cover that a little bit and so that's not a small amount of money it's not a very large amount of money when it comes to GDP or market size but it's a significant indicator in terms of where things are headed and then there is another and you see here another FX transactions about $250 billion worth of FX transactions that's a drop in the bucket of total FX transactions if you look at the Bitcoin market cap that's about $130 billion and they trade about $20 billion a day so $25 billion and FX is not a big deal but this is just the beginning this is the starting point where the banks are starting to look at this and what are they using what kinds of technologies are they using and they are using blockchain but it's not typically the blockchain that you might automatically think these are some of the chains that they are using and these type of blockchains evoke emotions in people certain types of reactions and these are typically some of those justified but these are the blockchains and they are getting adoption and people are buying licensing fees paying licensing fees for or deploying out into production so there are systems that are going into production that are based on some of these now whatever your opinion is on Libro and things like that I try not to take it an opinion on any of these I just look at what the situation is and try to find what's factual and what's not factual around it but I think it's important to understand that some of the technical terms around blockchain are not translatable or understandable by business people right so you say immutable you say consensus you see these kinds of terms their eyes will start to glaze and what I try to do because we talk to a lot of executives they say blockchain is a platform for digital exchange and you know you saw double spend and all that kind of stuff economic agents who have incentives and disincentives who get involved with each other what those incentives and disincentives are whether it's proof of work whether it's your mining or things like that is a separate question and then the blockchain that we're specifically talking about is enterprise blockchain is more about mediation than disintermediation how do you get people to work together as opposed to getting rid of the middleman and so that kind of resonates with some people and then some people get religious on me and get angry but you know it is what it is so and then there's a battle between and I was here at the I spoke at the Bitcoin conference that was here at MIT six months ago and that was a bit of a ruckus because I said the permission world and the permission less world is almost indifferent they're converging so if you look at for example a blockchain called quarter DLT called quarter it's a quote-unquote permission chain but they have a permission less or a permissioned version of it that's open to the public so you can get permission into it as long as you identify who you are and things like that and if you're doing financial transaction that's useful because KYC, AML and all that kind of is baked in and this is happening everywhere if you look at Hyperledger which is donated by the Ethereum Alliance this is an Ethereum client designed to be enterprise friendly and it can be both permissioned and permission less in both use cases and you see this as a trend this is a trend we're going to start off as permission and we will expand and become permission less eventually what does that mean as things start to expand if you have a large number of participants in a permissioned system it effectively is a public system you just have to get permissioned into it like getting a library card and then the other question is of centralization even in the Ethereum world and the Bitcoin world and I've referenced the paper here and I'll give you a link to the slide deck later these worlds are still grappling with decentralization if you look at the paper here a ton of power is concentrated among a small number of blockchain participants so decentralization overall from a pure point of view from a purest point of view is still somewhat elusive somewhat of a pipe dream so it's kind of a shades there's shades of decentralization and decentralization and I personally try to avoid that debate which kind of happens quite a bit especially in academia people take really strong positions and focus on some of the things that really really matter here's another paper that refers to the trilemma of blockchain which is you can have only two of the three you can have either self-sufficiency rent-free meaning you don't pay for transactions or it's resource-efficient so there's no mining costs and things like that you can have only two of the three so which of those two do you pick depends on your use cases your business case so permission and permissionless world the two worlds are converging to the point of little indifference there's a little that is different between the two you've seen five years from now the public blockchain world will become a little bit more permission because of regulation and things like that and the permission world will become a little bit more open and it's kind of converging and what matters and especially in the things that we do is does this technology move civilization forward does it move a use case forward whether it's permission or permissionless or things like that does this move it forward does it solve a problem and then we adopt it so that's kind of our view now these are rates transactions rates for blockchains I think most people here are familiar with the transaction rates for Bitcoin and Ethereum relatively slow like XRP we saw IOTA today are significantly on the high side if you look at Visa's annual report and see what they do in terms of transactions this is their 2018 annual report 124 billion transactions for the year they're working at a different level compared to Bitcoin doing seven transactions per second and you do the math it's a drop in the bucket and their capacity is to be able to do 65,000 transactions per second and they hit those peaks during Christmas they hit those peaks so these public chains have these issues or I call them trade-offs there are some issues that you're willing to take for certain benefits that you're willing to get and sometimes you're trying to trade-off for other things whether you go for a permission chain or a permission less chain there are certain trade-offs that you make now if you decide to make certain trade-offs will you arrive at the conclusion that you want to build a platform around let's say using a permission chain you get certain benefits there are certain advantages that you get one of the advantages is to build rich and deep types of tokens or digital assets and that's what's occurring now we're engaged with some of these organizations and this is what I really cover maybe the next 10-15 minutes number one if we assume and there is economic theory and research that supports this if we assume that a supply can create a market if you have supply not demand but if you have supply that can induce the existence of a market if that's true and if transactions per second are correlated with capacity and capacity is correlated with supply positively correlated and if the size of a market indicates how much data is emitted by that market the more data that market would emit that's true and if we agree that where there is sufficient data AI comes if there is no data there is no AI if we agree to these things then sorry my clicker is not then we can say that there is the rate of AI adoption is correlated to capacity of a market so the more I can do the deeper the transaction the faster the transaction the less fees on the transaction the more data I will produce the more likely I can have AI come along and do something with that kind of data interact with that kind of data and this is where the financial world is heading they see exactly this I can build certain types of assets I'm going to talk a little bit about that and then I can start to employ certain type of AI and there is a breakdown that it's going to go down to four different steps of how the industry is moving forward some of those steps have already occurred and some of those steps we're still in the middle of and some of those steps we can clearly see that are coming so first I'll call it errors or steps whatever you want to call it is the proof of concept error we're kind of past that error now we're moving past that especially in the permissioned DLT space people are said hey we've done the proof of concept we see that this makes sense I now want to build something and I want to take it into production then error two is people start toying around with smart contracts and tokens in every talk that you go to any blockchain event it's pretty much about smart contracts and tokens and then the error three which we're moving into now the next two years is native digital assets and machine learning apply to that and then finally AI and I don't mean AI as some of the stuff that we saw today I mean AI that's directly embedded in the blockchain not external extremely external but directly involved in the blockchain the first error this is somewhere around 2015 2016 when it started we kind of ended quarter one 2019 this is when a lot of enterprises said hey we did our proof of concept in 2018 or we're wrapping up a proof of concepts or a bunch of proof of concepts and now we like what we see with these DLTs that we're using or these blockchains that we're using and we now want to move into production or we want to build a team around building stuff that's into production at that stage there was no AI machine learning needed for you to even say you wanted to bring machine learning into a project involving a POC would require extreme audacity like what are you talking about trying to figure out what blockchain is so there was no need for that there was no real data for you to apply we're now in the phase of adoption of low hanging use cases and I had to put acronyms there like supply chain trade finance and insurance these sectors are heavily investing in blockchains now enterprise blockchain and use cases and applications we see that happening because we're getting the calls we're getting the emails I got an email today from a major bank saying hey we need to can you come over and talk about DLTs important point at this stage tokens represent something a token represents an asset or represents a right or represents a utility and that's what we think of when we think of our tokens but that's not where tokens are going to stay and a lot of the DLT projects are around cost reduction how do I eliminate or reduce reconciliation costs which is hundreds of billions of dollars in cost that are hidden in most businesses because businesses think that's how you do business and those reconciliation costs can come out people are using spreadsheets they're rekeying stuff in all that kind of stuff at this stage AI and ML become applicable so hey this is something that we can start to combine how do I figure out certain things using I'm going to give some examples using let's say machine learning and token economics the third which we're kind of moving into the next couple of years we'll see especially the beginning of next year is native digital assets these are digital assets that used to represent things but now they are exactly those things so for example I'm going to give you an example like a credit default swap you may have a token that represents a financial instrument like a credit default swap but that token is going to go away the credit default swap itself will be born on the blockchain in fact I will start to be able to create my own types of financial instruments on the blockchain we call it smart contracts but it's beyond smart contracts it's smart contracts that are tradable themselves I'm trading those smart contracts tokens in the Ethereum world are just a number and an allocation table I've got an Ethereum address and I've got a number associated with that address and that's what a token is but tokens will shift from representing an underlying asset or underlying thing to becoming that underlying thing I will now create a digital asset I can design its economic behavior so this is the economic behavior and push it out on the blockchain at this stage AI and ML become a strategic competitive advantage this is where companies say I'm going to combine the two because anybody can create tokens anybody can create digital assets but now I need a sustainable advantage and this is where AI and ML will converge with blockchain and there will be tons of data at this point sitting on the blockchain as much as there's data on Ethereum a lot of it is garbage even on mainnet there's a lot of garbage data on Ethereum there's a lot of garbage data on Bitcoin the fact that you can extract that data and mine it is of little use because what are you going to do to predict the price of Ethereum but there's not a whole lot that you can do but if you have very rich trading data I'm creating all these assets and I'm trading all types of assets you have an enormous wealth of data that you can mine and do predictive stuff with so for example there's an organization called ISDA which is a standards body that creates standards for complex derivatives if you want to issue a credit default swap you would use a ISDA contract let's say it's a template you fill out the fields in the template and boom you have a credit default swap and they've just announced that they've created smart contract templates and you can start then you start to use this to create your own credit default swap purely and natively digital it doesn't refer to a contract that's trading on a traditional market it's not a token that refers to a contract that's on a trading market but it's itself a digital asset so it's digital first maybe not even paper at all and then you see semantic analysis of the legal documentation which is ultimately training AI and machine learning models to then eventually produce their own legal documents so the ability to do semantic analysis is the first step for these models to be trained to go reverse out and produce documents themselves this is from Gartner by 2025 we'll see $176 billion blockchain market by 2030 that's 3.1 trillion that's not from necessarily from public blockchains this is from enterprise blockchains and enterprise adoption and the movement of money and movement of value through enterprises which is significant right and this is going to be the ramp towards which was mentioned earlier the digital investment assets I can design these assets I go onto a screen it could be visual it could be programmatic I design the assets I design the assets economic behavior or I let an AI do it AI then tests the asset AI then runs the risk model runs Monte Carlo right and then I click a button called publish and I publish that asset on the chain and it gets traded right what happens then is exotics exotics are these esoteric financial instruments they're not the norm become the norm meaning that an enormous amount of financial creativity comes into the digital asset creation say hey I want to create an asset that is pegged against the treasury but I wanted to cap it here I wanted to go there I wanted to reference that I wanted to do this so I create this really interesting digital investment asset that has never existed I can do it rapidly and then if I like it I run it through my models and if I like it I publish it and it's out on the market fairly quickly right and then it's traded and then I can apply machine learning so I can I can put a letter of credit as a digital asset a digital investment asset a letter of credit I publish a letter of credit I can do predictive analytics on the letter of credit what's my risk on that credit when do I expect it to be cashed out by the the issuer the beneficiary all kinds of things I can start applying machine learning to that that's probably the next couple of years and then we move into this other probably a little scarier world right and where AI becomes economic agents so the AI start trading right and the AI are doing the risk analysis and even the AI is doing the designing of the assets based on the data of the counterparty that they might have on the blockchain right the idea of smart contracts go away because the term smart contracts is a bit of a misnomer it actually means nothing right and these smart contracts are basically AI agents they're plugged into the blockchain right because blockchains will extend themselves and be able to invoke or be invoked by external things or oracles and things like that and smart contracts start to become basically AI agents the blockchain will become like TCP and UDPs gets pushed down to the stack just basically part of life not something that we think of consciously like we don't think about the internet consciously anymore maybe 10 years ago we did and the need for AI shifts being a competitive advantage those who don't have AI and ML cannot even enter the market because the incumbents would be significantly stronger than the new entrants and we'll start to see that and what are the agents trading agents will be trading digital investment assets so the AI creates an asset it feels like there's a market it detects there's a market it structures the asset it runs the models on the asset it publishes the asset another agent AI agent purchases the asset and then it's traded how do we know that that will happen because it happens now is algo trading and high frequency trading is exactly what happens so you have algorithms that are plugged in they just don't happen to be using blockchain because it doesn't make sense to use a blockchain and there's no blockchain that can support the types of transactions per second that high frequency trading and algorithmic trading require for example in algorithmic trading the way that you do price discovery is you flash bids you bid and you pull the bid you put up a bid you pull the bid back down you keep doing that and until somebody nibbles that's how you find your price and that's not really possible on any blockchain today but once we get there in a couple of years the blockchains most amenable to doing that are these enterprise blockchains that can sustain high TPS rates will become the place where you can start to do this type of high frequency trading and then basically the trading are automated right and from there it's an easy step towards artificial intelligence for them for these agents to start trading based on economic data that they can collect directly from the blockchain so where is this all going we are going towards a world where AI will create assets and trade assets and these assets traded would be traded on a high speed blockchain right digital investment assets traded on a high speed blockchain right when that happens maybe 5 years from now 10 years from now, 15 years from now but that's the direction that we're headed and the blockchains that support that type of capacity are going to get there faster are going to get the AI adoption faster are going to need or require the AI adoption faster an example of AI trading is this project on github called Genotech basically what it does it creates random algorithms completely random takes a let's say you know yesterday's closing adds subtracts you know divides it by 5 random algorithms and each algorithm is associated with a single bot it spawns a million bots these bots trade the bots that do well perform well based on some benchmark spawn additional bots they mutate and they spawn additional bots the ones that underperform are killed off and the ones that are spawned off are then evaluated they can improve on their performance and so this kind of work has been ongoing for some time this project's been around at least for 5 years you'll start to see projects like this get on high speed blockchains I want to be able to trade native digital assets and I want these bots to find my alpha or my the profits above the market return rate and then also getting involved in the digital investment asset space or the digital asset space are central banks, central banks use these systems called RTGS and LVTS which is these core systems to reconcile and to net out and if they're also using blockchains then there may be possibility for AIs to plug into that as well and this is a statement from the WF on how central banks are starting to position the US Fed has kind of said we're not involved but I think they are but other central banks globally have started to look at and we're involved in advising a company that's involved with the central bank as well so conclusion DIAs represent a real commercial opportunity for blockchain and AI to converge with real impact, there's real money to be made and then my robot tie-in they'll show up at your door you can't make the margin call so that's all I have, thank you I take any questions if anybody has any questions I have the slides up there, the bit.ly thing yes thank you I actually have two questions the first one is more of a design question, I'm just trying to think about how do you piece together blockchain and AI together are you thinking more about using blockchain data to train AI models although if you have a lot of data in pentabytes of data on a blockchain it may not be very sustainable from the blockchain's perspective or are you using blockchain as some kind of secure storage for AI, for example model parameters or checkpoints of AI on to the blockchain I'm just thinking about how you thinking about putting those two together so it depends on what blockchain you use a petabyte for certain enterprises and how they store data is probably not a big deal so there are blockchains that can handle petabytes or a node that has petabyte data it's not a problem for certain blockchains but to your point so these AI would mine that type of data they've been an enormous amount of data to mine and then build models off of that and that doesn't mean that's the only source of data they would use but that would be a big part of that the problem with data in the academic world it's very easy to do and I know because I'm in the academic world it's very easy to create models off of clean data in the real world to get clean data is very very difficult but what blockchains allow you do like DLT is what they allow you to do and I think there's a point I put up there is you have cryptographically insured consistent data model right all of the nodes must agree that that's the data model and therefore that helps with the data quality thanks and my second question is more about the fourth era where AI agents is a norm I think one of the risks a lot of people have about AI is like really deep nerdy models that ends up becoming a black box that makes it difficult to debug I was just wondering like given a scenario let's say that you have an AI agent that's developed this very complex structured like exotic derivatives and then decides to then develop it into another AI agent buyer through some type of complex negotiation do you think that this could be a risk that this exotic derivative structure could become something that may not be explained more interpretable if it's been conducted by two very deep AI agents yeah I think that's a very good point that's a very fair point and I think that is a possibility so today when you design like you have financial engineers that design an instrument that takes a long time it can take six months, eight months to come up with it even longer than that and then you have to go through compliance and you have to go actually before that you go through risk models you do Monte Carlos and all kinds of stuff and then things still can fall through the cracks even though relatively speaking those models are simple compared to let's say what in a model that an AI produces or an instrument an AI produces there's these correlations all these correlations I'm going to produce this little asset here now this digital asset based on these correlations that I see in the market that this will produce alpha for me and can something slip through the cracks of risk models and not catch something and potentially become a financial contagion yes and we see that in the HFT is one bad algorithm can rip apart a trading floor I have a quick question you are tokenizing the assets assuming you're using some smart contracts is those smart contracts you created or you're using some kind of your C standard or what and if so if there are your own custom contracts are you using like open sepuline are you proving for yes so when I was so era three I was referring to or era two I was referring to tokens I meant it in a very generic way it could be RC 20 it could be RC 721 it could be any kind of things the point is that if you look at a token what a token is is a hash map it's a hash table it's basically the key is an Ethereum address yeah but my question is because you were saying you were creating it seems to me probably misunderstood that you were creating those contracts on the go and in my experience creating, automatically creating the contracts that are not standard contracts it's been tough to to have it right so they have no security issues and stuff because you're coming from the Ethereum world I do a lot of Ethereum so that is a problem in the Ethereum world like Zeppelin and you have to get audited and all kinds of stuff and they bust you up and say well this is the severity that's a medium severity but if you go into the DLT world you have a lot more tools because you're using the full strength of a well established programming language or Turing complete well established programming language and so the ability to create that and the risks are lower and there may not be a cryptocurrency involved like let's say Ethereum things are not native on the chain even though the digital asset is something of value that's traded but there may not be a cryptocurrency involved so I think it's the complexity around creating a smart contract in the Ethereum world is not for one to one translatable into the DLT world even though there are complexities there is as well so your point is correct there are complexities but it's not the same as let's say in the Ethereum world the Ethereum world is just one tiny mistake that some of the best solidity guys can't catch and boom you've locked up 10 million dollars worth of Ether and boom you're done in the DLT world if somebody does a bad trade you pick up the phone and call the guy and say dude I know who you are and that trade was bad and we're going to court so there's other types of circumstances around it yeah okay thank you thank you Eduardo by the way this is my first time in Boston I came to New York back in August and I must say that it is a lot colder now but there's definitely a traditional Christmas feeling because in Australia it's summer it's hot so it's great to be here my name is Emma Jane and I am part of the Australian based space technology company Aeroid Technologies today I want to talk to you about what I believe to be one of the greatest innovations in robotics and automation over the next few years machines are going to start playing a much bigger complex role in industries and each one of our lives I also want to look into the future and convey an idea of how self verifying communication protocols modularized swarm robotics and decentralized autonomous organizations are going to change where we are now let's start with what industries have achieved and what we know so far software is crucial for communication verification and connectivity lately lots of the research and development has been around applying secure immutable technology layers like blockchain most usage of DLTs in robotics focuses on maintaining a secure log serving as a ledger storing events and validating and publishing information to the network blockchain is still in its early development and yes although improvements have been made on individual blockchains integration into the real world is still in its early prototype stage so talking about applying distributed ledger technologies into robotics the main problem that is still yet to be solved is having a truly distributed and decentralized connectivity from the lowest layers so that all of the robotic components can verify and interact with each other removing the probability of single point of failure within individual systems imagine the main components of a robotic system we have vision control power distribution communication locomotion all checked and verified by a secure peer to peer communication protocol the most challenging aspects of robotics and system automation as you would know usually comes down to the sensors because they are never 100% reliable if you tell a robot to move 100cm most likely it is going to move 90cm or 105cm so we need a better way of validating that the output information is accurate and reliable so why is this so important well often it involves people's lives and hundreds of millions of dollars let me give you an example reliance on sensor information without proper verification cause the fatal crashes of the Boeing 737 max planes earlier in the year this cost the lives of around 600 people another example where the risks are higher and the chance of failure is much greater out of space in 1999 the Mars polar lander was a mission that took over five years worth of planning and work and cost over 300 million dollars crashed into the surface of Mars after a sensor received the wrong information causing the engines to switch off some 100 to 200 meters above the planet's surface an entire mission failed in a matter of seconds because of one wrong data feed from the sensor I can stand here and give you dozens of examples but these incidents these failures they slow down the progress in fact often they slow down the entire industry there is still a long way to go there hasn't really been any memorable or inspiring missions since the 1960s when the first astronauts landed on the moon I have always had a passion for space I remember begging my parents for a telescope for my 15th birthday I remember the day I got accepted into the space engineering program at the University of Sydney and I remember writing letters to NASA since I was 10 about my ambitions to become an astronaut since they never replied I promised myself that by the time I turned 21 I would be part of the space industry I am fascinated with the idea of applying emerging technologies into space to make a change and bring about new innovation technologies like decentralized verification for machine to machine communications and operations can give a greater level of autonomy this autonomy and its capabilities are vital for isolated outer space operations and missions if we are really thinking about setting up colonies operations in the next couple of decades then we need to start seriously looking at these technologies especially when also thinking about the communication relay issues that come without space so to give you a little bit of context here every 100,000 kilometers you go from earth there is a latency of 0.47 seconds between the ground and the spacecraft I know that this sounds insignificant just 0.47 seconds but latency creates bottlenecks for the moon there is a two-way time delay of 2.6 seconds and for Mars this latency goes up to 40 minutes in fact in the Mars rover missions because of this huge latency sometimes the rovers could literally only move a couple of meters in an entire day so we can't scale these missions with the current way that we are doing things imagine even having just a few rovers or some small pieces of machinery and equipment it is going to take weeks to months to actually achieve anything useful providing accountable autonomy self verification and cluster based communication capabilities is the only way that large scale operations like natural resource mining and human colonization can take place in outer space at Aeroid we are aiming to develop and apply a verification and communication layer to the machines at the most fundamental layer we are developing software for robotics and autonomous systems our goal is to create a scalable and compliance ready software platform for machine to machine communications and operations space innovations over the past have been focused around hardware for example SpaceX with reusable rockets I believe that space hardware innovation should go hand in hand with software so we are addressing one of the key needs of creating a stable and scalable software communication protocol for outer space missions and operations we have been working for the past six months we have been looking at lightweight and low power consumption blockchain protocols we have been understanding accountability and governance in autonomous operations and also verification for machine to machine communication methodologies according to our findings some of the software architecture used in space applications today is around 10 years old these systems are highly concentrated, they are highly centralized and as you would know this brings in the idea of single point of failures can limit the data transfer bandwidth and also leave the system open to lots of security vulnerabilities if we talk about sending payloads into space this costs tens of millions of dollars right now the cost of sending around 1 kilogram into space is around $20,000 I know that these costs are reducing with the use of reusable rockets but they are still very high so similar to reusable rockets why wouldn't we send payloads that are adaptable and reusable imagine self-adapting reusable robotic modules that can connect like Lego blocks to work together to perform different tasks achieve different goals far from earth without having to rely on any communication from earth at NASA for each space mission there is a dedicated operations team by this I mean that they have to allocate specific resources and people purely for the task of watching over the machines watching over the spacecraft performing checks and balances and monitoring the machine health this is hugely expensive it takes up a significant cost of the overall mission budget and also isn't feasible because sometimes these operations teams end up costing more than sending the spacecraft into outer space itself so we really can't scale we can't do a lot of things efficiently and properly if we are always relying on the ground over the next few years we are going to see a huge transformation in the commercialization of the space industry this will not be from NASA or private companies doing exploratory or discovery missions a huge focus will be on industrial engineering resource extraction defence and tourism so imagine if we could set up mining operations on the moon or an asteroid imagine multiple machineries robotics working together without having to rely on communication or verification on Earth or systems on Earth having secure self-governing machine to machine interactions and checks and balances will give a greater level of autonomy for the operations and also take off a huge load of pressure from these operations teams IOT robotics, blockchain machine to machine economies and the space industry have the potential to generate over 8 to 12 trillion dollars in economic value by 2025 so coming back to aeroid and our machine to machine communication technology we are also looking at incorporating the concepts and principles of DAO decentralised autonomous organisations and seeing how this can apply into a machine environment I'm sure that most of you are sort of well versed in the area of DAO's but just to reiterate in case some aren't DAO's looks at the idea of running a normal organisation but in a distributed and an autonomous manner through smart contracts and mechanisms so this brings in the idea of machines performing checks and balances on each other in terms of validation and verification think of it a bit like machines policing other machines but having the communication and the verification operate on a more cluster mechanism so now you have a hierarchical system in the network unfortunately I would love to sort of go into more detail with you of exactly the technology that we're working on and the specifics behind it but we are currently in the process of acquiring two patents and as you know it's sort of very touch and go with these things so I've had to restrict a lot of what I really wanted to say and I guess that is one of the reasons why my team and I are so excited because our technology doesn't just apply into the space industry but theoretically it applies into any machine to machine operation including IoT devices and industries like smart cities autonomous vehicles and supply chain logistics before coming to Boston I was actually in Dubai over there they are very future forward thinking in terms of making their city a lot more smarter a lot more connected they even have a government blockchain initiative and just last week actually they announced their blockchain policy strategy approach for 2020 to give you one example the rodent transport authority in Dubai they are looking at implementing autonomous vehicle infrastructure so that a driverless car in the city they can pick up drop off passengers collect payments pay for tolls pay for parking act as a monetary agent there are a lot of use cases like this emerging around the world and my team and I do some work in Dubai so we're excited to really see these technologies being properly implemented going back to Aeroid and our vision we really thought about how we can affect change with what we're working on how we can show something that's really important moving forward and also inspire and catalyze the future of innovation particularly space innovation so we made a huge commitment we made a very bold move we started the lunar industrial initiative 2021 the lunar industrial initiative is our plan to send four adaptable robotic modules to the moon in 2021 to demonstrate our proof of concepts of our software communication technology so I'm sure that most of you are wondering how are we going to execute this well there are three major stages stage one we are applying our software protocol into swarm robotics swarm technology we're currently working with the University of New South Wales robotics lab in Australia to refine and improve our protocol stage two we will be testing these adaptable hardware modules these custom built rovers in moon like environment test chambers so at Mount Strollos in Canberra in Australia there is a space testing facility and this is really good for understanding what changes what adjustments need to be made to the hardware and also our software protocol because I can tell you building robots for earth is very different than building robots for outer space as part of our initiative we also want these robots to demonstrate some proof of commercial viability so at stage three we are looking at incorporating aspects of project wild into our initiative project wild it is headed by Professor Andrew Dempster in Australia and also part of the Australian centre for space engineering and research the main goal of project wild is to eventually mine water on the moon right now they are looking at mining at the moon's polar craters particularly the south pole so why water well again in terms of commercial viability water is the most versatile natural resource that we found on the moon it won't only be used to resupply astronauts with oxygen water but will also be used for power generation and refuelling rockets one of the unique things about project wild is that they are taking learnings and methodologies from Australian mining sites so instead of sort of taking a space engineering approach they are looking more at current earth mining the Australian mining industry is very well established well advanced particularly in terms of the tools and the extraction techniques that they use for extracting and mining natural resources in remote isolated environments in the middle of Australia so as part of stage 3 we will also be mapping and modelling the specific course and details of the operation we know that mining water is a huge undertaking so we are also looking more closely at navigational operations for the swarm robots to perform because our software technology will give these robots better communication and better verification to send these robots to the moon we will also be partnering with a commercial space carrier like moon express we know that this is a huge feat so we are not alone we are working with the University of New South Wales we are working with members of the University of Sydney International Space Society and also the Asia Pacific aerospace consultants and a venture capital firm so if we pull this off this will be the world's first multi robot autonomous swarm operation on the moon this will be amazing this will be this will go down in the history books I'm sure that most of you are aware of the huge benefits of using swarm robots swarm technology instead of having one specific machine set for one task these benefits become even greater in rough terrain environments like the moon we're sending one robot for one specific operation isn't viable it brings in the idea of single point of failure again and also high costs the Apollo missions they cost around $600 billion in today's standards and project Artemis that is NASA's latest lunar mission that was just announced this year that's set to cost at least $30 billion so imagine if these adaptor robotic modules could perform mining operations on the moon and also solve logistical problems that will inevitably come from sending one piece of hardware or machine to the moon to perform one specific task these are the kind of technologies that are going to contribute to human colonization in outer space so if the problem is high costs time delays and single point of failure then adaptable reusable robotic modules and self verifying communication protocols is the way to go providing a decentralized self governing infrastructure for machines will give greater accountability will improve autonomy and will also enhance the communication capabilities we know how crazy how risky our dreams are so whenever anyone says that we are working on something that is precious too challenging too hard I always like to think that someone has to do it because deep down I believe that we are all explorers and we are all curious creatures it has been an amazing journey for me I am learning every day the challenges that I have to face but I love the energy and I love the inspiration my dream is to say that one day that I contributed to the space industry even if that is just 1% so it has been a pleasure speaking to you all Eduardo thank you so much for inviting me I know I had to keep it to a high level but I would love to speak to you more technically afterwards so please if you have any questions or feedback I would love to hear from you it is too crazy for questions it is more like a statement than a question so when you do it maybe you should make an announcement saying that you made this announcement here so we all remember that we were here when you made it in 2021 so I just have to say that you should push for that direction definitely the goals are very high but definitely somebody has to do it moonshot thinking let's have an applause for Emma consulting and deal with a lot of retail and CPG executives who daily ask you different things about blockchain I'll talk more about that once again just so that everybody remembers it as nice blockchain is immutable, decentralized, distributed than a synchronized database I won't spend too much time on this there has been in 2019 itself 2.7 billion in spend on blockchain solutions I'm not sure why this is not coming here and a total of 44% blockchain companies which reside outside of the US the major investments and the major experimentations happen in the financial services industry with retail just lags behind by about 5% a few of the statistics that are important in the retail industries is that they are 18% of retail and CPG companies who already started working they are all in the POC and experimental stage nothing to scale at the moment and about 9,000 projects every year over the next few years which is set to grow yearly by about 8,000 projects supply chain in the retail and CPG world has the most number of applications and the most number of POCs today a lot of new blockchain applications and use cases are rising supply chain for traceability because nowadays everybody wants to know whether their food is organic they want to know where it's come from they want to know whether the products they are buying is creating deforestation or not these things have a huge application with regards to blockchain which is possible and corporately focus on sustainability to be able to now do this the next thing which is very interesting is online marketplaces people want to know whether their products are being sold by 3 third party sellers who they are who is moving to price compression move which marketplace changes which reacts fastest and who is the first to move these are things which have huge applications which blockchain can be a fuse there is also others which is data processing and payments which I think everybody is aware of but these are some of the things which are upcoming and a lot of companies are focusing on them out of all the projects only 8% make it to finally production and are actually maintained and the reason is I would talk about the top 3 challenges in the retail sector with regards to implementing blockchain yes even though nobody in this room would confuse it there are a lot of executives who still confuse it with bitcoin there is a lack of understanding as to what blockchain really is to be able to actually convince the top management and of course everybody the fear of missing out everybody wants to implement it everybody wants to know what it is there are a lot of innovations in it but to be able to scale it it's not yet happening everybody in the every company has an innovation champion and if you ask anyone of them today they would say yes we have a pilot running in blockchain we are going to set aside budget for it in the coming years but that year has still not come there is also a lack of digital regulatory body which is in place and thus there is no network effects to be able to actually scale this there are too many different consortiums there is the IBM food trust which is taken into consideration with about 10 of the largest food companies there is the hyper ledger fabric and there are many others where in they all form different consortiums so to be able to actually get a scalable solution is difficult the main problem for implementing would be scalability in retail three things matter performance privacy and ease of use performance with regard to processing of payments and I think Jamil had given you a rundown of the transaction process so I won't go into that but I think the user is not even an average process is about 65,000 transaction per second so blockchain either Ethereum is not up to mark even the new other ones like Corda etc. still have to scale up to be able to process at that speed programmatic advertising the different nanosecond decisions that go into loading a page on Google with advertisements with the other companies and the other companies that actually get that all working takes a lot of computing power and energy which at this point we are not there yet privacy with respect to the new regulations of the European GDPR wherein we cannot store consumer data we have to be very careful about how we store it how we share it that is something which takes into consideration where blockchain can sort wherein they actually make a new business model about privacy and to be able to track anonymous users on Bitcoin and other chains so this is something that is between Microsoft, Intel and a few other companies wherein they use the trusted environment to be actually able to keep your data private once again ease of use switch which is a company which is an application called speed and to be able to it's like a virtual wallet to be able to actually use gift cards and select different gifts online it's basically helps you between transacting between traditional and cryptocurrency this is just lately in the market it's not up to scale but it's something wherein you sell direct to consumers and of course efficiency related to the energy and consumption of what we actually use a few internal obstacles that companies face whether evaluating the cost benefit analysis or whether convincing decision makers are some of the things that companies really consider today to be able to see it as an impediment to actually implement blockchain there are some use cases in POCs which are in production for example traceability McDonald's used it to be able to track with the IOT sensors the transportation of food so that when the temperature decreases when you're actually transporting chicken it would be sent to the through IOT sensors to your database and then to be able to actually track that so that you know and you reduce spoilage Walmart also did something similar to traceability from origin to a scale with regard to deforestation in that aspect loyalty programs is something that companies are also experimenting with Singapore Airlines is doing something with the hyper ledger fabric in which Microsoft is part of but once again these are all in the infancy stage digital identity this is something that is part of both financial as well as retailers are looking at with regard to having your own digital identity and to be able to use it creating your facial recognition or a thumb print this is also used in the retail sector when companies like beverage in the industry like they want to sell alcohol online and you need to validate the user with respect to age etc so this comes in handy a lot with regard to that Alibaba in China who is using I would say China is the leader in analytics and they are using they have actually piloted their online luxury pavilion called team all in where they actually use blockchain to track fake goods which is as you can see a 461 billion dollar industry in China being one of the most produced of fake goods so Alibaba is actually using a lot of their own cloud based blockchain services to be able to combat that the China is also one of the largest countries with respect to filing patents within blockchain as you can see about 49% come from China this is a real world use case which actually happened in which a large toy manufacturer they wished to have a blockchain based digital identity what we did was save their identity on the website, on the phone wherein it had a private and public key then they were able to scan a QR code once they log into a URL and then you could actually get through to whatever URL you want to this is within the enterprise and they didn't want to go public with it they just wanted to test it within the enterprise and then move to their suppliers and customers etc you would think this would be the solution that they had asked for the product architecture is basically based it's pretty simple we used a blockchain service and we also were able to exchange with the SAML tokens to be able to actually access the URL and provide through identification your access to the login page however once we presented it then the challenges came into place wherein they had more questions where do I have to maintain two separate systems is it cost effective can I access non-samal applications if I do that then why do I need blockchain is it really secure this is what I was talking about earlier I was talking about having a top-down approach or understanding and with respect to prioritizing security what we had to actually do was integrate this with an open source and actually redesign their VPN to be improving including only the blockchain which as you see is a small part but you actually have to do the tunnelling etc and then kind of basically replace your Cisco VPN with regard to that so this would be integration with other applications to actually be able to pilot blockchain there are a lot of technical innovations coming up there are a few things which people might have talked about something which is the blockchain as a service wherein companies can now just call an API rather and include it in their own networks there is hybrid blockchains wherein you can use public or wireless private you can have the transparency of a public blockchain but still have the security of a private blockchain a federated blockchain is different in the sense that there is a federation wherein few people are identified say from different companies or different people to be able to actually validate or give consensus to the data interoperability as many people have talked about the different types of blockchains that are available in the market so to be able to transact from one to the other and actually make a seamless transition for the public is something that is happening and people are working on it to be able to come back and it will happen in the future Ricardian contracts which is the new version of smart contracts for example it is actually a handwritten contract which people are readable and then converted into machine language through blockchain tags this is something that if for example the person is insolvent or the person the deal does not go through due to some reason this can then be tracked and it would not be executable which definitely is something better than what currently smart contracts have with regards to its limitations and finally stable co