We are now life Next the whole world has changed Everything is different Yet so many things are still the same we find ourselves In a new era we didn't expect to be here But it's so anyhow next consider Considered just how far we've come in technology Considered just how far we've come in the last 10 years in Communications how much tech has been developed in the last 30 years How much tech has been developed in the last 50 years and then how much technology has been developed in the last year and Where are we headed? by tomorrow Next now. I want you to consider that while we think about whereas technology then consider How far you've come and your individual and personal journey how has your distance been and More importantly to the question. How did you get here? What did it take? For you to arrive at the very steps that you find yourself in Right now How much opportunity how much help and how much direction was given you? Next stay with me. We have a trek ahead We have a very small window together a very small journey You and I stay with me Next we have to go back We have to go back We've come so far in technology and in our individual paths and our individual directions Of where we have arrived to finding ourselves. We were at and right now How advanced this world has become? But we have to go back We left some things behind We left communities Behind we left dreams behind and we have to go back Next we have to get those that left behind because if we don't do that Then all the technology that we've developed and all the technology that we create Will never be as great As it can be And as it should be Next my name is Christopher Lafayette. I'm an international and national speaker I've had the benefit and pleasure of speaking on Technologies such as virtual and augmented and mixed reality artificial intelligence machine learning and deep learning I'm an emerging technologist, but like you as a technologist It wasn't always this way. I grew up in a city called Oakland, California And I remember coming home every night and walking in and seeing a man sitting at a chair in the desk with a little lamp on and He was building up and tearing down laptops and desktops Putting them together and taking them apart again Neighbors and friends and colleagues would always give them these computers and laptops They put together to take up build them make them better fix them and give them back And I can remember sitting with this man in a car saying dad What's the internet and he would tell me and dad How does the web work? And he would answer and he would answer every single question that I had And little did I know that he was planting seeds and I was asking questions That would benefit me so much and so far in my career that I had no Sense insizable magnitude of what was happening. He was pointing the way And I was seeing someone that looked like me when I came to Silicon Valley with black-colored skin I didn't see many people at all that looked like me The fact one and only few examples that I ever had a technology Was that man that said at that desk with a little light on and technology I came to a world where I was taught by people that didn't look like me That mentored me and trained me and taught me And so the two instances that I've had in my life Thus far have been that man and Tech community That took me under And helped bring me up to where many of you are at today next Black communities We have to go back We have to get those that we left behind to bring them to where we and Many of us and you and I are at right now And let's be honest when you look around your office When you look at your zoom conferences When you look at the conferences that you attend and events that you have the pleasure of attending How many people when you look around That don't look like you That do not have black colored skin You see technology when we talk about ecosystem. It's not hardware and software and sprockets and Boards and raspberry pies That's not technology technology. It's culture It's human characteristics that are permeated in and throughout technological ecosystems And see the more culture that we have in our ecosystems It makes that ecosystem just that much stronger better healthier And so we have to go back our ecosystems may seem fine But they will only ever get so far Then we have more road to go Next hidden geniuses we go back for the hidden geniuses We go back for the ones that don't even know that they can build technology We go back for the ones that use our technology that we do build and have benefited and they have no idea That you are the ones that help build it and like you They had dreams But somehow some way someone provided you an opportunity or helped show you the way Can't we pay that back and can't we pay that forward? We have to go back next We have to teach We have to show And not just give it handoff But to show them Which way down the road to go and what to avoid What to go around How to look at this whole world of technology that you and I spend in almost every single day It with new eyes And new perspectives Their contributions will only level up what we've already developed and what we've already built Because the more culture we have in our ecosystems the stronger we will be It won't attract and makes us stronger and it makes us better, but it's so much more than just a feel-good initiative It drives revenue It drives opportunity Making our products more identifiable It diversifies And yeah It feels good Next To point someone the right way To give them the direction That's worth everything to those that don't know which way to go I use a small analogy that in the time of slavery, yes, that may seem drastic But it's real In the time of slavery There was a woman that came and with free slaves and people that have never been two miles outside of their radius their whole entire lives And when she had them she put them on a road Called the underground railroad and she would take them and she would say look up To the north star Follow that star And there you'll go to your freedom Now how much value was it? For someone to point them in the right way I liken that under technology and opportunities For those that do not know the right way Next It's so the greatest barrier and I had to look at myself And I yet submit to you that the greatest barrier And the greatest obstacle that we face to helping people go in the right way to going back and to getting the ones that we left behind Next The greatest limitation that we face In the greatest obstacle When we turn on our TVs as we've been seeing over the last several weeks And many of us seeing people that don't look like you and me seeing people that do look like me Frustration and hurt Hatred pain Dealing with racism and anti-racism screens for freedom screens for more and better That's not the society that we want And we now realize that part of the greatest limitations that we faced next Is you and I We haven't done enough We have not done enough Next And so I had to take time to look at my own self and say what have I not done What more could I do it was a powerful time and a powerful thing that happened But the answer came to me Servant leadership going back to first principles giving back that which was freely given to me Next so I built a platform Called the black technology mentorship program. It's an initiative that I recently launched There's so many people that have joined and came on as mentors And mentees and allies Is it chris? How can we help? How can we answer the call? What can we do? For some I said an hour out of your whole entire year is what I might want For you to sit in front of two thousand mentees students and to simply tell them what you do for a living May seem so mundane and so Small to you But for them It's almost bigger than life It creates more imagination to anything they may have ever come in contact with For the path with their career And for the path of potential entrepreneurship And so I'm asking you three things today I'm asking you to look within And see if you have the heart to become a mentor I'm asking you to go to chris or falafi at calm and not to turn your back on this But to hear these words and to do something about it To join me on this journey to teach and to give back That's number one number two Live it and fund it We just launched a fundraiser just today When you sign up for that mentorship throw a few dollars in If it's a hard time for you then share the initiative But we'll take your resources as well because some of these kids don't even enjoy wi-fi to get in and make even a zoom conference I want them to have the things that we may sometimes take for granted I want them to be connected. Can you imagine what it would be for one week without wi-fi? Now imagine almost a whole lifetime without wi-fi. I want to connect these kids Next and the third that I asked you Is to be the hidden hero be the one that they don't know about Be the one that helped change their lives and they may even not even ever knew that you were the one to do it Be the hidden hero be the one that no one knew In your office Could be the person To help change thousands of lives By small impact. Can you be that person? Can you be the hidden hero? Next because when you do find yourself becoming a hidden hero You'll take the first steps to removing barriers to innovation I'm so fortunate to have this opportunity at this time I'm so thankful for that man that sat under that little lamp It told me all the things that I ever wanted to know about technology All the things he could give me I'm so appreciative that the technology community You who i'm talking to today Has taken time to help teach and train me And help point me in the right direction Join me In helping point others in the right direction Thank you linux foundation Thank you all for taking the time And I hope in my heart That at least one person Somebody heard what was said today Thank you Christopher are you still there? I'm here Okay, we received a question from lisa I apologize if I am not pronouncing that correctly And this person's asking what's the link for the black tech mentorship program? Absolutely. So if you go to christopherlopiette.com You just go there and log in and all the information is there We've had such a such an incredible amount of people attending and Like I said, we just got started with this fundraiser just today. I haven't even gone public So this is the first time that we've made the announcement on that We'll be going public with it soon and our sponsors and people And we'll be making announcements about that even soon enough as well and Just such a good showing up and signing up of mentors And even our mentees our students and and and with our allies as well and even volunteers That just want to hand give a lending and and helping hand So I encourage everyone to go to christopherlopiette.com and just check that out And then you can always follow me on LinkedIn And hear more of the story and more of what we're sharing and a whole lot more of what we're going to be doing and And always reach out and you can always reach directly as well Wonderful. Thank you so much. And I think we have about a minute and a half left Does anybody else have questions for christopher? Okay, I think we might be all set and everyone is welcome to continue the conversation in the diversity slack channel In the event slack Fantastic. Thank you so much


The floor may not be in your old pot. Wanted, one-way Oswald, wanted from the CIA. Bounty, $50 million, dead or alive. That was the wanted poster shown in the small town of Lockhart, Texas. The police of Texas were on a wild manhunt for one specific man, one man that only sparks rumors. One-way Oswald, a man in his fifties, described with dissociative identity disorder and ADHD. He has three personalities, each described by the CIA. Budson, taken from movies like John Wick, Mission Impossible and Other Spy and Assassin Movies. Budson is clever, cunning and strict with no sense of impending forgiveness. John, a retired priest who is described as warm, sweet and even caring, but has a bit of dark humor.  Lewis, farmer on one hand, father on the other. Lewis is like a father figure with a very dad-like sense of humor and a sweet personality to him. This is the one Oswald sticks with. Multiple series of eyewitnesses and reports from the police were rumored with some people leaked with some of the documents. Here's one of the example reports. It was shown that on August 20, 2005, two of the lamppost cameras caught sight of one-way Oswald taking a route via hitchhiking. A couple, revealed as Donald and Carol Shiftwell had taken the hitchhiker inside. About two hours later, Oswald came out and left the two's bodies. To this day, Oswald still wonders. An interview was done for Oswald, all that recovered from it was the interview papers. This is a recording and will be used against you at all costs. So tell me, who am I talking to? I'm Lewis, but everyone calls me one-way Oswald. I'm everyone's father.  Aw, didn't kill him, sir. It was someone else. Can we talk to this person? You better got a job for me. I'm too damn old for this.  Tell us why you killed that couple? I was professionally asked to do so. Who paid you?   Do your damn jobs, and stop arresting the good people. You can't? This interview is done. Make one move, and you'll lose an arm. One-way Oswald, a name that's feared amongst Texas. To this day, people still rumor that he's still at large, making his great escape into El Paso, Texas. If he's successful, he may slip by the police and CIA. As of right now, one-way Oswald perfected his escape flawlessly and had made it to El Paso, Texas, where he performed five more murder cases. Eventually, the police and the CIA stopped following one-way Oswald. Now, one-way Oswald is on a new list. His list of unfollowed criminals.


I'm Jake Massimo, and we're talking about some joint work with Martin Albrach, Kenny Paterson and Uri Soromarski, which is Prime and Prejudice, Primality Testing under Adversarial Conditions. I'm going to start with a couple of demos. They're going to be quite quick because I don't have much time. First we're going to look at GNU GMP, and we're going to look at the Primality Testing GNU GMP, which takes two arguments, the number that we want to test, and reps, the rounds of testing that we're going to be performing. So we can kind of think about this reps value as essentially how many millarabin iterations we're going to be performing. And in documentation we're told that reasonable values of reps are between 15 and 50. So here we have a little script just to do a quick demo. I wanted to do this live, but I couldn't. So we're going to have to use some screenshots and our imagination. So here is a 1024 bit number that we give to GNP. We want to test the primality of up to and including 15, the minimum rounds of testing that is advised. So here we see that each time GNP declares that this number is prime, even up to the 15th round of millarabin. That's great. So let's take a closer look at this number. Well, in fact, this number isn't actually a prime. It's a composite. It's made of two larger primes, more explicitly. It's of the form n equals 2x plus 1, 4x plus 1, where x is some km plus 189, where m's are approach to small primes and ks and buffer to get it to the correct bit size. What's interesting about this number is that this result is actually deterministic within GNP, so this number will always be declared prime by GNP when using this amount of reps, so less than or equal to 15, the minimum recommended. Cool. So let's look at another example, OpenSSL. So here we're going to be looking at the equivalence of primality testing function in OpenSSL, which again takes a number that we want to test the primality of and checks the amount of rounds of primality testing we want to do. Now OpenSSL are nice in that they actually give us a function which takes the bit size of the number we want to test by default and gives us the amount of rounds of testing we'll need to do to achieve an error rate of less than 2 to the negative 80. So this is what happens by default. Of course you can pick the amount of rounds of testing you want yourself if you want to. So another quick demo. This time we have a 2048 bit number up here, this big one at the bottom, and we're going to run it a couple of times to see how it measures up. So firstly, OpenSSL correctly declares a composite, nice one. I'm going to put the same number in again and it's composite. So the error rate was 2 to the negative 80, right? So how long have I got? Let's try it one more time to see what happens. Okay, nice. This time it actually declared it prime. So this is pretty sweet. In fact, we got a little bit lucky here, but OpenSSL will incorrectly classify this composite number as a prime one in 16 times. So this work comes from some wider work that we've been doing on the implementation landscape of primality testing in cryptographic software and some mathematical libraries as well. For each library we've been looking at what sort of primality tests are being offered, how they implement these tests, and how these tests handle adversarial input rather than the random sort of input that they're set up to handle. So a real quick overview of what we did. We basically documented the failure rate that these probabilistic tests say that they have. And we compiled these into a table and we also compiled the highest rate of failure that we could get ourselves. So we can see highlighted OpenSSL we have one in 16 times. We also have some 100% failure rates for GMP and some other small libraries like JSBN, CripLib, LibTomLib, CripLibTomMath and WolfSSL. Thank you for listening. If you want any more information, the paper is on e-print or just come and talk to me. Thank you.