안녕하세요, 여러분. 안녕하세요. 저는 성연입니다. 한국의 대학생의 PhD 학생입니다. 저는 체스러스에 반영합니다. 이 학생들은 시큐어 ECDSA 인플리멘테이션을 제공할 것입니다. 이 학생은 성연, 님들과 성민의 시옷과 함께하고 있었습니다. 이시드 S.A.는 디지털 시그니처 스킨에 대한 리플리젼테이티브 디지털 시그니처 스킨에 대한 엘리티컵 크리프트 그래픽이 있습니다. 이시드 S.A.는 디지털 시그니처에 대한 중요한 롤링을 제공하고 있습니다. 이시드 S.A.는 시끄리티 서비스의 wide variety of security services. 이시드 S.A.는 RSA와 speed and memory-compared strength, thus it is prepared to be used in constrained environments such as smart cards. On one hand, size-channel analysis is known as practical means to break a crypto system. Although such a crypto system is designed to be secure theoretically, it causes size-channel leakage such as power consumption, electromagnetic emission, and timing when the crypto system is executed in a real environment. Since such leakage are called depending on a secret, attacker can recover the secret by using the leakage. Thus, it is well known that crypto system must be implemented securely against size-channel analysis. However, the signature implementation might not be trivial. Also, it is needed hard work constantly because another attack might be appeared such as this presentation. Next, I will show the overview of 이시드 S.A. sign algorithm and size-channel analysis against it. Let me explain 이시드 S.A. sign algorithm first. The following is a brief version of 이시드 S.A. sign algorithm. First, if a model key or non-sk is chosen randomly. Second, scalar multiplication kp is computed. Then, signature is computed through long integer calculations. In this procedure, scalar multiplication and long integer calculation trace secret key d and non-sk. If these operations are implemented naively, then it works depending on the secret values, and it is reflected in leakage such as power, em, or timing. Size-channel attacker can recover secret from such leakage. I will present a few of size-channel analysis against 이시드 S.A. sign generation as overview. Size-channel analysis is divided into single-trace attack and multiple-trace attack depending on the required number of trace. Let's first show single-trace attack. S.P.A. is a simplest side-channel attack. Here is a power consumption trace of scalar multiplication as a representative example of S.P.A. Since this trace has two distinguishable patterns representing point doubling and point addition, attacker can identify secret immediately by identifying such patterns. To counteracting S.P.A., scalar multiplication can be implemented by performing regular operation like this, using double and add or raise algorithm, or using only unified point addition. However, advanced single-trace attack, collision attack, can recover even protected by such countermeasures. There are several collision attacks, but here I will introduce only H.E.C.C.A. and Rosetta. Scalar multiplication has two core operations which are point doubling and point addition. DG point operation are based on finite field arithmetic. Also, each finite field arithmetic is implemented based on long integer arithmetic. Thus, single-point operation can be separated into multiple-word arithmetic. H.E.C.C.A. and Rosetta exploit the collision characteristics between base arithmetic of target point operation. Attacker can know whether collision occur or not by comparing two sets of word arithmetic of target long integer operation. With this characteristic, the attacker can discriminate secret scalar. On the other hand, the other kind of side channel analysis is the multiple-trace attack. This class of attack uses statistical method for finding secret. Like S.P.A. in single-trace attack, D.P.A. and C.P.A. are representative multiple-trace attack using different sub-means and correlation as a distinguishing list respectively. So called HMP, hidden number problem is the other representative multiple-trace attack. If the attacker can get partial information from scalar multiplication or long integer operation, such partial information can be converted into the closest vector problem related to secret key. Then, the attacker can solve using solver algorithm of lattice problem, such as LLL lattice basis reduction or Babay's realist plane algorithm. In this talk, our attack is a new multiple-trace attack, but use the collision technique for sub-trace clustering. Regular table-based scalar multiplication is our target algorithm, so I will introduce more detailed. Regular means that scalar multiplication perform an identical sequence of point operation independent to scalar. One hand, table-based scalar multiplication is widely employed when it computes over a fixed point like ECDSA's signing. It handles some scalar bits chunkwise at a time, not a single bit. Thus, it is well known that it is efficient. Fixed-based CUM, NAF-Windowing, TSM are the example of table-based scalar multiplication. Regular table-based scalar multiplication can provide no perfect security but give practical security against side-channel analysis. In next slide, I will show how table-based scalar multiplication is working. Table-based scalar multiplication consists of two processes. Each process is algorithm 2 and algorithms 3 respectively. First procedure is a preparation of pre-computation table. The pre-computation table is computed according to a specific scalar multiplication algorithm. Each entry is a consequence of scalar multiplication on corresponding specific scalar. Second procedure is a scalar multiplication using the table. First, index sequence KS is computed for inputed K. This sequence consists of low index, which of entry for referencing entry in the table for loop. In the main loop, two operation is computed. Appropriate doubling is first computed according to function WS. And entry in a column corresponding to the loop is loaded and accumulated according to the index sequence KS. I will explain how scalar multiplication is work by example. Let's assume index sequence K is given according to inputed scalar K. Each component of KS represents a low index of each column for referencing table entry. Like this, each entry is accumulated according to KS for each loop. This procedure can be also presented as an expression as follows. And expanding this expression, we get a linear expression of the level to entries. In here, W is a doubling-related term, and T is a chunk of scalar-related term. This can be interpreted as each entry reference has an effect same weight. Now, I will explain on Abelky recovery hotel. This attack requires two assumptions. First assumption is that WS is a function of index J. Simply speaking, doubling operation depends on your loop index. The second assumption is that side-channel attacker can get sufficient trace on multiple ECDSA signing with fixed-private key and pre-computation table. This can be considered as common sense in view of multiple trace attack scenario. With these two assumptions, our attack can recover secret key by exploiting only collision characteristics between unknown entry referencing. In this slide, I will explain concept of our attack. When multiple ECDSA signature generations are performed, attacker can collect trace on scalar multiplication. Each trace occurs during this below expression is computed. Trace include leakage on each entry referencing. We use this leakage. With visual inspection or some side-channel analysis technique, attacker can extract sub-trace related to each loop or referencing table entry. Then, on two sub-trace corresponding to the same loop, in other words on vertical sub-trace, the attacker can distinguish whether the two vertical sub-trace is on referencing the same entry or not by collision attack. This can be possible although there is no information on the table entries. For all vertical sub-trace on each loop, attacker can group and label it by pairwise collision attack. Let's name the label sequence as collision information. On one hand, ECDSA signature expression can be converted like this. Note that attacker don't know information on nodes. However, if two collision information has same group label in same index, this means each nodes has the same table entry as your component having same weight. In short, collision information is a relation information between nodes. Thus, if attacker can find linear dependency of nodes only exploiting this collision information, attacker can recover secret ID. Next slide, I will how attacker can find linear dependency. For the convenience of explaining, we consider 3x3 pre-computation table as an example. Attacker has no information on the pre-computation table, but by means of side-channel analysis, the attacker can easily guess secret parameter like the size of the table. Upper mentioned, each trace includes a leakage on table entry referencing. Attacker can cluster sub-trace vertically and get collision information. Each collision information present how nodes are related. Attacker don't know real value of entry and low index from collision information. However, attacker's goal is to find linear dependency of nodes only using this collision information for recovering secret key. Thus, with this setting, I will how to find the linear dependency in next slide. Attacker has no information on the relation between different group labels. Thus, we consider each group as to be independent. For that, convert vertical group label in one-heart representation. Since the pre-computation table has 3 rows, a label is converted into 3-dimension one-heart representation. So, in this case, collision information is transformed 9-dimensional vector and call it converted vector. Then, the value of converted vector means that how many corresponding entries in the table is used for constructing nodes. However, attacker don't know how each component of converted vector map the table. But no whether same entry is included between nodes or not with this converted vector. At this time, if there is converted vectors only one more than the dimension of vector space, there must exist a linear dependency of the vectors and the attacker can find a linear dependency by Gaussian elimination. Then, linear dependency of converted vectors is equal to linear dependency of nodes. Therefore, attacker can know a linear dependency of nodes resulting zero. Finally, from this, attacker can recover secret key by simple algebra. Furthermore, if attacker find the basis of converted vector space, then all table entries will be founded but without index information. As I have mentioned many times, this attack can be possible even when there is no information on entries by only exploiting collision between side channel leakage. But in current, there are some limitations. For finding linear dependency, collision information must have no error. If error occurs, attacker cannot find meaningful linear dependency. Thus, if error can be possible, current only solution is doing trial and error process with sufficient flow of trace until success. However, clustering error can be possible due to signal to noise ratio. I will show the probability of error is significantly low in ideal environment. The ideal environment means that signal to noise ratio SNR is so high that side channel leakage clustering algorithm is working well. So, set the leakage property. Let consider leakage is loading entry of pre-computation table. Then, the entry is the coordinate of point Kp. Since the coordinate of Kp are determined by scalar K, for convenience of explaining, let's assume loading entry in table is just loading scalar 30 to bit word wisely. Also, let's assume hamming weight model. Then, the target leakage consist of 8 points. In this setting, error occurs when different points have same hamming weight leakage. Thus, we confuse the probability. First, the probability of two hamming weight of the two different words being equal is the below. Then, when two different entries are chosen, the probability of two leakage being equal is the below. This probability is quietly low. Thus, if SNR is sufficient, then our think must success. Next, I will show our attack is simply applied to fixed-base comb and TSM as case studies. First case study is on fixed-base comb's color multiplication. It is a representative table-based color multiplication. For the shake of simplicity, we consider original version of fixed-base comb method. Fixed-base to comb algorithm is not in here. Please refer to paper for the algorithm. Fixed-base comb's color multiplication for only one point doubling for loop. Thus, Ws is a constant function output only two. And since fixed-base comb using the same table during the main loop, let's consider the original table as a single column in our setting. Then, this can be interpreted as our attack straight forwardly. Then, according to the security parameter of fixed-base comb method, we can compute other parameters, especially the dimension of converted vector. Thus, from this, we can determine how many traits are sufficient to succeed our attack necessarily. Second case is TSM's color multiplication. This algorithm is designed only for counteracting single-trace attack. With different to general color multiplication, TSM have output k and kp. In other words, TSM cannot compute kp over inputed k. Thus, TSM has limited employment such as ECDSA signature generation. Unlike fixed-base comb, TSM is not familiar to you. So, I give color multiplication algorithm. TSM uses two pre-computation tables of color and point. Each entry in scala table is a randomly chosen, and each entry in point table is computed according to corresponding entry in scala table. TSM's color multiplication shows low randomly and accumulate corresponding low entry in main loop. This works with our target algorithm safely. Thus, our attack can be applied easily. From TSM's color multiplication algorithm, we know TSM have no doubling operation in main loop. Thus, we set ws and table size the follows. Then, as in the previous case, according to the security parameter, we can compute the dimension of converted vector and we can determine how many traits are sufficient to succeed our attack necessarily. Finally, I will show experimental result as a proof of work. We experimented on 256-bit TSM's color multiplication having 4x120a pre-computation table. With a practical view, we implemented first accumulation of scala in point just by loading it. And in remain loops, we implemented to perform long integer addition and point addition for accumulation. On chibisporto stm target microcontroller, we collect only 513 power consumption traits on TSM's color multiplication. According to our attack complexity, it is sufficient to succeed attack. This is the total power consumption traits for TSM's color multiplication. Attacker can guess security parameter easily by simple means of side-channel analysis such as visual inspection or cross-correlation. Then, the attacker can identify and extract all targets of traits from the total traits. We describe a detailed process on faithful. Please refer to our faithful for it. For prefailing collision information, we first find interest points on load leakage using Perlian's traits. In each quadrant, upper plots show real group labels, and bottom plots show Perlian's traits. Great box indicates selected interesting points for load leakage. Left upper part is about loading scala and point in the first loop. In this case, load leakage is clearly presented on Perlian's traits. The remaining parts is about sub-trace corresponding to last loop operation. Right upper part is about sub-trace for scala accumulation. Two bottom parts are about sub-trace for each coordinate when point accumulation is performed. With different parts to loop, load leakage is not clearly presented on Perlian's traits in all three parts. But because load operation is performed priorly, attacker can guess it with some trials. We had succeeded clustering with no error using this load leakage. I skipped the clustering algorithm in here. But in our paper, we provided correlation-based clustering algorithm for full class. And this clustering algorithm works well in our case. Please refer to our paper for detail again. Therefore, we finally had found secret keys through our attack. Thank you for listening. If you have any question, feel free to send me e-mail. Thank you.


Hello and welcome to the impact evaluation for social entrepreneurs workshop. I am Rachel Brophy. I'm joined today by my colleague Carly Gallo. We are both at the resolution project, which is a nonprofit organization based in New York that works internationally with young social entrepreneurs starting supporting and launching their social ventures. Hey everyone, I'm so excited along with Rachel to be giving this workshop today. We are going to try to make it as interactive as possible. So throughout our presentations, we're going to pause to have some interactive components where we'll be working through various different exercises to make sure that this is both theoretical and practical. So definitely get a paper pencil or pen and get ready to work with us. There will be some designated times where we're going to be asking questions throughout so you can use the Q&A function during those designated times. So what is impact evaluation also sometimes called metrics evaluation and learning impact evaluation assesses what changes can be attributed to a specific project or program. So impact evaluation involves comparing actual changes with expected changes, which are goals, comparing achievements to a previous period of time and are measuring against achievements of a similar project or program. So impact evaluation is directly tied to an organization's strategy and learning. So strategy can be defined as a roadmap to achieving an organization's mission in an effective and efficient way. The process and organization will set goals and then through impact evaluation, you'll understand how it is achieving those goals. Learning can be defined when an organization adjusts its programs and strategies as needed based upon the impact evaluation data that is collected. So for example, at the resolution project, we use reports from our fellows who are constituents, as well as their guides their volunteers with the organization they mentor our fellows. And we collect these reports to assess the impact that the fellowship is having on our individual fellows, the impact of their work, their social ventures is having on their target beneficiaries in the communities that are looking to work in. And we use that data to help us improve the work that we're doing. We use it to improve the fellowship. We use it to refine the programming we're offering and making sure that we're continuing to be relevant to the population that we're working with. Yeah, and to get a little more specific about how we collect this data so we ask every six months from both our fellows and our volunteer mentors when we call guides to fill out what we call a semi annual report. Both of these reports are very tailored to meet the needs of both parties experiences. Through these reports, we find out like the Rachel was saying a lot of our programmatic enhancements each report is read by two staff members, and we take a lot of time to analyze and then learn from these findings. In addition to that we also have something called a monthly guide report that we ask each guide on a fellow team to complete monthly. These reports are much shorter but we are working with over 500 fellows in 81 countries. So they help us have a really good temperature read on how our fellows are doing. If there's any red flags if there's any immediate resource allocation that we need to tend to. And these are two really specific examples of how we're collecting impact data at the resolution project. So let's go ahead and jump right in. How do we do this. This is a really good high level overview of what we're going to be talking about during the workshop. So first, setting your smart goals. We're going to talk about sending two to five smarty goals and the way that we define smarty here is strategic, measurable, ambitious, realistic, time bound, inclusive and equitable. Those last two actually may be new to some folks who are familiar with impact evaluation and we're going to talk about those soon. Most of these goals should relate to your ventures mission, and at least one of them should focus on running an effective venture. This is also a logic model logic models are visual tools for mapping how the ventures activities will lead to impact creating a logic model will help you think through steps and assumptions in your venture. When you're creating a measurement plan measurement plans are tools for thinking through the information that you will need to collect to show that your venture is making progress towards the goals. You'll also figure out how to collect it then when you're going to collect that data. And then finally, monitor, measure, learn and repeat. This will not be the only time we're saying this during this workshop planning for impact evaluation is not enough. The most important parts of the job is to monitor what the achievements of the venture are and use that data to inform how you are going to run your venture. So planning for it is not enough collecting is not enough you need to analyze and repeat. So diving a little deeper into smarty goals. Here we have an acronym and the s stands for strategic, it reflects or specific you may have heard as specific as well. It reflects an important dimension of what your organization seeks to accomplish this could be programmatically or capacity building priorities. As measurable, we can define as including standards by which reasonable people can agree on how to meet their goal. So when you're measuring something this can be by numbers, this can be by defined qualities, make sure it's consistent, ambitious or achievable. So challenging enough that the achievement would be a significant progress or a stretch for the organization. You don't want to give yourself a goal that you know you achieved last year and just repeat. That's not enough you need to stretch yourself a little you need to make it a little bit ambitious, but at the same time moving on to our you need to make it realistic, and make sure that it's relevant as well. Challenge, make sure this is challenging but it also takes into account the resources that you have available, especially if you're working on social ventures if they're nonprofits. You know, take into consideration what resources you have at your fingertips, and make sure that it's possible to track this and worth your time and your team's energy to do so. And it's probably you would think one of the easiest ones but I think it's one of the ones that people forget most often and it's one of the things that's most important. So make sure that your goals include a very clear deadline. Now at resolution we do this by providing a month and a year so by August 2021 will have achieved this but you can also go by quarter as well. But make sure you're making sure that it is time bound and then inclusive. It brings traditionally marginalized people, particularly those impacted by your work into the process activities decision making policy in a way that shares the power. This part is critical. And this might be new to some folks who are familiar with impact evaluation out there. When it comes to inclusivity for us at resolution we've created something called a fellow council. This is a junior board of fellows that we will touch base with to do temperature checks to see if we're staying honest to our fellowship. If we're actually creating strategic goals that are meeting their needs. And we often have them weigh in on what strategic goals should be shaping for the fellowship and then equitable. It includes an element of fairness or justice that seeks to address systematic injustice in equity or oppression. This one might be a little trickier and it may take you a little bit longer to think of when it comes to your programming, but it's really important to include. It's really critical to make sure that you're including it. So like we said before, we're going to spend some time now actually being giving you all the ability to jot down a goal for your project organization initiative. We're going to have the acronym for smarty here we're going to give everyone about three minutes if you don't have one in mind we've created a fictitious example for you, hand washing for health, which seeks to improve hygiene, and reduce the spread of infectious diseases by working to promote hand washing and other good hygiene practices so you can use that example throughout if that's helpful for you as well. We're going to give everyone three minutes now. Now is also a great time if you have any questions, please put it into the Q&A and Rachel and I would be happy to answer them. Alright, I hope that everyone had some time to write down a goal. I know that is three minutes is not enough, but hopefully this started, you know, getting going for that. I'm going to hand it over to Rachel now to introduce our logic model. Thanks Carly. Yeah setting goals is really important, but then being able to actually track your goals and measure your progress is equally as important. We're going to talk about a logic model. So you have your goals, and then you're looking to measure your inputs, activities, outputs and impacts. And what that means is inputs are the materials used by a program. So, for example, inputs for a code drive would include coats boxes, maybe a truck to transport the coats. Those are the materials used by the program. Activities, which are what the program does with the inputs to achieve its goal, which can include specific activities as well as strategies employed by the organization for larger goals. So again with that code drive example activities would be publicizing the drive, actually collecting the coats delivering the coats, things like that. Then you're looking at your outputs. So those are the specific products of the activities. These are often measured by numbers for the code drive like the number of coats collected. Outputs are actually very commonly reported by an organization as measurement of impact. So they're usually more a better barometer of effort, you will oftentimes find yourself reporting on your outputs or thinking about your outputs as the thing that you have done. And that's not why you did the venture in the first place, that's not why you're doing a code drive you didn't do it to collect coats, you did it to make an impact. So it's also very important when you're thinking about your goals and how the impact you're going to have is what your impact the changes to the beneficiaries as a result of your program. They're related to the outputs, but they're not the same. So impacts can be changes in lifestyle behavior skills attitudes, decision making things like that. So impacts relate to the differences in beneficiaries after the program. So with the code drive example impacts could be reduced sickness due to cold exposure. You're talking about children fewer days mist of school impacts should be used creating smarty principles. So going back to that goal, thinking about what is the impact you're trying to measure. So if we look at the logic model in this framework, you see inputs directly relates to activities outputs impacts. We have two new features here. Those are indicators of progress and measurement techniques. So your indicators of progress are the measures or metrics you use to determine whether you're achieving success. For example, again with that code drive your indicators of progress might be reduction in sickness of beneficiaries. The measure of progress must be clearly measurable and help you identify whether or not you've achieved your desired impact. And your measurement technique is how you're collecting that information. So oftentimes you'll you'll collect information through surveys questionnaires observations interviews, there are a lot of ways you can collect. This can seem a little bit overwhelming or daunting to think about. So one example we love to work through is a sandwich. So thinking about a sandwich through the logic model. Okay, so you're going to make a sandwich your inputs are the things that go into the sandwich.  These are actually making the sandwich so maybe you have to cut the bread, or the vegetables, maybe you have to cook the chicken or whatever it is that you're you're doing. That's the actual activity with the sandwich together. Your output is a sandwich. So again this is where a lot of organization stop this is where a lot of work sometimes comes to a halt and you're like well my output I made a sandwich. You make a sandwich just to make a sandwich you made a sandwich because you were hungry. So your impact needs to be, did it reduce your hunger. So, in this case your indicator of progress would be maybe the amount of snacking you do over the next couple of hours. And the way you'd measure that is observing your eating habits. So again thinking about the sandwiches a great way to sort of assess, you're not looking to create a sandwich, you're looking to eat the sandwich and reduce your hunger. So that's the impact and how are you measuring whether or not it's had the intended impact. So again we're going to take a little bit of time. We might reduce it just just slightly. So our apologies if we come back just a couple minutes earlier than it says, but we want you to continue working on your example, taking that goal that you had started to flesh out and setting a logic model, just thinking about what are your inputs, what are your activities, your outputs, what are the impacts. How are you going to know that you're making progress and how are you going to measure that progress. Again, if you didn't come up with an example, you don't have anything in mind, you can use our fictitious venture here again, thinking about a goal related to that. And just start thinking about what are the various aspects that you'd have to think about while building a logic model. I'm going to come back in three to five minutes. So if you want to take some, some quick time to jot about it and think about what it is that you would do. All right, I hope that everyone had some time to start their logic model. I know that five minutes is very ambitious, probably not achievable to actually create one. And I know that there was a question that came through later in the presentation, Rachel is going to address that. Great. So moving on to measurement plan. Measurement and analysis should be integrated into the Ventures overall work plan. The frequency is from your measurement plan to determine where to build each aspect when it comes to collecting data, analyzing data and making decisions using data. Make sure your team is looking at the metrics you're collecting and using them to inform planning resource allocation and requests for help. If you use your measurement plan, consider whether you need to revise elements of your programs. So is your data showing that one program is more effective than another is less efficient than another why, or revise elements of your goals and measurement plans. So are your targets being, are they reasonable? Are you achieving what you set to actually achieve? There are a few best practices that you should, you know, work on that will help to inform your work and keep in mind. So first, consider resource realities. While understanding your progress is critical for strategic and fundraising reasons, you need to balance the resources spent on evaluation with those available to run your programs. Again, if you're working on a social venture, if this is a nonprofit, just really mindful of those resource realities that you have. Your mission is always going to come first and measurement will come second to that. Value consistency for your data to be meaningful. Make sure that you're measuring and reporting consistently. This means at the same intervals. So we use that example before how we have our semi annual reports every six months. So use the same intervals, the same cadence. This is going to be helpful for you and your team to evaluate but also going to be helpful for community members to know when they're expected to be reporting back. Using the same measures. So whether this is your measuring in dollars, how much money raised, leaders, how much clean water has been collected or distributed, number of students that have been impacted. Make sure that you're consistent with your measurements. And then using the same methodology. This is really, really critical every time you're collecting this data. So whether that is through a report, whether that is through the survey, whether that is through interview questions, or even budget documents, make sure that they're consistent every time that you are collecting this data. Prioritize transparency and inclusiveness. This data is not just for you. This is not for you to collect this data, analyze it and then just keep it on your Google Drive somewhere. This is something that you need to be sharing with your partners, your community members to keep everyone engaged and expand the pool of those who are helping you to ensure that the venture is effective. What we do at resolution is we collect all of the good quotes that we find at the end and we share them with the team. This helps to reinvigorate everyone. It reminds everyone why we come in at 830 at 9am. Everyone, every morning to make sure that we're helping our community. It reminds us of the work that we're doing. We also use a lot of our data in our annual reports to report back to our corporate partners. It's really critical that you're not just keeping this data with you, share it, be transparent with it. And then avoid overburdening your community members. So you need to strike a balance between getting the information that you need with the amount of time and effort it will take your community members to provide that information. There's no magic formula behind this, but it's really important to ask your community members directly what's reasonable for them. For us, we work with undergraduate students a lot. For the fellowship, you have to be an undergraduate student to apply. So when we're asking for semi-annual reports, we're trying to work around final season. We're trying to work around when our fellows are graduating, when they're having major life transitions. We have 500 plus fellows, so we can't always get it right. But just being really mindful of when that season hits or when that time during the quarter is. If people are particularly busy, you're not going to get the best data that you need. Amazing. So here we have a measurement plan example. So I'm going to walk you through the example and then Rachel is going to have a lot more to connect the stuff that we've been talking about. But we wanted to provide you with a tangible example. Again, continuing with hand washing for health or H4H to kind of solidify what one would look like. And again, this is a very short measurement plan. I hope that all of you take more time and have a much, much more expansive measurement plan. But here we're looking at our inputs. So for H4H, we're looking at volunteers, hand washing curriculum, instructional videos and games. So these are the inputs. These are what they're putting into the work. This is what they're giving out. Activities. So for activities, we have training sessions. So the activities is where the volunteers are getting the hand washing curriculum. That's where they're getting the instructional videos and games. Through these training sessions. The outputs are the students trained and students using good hygiene practices. Like Rachel mentioned before, this is oftentimes where organizations will stop. They'll say, oh, this is the number that we need. You need to go beyond that. There's much more that you need to collect. It needs to be more specific to make sure that you're actually meeting the goals that you've set for yourself and making an impact. So moving on to indicators of progress, we have really defined really specific indicators here. So the number of students ages to six, six to 10 trained by H4H, number of students using good hand washing practices, number of family members using practices, and then the average number of annual sick days. So these are going to be our indicators of progress. This is what we're going to be looking at to see how we're doing measurement techniques and tools. This is what we're going to be using to measure those indicators of progress. So H4H has participant logs. That's where you can see how many students ages six to 10 were trained by H4H annual follow up with sessions with schools. This is a great opportunity to see the number of family members who are using these practices, see the number of students who are using good hand washing practices, and then student attendance data. This is where we're going to get that number of the average annual sick days that have been taken by our attendance data. And that's a really critical number, right? Because that is the end game for us. We want to decrease that. So when we look at it and we put it all together, the impact that we're going to have over the next five years is have the number of school absences due to sick days from 10 to five for 1000 students ages six to 10 in our made up resolution land. So that is the impact that we're looking for at the end. I'm going to hand it over to Rachel because I know that she has a lot more to say on this and I think that we've had a few questions come through as well. Thanks Carly. Yeah, so when you're looking at our measurement plan, so you're looking at sort of all of those components of the logic model. Now you're looking at your actual measurement plan. How are you going to measure this? So what are the factors that you need to consider? You want to think about what do you want to accomplish? How do you measure your progress? Where will your data come from? Next year, how are you going to measure that? I know a lot of times it can feel very overwhelming to think about, you've got a big project, you're starting to think about like how are you going to make impact? It can get a little overwhelming. But if you start basically asking yourselves the very basic questions, who, what, where, when, why and how, you can start to build out a plan.  Now just think about how, how are you going to do it? So again, we're going to give a little bit of time to go through some examples. I know there have been a couple of questions. We're going to make sure either to address them towards the end in the question section or if they're embedded in the presentation, we'll get to them at that point. But here we again want to give you a little bit of time to play with it. So again, you've sort of identified hopefully a little bit of a goal, figured out some of your logic model, your indicators of progress, your inputs. And now just spend some time again with that who, what, where, when, why and how, and start to actually sketch out a little bit of a plan. You're not going to accomplish all of this in five minutes. This is a hope to, to give you a little bit of a crash course 101 into the whole process. So, and again, if you, if you haven't come up with a goal, if you're sort of new and thinking about what your, your project might be, you're again welcome to use our fictitious venture. Just a quick note on that. We've been using this example for a long time. Well pre COVID so our apologies if it's triggering example certainly wasn't meant to be it. It was just an example we've been using for a long time. So again, if you if you want to use our fictitious example here, you're welcome to do that. And then we'll circle back in five minutes and we'll make sure to address the end of the presentation as well as those questions that have come through. Alright, same with the logic model very ambitious to create a measurement plan in five minutes and I hope that you all just started to think about this at least. So I'm going to hand it over to Rachel to close it up a little and then we're going to address some of those questions that you all have been asking. Thanks Carly. Yeah and actually this last one I think relates to the first question we got which was fantastic about how do you measure progress in real time. How do you think monitoring to improving course correction. The first question is because planning isn't enough. You have to actually use the data that you're collecting. It should be iterative and ongoing. Oftentimes we think about really lofty long term goals and those are great. We should have long term goals for the work that we're trying to do, but short term goals are actually even more important sometimes setting those goals that are time bound and you know Carly talked about the beginning, you know resolution oftentimes we'll talk about maybe an 18 month goal, the six month goal. What are those goals that you are looking to achieve in a short term. And then what is it that you're looking to have an impact on and how does it actually factor into a longer term goal. Oftentimes progress that you're seeing in a short term goal can really help you quickly course cracked and figure out what's working. So at the organization at resolution we've oftentimes used our data to course cracked to think about things so we have some assumptions. So a program is going to be great. We get data from our fellows it's like actually it'd be better if it was this. We prefer this instead, or this was great but what about this, and that's allowed us to shift to change to evolve. So, I think oftentimes we think of impact evaluation as a, is a long term thing, and it is, but it's also short term, it should be iterative it should be ongoing. We should be thinking about what are the short term goals, how do those goals lead into a longer term goal. It's, they're really sort of snowball into each other. And so if you think about the short term things sometimes that can really help you figure out how to use that data you're collecting real time to course cracked. So that's, yeah, analyze, learn and repeat. And so that is really how resolution does it. We hope that this is a really helpful model. Again, this was a really lofty thing to do to be able to go through an entire metrics and evaluation system in an hour long presentation, or just under. I know that we've only sort of hit the top of the iceberg here. But we have some great questions. So we're going to, we're going to continue to answer those. Again, please do use that chat. If you have any questions. If you want to find my email and Carly's email there, please feel free to reach out. You know, I know we only have about nine minutes left. We might not be able to answer everything, but please do feel free to contact us and continue the conversation. Carly, did you want to answer the questions about how to convince donors to resource metrics evaluation and learning. Absolutely. I think that's a really phenomenal question. So it seems like it should be easy to convince everyone why is important, right, because at the end of the day, it's really one of the only ways that you can determine if they're if you're having an impact. But when it comes to your donors, your supporters, your sponsors, that is how they're going to see their money is being put to use. That is their case to bring back to their CSR to bring back to their companies on a large scale and say this is the impact that we've had this year. It's not enough for them to just funnel money into your organization without actually seeing how that money is going to use. So through actually investing in impact evaluation investing in monitor and evaluation taking that time you're able to make the case for why they should be giving you more money because they're able to see the impact that their money has had they're going to be able to have a trail to see where their funds have gone and continue wanting to work with you. So it's really just about being able to deliver what you know they want to see at the end of the day through impact evaluation and the data that you're collecting. Fantastic. I know we have another of other great questions here. One of them is is sort of related to what Kylie was just talking about which is how much of your budget should you be allocating towards metrics evaluation and learning. And if you go back to our smarty goals. One of those was about resources. So you really should think about the resources you have evaluations really important, but doing the work that you're doing is even more important. Making sure that you have the appropriate resources. So resolution where a staff of about 13.  That doesn't mean it's not important to the organization. But it means that that's sort of what what we're able to allocate to impact evaluation. So you can do this with not a lot of resources. And then when you think about your budget it's great to think about putting some money aside there's some great free tools out there that you can use. Survey monkey. It can be a great tool. It's got a lot of data analytics already built into it Google has a great suite of resources as well. So there's a lot of free low cost things out there that you can think about using.  A lot of nonprofits do because they provide really great packages to nonprofits resolution uses that we do a lot of our data collection and analysis using tools that are either native or plug into Salesforce. So that has been sort of one of the places where we've allocated resources to technology, but there are some really great free resources out there. If you're just starting out. It doesn't have to be sophisticated. Think about some of the surveys you take. You know if you're on a website and sometimes they want your feedback. Those aren't necessarily always the most sophisticated, but they can collect some really important information. So resources oftentimes is probably even more time than it is money. Rachel, I think to that point it would be really important for us to mention that you can also get creative with the people that you have in your network for resolution. A lot of our impact evaluation reports were created from working groups were created from people in our network. A lot of those questions didn't come from us because we're so close to the work they came you know from these working groups from people who are familiar with resolution, but also really versed in impact evaluation so they're a subject matter, subject matter experts within their field. So figure out who's in your network and see how they can be also helping you create a working group around you know when you should have reports what should be on those reports as well. I think that you know doing a deep dive into the resources that you already have is a really great suggestion. Great. I see a number of other questions here. I'm just going to read them out mostly because Carly can't see them. So we've got a question here about insights and measurement of social or behavioral change. What can be more qualitative. A lot of us in the nonprofit sector and social impact, oftentimes are working in qualitative things. So what are those qualitative variables leadership, ownership, social cohesion, equity, and how do we measure those. So let Carly think about that for a second as I answer one of the other questions here. Which is about how do you get data that's real and unbiased if you're expecting people to report on it. And this is something we've tackled a lot of resolution. We have self reported data. We ask our fellows to report. They could be making things up. We don't think they are, but we are relying on them to provide us information. I think there's a couple of ways that we can do this and feel comfortable about that information. One, we also survey there are volunteers are guides. So we have a little bit of a check. We ask our fellows some questions, we ask those mentors that are working with them. And that helps us assess our is the individual implementing the project and someone who's working with them sort of seeing the things in the same way that can be a really helpful way. We also build a relationship with our constituents. We want them to be honest with us we cannot improve as an organization on what we deliver. We're not honest with them. We make it really clear to them that filling out impact evaluation reports every six months are not an evaluation of them. This is not a time for resolution to check up on them. Make sure they're doing what they were said they're doing. But that's the relationship we have with our constituents. You may have a very different relationship with the people that you're getting your, your data from. I think it's important to think about what that relationship is. So does that maybe impact the type of information people will provide you. Sometimes there's some really good public sourced databases that you can compare your results to that doesn't exist for everything. No, our work it's not as applicable because we're running a very specific unique program, but sometimes there are really great databases out there. In the universities, a lot of students in grad school are doing some really great work, and that can be a great source to data check against a public sourced set of resources. Carly, do you want to do I go ahead and answer the next question about qualitative variables. Yes, I will try to do it within a minute and a half that we have left. And whoever asked that please feel free to email and I would be happy to have a much broader conversation on this, but when it comes to qualitative data it also ties into what Rachel was just saying about the nature of the relationship that we have with our constituents in our community. Because when we're collecting qualitative data we have questions built into our semi annual reports where we can measure their progress and leadership where we can measure different different qualitative data but we also have different checkpoints with them, where we have individualized conversations. Again, in kind of an interview format but much more comfortable to be asking how their fellowship is going and that's where we'll find out a lot of that qualitative data is through those conversations. Again, making sure there's consistency with how we're measuring to make sure that we're asking the same questions for each of our fellows, but that's the type of relationship that we've built to be able to collect that data. So those checkpoints at very transformative parts of their fellowship so after six months of their onboarding process, and then after two years we found that those are really, you know, inflection points to figuring out how they're doing within their fellowship and within their leadership roles as well. I know that we're at time. Yes. So thank you all so much for being here. Really appreciate your attendance and your interest in impact evaluation, your dedication to making sure that you're tracking the impact that you're hoping to have. Again, please feel free to contact us. Our emails are Rachel at resolution project.org and Carly at resolution project.org. We'd love to continue the conversation I know we have a couple of questions left. Unfortunately, we're at time. We really hope that this was a great intro to impact evaluation and please do feel free to continue the conversation with us. Thank you so much everyone.


Ladies and gentlemen, the railroad out. And here comes the star-studded show trade. The Ninety Association of American Railroads presents Florence Ziegfeld's musical success, Sally, starring Gordon MacGray and his two guests, Marion Bell and Jack Kirkwood. Our choir is under the direction of Norman Luboff, and our music is prepared and conducted by Carmen Dragon. Yes, tonight another memorable musical hit is brought to you transcribed by the American Railroads.  And now, here is our star, Gordon MacGray. Hi, the Miller and Good evening, ladies and gentlemen. We're looking for a silver lining tonight, and we all expect to find it in Jerome Kern's great music for Sally. The Sally of our alley is charming little Marion Bell, so don't be surprised if I fall in love with her in the next 30 minutes. I'm Blair Farquhar, a poor unfortunate guy with only a couple of million bucks in the bank. Jack Kirkwood plays the Grand Duke Constantine, whom we meet back in the little country of Czechargovinia. Duke of Czechargovinia? That's me. Revolution! We have found out about you and Madame Newcarova. No! What did you find out? That you bought her a string of pearls with the taxpayer's money. Oh, is that all? For a minute I thought there was going to be a scandal. You are deposed! You are now a fugitive! An exile! A bum! Of course I didn't know anything about Balkan revolutions in those days, and when I dropped into a New York restaurant for a bite of lunch, I didn't have any idea that the man who was waiting on me had once been the Grand Duke of Czechargovinia. Waiter! Waiter! Yes, sir? Would you please clear off these dishes and bring me some food? No, clear off the dishes. All right! What are you doing? Well, if I don't smash them, I have to wash them. Then I hate that. They hired a dishwasher, but she isn't here yet. Well, bring me your number three speciality. Yes, sir. Right away, sir.  Hello. Well, hello. Are you the proprietor? No, no, I'm just a poor unfortunate customer. Won't you sit down, have lunch with me? Oh, no, I can't. Why not? Don't you eat? Sure, but I'm just the dishwasher. Isn't that awful? Well, don't worry. Things are bound to look up. There's a bright side to everything. Even the dish pans? Sure. Please don't be offended if I preach to you awhile. Tears are out of place in eyes that were meant to smile. There's a way to make your very biggest trouble small. A happy secret. The sun is shining. I'll wash my dishes now. Good luck, Sally. Here's your lunch, sir. Thank you, waiter. Are you Mr. Farquhar, the well-to-do millionaire? He's my father. Oh. Well, I understand he's giving a party tonight in honor of the Grand Duke of Czechoslovakia. Will you be there? Not if I can help it.  Did he want your dessert now? No thanks, I don't care for any dessert.  You know, in all that high society, there won't be one girl as pretty as your new dishwasher. I didn't notice. Is she beautiful? She's Julian. Cinderella. Hey, you sound like you're falling in love with her. Maybe I am. She's somehow different from the rest. I can't describe her white. She seems to be just right. She won my heart. That's all matters, not how she is dressed. I wanna hold where the sun... I can see the headlines. Millionaire falls in love with dishwasher. Do you think maybe I've got some soap in my eye? Dishwasher. You're beautiful. You're cute, too. What's your name? Konstantin Alexandrovich Fedor Gregorovich. What's yours? Sally. You've got short changed. Sally, do you want me to help you do the dishes? Oh, you've got a job, Mr. Konstantin the Towel. We are deeply honored. Are you helping? I'll be through twice as fast. Even faster if I break a few, eh? I wonder if I'll ever see him again. Oh, so, eh? Blair Farquhar. Oh, I'm going to a party at his mansion tonight. Really? Yes. You see, I'm actually the Grand Duke of Czechocovinia. Gee. I wish I could go. Then I'd get to see Blair again. I've got it. What have you got? Sally, I'm going to escort you to that party as Madame Nukerova. Uh, Madame who? The famous singer, the Czechocovinian Nightingale. What if she finds out? She's back in Czechocovinia. She'll never know. I'll put my hair up on top of my head and wear false eyelashes. You'd better wear a little more than that, I think. I'm taking an awful chance. What if they find out that you're a dishwasher?  Hmm, you've got a point. It's a deal. We'll go to that party together. The Duke and Duchess of Dishpam. Just wait and see. I'll get out of those soaps yet. We'll return for the second act of Sally in just a moment. But first, last Thursday night, the four cities of Davenport, Iowa and Rock Island, Moline and East Moline, Illinois celebrated an event in their history which marked a milestone in the growth of American unity. For there, just 94 years ago, the first locomotive steamed across the first railroad bridge to span the mighty Mississippi River. Binding together east and west with bands of iron. In the same month in which the bridge was opened, a river steamboat rammed it and both steamboat and bridge were burned. Suit was brought to prevent the rebuilding of the bridge on the ground that it was an obstacle to navigation. To represent the railroad came a then little-known Illinois lawyer, Abraham Lincoln. And in that suit, in which there was established the principle that bridges carrying railroad tracks might be thrown across navigable waters, Abraham Lincoln made one of his first great contributions to a united America. Last week's celebration in the four cities which have grown up where railroad tracks first crossed the Mississippi recall the dramatic story of the struggles to get railroads built in the 1850s. And today, as the 1950s begin, this nation needs its railroads more than ever. The building of those railroads made it possible to settle and civilize a continent. Their services today are an integral part of the marvel of American production. For even in the midst of the richness of today's transportation facilities, it remains as true as ever it was that the railroads furnished the basic transportation of the nation, essential to its continued prosperity and peace, to its safety in war. Here's Act Two of Jerome Kern's Sally, starring Gordon Macrae as Blair Farquhar, with Jack Kirkwood as the Grand Duke and Marion Bell as Sally. That night, we had a party at our Fifth Avenue mansion in honor of the Grand Duke of Czechogovania. And when the famous singer, Madame Nukerova, walked in, he could have knocked me over with a balt and duked him, because he was a dead ringer for my little dishwasher salad. Ah, Monsieur Farquhar. Bonsoir, bonsoir, bonsoir. Madame Nukerova, one thing astonishes me.  Oh, perhaps we met in, ah, Europe, yes? Oh, when I was overthrowing a kingdom. Is it true, Madame, that you were the woman who caused eleven Balkan revolutions? Oh, twelve? Who's counting? That's amazing. Such a beautiful girl, and yet such a firebrand. Your party, your intrusion, our confusion is sublime. We've ever, ever met a girl like you. I must admit, I'm rather unconcerned. A type that must have... Would you come and walk with me in the garden? There's something I want to tell you. Oh, I'd be delighted to see your garden. Stonishing how much you look like a friend of mine. A dishwasher. Ah, this little dishwasher. She is nice. Ah, I think you're prettier. Ah, it's the moon in hand. Who's that lovely bird? It's a whipper-will. There's a nest of them in the willows.  When I was a little girl, I used to listen to the whipper-will and dream of living in a garden just like this. Humiliation. They found out about me. He's no Grand Duke. He's nothing but a waiter in a restaurant. Well, I have to do something to put some money in the pot, boy. Well, here is a Grand Duke. You should be ashamed of yourself, Carola. I'm just a dishwasher. Sally. Oh, as long as you thought we were fancy pants foreigners, you were nice to us. But you laugh as soon as you find out we have to work for a living. But, Sally, we didn't mean it. You think we're phonies? A lot bigger phonies than we are. When Sally and the Duke marched out of our party that night, I figured I'd never see her again. But I figured wrong. For beauty and talent like Sally's couldn't hide forever behind a stack of dirty dishes.  Behind those footlights, Sally really found her silver lining. Congratulations, Sally. It was a great show. Was I all right, your honey?  You got him right in the bottom of your dishpan. I should be happy, but he didn't come. Oh, Blair. Oh, but after the party, you said you never wanted to see him again. Your Highness, when a girl says that, she wants to see him twice as much. Oh, okay, Sally. You wait right here in your dressing room. I'll find that guy if I have to scour New York. If I have to scour the United States. If I have to scour the world. Hello, Sally. Quick scouring job. Congratulations, Sally. I think everybody in the theater loved you almost as much as I did. You're sure you wouldn't love me more if I were a notorious woman who starts a revolution every Wednesday? Oh, Sally, it's you I love. Will you marry me? No. Why not? That's what every girl's supposed to say the first time she's asked. Oh, what do you say the second time? Why don't you try it and see? All right. Will you marry me, Sally? Um, maybe. What happens the third time? Well, don't stop now. I can find out. Sally, will you marry me? Of course I will. Wonderful. I promise you one thing, Mrs. Farquhar. Oh, what's that, Mr. Farquhar? After we're married, I'll always help you do the dishes. Look for... And our thanks to Paul Fries for his part in tonight's performance. Sally, with booking lyrics by Guy Bolton and Clifford Gray, and music by Jerome Kern, was dramatized for The Railroad Hour by Lawrence and Lee. It was brought to you each week at this time by the American Railroads. All through this broad land of America, there are things to see, places worth traveling to see. All through the year, and especially in the vacation season, there are observances and celebrations to add special interest to the scenic and historic spots of the nation. And wherever you go, and whenever you go, there are railroad trains to take you there and to bring you back to your well-known safety. And now, here again, our Marion Bell and Jack Kirkwood. Marion, you sang Sally just as beautifully as you sing Nadina in The Chocolate Soldier. Thank you, Gordon. I was down to see you at the Philharmonic last week, Marion. I know, Jack. I heard you laughing. How did she recognize me? Who's on the show train next week, Gordon? Well, Lucille Norman will be singing the title role of the Pink Lady, and I'll be a Parisian playboy. How about this, MacRae? One week he's a New York millionaire, and the next week he's a Parisian playboy. What are you trying to prove? Well, it's a good way to put some money in the pot, boy. Good night, you thief. Well, it looks as though we're ready to pull out. And so until next week, goodbye. Holly was transcribed in Hollywood and presented by special arrangement with the Tams Whitmark Music Library. MacRae is currently being seen starring in the Warner Brothers Technicolor musical hit The Daughter of Rosie O'Grady. Our choir is under the direction of Norman Luboff and our music is prepared and conducted by Carmen Dragon. This is Marvin Miller saying goodbye until next week for the American Railroads. And now keep tuned for your Monday Night of Music on NBC.


Welcome to Jalassa News. My name is Rob. Today I want to talk to you about is where we're potentially going in 2023. I want to take a look at just some simple data points. And I got to tell you, the first month that's coming up January 2023 is not looking good. However, moving forward, I think we've got a lot of ways to go. Also, we'll take a look at some active addresses and how there are some different products that are actually building in this bear market. And finally, I want to talk to you about a call I took on a crypto product that we've covered here on the show and where things are going as far as globally in the crypto market in 2023 and 2024. And it really does have to do with a tokenization of securities and security assets. And this was, it just blew me away about what's happening behind the scenes that nobody knows about because nobody has any idea what's coming. So first things first, let's take a look at what's going to happen potentially in 2023. This was a chart put out by Rect Capital. I link their Twitter account in the description. You can check it out. And again, I'm a big believer in four year cycles. So again, 2012 was having 2013 was an all time high 2014 and 15 is a dip in a reset. 2016 we had a Bitcoin having 2017 all time high 1819 dip reset. And then just 2020 we had a having again. We had an all time high in 2021, we're going through a major dip and a reset, which will happen in 2023. Those are the four year cycles. But the way that Rect Capital took a little difference, different look at it was instead of starting with number one, which would be what I would say number one, the first time, which would be the first having there. They're starting everything at the all time high after the first having and they said, just take a look at this. So in 2013, this number one here, that was the all time high. Then we have what I call as a dip in 2013. And then 2014. We have a reset. And that is, even though we see it's, you know, the full year after the all time high is bad, the reset year is actually not too bad. And then we go into a having in 2016 2017 all time high, a dip and a reset. And of course, having in 2020, we're looking pretty good. 2021, 2021, we had an all time high and see, look at that wick going all the way up there to almost $70,000. And the number two here is what I say is the dip or the year afterward. So if we just take a look at three, usually two years after the all time high, three over here, three over here is actually a pretty good green year, then going into, of course, the next all time high. One thing to note here is this, diminishing returns are definitely in play. You can see here the number one in 2013. That's a pretty big candle. And 2017, still a big candle out as much. And then look at 2020, or 2021, excuse me, not too much action, but it's still went to 70,000. So again, I think in 2023, we can see some some pretty good reversals. However, if we take a look, this is from Ben's website and the crypto verse, we take a look here at the monthly return tables, just look at January for all the years. And you can see that we've got 1234567 green months, and then five red months. And most importantly, the month or the two months after the all time high, remember the all time was 2013, two months afterwards, January was a pretty awful month, negative 31%. And 2017 all time high, two years after that, it was still a red month, negative 7%. And then in 2021, two years after that, I still think January is going to be a pretty crummy month, moving into maybe February, you might see a better month, and then March. But I still think 2023 can be good, just depends on how good it can be and how long it's going to take. Again, there's a lot of macro factors, we're going to start to see. I mean, even if the Fed pivots, you're still going to have months after that, because they probably broke something, there's still going to be supply chain issues, there's still going to be inflation, there's still going to be all this talk about the wars and things that are going on. So the macro discussion, I think is still going to be pretty awful. But I see that we're going in the right direction, moving forward. So let me actually think about that in the comments section. And I will just say this, just remember, and we talked about this before many times, I still think we can go down even farther. So again, if we take a look at the different timeframes, usually we fall about 84 to 85%. And that would put us at a 10K Bitcoin. Can that happen in January? Maybe. That's what we got. So again, let me just think about that. Now let's move on to our next piece, active addresses. And this is important to take a look at to see like, who is growing, who is doing good things. But also, it's good to note that on chain metrics can kind of be a little funny. So this is from, it was a tweet by Web remark and insights. Go ahead and follow him link description. But he takes a look at deli active addresses of polygon. He said, wow, look at that. Deli active addresses is around 1 million in the last 30 days. You can see this is actually broken down by days. Taking a look here from November, all the way to December. And of course, this is a day by day by day. It's looking pretty, pretty positive. What's happening here. However, when I take a look at this, I'm like, wow, that's pretty awesome. And then let me see just how that is on the website. This is Nansen. And you can just see that over the last gosh, what is this over a year? No, this is all of it. Since the inception of polygon, you can see the active addresses. It's pretty good, but not as much as it was back in September. We had almost 1.6 million here. And of course, during its all time high in October, you know, 1.5 million. But we're still looking pretty good. And I thought to myself, well, how is that for Bitcoin? Take a look at Glass Node, Bitcoin active addresses, we can see right here, you're looking at almost a million. So you're telling me that polygon, however they define it here, they've got a lot of active address that which is good. However, if I just take a look at Glass Node and pull up polygon, a much different story. Glass Node over here will say, Hey, this is you've got 5000 active addresses, you've got 7,488 addresses. And the way they define it is this, the number of unique addresses that were active in the network, either as a sender or receiver, only addresses that were active and successful transactions are counted. So we take a look over here, what do they define that as? And then it's just at just interaction. And the number of times events were broadcast by the specific entities or smart contracts, or how things were moved about. So again, for this one, with Manson, just take it with a grain of salt for all this on chain data, you can parse this up and make it look awesome or make it look crappy, just depends. But take it with a grain of salt, because there's different ways that metrics will show you different things, not to take away from polygon, I own polygon, I want it to work really well. But this is not a moonboy channel. And that is just the data that we see. And yeah, that's what we got. And then lastly, let's finish up with some positive news. Now I didn't, I thought it was interesting, but I didn't really put two into together. This is Larry Fink. And he is talking at some summit, and he's taught and Larry Fink is a CEO of BlackRock 10 trillion assets that are management. And he's talking about how big tokenization of security is going to be securities being stocks. And I just kind of brush it off like that's cute. That's adorable. But then I was reached out by these guys from Arcton. And I stopped talk to Francisco and Meron's Meron's is is a securities lawyer in Switzerland, Francisco, he is a blockchain developer. And they talked about how yeah, they said we we're also looking because of the sick token securities here in Switzerland, that is our our main business. And they explained to me what a security token actually was, like, that's great, fine, sounds good. And then I just talked to somebody yesterday friend of the show, I can't tell you what the project is. But we talked, it was supposed to be a 15 minute conversation, it was an hour and a half. And what he told me, he said, look, we've been reached out by numerous institutions and entities globally, not just America. And what they want us to do is they want to build on top of our project to offer tokens securities to be tokenized. So their customers can have access. I said, what, what is the whole point of that? They said, because it's just, it's just cheaper, easier and faster and cuts up the middleman, which is what we've been talking about for so long. He goes, So what they're going to be doing and I'll be talking about this later when I can tell you more. But what they want to be doing is to service industries like with pick day, I don't have no idea what this is. This is asset management wealth management. We've got 700 billion asset management.  And they want to build on top of us. And I can guarantee this isn't the only crypto platform what they're doing. And so we're going to be doing money license and different different things, which will essentially make them a bank moving forward globally. I can't get into the details of it yet. But look for that in Q2 Q3. And he said, and what he told me was he said was this is the future. This is where things are going. These are the things that are happening for real world assets to be tokenized. And he goes and it'll be built on multiple solutions, multiple layer ones. And so the whole narrative from here, which was well, Larry and BlackRock that was build their own blockchain, I told you, no, they won't. They may, but I don't think it's it's very wise. We took a look at how many businesses Facebook has acquired, even though they could definitely just build their own. It's just faster, faster, cheaper, easier to build it on the on the platform, use another platform, and just go that route. So I'm excited for 2023. And I think this could be the new paradigm shift people are talking about. And yeah, I'll let you know about that when I get more information, you can talk about it. But that's what's happening. Then lastly, just let you know, the sweat coin, January challenge, I want everybody to get in shape, or as as best of shape as they can. The best way to start with doing that is just walking. sweat coin is of course, I'm biased on this channel, I want a bunch of sweat coins myself. But the app itself is free to use, free to download and you get free crypto, which is the sweat coin app. I reached out to all the people that I knew. And here's what we're giving away. We're giving away over 5,000 sweat coins. We're giving away a ledger Nano X. We're giving away a lifetime membership to token metrics, 10 coin ledger premium memberships, we're giving away two arculuses. We're giving away meld tokens, meld bank managers, we're giving away three, six month premium memberships in the cryptoverse, 30 shield folios, premium membership of 10 set ladies, epic art, which is crypto physical art and of course, some Yetis from I trust capital and some pens. And it's all going to happen within this this month. So there's a link in the description. All I want you to do is just just download the app now, start walking. Top 30 people are going to win these things. And I'll explain on January 1st, exactly how that works. And that's it for today. So look, like today's video, give it a thumbs up, also consider subscribing to talk about our time sensitive and that's it for today. So thanks so much for stopping by I appreciate you. And I'll see you on the next one.