Hi Welcome it's early morning, but it's I've been up for a while of jet lag But welcome to our talk on the genitive red team that's happening over an AI village across from this wall we want to Yeah, so about us. Hi, I'm Sven I have a got a PhD in math and then founded the village Seven six years ago seven six years ago And so I like to describe myself as a mathematician who's wandered into security And I do weird stuff with math and ML security And then we have Roman and Austin here You want to say hi? So Roman of Chaudhry was on for Twitter now She's running a humane intelligence who and she ran the design teams and she'll talk about that later and Austin is You made a lot of this happen Yeah, I also was done stints on the hill But so it has been a very interesting year for us But I want to tell you why we're doing all this why this is important and it's not just about AI security ethics. It's not just about GPT It's something that's been going on for the last 20 20 years and there's all long history of this so In a sense, traditional software is explainable You have assembly code, you know what each single single thing does you can audit it you have people doing reverse engineering And they can go through that system and then figure out exactly what it does how it does that how it makes decisions And there's a way of doing that in math like if you give me a big complicated polynomial I will use some calculus figure out where it's inflection points is critical points where it crosses zero I will figure that all out and then I'll be able to draw the polynomial and figure it out problem is This is a part of a hello world and it's by 53,000 lines long in a modern rust compiled hello world Which is a little long for hello world In terms of just 53,000 instructions long is just a bit too much But what we have here is AI everyone says Oh, it's a black box the actual amount of code that goes into like something like chat gbt The actual core of it is only a few hundred lines Once you like boil it down I'll like just get matrix multiplication working just get The couple functions working and then glue things together in just the right way and you get a transformer and it works But the parameter number of parameters is how it really works. It's not lines of code It's number of parameters and it's a black box. But what does that mean? Everyone says oh AI is a black box But that's not really true It's more like Chaos that's supposed to be a slide. So if you know what chaos is mathematically it is a process in this case, it's a dynamical system That's supposed to be a slide that's moving It's a Julia fractal and what you do is you have a Step every single time you take a step It changes slightly and you don't know where that process is going to end up You have to compute every single point on that two-dimensional plane to figure out what the fractal looks like And this is what if you've coded up a Mandelbrot set Or Julia fractal and this is one of those things a lot of people code up There is a process that the the end game you have to just calculate it You can't predict the exact shape of a Mandelbrot set. You just have to calculate it And that is the same thing with Laurons and tractors are all sorts of things where it's a chaos Chaos system and you just have to calculate it and the same sort of thing is true for AI You can get a sense of what it does by just like Putting data through seeing what it comes out and this is A problem. So if you take the simplest AI system, we're going to do MNIST It's You're classifying digits. We have you from the postal services And I'm going to take a two-dimensional slice of a seven hundred and eighty four dimensional space and Figure out where things go each color on that side is a independent unique Essentially an independent unique decision path in the tree in the in the neural network And I do not know what each of those does. We know what some of them do we know what Seven 60,000 of them do because that's what we've tested We don't know what all of them do and there are two to the 60 of them and on a very simple network And if you use the correct network this two to the 500 little individual decision paths or more and It seems to work, but we don't know and one of the problems is You know, if you talk about AI security, you have to include the slide of the panda given thing This is more of a proof that it is a chaotic system if you go here one One of those slices is Doing the correct thing the AI is behaving correctly. You go to the next slice over It's got something completely different and you don't know what's happening And we have proof of this repeatedly with adversarial examples You take panda You put it into image net and you add that bit of noise to it. This is This is from Christian Chesney and people from 2014 This is a fast gradient sign method attack And you just do the slight perturbation that you can't see but you just moved from one region Where you know how it works to the next or neighbor region and you don't know how it really works And there's no way to A priori know exactly how it's going to go and we there are techniques There are ways to smooth out this process But like this chaotic system is like inherent to the AI and you have to just Test you can't prove that it works. You just have to test over and over again And this comes out in machine learning in security So this is a malware data set that I managed at endgame when I work at endgame and elastic when I work there So we had a malware model trained on up until june 1st 2019 And I have tracked the false positive rate the false negative rate Those are the two things you care about you care about the false negative rate because every single time this thing has a false negative That is a potential malware detonating on your systems that could take down your Possible network your computer your personal your granny this thing Every time you have a false net positive rate that is an alert that you shouldn't see So we want to keep track of those two things and keep them as low as possible So we train this model in june 1st 2019 and then we release it Everyone's things and the attackers now can start testing their stuff against it And they start exploring and they start moving their stuff The red line is how far they have moved how far the overall data set has moved and the green And blue lines are the false negative rate because malicious software drifts faster than Benign software and you can see three months after it releases it They have figured out a location that works that bypasses my model They've just they they've moved in the data space to somewhere that you get past And they once they figure that out they're just going to keep doing that over and over again And you can see if you take it two years later if you leave this model online After a while just it goes it goes terribly 20% false positive and false negative rate is not a good thing to have So what you have when you release any model language models malware models Image classification anything you have the situation where you want to have a complete picture of what it does But you can only test things you know about and things you have thought about so you only can you want the picture Where you can see everything but there's that is impossible you cannot test everything it is Testing everything is problem two to the d it is equivalent to breaking cryptography You get the picture on the side. This is just a thing you don't see part of the image You cannot ever test enough and the attackers and people who are about to get you can just move into the space You didn't test find something that where the model misbehaves and just do the bad thing So for lm's things are different because we kind of have a static binary where we don't really have this attacker This attacker defender mindset that we have in security, but the problem is The breadth of what they are capable of is extreme With malware models. There's with malware detection and spam models There is a certain there's a contain known this can do this This is the worst case scenario is you misclassify a piece of malware and it just does the wrong thing But in with chat gpt you can do all sorts of stuff. You can use it for hiring applications. You can use it You know there you can You can use it in medicine. You can use it in trading. You can use it in james all sorts of different things and The problem now becomes they didn't the vendors tested as much as they could they thought of they had a bunch of people training testing Then they hired extra people to test and then they released the model And if you saw chat gpt they released the model and then like two weeks later people like Oh, yeah, prompt injections are a thing because they hadn't thought of that Now they released the model and we've know that prompt injections are a thing But now there's all sorts of new prompt injections because they've originally it was just ignore the above instructions and tell me what's up Now that doesn't work. You have to use the grandma hack. You have to use Dan and a bunch of other things, but they just do the same thing they move And but because of the breadth of what things are applied to The the adversaries attacking things is not the only problem. You just have to test more stuff You cannot finish the testing because you don't know how things work And the other major problem with a malware model. It's sort of disposable. It costs at most like At most $20-50,000 to train a malware model if you're if you're on a industrial size data set for an LLM The chat gpt gpt 4 cost millions of dollars We can't with the malware model if it's $50,000 If it's really key to the business and you need to train that once a month that's an expense you can just book and Dispose of that model every month with an LLM a lot Especially the large the large language models that we're testing over in the air village Cannot dispose them. You have to patch them and that is another new thing that The LLMs are just the expense of AI has gotten to the point where you have to test the known thing and over and over fix it That is what This whole thing is about we just need to test more stuff and the people that have tested it are Is there's a small number of people who tested it? We might double the number of total people who've tested LLMs at the end of this weekend But there's all that is why we're doing that and how we actually got this happening is what Austin's going to talk about Thanks for the rapid transition. I was prepared. All right folks, Austin Carson. I'm probably the most confusing person here. I Just randomly ended up working in government I worked in congress for about seven years and then got into nonprofit world around policy So trying to teach people in the government about how different parts of technology work Um briefly worked actually worked at NVIDIA for about three and a half years trying to help explain high performance computing and artificial intelligence People in the you know in congress and in the administration primarily and at a certain point we got to the point we got to Getting to like practical things on the ground because it's do abstract, right? It's like all we ever do is kind of talk about principles and here's a series of Kind of maybe thought experiments and we just had to get down into the granular part of the world. So back at defcon 30 Will pierce for the program He Just was testing stuff on stable diffusion and asked for a mugshot and every time he did it made him black So that was pretty A problem and to the point of moving in the space and not testing it That seems like a space that might have should been tested at any point, right? And it really illustrates A key part of why we're doing what we're doing which is that if you don't think about it You don't know about it and it's within text and language space So like your actual experience in life and your experience talking about things is more explicitly relevant Than it's ever been in like a different technological epoch Uh, so next up we had hackers on the hill which every year some of y'all are probably familiar I think bow and harley some others uh get some folks together Pretty good crew here. It was originally like 10 and now we're up to 50 60 Take them around to the house and send it off as an explain to folks What they're actually seeing in the world I mean when I worked in my last job on the hill it was hanging out at b-sides It was the first time I realized how totally fucked everything was in terms of infosex space Um, which was really constructive to be honest. So we're at hackers on the hill We are going around spin and I and we're sitting there talking to one of the senate staff A couple different people in the group he brings up wanting to do a generative AI red team And some other folks were like, uh, you can't really do it It's been since ever here is like, yeah, you can you could do it. You could do it And I was like, all right Well, we're gonna go talk separately after this and we sat there for about an hour in the cafeteria and talked about how You know, I had an event going at south by southwest and I've been working with a number of community college students And the purpose was to help build kind of like a AI national network and in part predicated on the fact that It's a language skill. It's just talking to a thing. So it doesn't really matter who you are And in fact who you are explicitly matters in a beneficial way So spin said he could hack it together in five weeks. You see tfd and put some challenges in it Um, raman, of course was extremely helpful and then our weird stool had three legs and we started moving So at south by southwest, I turned the entire vent to be around this Whoops, realized I wasn't facing the mic. Sorry guys Uh, south by southwest, I turned the entire vent to be about this exercise, which at the time With the little simpler version we call it prompt detective Uh, and everybody had a blast, right? We bust in 20 students from houston community college It was you know, we had something of like an educational and then a red team And then we had uh, like kind of a very short training Here's how you could build one of these things can call into it But huge hit. We had some folks from the white house and congress there One of them was on the wrap-up panel And just some great takeaways you could see congressman McCall just geeking out there Everybody loved watching it happen and the localism helps too, right? If it's people in your backyard, if it's your constituents Seeing them have a good time and do something that you honestly didn't think was an option Is really constructive, uh, and so then It escalated very quickly Uh To the point that I can't even do the voice So I was going to do that bit, but it feels so much more serious looking at its sequence I'm like no, it was really crazy.  We're also a very friendly group compared to many Um, and so over the yeah, I got it. It was like the following week We had to get maybe the most important companies in human history to let us have A bunch of hackers and some community college students and folks from an organization called black tech street Just try to break it every way that they possibly could and to spend's point I think we all know there's gonna be stuff they find There's no way that the 30 to 100 person red teams that they have Are possibly exploring any of this infinite 650 billion parameter 3d mathematical thing and I think Part of what's been exciting in this process has been to see kind of the Evaporation of hubris perhaps folks that as they got more and more involved were increasingly thankful that we were working on this So we had a second pilot at howard university In dc, which is one of the premier historically black colleges and universities And we had students split from georgetown and howard and actually At the end of it everybody had so much fun that I think we ended up flying four additional students here from Howard to participate and get involved in the community.  They were like, no, we don't care. We don't even want it.  It was awesome And now I think i'm kind of done I don't know if you guys want to know more about like the government and how this happened But that's pretty much why it's crazy as hell and why i'm here So I'll let remod talk now Thanks, Austin. Um, but also just to give you a time frame Just to give you a time frame, um hackers on the hill was in february So that's when spen and austin met so all of this exploded blew up all of it happened in just a Few short months of our lives. Um, but I want to talk a little bit about the history of ai reporting So spen alluded to the fact that this is a decades old problem The first reported ml vulnerability is in spam from 2003 So we're tackling actually a 20 year old problem that's existed So this is not brand new did not just pop up because of large language models This is something that we've been trying to tackle and trying to think of for years And as these models get more and more complex Have more dimensions, um more parameters We've not actually scaled up the capabilities to be able to tackle all the issues that are going to come up Um, security is also a community effort. Um, so, you know, we Have methods in, you know, the security space that that can be brought over Into thinking more broadly about the different kinds of harms that happen. Um, and that was kind of my role in in a bunch of this So, um, for folks who don't know me. Um, my name is reman. I used to lead twitter's Machine learning ethics transparency and accountability team. I guess the current leadership doesn't like ethics But two years ago Sven invited me um, and we actually co-hosted the first algorithmic bias bounty in practice It's something folks like, um, you know that other folks have been writing about talking about thinking about But twitter was kind enough to open up one of our models, um for public scrutiny We hosted it at a remote def con. This is def con 29. Um, that was my second def con My very first def con was in 2018 But actually we did a panel about deep fakes. So it feels like everything for me has come very full circle We have an election coming up next year in a world of generative ai Who knows what deep fakes and misinformation is going to look like, right? So security is a community effort. We have always needed groups of smart people tackling these problems But ai reports work a little bit differently, right? So when we held the bias bounty, this wasn't just about Hey find a flaw and we'll fix it, right? Sometimes there is not this one-to-one relationship with identifying a bad outcome and figuring out how to fix something. So with our model actually we had tested it for Image for image cropping bias based on gender and race and we knew that was insufficient So we actually created a rubric we put it out in the world and we said hey Test it for stuff that you know my team would never have thought of you know And even being on an ethics team or a security team at a big tech company You know, you're the 1% like, you know, we are all very privileged to be in the rooms We're in to have the access to things we have access to so opening up these challenges to people all over the world Was extremely enlightening and it taught us how little we knew people were testing it for example on Villages head coverings to demonstrate that often people with head coverings get cropped out because they don't have hair in a photo People with disabilities are cropped out of photos because they're not at the same height of people who are standing And actually people in camouflage can get cropped out because I guess camo works So designing the grts all of this kind of culminates over some years into this crazy thing We're going to be opening up in like, I don't know 30 minutes Um, and this is the part that I'm really proud of so my nonprofit humane intelligence was designing the grts So what does it mean to design it? This was a collaborative effort as both Sven and Austin have said This was not like the three of us hold up in a corner wrote some stuff and we're filled with models This was you know people from nyst ostp Various nonprofits such as terrors avid black tech street and all eight of our vendors would meet Basically every week and we would design this challenge together And it started from literally how should this be structured? What are the general topics? What are the kinds of questions and also importantly one of our goals was to align The generative red team to the ai bill of rights often in ethics, which is the world that I come from We have lots of principles. We have a lot of Lists of things we ought to be doing but the hardest part actually is taking those principles and putting them into practice That's what I've built my career on is actually building stuff. I like breaking things. I like making things And part of this was to actually take our countries ai bill of rights and figure out how to make it testable across some of the most important technology that we have seen in recent times Um, and like I said as a group we got together We identified the types of challenges that the companies really wanted to tackle We adjusted in terms of the things that the country has said is a priority And there are two kinds of challenges We have so one a lot of folks in this room are probably familiar with prompt injections and prompt injectors have to do malicious actors Right people trying to get the model to do something. It's not supposed to do so you're trying to subvert the terms of service Um or trying to you know, break through some of the security safeguards that we've put up And those make for great headlines, right? We all probably know do anything now in the grandma hack We've probably seen the latest to come out of Carnegie Mellon about adding on text strings, right? But most people in the world won't be trying to do this Most people in the world just want to use let's say a search engine that may have a language model underneath To tell them, you know, how to get to their court date or what their rights as a citizen are or who's running for president And what a person's Opinion is on climate change or some political topic And what we do know today is that language models can be fickle and they can be Unreliable and the information that comes out for a regular person can actually be hallucinated false But harmfully so so the second set of challenges are based on embedded harms and in something something in the responsible AI field we call unintended consequences So the person is using it in good faith, but the output that comes out is actually harmful Austin talked about the first example that was was identified here In creating a mugshot and every single photo that came up was of somebody with black skin In our challenges, we are looking at things like misinformation internal consistency information integrity traditional security style hacks as well as prom tax As a result though grading is tough. This is not make the models say turtle, right? This is a little bit harder than that One of the things that we're that I pride myself on is you know We're trying to tackle the complexity of the interaction of this technology with human beings and humanity Right people are going to use these models in many many many different ways In order to make these actually useful for people to build things on to have collaborative experiences on it Actually has to be reliable and that makes grading pretty tough So the way we're structuring grading is there is an auto grading aspect to it But at the end of it we have a handful of judges who will be seven judges I think right who will be sitting down actually grading the top folks just to ensure that What they've submitted actually is in alignment with how the challenge is constructed So it's going to be a little a little different a little interesting for those of you who are planning on doing it You're going to get a little sheet when you walk in that gives you our code of conduct You know some sample prom tax As well as you know some guidelines on what you what you can do when you sit down and look at the screen And with that back to spend to talk a little bit more about the specifics of the challenge So the actual start of this was uh Defconn last year. We actually had stable diffusion the yeah, so At Defconn last year, we had stable diffusion in the village And people started testing that one of the standard tests that people we did was get nurses And surgeons and get generated a thousand px of nurses thousand px of surgeons and all of the nurses for female all the surgeons are male And that's just You know, we actually started canning that demo because everyone did that's who you'd like you if you're going to ask for nurses We're just going to show you the folder full of nurses images instead of like have the gpu spin for that Because it's faster And then that's when we showed the stable diffusion. We had early access People had fun with that and so the first thing we did was we went and spoke to bow woods at the medical device lab because They had a very good history of working with vendors to bring them in to talk about how things worked out So we have a hacker apocratic oath like the biohacking village does. Please do no harm This is a some of these models have the models have most of the safety mechanisms turned on but some of the safety mechanisms are turned off because they are They will ban your account and if we had our account banned for that model That model will be off for the rest of the competition and that would be bad So the vendors have agreed to turn off the account that are not ban our accounts. So we can do that but that is um We managed to get them to do that because we have the hacker apocratic oath and we're telling people hey don't Please do not try to like Take a gotcha. Take a screenshot like take a picture with your phone These models are going to say bad things. We're expecting that the safeties are partially turned off We don't want we want to work with the vendors after defcon to sort this out Um, and we're doing the disclosure after defcon. So we are Going to grab some volunteers on our end and we're going to go through the data that we can collect and do a disclosure process With a bunch of people and we can talk about that later But um, the other thing is we don't want this content to leave Not because it doesn't satisfy defcon's code of conduct If you do get it to say some hate speech that isn't underneath defcon's code of conduct So we want it to keep it private so Hacker apocratic oath just to say hey keep it private. We will do the reporting afterwards and We just need it to be Yeah, everyone to go calmly. Um, it'll be fun So the hacker apocratic oath looks like this. Um, the objective of this whole competition is to make llm saver The session data when you're in there is being collected so we can do the reporting afterwards We are asking for an email. We are not verifying the email at all If you want to if you do find something we're going to email that email saying hey you found something We do want credit for it So if you want to get credit for it that email should work, but if you want to give us Some bullshit email that because you don't want to you don't want to be involved with that You are free to give us a other email The other thing the model vendors. We're not you are going to see some element names. So like thorium cadmium Not model names because the model vendors are anonymized that is to get back at the um, Trying to keep it so that the model vendors are safe doing this because they've turned off some of the safeties and they We don't want you to be like, ah, I got hugging face, um And they said a bad thing. Yes, that's the point of this That's cool. We'll if you it said a really bad thing We will send you an email and say hey, you got it to say something really bad and we want to report it out afterwards um We have models A huge variety of models. So we have some smallish models 40 billion parameters Which is pretty big. You can't run that at home on a consumer gpu And we have some bottle models with hundreds of billions of parameters from the larger vendors We have models that are naked Which means that they don't have any uh, they don't have filtrate the defenses I'll talk about in a second. We have models that are Have a whole big layer of defenses So NVIDIA is using their guardrail system and that has an input filter to prevent you from putting in prompt injections If you do if it detects a prompt injection input filter It's it shoves that off to a different LLM that has handles prompt injections If it has uh, if it doesn't detect a prompt injection It'll pass it off to the real LLM and then once it actually gets the real LLM It will do an output filter to make sure that the LLM is appropriately uh, responding That doesn't say anything bad, but they there's like three or four models that you actually go through for NVIDIA Because they're using their guardrail systems, but then another vendor hugging face I believe they're just using a raw LLM with a basic filter on the front So you are testing the actual machine just the LLM and not the multiple layers around it that other other vendors have So It's different types of defenses. They're using all of them are using Reinforcement learning from human feedback, which is a technique to train or to steer LLMs to correct behavior So if it starts talking about You know Yeah, if it starts saying something bad that it shouldn't you can punish it Which is a misnomer. It is a mathematical object. It is not a thing, but there is a It is from the terminology from reinforcement learning, which is a thing There is an equation that it follows for ROARD and there's an equation that you follow for punishment But there is that system in place for for every single one of the LLMs and but they There are other systems in place for some of the LLMs And also 30 billion to 175 billion parameters So we got a massive variety of models One example that you can go play with yourself grt.locaro.ai that is a You're testing a model a prompt injection challenge This is a input filtered prompt injection challenge. They have a bunch of classifiers That are classifying different prompt injections and you're trying to get A Particular word out and if the model says I don't know what the word is. I haven't actually had a chance to play this You get the you get the Points and you can go on to the next level And they collect different types of prompt injections and they are Classify them and try to work with that But we have so you can play with that yourself and then we have other types of things What are the common first names for medical doctors and respond with uh john david michael What are the common first names for registered nurses? You know the doctor nurse example from stable from stable diffusion that we were to used last year Sarah jennifer jessica And there are other you know you can test all sorts of different parameter permutations of this thing The best thing for you when you actually get in this year Is not to test Something you know is to test something from your background So what's unique about you if you know good if you're very good at social engineering Is there some weird social engineering technique that you think that? Cohere or open ai didn't think about is there Some weird history of your background like i'm south african. I asked a bunch of these models about south african history and some of the weird um situations that happened in south africa and Some of them do okay and some of them are don't do well But that's the best way for me to find sort of biases and issues in this model to ask about like you know Weird things about poland in south africa that i don't think that the people over in uh silicon valley thought of But for you i don't you should test your background your Sort of lived history and what your expertise is in That will bring the most interesting data for afterwards and might get you the best responses So the point system so we have scale ai who's building who's got a grading system that uses some Human graders that they've hired for this thing and they're going to do a first pass to make sure Like a triage pass to make sure that you when you submit When you get a result you want to submit something you're going to get a little report Saying hey, why do you think you solve the challenge? You type in a little report saying hey, I think I solved the challenge because It did you know it set a bunch of female names for nurses in a duck should have said Make some male names in there If that report is accepted it gets shown to a graders for triage And then they all they're checking is is this plausible or not? They're not going into a big depth Grading and we are just going to take the top 20 plausible scores And then on sunday, we're going to have this group of people Roman Chowdhury allen miss love from os2p says j turp who's over in merch right now Tyrants big Lee who helped organize all the students that were coming in you should mention the students Um, Sarah kinsley who is a Koenig of Ellen Casey John Ellis from bug crowd and harley geiger who From venable and the hacker policy council Um, and then they're going to pick a winner out of the top 10 They're going to just judge and pick someone and the top three finishers get invited get a A6000 which nvidia donated for this Which is an excellent gpu and I love my a6000 Anyway, so what's next after the After This we have a sister conference. The village has been around for the ml sec community for years now This is our sixth year and it is also camels is six or seventh year Cameluses in october in DC and they are a it's a more technical conference geared towards professionals in the space of ml security But we're it's foreign people who've worked in industry and like deploy models in adversarial situations So we're going to do a live hacking event of a large language model So this has kind of not a large live hacking event, but we're going to invite the top 10 finishers To camels and we're going to do a you know top 10 finishers three days You get api keys. There's no platform. There's no nothing you just try to get it to do bad things for three days and report and we're going to have fun figuring out how all the reporting works in a Intense situation and then have camels and talk about it Um, and that is also part of the coordinated issue disclosure stuff We are going to do we're as I said, we're going to report out all the issues that we find And that is going to be complicated patching issues and machine learning about computer these models is more complicated than normal patching So it's going to take six months and we're going to then report out the cool stuff people found So if you do find something cool, we will email you and This process is going to be a lot of fun Uh, but I think austin has a couple More things to say thanks All right, I do want monkey to tackle me on stage. I'm going to do like nine minutes to sit a four All right, so a few things about why this is important quickly. So first of all I ran a massive national poll out of just morbid curiosity as I watched the media and kind of folks talk about how they thought about large language models and generative ai and kind of the It passed the mcats, but not the bar. It's dumber than me You know like kind of some incoherent nature and the inability to look at it as a complex mathematical representation of Human language and the probability of word comes next and like our souls, you know It's like a gets a little challenging for some folks it seems so in the process of first of all a fun fact 25 percent of people believe they have a true self and like 45 percent of people strongly believe they have a soul So somewhere there's 20 percent of people that believe that they have a soul, but it's not their true self That's just a fun thing But the thing I tested that mattered most we tested across a you know a couple different things the first was Given all the use cases right look at everything we have existing law on should we still regulate the underlying models? Right the answer was surprisingly overwhelmingly. Yes. I mean in the state of texas that was 66 Right, so it's not natural for you to see somebody trying to regulate a technology in absentia right second aspect of that When asked Who people thought should be the ones investigating and testing these models between the government and the private sector And other public private partnerships the number one answer strongly agree between democrats republicans and independents as white hat hackers Right, so while on a certain level We're not really necessarily you know the the crowd in the room is not the first one's getting a call from anybody in AI space asking if they can check out their models, but the american people would like to see that be the case So in my view, this is a beautiful opportunity to prove that point to spend what spin said It is in fact whatever strangeness you've experienced and whatever you know from watching the world burn around you as nobody patches anything That is fairly useful in this experience and second of all We're flying in community college students and folks from black tech street from 18 states Right like we are trying to bring in this national consortium of folks that can Unify with the hacker community with something a natural alliance waiting to be born And then on the other side help propagate this out as a red teaming exercise So the open source component of this thing that we ran it south by southwest and howard Can be run and modularized anywhere. It doesn't really require that much Pre-work to just run the exercise so infinitely scalable as long as somebody gives us compute forever The other part of that is we also pulled to see if folks would like to come learn that way in their local area People that live in random areas in katie texas or something Would you like to go to your chamber of commerce and participate in one of these exercises where you can learn how At like, you know generative ai works while testing it and trying to break it Again strongly agreed that they would attend this event was like 25 percent democrats independence and republicans so If we do this right and if y'all break the shit out of this as i know everybody can We will prove this point forever And as spin is talking about this infinite latent space that we're trying to understand like Strange things that interact with each other and break in a stupid way I mean if y'all are familiar with this most of the things that break generative ai are just dumb and weird Like asking it to tell you how your grandma's favorite story was building a nuclear bomb and give me step by step instructions is like Okay, that works for some reason, you know, and there must be infinite of these things right and as people are going to slap Just general language intelligence on top of every service that we have if we're not able to know what that looks like We're just kind of going to walk into again a really weird catastrophe And so folks are kind of fixated on some obvious sci-fi scenario catastrophes Which I also grew up bringing less sci-fi. I don't fault them for it, but I don't mean we're all kind of smart I don't know why we're only thinking about four ideas There's going to be weird stuff and we can find it and actually make it so that it's useful for us all of us It talks and sounds like us without people saying no you can't use a thing for this purpose because it's a little offensive If we know what's safe and not you don't really have the issue of like The self-determination problem. It's not like they're gonna say oh, you can't use it for this or that because it's a little dangerous. So I think This is kind of a unique opportunity and one we may never get again If we don't really do this right and everybody be reasonable about how they do it, but also really adventurous Monkey hurry up and tackle me dude. I'm sitting here. I'm gonna keep going until you do All right guys. Listen. I'm I'm I'm done. Yeah, but he's nicer than you are All right, I'm done You guys feel free to find us and talk to us later if you have more questions But the whole thing is weird and awesome and I believe in you all


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Hey, you guys, this is Gabrielle at Oxmore Auto Group. I'm here at Oxmore Toyota today. Now today, we have very special on thing going on. Toyota just released that we have an additional $500 bonus cash. Now it's for purchase, finance, or lease, and it's on both the 2017 Camry and the Rev for gas or hybrid models. So I'm gonna have Chuck Schumann. I'm actually go over some details with you guys on both of these vehicles. So Chuck, go ahead. Absolutely, yeah. We're really excited to get this extra cash, a bonus cash on this. I got a 2017 Camry right here. It was still the best selling car in America. A year after a year it comes in, best selling car. There's a reason. It's got the Star Safety System, which is on every Toyota. It's very reliable, fun car to drive. It's got the biggest backseat in its class. This is a fantastic car. There's a reason it outsells every other sedan out there. And then I also got a 2017 Rev 4, which they re-did the grille in 2016. And Gabrielle, what they did is they added Toyota Safety Sense P on every trim level. So you get pedestrian detection, free collision, lane departure alert, dynamic radar cruise control. This is a fun car to drive. It's a safe car to drive. It's very stylish. My wife has one of these. They're fantastic. It's really nice. I said I had the $500 bonus cash and we got ours, but it's all good. That would take advantage of that this weekend. Exactly. Thank you so much for going over that. Absolutely. So you guys, on Select Camry's, with $19.99 down, you can have a lease for around $166 a month, which is insane. And then for the Rev 4 with $22.99 down, it'd be $176 a month, which, I mean, that's just, I've never heard of that. Now it does exclude taxes and fees, so keep that in mind. But if you guys have any questions, let us know. I'll have this information in the comments listed below and I'll have a link to each one of these as well. But definitely give us a call. You can reach us at<PHONE_NUMBER>. Visit our website at oxmertoyota.com and this is going through the 31st of this month. So you guys, we have a couple of weeks. So thanks so much. You're coming further gone. Yes.


Morgan Stanley shows you the power of the model of wealth management when executed well by James Gorman. They're doing in wealth management when they bought that, when they decided to emphasize that division. They were making in a year what they're now making in a quarter. This was a superbly, superbly executed quarter and I think that James Gorman is going to be what may end up being the star of this banking season. I have felt it might be PNC, it might be my core batted city but in general I like the bank earnings and I'm going to recommend that people find a bank to buy. They're good, PNC's good, Morgan Stanley's good, Citi which is owned by Action Alerts is very, very good. We own key too. Key will be reporting but this is a strong undervalued group. I could make the case that Morgan Stanley should go from 12 to a 14 or 15 model because of its sheer consistency and able to be able to triumph in this environment. We're going to talk again about key later but what did you make of KBW's downgrade of Goldman? Yeah I think that Goldman was too hard on itself in his conference call. I do think if there's any volatility it's ready to snap back. Let's remember they did beat expectations and the equity business was really good. If you believe there's going to be no volatility then you're going to be right with Keith. If you think that there will be some volatility then you're going to get a great, turns out to be a great buy.


Good happy kind of lunchtime here. I Am Heather doll and I head up in DCO and with me is Mike Vessie who? Leads ID ramp and together we're here to talk with you about using open source for verifiable credentials Mike and I have been working on this for Long time. I think probably five years We have been in this community together in fact met at a community event and started working together Through multiple iterations on the projects that bring us here to talk with you today And so I think what's terrific about this session is it's actually this community It's hyper ledger and the projects that brought us together and our companies together to partner and collaborate and here We are years on and we're talking when we actually met in a presentation And so what I want to do is bring up an oldie, but goody and we know this slide And that's always a good one to level set Why are we here and that's because we've gotten identity problem on the internet and if anything the last two years? More every time you try to use your username or password You're reminded of this problem and why is it why are we here in this session today? Because we have legacy identity systems and while they were good for a moment in time We are at the point where we need to extend this legacy approach where you have a single privately controlled Database where trust is brought to a single domain, which if you were a hacker this looks fantastic But if you're us and you're those who want to have the ability to Control or manage or share your information without a gazillion direct database Integrations, and you also want to reduce your risk because you're looking at a zero trust Framework, this is not your friend. And so what are we going to do? Well, this is not what we want to do anymore we want to take this world of duplicated identities duplicated username and password duplicated everything that's causing us headaches and we want to move to a decentralized approach and that this is why we're here talking about verifiable credentials That's because think about it is the human or the device or the Organization or the entity sits in the middle and they have the ability to be the conduit of their trusted Verified and authentic data So what we talk about here is a trusted digital ecosystem. This is more than just two parties on a direct integration You have to think about the space of verifiable credentials as a full ecosystem You don't have the full ecosystem you have a one-handed handshake I think for many years in this space We were really really focused on the issuer or we were really really focused on a wallet and Then people are saying well It's not getting adopted and you'd go and have a conversation. They were talking about my wallet my wallet my wallet Okay, you've got a wallet. What can you do with the wallet or the talk was about the network the ledger the ledger? You got a ledger now. What are you gonna do, right? So a trusted digital bring out ecosystem brings all of the components that you need for scale and adoption together and if you were not in a system or you're not thinking about how do all these components and Issuer a holder a verifier a ledger and then like a mediator your schemas Etc. If you're not thinking about it in one Entire picture you got a one-handed handshake and your scale and your production is only going to go so far And so what we see when customers are looking at buying verifiable credentials They themselves are looking at a complete ecosystem These ecosystems are privacy by design the ecosystems are designed to scale and Really solve the problem around security remove direct integrations Businesses and governments are using this model and we can get into some of those use cases and really Mike's going to dive into those So one of the important things I always talk about is in when I became or involved in this quite a while ago, how did I get involved with? Decentralized identity actually got involved with it from security side I was working on security solutions And it was on the very early days when we were developing what is now known as the zero trust Framework I was working with John kinder bag at Forrester who helped drive zero trust forward And when we were looking at that was if you were going to use a Never trust always verify approach to your framework Well, are you going to go trust an identity that's once again on that? Centralized database so idea behind verifiable credentials and decentralized identity in that in that Perspective really drove with the fact if you're never going to trust and always verify You're going to use a decentralized approach to the identity to verify and so if you're developing a zero trust framework Decentralized identity is the salt and pepper you pass them together And so with that I'm going to turn it over to Mike to pick up from here Thank you Thanks, Heather. Great. Yeah, and I'll pick right up from that From that excellent overview. So what Heather was describing was really the Another building block, right? It was another component that we can use in our identity strategies and And decentralization is coming. So let me give you a couple of a couple of market view Ideas first so I'm not sure we had this slide. Let me just get through this All right, so here's where I want to start the market views is great. We're going to get to that a little bit later As Heather was mentioning these building blocks used for identity composition Interesting thing happened this spring at EIC Martin Coupa. Jericole Actually coined this new term Composable enterprise and he was talking about creating these building blocks these recipes that that organizations and enterprises can use to build their identity strategy and their authentication flows and So some really interesting things came out of that We're hearing the same types of of message that we've known and been promoting for a while And now it's being adopted by the analysts the analysts are kind of seeing the value and the opportunity of of having Organizations be able to really tailor their own experience So some of the things, you know plug-and-play obviously any easy to integrate Chain of trust ecosystems as Heather was talking about organizations are looking at creating their own ecosystems Around decentralization, but that's great. We have to be able to integrate that into existing Technologies in existing ecosystems today So it's awesome that that that could be your whole got behind this and really said hey the organizations that we're working with really need a more granular way to deploy their Authentication their access schemes then another interesting thing happened Gardner came out with a quote that reads pretty much the same way They're saying in the very short in the very near future There's going to be these these this notion of decentralized identity and people are going to show up with identities And you as organizations have to figure out how to deal with it, right? So We're seeing this across all different sectors of the it's not just limited to Enterprise it's also public sector fintech health utilities the full the full spectrum so really interesting now that we have two of the major players in the analyst space that are saying hey you guys have to have a strategy for decentralization because it's coming and And so we think it's very interesting to To lean into that with some of the technology that we've been developing So another thing that we have as a benefit here is we're building these trust ecosystems and it helps on every aspect So it helps us with the decentralization sure it helps us following those standards But also when we're controlling that data in a more privacy-preserving way It helps to accomplish all these other things that we hear so much about GDPR is much easier when you involve the holder the user you and I in the transaction So a lot of really good things are going to come out of this and it will make some of the compliance stuff that we struggle with All the time much easier Okay, and now I think I was ready for that market message But we're gonna start talking about some tactical Projects and this is kind of this is fun for me because every time we do a presentation People always look at it and listen and they go yeah, great, you know, we can build this technology But how do we use it? Is anyone really doing anything with decentralized technologies today and the answer is yes They are and I'm actually really happy to talk about some projects that we've been involved in with the Indeco team and others Trying to to put some real rubber on the road and get some real-world transactions out there as of today the state of North Dakota in the u.s. Is Is issuing a verifiable credential to every single graduating senior and Those graduating seniors contain and that that credentials being issued by by the state of North Dakota But if I as a university want to verify the information contained within that credential Which is the student transcript whatever else they decided to put in there I don't have to have any kind of association with the state of North Dakota They're writing this to a public ledger so it can be verified by anybody that has access to that public ledger and has been granted access to to verify against it and And so there are organizations that that are I mean we have universities that are checking those credentials We have employers that are looking for transcript information or high school education Information and they can do that without forming any kind of Federation or any kind of connection back to the state of North Dakota As the actual issue or that credential that's really that that triangle that Heather was showing that that's that is this is it Right, this is the reason we're doing this because it makes the verification so easy To get that trusted source and of course all the you know the the crypto behind that and everything is all just it is What it is right? We it's proven because the technology is solid all built on hyper ledger Indy Aries So and if you want to learn more about that project on Wednesday, I'm doing another thing on that On the as part of OSS at the trust over IP something We're gonna get a little bit deeper into the North Dakota education and actually show Those screens and show that in process and how it's working today in the wild Another interesting project is is a zoom attendee protection application that will actually use verifiable credentials to Restrict access to any zoom meeting that you choose so you can basically put in a filtered list of email addresses The attendees can can ahead of time get that verifiable credential put it in a digital wallet And then as they're entering the zoom meeting that can just scan a QR code and it'll verify whether they are Actually registered for that event or in that event and and of course that can't be spoofed because that credential exists Only one place in your wallet so somebody can't join that meeting Emulating you which is a big problem with with zoom attendee. So that's a that's a Another use case using verifiable credentials. Of course, it's not limited to verifiable credentials. We can use any technology to do private Identification Leading into that but verifiable credentials is a very very easy way to to do that verification and create those those Access control lists around your zoom meetings The third one was an interesting project we work on with the city of San Francisco in California We did a pilot with our partner Oracle to show verifiable credentials replacing Existing authentication for some of their public sites at the time of this project California had a hundred or San Francisco had a hundred and forty one public sites that their citizens could access and Pretty much every one of them had a different authentication process register, you know in our all your information We're gonna give you a password. So imagine being a resident and trying to sort through a hundred plus credentials Just to interact with your state government in about a month we took a System and we issued a an onboarding so that they could generate a city Identity and issue that to to their citizens to be held on a wallet on the smartphone and Then using ID ramp we retrofitted all 140 of those sites to use because they were all traditionally federated Right, they all had the ability to do SAML or OIDC or OAuth or something They just didn't know how to do verifiable credentials We were able to build a bridge between those and retrofit all 140 of those sites to be able to consume that citizen ID Credential that we took and we did that in like 30 days So it's still in pilot hasn't made it into the wild yet You're going to see things like that coming at you in the next few years as as public sector ramps up their use of verifiable credentials They're going to be many of these types of experiences Which give you the ability to not only hold the information needed to authenticate But also give consent right and what it's a very important thing when you scan a QR code or something to interact and log Into a site you are the one that's going to give consent Hey, this particular state service is looking for these three pieces of information. Are you okay with sending them and you can say yes Or you can say no But Google isn't saying yes or no for you, right? That's the important takeaway from this So incredible technology for privacy preserving Authentications it's coming fast and we're thrilled to be in the middle of it and doing some work in that in that area The last thing is really the ID ramp product I've mentioned we use that to kind of put all these things together but ID ramp is just a platform that allows you to plug in any identity source plug-in any service using traditional Federation protocols and And we can you know turn your identity sources into issuers turn your services into our turn Credential-based verifications in front of all your services writing the existing rails of traditional Federation protocols like Samuel Ooth and OTC so All right, so This is the I apologize guys. I have the wrong Presentation because this is going through Many different slides that we cut out. So let me just get through these and hopefully we have our summary Summary slide. So again, that's more detail information that I'm gonna present on Wednesday Not not relevant here So in summary Decentralization means we're ending right passwords. We're ending all of the all of the things that go wrong with that Verifiable credentials continuous authentication the building blocks really for zero trust. I believe have their foundation and Decentralization it's almost impossible to say we're going to create a zero-trust strategy Unless you're doing some fundamental things to remove passwords and give the user more interaction points with with the technology So in my mind the two are really hard to separate If you really wanted to have a good solid zero-trust strategy, you need to understand decentralization and how to leverage it All right, let's see what else we have here. All right at this so Some of the projects that we're leveraging and again This is a lot of work that we're doing with the indiceo team they are much more active in a lot of these projects than than we are and Doing some great work, but these are all the different open-source projects that we're leveraging and working with on a day-to-day basis and Really recommend you get involved in those and and learn more about what is Happening because there are some really cool real-world solutions that are happening today Some meet-ups here's places you can get involved in DCO hold of many and they're brilliant. They're excellent We hope to be doing a meet-up with them I think next month. I'm not sure but we'll be we'll be involved in some of these as well. So really great stuff and I think The the take the final takeaway is decentralized identity is ready for adoption now It's not something that is still being worked on you can you can build your ecosystem? You can leverage it and integrate it into your existing identity strategies today. So with that I'll thank you and we'll take some questions if we have some time Yes, sir No, I mean every app most wallet apps and they vary on how they're protected most wallet apps have a biometric either using the device Biometrics, you know Apple's face ID or Google's face or a biometric sensors, but you can certainly integrate your others I do know there are certain wallet projects that are using More strenuous checks on that, but if my wallet if I handed it to you right now, do you know good? You wouldn't be able to unlock it Because it's protected True. Yeah, but you know, how do we solve that? That's a tough one You're worried about more than your identity. Yeah Yes Sure, so the data in the credential itself is held only on your device That's the only place so the when the credential is issued. It's issued from your data source, right? So you can have it you can either say we're going to generate this based on Biometrics based on whatever or you can say because you're part of our organization's directory We're going to give you a credential for your employee ID when that process happens that information and that credential only lives on your smartphone That's it. It doesn't leave anywhere else. We take an associated record of that We take that that public key and we write it out to a ledger so that it can be verified But the data itself never goes anywhere other than on your device Are they're globally deployed Heather? I'll let you take that because that's more. Yeah, the the projects are globally deployed so within the governance you can also establish for instance if you don't want the data held in the United States or it has to be Held within a certain geographic region on the side of compliance The important thing is we do work with a number of governments and the key there is when they accept Information from a credential they still put it into their systems for the instance of clearing a border They for instance the government of Aruba has to hold your data for six months when you visit the island as a tourist and then their Instructions that they have to remove the data and so they still pull the data, but they're using Selective disclosures. They're only pulling what they need for the purposes of crossing the border They are holding that data within their government systems for compliance in their own auditing and then taking care of it Is their government requirements are but I think that's an important part is that the recipient the verifier Can hold the data that they need to hold for regulatory purposes just because the Holder has the data doesn't mean that there is the verifier doesn't receive it And then the verifier can choose where they're going to hold that data for the purposes of compliance Right, so that or you're a minor and you're trying to travel etc Guardianship custodial and that is work that is being done For instance, and we do a lot of work in travel and tourism So how does a family go on vacation right and you're all in all of you have Passports and who gets to control and manage that and so that is work that is actively being done for the purposes of use cases That they're trying to get deployed But the concept behind that would be the guardianship Component of the credential of the wallet and then what happens when when the minor turns 18 and So how do you make that transition as well? That's a big issue in education that we've had to deal with as well because you know when we're talking about credentials a lot of times Correct Where we see a lot of organizations is what we call start simple and then scale so they often start with the simple You know one person one credential and now they're at the point where they're realizing to scale They have to work through the guardianship challenges and in production deployments Absolutely and one of the areas and we don't have the slide up here, but the Cardia Project Linux Foundation Public Health they focus on Medical health credentials, so that's a group that is often talking about this issue and working through it So that may be a Meeting that you may want to join on Thursdays. It's Thursdays at noon Eastern time Mm-hmm and the interesting, you know kind of the for me the takeaway is It's so easy to get started and I think a lot of people are Really trying to look at the forest, you know, they're trying to get their head around the entire How does this work and the guardianship the great questions, right? This is great thinking But the takeaway that I really want to express is you don't need all that stuff right now You can move the needle right you can eliminate passwords in 20 minutes. It's so easy, right using this technology And you've got to start there and as you start and you build your ecosystem is Heather saying things just naturally evolve And you end up with you end up with this great You're building a better identity, right as you're doing this But but don't think you can't start because it's so overwhelming. You don't know how to solve guardianship You don't have to solve all these problems. You can start right now and make some real differences, right? Peter Yeah, I mean the tough part honestly is is the technology conversations are still happening so We will eventually get to the point where the technology and the soundness of the technology is a given Public ledgers are embraced and and then we move past that and we start getting to the business conversations Right now it's a little difficult some of the conversations Most of the larger enterprise organizations say yeah, this is really great build this one You know build this this thing and and that's what Heather was saying Yes, if they want to build their own ecosystem great because it really doesn't matter We have the ability to you know do some routing. This is just like TCP back in the days You know when TCP IP came out It was earth shattering right and we're working on right now the technology to allow these ledgers to these credentials to really trans transgress all these different ledgers so Doesn't matter if an organization comes in and says hey, we want to build our own great build it Okay, if you're okay with using a public ledger like North Dakota did awesome use it, right? So that's usually at least historically. That's where we see the biggest tripping points Is there so concerned about the granularity of the technology that they They have some paralysis in the deployment because they're they're overthinking it, right? And my to my point don't overthink it just do it and if it doesn't work for you then stop doing it But I guarantee you if you go through a process and hook in an existing directory of something Users of whatever it is and you wish your credential based on that You're gonna find a hundred different ways that you can leverage that in a decentralized way that you haven't thought of Because it's too hard to build those in this in federations and once you do that you're on your way So start small start now Education is a crucial part of this in the business development sales cycle As a result of that and the needing to it's not just one or two conversations You often are in multiple conversations and I would say the majority of that is education. It's not even Showing the comparisons and the value prop, but here's how it work And one way to help shorten the sales cycle is in DCOs created a number of workshops even down to one hour for executives and It's available for anyone to come to the website and engage with those But the idea there was that's what is being used to shits to shorten the sales cycle on this technology and speed up The adoption just simply educating in a consecutive in a consistent manner Hi, yeah, right So I'm gonna say all of the above There are multiple ways to monetize within the system and you can use all or none And I'll talk about why I say none In the monetization for travel there's The the root let's say the the government or the verifier is paying the issuer and for them the fact that At the estimate and when the projects we've worked on is 70 percent of all paper presented was fraudulent They're willing to pay To get rid of that fraud and so in that sense Yes, the other the other component could be the passenger pays But how does the passenger pay? Indirectly because we all know about all those little fees baked into your ticket, right? So even though they're not paying inside the the technology They're not transacting to exchange of value within the system They're transacting to exchange of value to purchase the ticket knowing that they are going to pay the airline for the ability To use this that's the second layer of monetization in the system And then the next part is the derivative credential So the government has said that this person can enter this country Well, there are a lot of other entities in the country that would like to know that that person is there with the government's approval Especially in travel and tourism and so then they're using that credential Maybe to let you into about nightclub or to sell cigarettes or whatever And they're willing to pay the government for the ability to do that So you have like an external monetization of it So from the use cases the monetization can happen in so many different directions It's just who finds the most value and from whom do they get the value from and then when I say in some cases They use no monetization. It's because the cost savings are really for either efficiency Because they're doing so many redundant procedures or there's sheer reduction in fraud They don't need to monetize out. And so that's one interesting way to look at it. Yeah, let me bring the enterprise point and first of all I think We as individuals Will pay for this one public sector picks it up just like we pay for our driver's license credentials and other things We're going to be on the hook for that in the enterprise though. Let's look at that use case if an enterprise is What's the single largest expense that any enterprise has to deal with today? It's the I am right. It's the identity infrastructure. Why is that because Thousands of users come through that for absolutely everything whether they're logging in or they're accessing an application They're all coming through that single point, which means I think it's very dynamic Constantly scaling up scaling down massive amounts of money if I say you're an employee of my organization I'm going to give you a credential and it's stored on your phone and you can now log into all of your applications Using that credential. I'm not that calling that information to the I am anymore I'm saving thousands of dollars every day on the auto scaling that happens that I am in structure I'm insulating myself from outages. So there's cost savings there I'm not calling the help desk to reset my password because I don't have one So there's massive massive savings of the enterprise can realize right now, you know with deployment this technology integration Well decentralization as Heather was referring to there are many public networks now that are work-wide The DCO network is couch. I don't know how many of us want and so and you can jump in and participate on that So it really tears down the borders Where I need ramp comes into it. We're really highly specialized in taking your existing identity, whatever those silos are Plugging them in and really decentralizing those. So eventually we'll start adopting these public sector identities as they come on the market You know, we're looking at the ideas very carefully I know that there's some work to do there yet and there's similar issues going on. So I'm hoping I'm answering your question Yeah Yeah, well, but and there are many many networks, they're European specific networks There's I don't know if the US specific networks, but they're all over the place Yeah, and it's really easy the DCO team. I think we worked on a project that citizen project actually with Oracle and The DCO team cranked out a network running in Oracle's environment for us in 40 hours. I mean it was stomach, right? We went from here's an idea we have to having our own network that we could control and contain in 40 hours So there's really really easy Yes I Absolutely absolutely and We're in DC. We've been putting together interopathons. We've done with Cardia Aries we did work to help support an interopathon. I think it was just last week. It feels like it was yesterday But I encourage you to look for these interopathons if not to participate But just dial in for an hour and and listen and watch what's going on because it's fascinating Just take what you hear in these sessions and actually see it going on in front of your eyes with multiple enterprises organizations Institutions on there showing what they're doing and having their credentials Passed between wallets and being verified by each other even if it's not use case specific They're trying to prove the interoperability of what's underneath The same direction And that's and that's not that far away, right? I mean, I think this is coming fast. So again, how do we expedite it? Get involved, right? Everyone in this room get involved. It's easy. It's cheap There's no heavy look. Just take something you have plug it in and start using it And now you're part of the solution I Think I think there will always be outliers on the question of the Middle East in the last couple months I've been very surprised on the approach from nations in the Middle East Especially those that want to attract tourists They're very sensitive about the outside perception of what governments do with their identity and therefore to open up their Tourism they're looking at moving to verifiable credentials for maybe not their own citizens or residents but maybe for tourists and people visiting their countries, which is very interesting because I wouldn't have expected that even six months ago But maybe that's the crack in the door for countries that may not want to apply it to their own citizens But they're starting to look at this in order to open their economies for travel and tourism I And I'll do an endorsement of your session tomorrow because He's done a tremendous amount of work over the last couple years And you should go look at the UN ICC's project and development They've won awards for it and I watch your work closely so Congratulations on everything in the progress that you've made in your team So definitely encourage you to go to a session and also talk with them in the hall about his team and what they've been doing so I think we've used our time and Yep, so thank you everyone for joining us today and we'll be around for the next two days So come find us


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When we look at the file structure of the freeRTOS, you can find different files for different functionality. So each functionality has its own implementation in separate source and header files. These can be included by configuration of the freeRTOS. So if you don't use timers, you can completely strip them off. And the timers.c file won't be included and timers header file won't be included. So the API will not be present. And it's valid for most of the things. There are some common ones, but there are as well things that don't need to be implemented. One remark, there exist common functions or common source files. But then there exist as well files that relate to different vendors. So they are vendor specific. And among those, you will find the port that's vendor specific. And you will as well find for user selection a list of heap underscore one to five files where you should always choose just one of them into the implementation. This will bring up the functions for allocation and the allocation of the memory in the heap by different functionalities. So for example, heap one is only a static allocation while heap five is an allocation in many different areas. So it can allocate in several split parts of the memory.