Good evening everyone and welcome. This is Melissa with the stockswush.com and I am actually here with Tom Tom, welcome Tom. How are you this evening? great, great So I'm here with Tom and Tom has known me for a very long time and Tom has been trading God like more years than I'm alive. How many years have you been trading Tom? How many years are you alive? Trading more of the years than I'm alive, but I could be wrong it's close. It's pretty close. I mean I didn't even call them trade. They were investments. It was like 1981 1982 so are you just tell everybody a little bit about yourself? So you started out in the market and you thought you knew everything in the world And then you made millions of dollars in the boom and then what happened? No, no, no you missed you missed There were there were like six booms before that Oh, okay This is before I haven't seen any booms, but so just No, there were There were there were several booms I I Mean when I started out, I just wanted to you know I read about the mistakes that everyone else made and so you know rather than focusing on doing something Right, I was focused on you know what I don't want to do wrong Okay, and So in in the early 80s, I know you know I went back and I studied the market and I noticed that it moved to four-year cycles and That the last significant low in in the market was in 1978. So in 1982 I You know, I became very convinced that we were making a An important cyclical low in the market And not only was I right, but I mean it was an incredible lift-off. I mean the especially small stocks went up three four five hundred percent in a You know in a very short time and back then everyone hated stocks which just gave them more fuel to go higher The unfortunate thing was as right as I was about that call. I mean I was I was pretty young I got suckered into you know some kind of scheme that I broke right concocted with You know with options that you know So wait a minute. Wait a minute. You weren't doing actual equity trades. You were doing options No, no, no, I was doing options. I'm sorry. I was doing stocks. I remember that Okay, I remember I mean the funny thing is one of the stocks It may have been the second one I ever bought trades to this very day. It's commercial metal cmc All right, let's look that up. Go ahead. Keep talking go ahead Yeah, that that was that was you know had an incredible run Now I was also told to you know, the bottom fishing was the the way to go And I mean it can be I mean Uh, but the oil sector was just crushed That year that had just gone through a boom And uh, we picked up this little driller called peninsula resources. They eventually went out of business Mm-hmm But uh We had another one m.d. Uh, I don't know whatever happened to them. I think it it's a different company now under that symbol Wait a minute. Wait a minute. Did you buy this stock here the cmc? Yeah, where? What did you buy in 1982? I can't even see 1982. What price did you buy it? It was like 15 bucks 12 bucks, but you know, it splits so many times since then Oh, okay You know, it like if you held on to it. It was a huge huge winner I mean it would spend years going sideways and and then make another run up in them. It's a metals recycling firm And it made another run higher um Now the one we're going to talk about the Oracle trade, but you do something that is completely different from me Which is that you actually read or investigate the fundamentals of stocks, correct? Yeah, the story. Well, I mean, but there's a difference between the trade and You know a trade and uh an investment I mean, I'd rather do an investment and a trade because I can take some off from the trade and hold the rest for higher prices and to me investing is Easier because if you're right, you don't have to do anything Yeah, but the bottom line is with training and obviously this is why I'd like to do it And why I've always wanted to do it and then I forced myself to do it Is that when you train you have the money immediately? You don't have the money immediately when you invest I mean, you're in a position where you don't need the money immediately, but let's be frank Most people are not in the same position as you Well, it depends No, it depends on their age. I guess I guess Well, no, I'm talking if somebody doesn't have a lot of money set aside in the same means They need money right away Everyone I know And it's kind of I mean they they don't really do stocks they You know through the work programs that are available. They just invest in the market, you know And I know but I mean we have to get outside of the range of people that you know 100 and no chance of failure in my opinion outside of the range of the people that you know so People if you pull yourself back into the universe Do not want to wait to get paid money. Am I right or am I wrong? I mean, okay here Here's a great example. Tom works for walmart when you get up in the morning You work from walmart part time and when you work from walmart you go in there Walgreens. Oh walgreens. I'm sorry. God. Why did I say walmart? I don't even know where I'm getting that from Anyways, walgreens.  I mean you do realize that um I mean at least the people the reason the reason you and I like to trade is because We're willing to put the work in I said walmart. That's pretty funny that I said that. I've known you for so long. I knew it was walgreens But it's like an oxymoron. It was like fruity and slip. I said walmart before Did I say that before? Yeah. Yeah. Yeah. Let me look at wmt. Maybe I'm like the stock or something Maybe it's like telling you something. Yeah, you told me once they're going out of business or something. All right, let me go I keep talking Mart are the walgreens whichever one the anyway, most people do not No Most people Do not want to spend the time or the energy to trade period. I mean Even swing trading forget about intraday trading. They hold on to these things for 20 30 years and For most people, that's the right thing to do. I mean it takes, you know, really an extraordinary person to First to be willing to intraday trade And then to be able to do so successfully. You got to, you know, be very quick on your feet and make decisions quickly Now, let me let me complete 100 opposite of you I think quick on my feet and you like have to take all the time in the world to do it So what is the answer then for that? Well, okay, here's what Because that's true. I mean, you know it's true. There's a there's a couple of there's a um Okay, what what what happens is this You will you will often get Better entries, although if I really like the play, I'll get the same entry which was the case With oracle of that word, you know that we're talking about no wait, and again told me that nobody gets better entries than me Now you're taking that back That is often the case not always the case. Okay, these specific Yeah, um, let's pull up the oracle I mean the only way actually the only way And we'll go over the only way anyone would have gotten a better entry than you on Oracle that day is and I kind of did I mean not a better But it was the same I used to limit order and got filled like 20 seconds later right Is because if if you would have had the order Preset, I mean oracle opened and collapsed and if you would have waited for the collapse It would have been too late. But how could you predict that though? That's the point I'm trying to make Yeah, exactly. Yeah, and um The other thing is is generally Generally, not always You will get a second chance In the entry. I don't know. This is where you and I have a fundamental Disagreement, although I will tell you that your text today here. I'm going to read it out loud to the room Or whoever's listening your text today actually said to me something. I was like I have to put this in blood You said Although let me find it. Yeah, where did you send it? You said today that I'm really good at the at the immediate entry. Where did you say that? Yeah, I can't find it. Maybe it wasn't an email.  Oh, all right. Well, I can't find it now. I thought it was a text, but it might be an email Right. Yeah. So then the night then you lost me. I'm always aggressive.  That's the key word Um, but I mean, this is the conviction conviction from what? Were you getting the conviction? Where? Yeah um, I'm either getting the conviction from um From the uh earnings report And my conviction level on oracle was pretty high Here's where it opened our oracle opened at 41 91 when it was in the pre market When there's a there's a there's a thing we're sort of getting ahead of ourselves here, but oracle I had forgotten about this oracle switched over to the new york stock exchange And it it was still pre trading pre market at 9 30 9 30 9 31 it actually didn't open on the nyse until 9 32 you can see it the the huge million share volume spike That's when it actually opened on the new york stock exchange. Let me go here. That was the day of this day here. Okay Right right there. Yeah Say what go with what you're saying Yeah, because because I remember that because there was another moderator that called it long that day um 42 42 15 by whatever that low was all right explain to people There's all kinds of other trading rooms and there's another guy that I know that that's Long and I he's often wrong on the opening place um, but nonetheless when it opened On on that huge block of volume you see that that bar was green for like three seconds And it looked like it was this one here at 9 32 Yeah, yeah, that was at a big green body and I'm like, oh no But it didn't it fell right down and and then I knew we had it We're pretty sure we had it I want to be aggressive. I want to wait till china clock. I'm asking you. Where did you actually enter oracle? Where did you put this stop? Well, I Okay, my initial plan with oracle was and then I was watching a trade pre market I was pretty sure that was the one I was going to do. All right, hold on Where did you all of a sudden get the conviction? This is at the night.  Well, here's here's here's here's the whole you know chronology of You know me and that the oracle played Well oracle has a tendency to to fade the gap and actually ended up doing that this day Um, no, wait a minute. No one knows who you're talking about. What do you mean? They the gap Oracle tends to whatever way the gap goes. It tends to end up the day in the opposite It's got a huge history of doing it like it gapped up three months ago and it sold off all day and um and One of the reasons for that is because it's one of these institutional favorites. They they like to buy it when it's down I like to sell it when it's up Are you saying you feel like it's rigged or what are you trying to say? No, no, no, no, no, no, it's not rigged. Here's a daily chart of oracle like give me an example. What do you what do you mean then? Um, like this day here where it gapped down here back in this is October 2000. Yeah, that's that's one and uh What's the other day and over in it looks Yeah, it looks like in march March of this year. Well, uh, yeah, um Where? Whenever it gapped over 45. Oh Here here. No, no, no, no. You were like march 18th march 18th rated this gap. This would have been right on the cusp I mean, this would have been like not a hundred percent. I see what you see here. Like it could have done it We actually played oracle on that day in the room. I was I was there and I I I tried it but I You know and this is like right on the it was like right I mean, this is weird. I will agree with you that but It was the reason the institutions do this not because it's rigged. It's because It's because the liquidity is there where they can um either get in or out of it and um These bigger names they they you know that aren't going out of business and you know in two years They you know, they're talking about oracle. You're talking about oracle, right? Okay, go ahead Now what I I I send out a short synopsis to some people um the way I think that Oracle's gonna go and What I what I wrote on it is that it has a history of fading But I think I thought this was the real deal and and the reason I wrote that is Wait a minute. Are you tired of the gap here? You lost me? Yeah the one in march Yeah, that's it go ahead say what you're thinking Well that particular day. No, no, no, I'm talking about the gap in march. I didn't like okay I thought I thought it was okay and we did it in the room and when I think something is okay I'll do it, but I won't do it with serious size You know and I I had no expectations on you know, I'm happy to make a nickel I don't have no idea why you'd ever take a trade with no expectations. You were like the opposite of me I mean, it's like every trade I take I take I have 100 expectation Every trade you take you're like Maybe I mean, I don't understand that. I mean, that's why I'm trying to pull you over like to the side of like the sun Where I'm trying to talk you into taking sides I've been trying to do this for like the last 100 years and you won't do it But the reason is that and and you email me the other day you're like I get 30% conviction from you I'm like, wow, that's a hell of a lot conviction actually And I talked about it in the room and and yet there's nothing that I can say That will make you take size and of all the people that I have ever known and of all the people that I've ever traded You could take size and you wouldn't be hurt if you lost two million dollars in a trade You wouldn't be hurt. I have no idea. What is it that you were going to get conviction and you're like, well, maybe I mean you have got that what is lacking from you and I'm telling you this right now And I'm telling you this to help you I can tell you in one short sentence. What what what I probably want to avoid turning this into a real job Um, what do you mean a real job? So then you're gonna work for Walgreens or Walmart?  I'm asking you right now It's it is 855 on Monday night. I want to know your plan of action this um What wait, we got like six things going on. I know but just answer one This this gap here in Oracle where your pointer is right that was Now the reason I did that with no expectations is It could have it could have continued. It's surely it really should have continued. It really should have Let's see what the market did on that day.  I mean they reported that night And I would be here and see they earnings were okay. No, they weren't even okay. They were Just look at the market because this is very interesting The qqq's on Oh, see this is wrong It's really really wrong Look what the market did on 318. No, look at that That's the market and let's go to the Oracle. Hold on. Let's go back And you know Oracle has gap down something's wrong here Oh, yeah. Yeah, I'm just looking at this now You know, wait a minute. I'm just seeing this. Are you long this over in the long term or what? Oracle? Yeah No Okay, because there's something wrong with this And I'm just saying this now Well, I'm just telling you right now that the day the gap in Oracle and the earnings It didn't go higher, but the market did and this is the market stock They're kind of shorter I know I know but again, I don't short bear bullish gaps But I'm telling you them that Oracle gap down here This was just recently on the 18 Yeah, that was the only thing Wait a minute. Hold on. Just hold on one second here Oracle's lower I know I know I just see this now. I just I'm just saying this now as I'm talking to you Wow that this this Hold on this gap here Gapped up High was 4310 Wow, I think Oracle is really Oracle still in an uptrend, but I think Oracle is lower now that I just know that one Do you think that yeah I mean, I thought about it the gap day, but you know, but I was too not enough information You just played the gap. It was still in an uptrend But I'm just seeing that now with the market and then the gap down that just happened a couple of days ago I'm seeing that I'm like that's a sign Because that's not right You're are you in this overnight or not? No, no, no, but I did notice the weakness today The thing I want to go over why I had more conviction than normal on Oracle. It was because I mean on these bigger companies All right, I'm bringing it up. This is the 18th. Let's go. Let's go to what you did. Okay, go ahead Right the the institutions that can be more forgiving You know on a minor miss on earnings and they often in an uptrending market They'll view these gap downs as opportunities to get a great company cheap But you know Oracle has missed their numbers Like every quarter for the last year Well, that's that's something to do with and I never look at I've got to ask you though. I mean, I'm just asking this on the video, but I actually never have asked you this This was the worst miss yet. Really? right and so My thinking is at some point these institutions are gonna say, you know, the old saying fooled me once You know, shame on me fooled me twice fooled me three times. This is try number four You know, I think they're gonna lose their patience with it and You know, I think it is gonna go down You know, probably a 39 anyway and then Then we'll see um, my plan with Oracle on on The day the gap was I wanted to short it at 42 50 And take it down to 41, but but about 15 minutes before the open it collapsed And that plan was out the window and so you had to take it where it opened and You know, we had We had a nice play on it Even even though, you know, it ended up, you know green on the day But I mean you'll answer this because I'm I'm surprised that you would be as aggressive as me because you're normally not I guess that I'm surprised you would be Okay, here's here's here's what I do Most days most days, but but the conviction level varies Okay and what I try to do is focus on The best available play um And I'll vary the size uh accordingly um But usually by probably no later than 935 I mean something now here's Here's we're gonna We're gonna You know, but it's not a difference of opinion. I guess a difference of attitude If you you go in with full expectations On on most plays and actually I will feed off of that to to an extent um But I generally go into a play with limited expectations um But I mean and I don't understand where how can you feel my ultimate the ultimate expectations is when I get into a play I'm not selling it no matter what I'm here what it does during the day And I have a I have a few of those that I mean if you want to pull up tbi tom boy indian I've had that since the day of the gap It didn't need I mean it but I mean go back to what you're talking about about at the fact that you have no Expectations like you lost me there. Okay. Okay. Look look at mba today This this gap down. I'd have done this to that thing. All right Let me just look at it because I don't even know what it is. But let me just look good Now first of all, I'm gonna look at the pre market nine o'clock 1 15 8 This is the problem. This is where it was gapping in the morning So if you're rating the gap you're gapping you're rating it here Now, I know it got better into the open but you're trading it on then on the fly Yeah, I know on on the rating this would have not rated well on on what you do But I thought it kind of went climactic on the daily had it just just huge. Yeah, it did I mean it did but I mean you can't be aggressive on this You know, so I thought a lot of people and this is what I mean I didn't have wouldn't have had any expectations on it. But if it fell 10 bucks, which it did you got something Let me just see here. Did you actually short this? Yeah, because my I was on the phone with real tech trying to fix my platform It wouldn't let me log in But I was watching it You know, and then and then what happens to me is that you know, I get you know, uh, a so-so day on you know on Kind of would probably would have ended up being because I this stock is what I was long this stock two days ago That's why nothing. I kind of know what I'm pretty familiar with it Um, well, I mean I gotta tell you that this Bar today is actually pretty devastating for this. Yep. Yep. Yep. Sure is It's gonna be to support like real quickly really like tomorrow. Yeah Um, but and you know, Melissa, this is another one. I it See if I can see it. Uh, I did this the day of oh, there it is on June 3rd June 3rd, I I did this About little not what yeah there I did this that day on the gap And I sold some into that tail and I kept some And that's what I mean. No expectations, but then all of a sudden it takes off You know, and I sell some more But this is where the gap rating would help you because to be honest with you I wouldn't have thought this was anything fabulous Like I know but I absolutely love the earnings I know but this is where you could combine the earnings with the gap reading Right. I do that every day. I do that every day. All right. All right What was the reason for the gap today? I I never could find anything some some big short seller said it's it's worth 60 bucks and he's short the stock It's crazy Yeah, I I I was I was really you know Herried this morning because I couldn't log in. You know, I couldn't out log in Until my you know, well, you're not supposed to do anything that it's like it's like a sign a sign to just take Had I had I done the room today This is the one I would have done because the other gap was at you and it went straight up I know but you know most of people to remember not going to short stocks at this price point I mean, that's the problem. I mean This is expensive but I mean, let me just look at the stop here. Well, I would have probably been a dollar See what you're looking at right now. You see that's so much better and so much faster than I do I mean, it just takes longer for my brain to process I think that is a result of what like what's the explanation for that? Why does my brain work faster than yours?  So what is it even has more capacity, but it is not as fast You think my brain has more capacity. That's the nicest thing you've ever said to me I should like I should actually like tally up all the nice things you said to me the last month I like to put it on as a testimonial My brain is built for power Right So and what I meant was mine had the greater capacity. Your brain is built for speed Right. What's your point though? That's different brains. It's not it's they're meant for different things. I know when you're trying Disagree, but you know what you're gonna do give me cocaine or something every morning I I tell you if I ever start to do k-kane, they're gonna have to lock me up because I'm actually dangerous on k-kane like don't ever even slip me any cocaine Like I've known that for years. All right. Let's just look at this here. This is I know, I know Off straight like a banshee It just fell off a cliff Yep I mean, is there anything that you think you could tell new traders to help them If they're looking into trading gaps I mean what advice on all the years of experience that you've had in trading gaps Could you give to someone that's brand brand new that never traded gaps never traded my system? Like what advice could give that person? You know, it's a it's a combination of what what you and I just discussed Not not everything works and You have to be aware of that But but you do need the conviction otherwise You're not going to get into the play I mean one of the I mean, I think this is as hard as for me as it is You know for you Is when something actually does not work Yeah You know, you look at it in almost disbelief because you can't understand why It's not why it's going against the best late planes. You could have possibly Have had and that's it doesn't work as one risky unit. Correct. But you know, but as We've done from time to time There is the human, you know, the human nature part of us that that likes to fight back at adversity, but as you know From experience, you cannot do that with trade. No, you can't I mean, this is what I've learned from the experience of the umpteen years. I've had I mean You cannot move a stock. You can want it to go and wanted to go wanted to go You can't you can't make it happen. Right. Right. And and you know, and you just you have to move on I mean all the all the the one we did the other day um I I um And I was was going to do this one over um Over Oracle and and I was the only one that did it and and and you're I mean and I had a thesis laid out for this and it was your Point system that sort of edged me into it And it was lzb lazy boy It was too thin though. The problem was it was way too thin Yeah, it was kind of thin. Um You know and um And I mean I did it the once and it had a little pop and I got out of it It essentially break even but then it set up against where I did give it a second chance And and that turned out to be the right thing to do um, you know, I see and I had I mean, I like to have a two pronged belief going into the gap not only the You know, I want the gap in the chart and I thought with lazy boy. I thought we had a a third Even a third effect or a third prong that would Uh sparks and fear into people holding the stock And that was the fed was meeting that afternoon and lazy boy is related to home building And I thought anything which is related to interest rates And there was fear that the fed could start raising rates and uh, which is bad for the sector So listen, I think you should write my blog because I don't have time to do it And you talk about things that no one is interested in like as far as like most people are interested in but I'm not interested in But I will tell you that the great thing about you is that you look at these things that I have no time to do But you know, what's so funny like Just for a second Melissa, that's that's the difference between a fast brain and a slow brain. What do you mean? My slow brain goes through all this stuff that you know, and you know, and you're more of a gap and Oh kind of girl, you know, I'm like, oh, we have this and we have this and we have this and you lay it all out This should really but I do have that in the morning when I'm reading the gap Do you understand like I'm do processing that Slowly from the time that I roll out of bed, which is way before you even blink an eye And I am looking at the gap and reading the gap. So that is my slow process. Do you understand the difference? Right, right, right, and you're very good at that. Yes. Yes. Yes. Yes But um You know, I and I still do I still think that the two of these combined together is um The two what? The the two of where you're just looking at the chart and I'm looking through what I could write in a blog is is pretty good You know the combination of the two But I'm never going to do it. You do realize that You realize that I'm never going to look at anything other than price action and reading in lifetime I mean, you should realize that by now at this point. I know I know I know But What I'm saying is I've already done it So you only have to ask one question. Do you like this? And if I say yes, then I've gone through all that But what you said to me the other day I was like floored when you said that you get 30 percent of your condition for me I was like, wait a minute write a testimonial because I mean that might have been just a number, but it certainly Well, I mean whatever. I mean it was like that's like pretty high actually I would say you're good at what you do and that's been true for a long long time a long like like like years and years and you used to send me these little email things A and B is good and and I and I have this great play on A and This was the first one that you ever sent me this and I don't even remember this It's the capacity thing again What did I say? What's that? What was it? You sent me this like four letter email amd is good And and I had a great day in amd, but it rallied first not and I walked Into this day I we've talked about this before and I've never understood Well, I when I emailed you back. How did you do an amd? You wrote me back another forward email that said amd annoyed me and This was um, at least this was three four years ago in september. Okay um Yeah, and I I mean that's it's no big deal. I just always wondered why amd annoyed you you know that particular And I actually think you've gotten better that day. I think that kind of popped that amd had that day I think you would have been in it and not uh, and not been stopped out because you give your your, uh Your positions a little bit more breathing room than you used to I absolutely must help with that That's that's interesting because um I mean what you said about you know, either the play is going to work Uh, or if it stops out it never it you know It it will never work And I I've seen that true. I can't think of a I can't think of one exception to that that I mean, I remember there was one that you did twice Um, which was cynics and it uh, this was earlier in the year and it never worked Coach never worked again. I mean no if they don't work that off of that they will they don't work I've definitely I mean it's been seven years, but I would consider myself an expert now I'm reading that first five minute period where I actually have to sometimes hold myself back Or I just hammer it But it's such an instantaneous thing tom that I don't even know like what I see like no, I sense it I sense it when you sense it It's like I can I can feel it. I can feel it through It's like adobe. I mean, I didn't even do this thing. I mean, did you do that? I looked at that. I looked at that Adobe when it had gone Into the previous day's bar I called that trade like I was that was like magical. I should have been in television when I called that trade Where was that here here? But look at this here today. See that was the problem.  Let's go Did you do it? On my call Did you do it on my call on the 17th? Yeah, the Adobe play. Yeah, did you do it? Yeah, that was good. That was like I remember you said Adobe can't get through radio when I call it That's pretty amazing It wasn't even gapping when I called it actually because it had rally It was already gone. It already filled the gap And this was like an enormous our trade. Wow. Wow. Yeah Did you do it? So you did it you're saying you did it? No, that was the lgb day. That was an lgb All right, okay. I guess I Well, you know, I could you keep saying I could someone could just do all my calls and actually I know every single solid to everything that I call and then because you would be the one with your personality Come back at the end of the month and say I did this I did this I did this I did this And this is a result because you track those things and I have no I don't really track them. I just I just remember I know I could care less because every day get up and have amnesia and I Did I have amnesia? Say that but there are some you remember what I said No, I have amnesia with the trade Right, right, right, right. Yeah, whether they're good or bad. I have amnesia But I'm saying that you you yourself could do everything you've got the buying part of your in your account You could do like every single solid to everything I called including the market by the way Yeah, I I just I just um, this is like crazy. This is the best entry You're ever going to get an adobe for the rest of your life I mean to take a 30 some cents stop and that and have a drop of dollar This is this is a very expensive stock and it's so whippy and it actually just sold off like a banshee My conviction told me this would work But the fact is a gap rating told me it wouldn't but I called the trade based on conviction See, you know the blog that you asked me to write right, right, which I did write on adobe the night before Right, I had adobe initially lower and then higher and it just scrambled my brain when it went higher And then lower no it was the dinner would have flipped like today. I mean look at this here today Look at this And then I do have to get going because you know, it's like 10 minutes past my bedtime, but let me just look Okay, okay farmer girl. I know They have a website out now for girls like you What's it called? Farmersonly.com or all the country girls are I know but do you really think that I need to be associated with that? Do you think that it's actually going to get me viewership by the television show? I know but markets neutral neutral slash bullish for the clothes today All right. Well, this was really really good. We're going to have to absolute 100 to do this again I think this will be helpful for people I appreciate you giving your insights on things that I do not look at But that many creators probably do look at or investors per se Do you have anything else you think you want to add tonight? Well, just the FNSR Friday was Did you do it?  I couldn't make this stuff up. I said 1950 It was a three times Friday. That's it ridiculous mess Ay, ay, ay, ay, these are the trades. I look back and say why didn't I make a million dollars? You always ask me that I'll say this one last thing and I'll let you go What was the one thing you said to me?  Well, why did I say it? No, you said be careful what you wish for you might get what you want But you know what tom? I have wished for things and I've gotten what I wanted. What do you have to say for that? Well, a lot of people do that. It's just most most people tend to enjoy The road to get to what they want rather than actually getting it And okay, so what's your point? Well, that was it. Oh, well in the other thing a lot of people You know will wish for something and then get it and and finds out it is not what they Had expected at all. Yeah, but what does it have to do? Well, I don't know nothing. It was just a it's a No, you were advising me when you saw so I thought Actually the whole the whole the whole the whole phrase goes be careful what you wish for you just might get it That's that's the way. Yeah, but I've gotten it. Well, is it working out? So far Hey, by the way, do you know do you know what I mean when I say that?  Everything nice. You said Yeah, but it's all still true. It would all still be true if I mean if I We disagree on something. It doesn't take it doesn't take back any nice things that I said I don't take I don't say things that I would Don't you is when you're saying mean things though. Never said.  This is ridiculous or whatever that case may be But it's still the same concept. I'm in your face Yeah, you're you're not there's just two things that that trigger First it has to be something I disagree with Anyway, then two I have to be tired and then and then what every once in a while you will be angry and that That's like the magic ingredient It's not just me being nice to you.   We still have them and We rescued him from like certain death 10 years ago What and when we rescued him he was like the nicest cat ever But once he became back to a normal cat because it was needs conveying And when you still have this cat Yeah, okay. All right. So then what? My wife ran over his tail with the car five years ago and his name is now none, but But he's still he's still here. He's with us and it's wait a minute. What is this?  Yeah That wasn't always the easiest to have to deal with at this, you know, as a friend with a friend So but now that you are doing well, you've become nicer and nicer and nicer The opposite of the cat is what I'm saying. So what's your point though? You've become nicer and nicer and nicer, but what's your general? Well, it's nothing to do with you and me that at the point the tip for people was you know to Things don't always work out and you don't want to fight a stop because it will fight back You know, and there's always another day. I mean if something doesn't work one day That's a great tip. That's a great tip for traders What you used to tell me and I never listen to you, but it's a great trip It's I mean it's a great tip because the fact is that on and on and on I would I would trade with I didn't like something or if I would fight it I would probably till four o'clock And you always told me you there's always another day But you you know, I'll say that too and and really it's it's it's it's really not be nice to melissa day. I'm just talking I know I told you put those taxes you sent me in a testimonial you keep taxing me. I'm like right a testimonial But you know When you had to you were often a great fighter too. I mean I know I used to call me a warrior. Yep. Yep. Yep. Yep. And actually, you know what the irony is like my broker It's almost like my broker would give me anything I ask for because my broker Like believes that I'm a warrior like my broker see me come back from Tremendous lost days and like almost to the point of insanity like my broker could write a book on me You know, and and that's a great It's a great great to have Yeah, but it's not a good way to live. Oh my god. I was like going insane like thank god I'm not living in that period like I could never go back to that. Please I can never go back to that and what you just said that that is kind of why I don't want to take enormous size No, no, no, you're holding yourself back. You could be making more money. You're not doing it. You're in fear about it I don't know what the issue is. You know, you know, how to trade you have me on your side I'm calling the trades 30% conviction. You're getting from the trades With the size that you could take I'm taking more risks now than you and you have a bigger account than me And I gotta tell you this right now. I'm telling this because I love you You need to consider that there's something in you that's holding yourself back and you're in fear You're in fear of the risk. You're in fear of losing your fear of the market And I'm telling you right now I'm taking more risks than you and I'm making more money these trades than you and I'm taking more risks than you And there's something wrong with that You have a bigger trade in account than me and you have been training with me as long as me and you See the trades I call and you believe in me and I don't know why you're not doing them with more risk That's very well said actually every bit of it is was very very well said I'm saying this is to help you. I'm not saying I'm saying this to help you Because you can quit that job. I kind of like go. I mean I'd like to cut back a day, but I know Yeah, but then But then I'd have to hire three girl assistants here to help me with this Well, whatever. Tom occasionally helps out in the live trading room. I'm doing that tomorrow, right? Yes, you are and Tom is 100 different from me in his actual Speaking and calling to the trades, but he has a great eye For charts because he's been training for a long long time and I will say that Tom Is very conservative in reference to his risk So that is actually a good thing for the trading room. Thank you Tom so much for coming this evening All right Have a good night. Thank you


Hi, I'm Jason Hibbitts with Opensource.com. I'm here with Chris DiBona, director of Opensource at Google. He oversees licensed compliance and also helps with their internal Opensource developer community. So you basically built the Opensource initiative at Google from the ground up starting in about 2004. Kinda. Yeah. What was that like? It felt that doesn't sound like it was an easy task to do. No, no, it actually wasn't hard. You know, Google already had a number of Opensource developers internally when I got there and they what they wanted by hiring me was to formalize it, make it easy, and as they grew, to make it persist, you know, so that Google could still feel like they can contribute and and release Opensource projects. And more importantly that we could also use Opensource software inside the company. And they knew that that would need a bit of care. Right. And they were growing enough at that point that they needed somebody whose job it was to care about that. So it was more a matter of coming in, formalizing what was informal processes. Okay. And then you know, looking after compliance in a scalable way for the then and still now very fast-growing company. Okay. Any changes recently? Or is that music? Imagine... Well, you know Larry you know, reasserted as CEO because he was our original CEO back in the dusty past and then Eric came in and then Eric became chairman of the Board of Emeritus CEO type guy and Larry became CEO. Again, Larry changed how the company was organized internally which changed some aspects of the work, but not for the worse or better just different. So but you know the thing about I've been in large companies before and large organizations before and you know it's just a matter of saying okay, here's how we're different now. If I were starting today what would I do differently? And so I do this thing at work about every two or three years I bring together sort of the major stakeholders and say okay, what are we doing right? What if we were going to start it today? How would we do it differently and and and just try to adapt? Right. And and I sort of take that as a measure of how I'm doing, you know because if they say to me, Chris, we're really screwing up this this mess. I know what it would concentrate on. This is why we did a renewed focus on get infrastructure for Chrome and Android which we've deployed externally as our kernel mirrors and the rest but all the Android folks are now running, for instance, on a version of Git that sits on top of our very scalable backends. That's a great approach to kind of check in every year. Yeah, no, well it's not every year. I really don't want to waste their time but it's interesting. So yeah, so a lot of people hear about all the perks at the Google campus. Can you give us a little bit of insight as to the culture at Google and kind of my main question here is that you know is there a default to open mentality there? Well, you know, I would love to tell you that that's the truth but I mean most people, you know, at a company like Google, there's a default to coding. Okay. And and some of those projects are open. Some of those are closed. But then we also have people who are very passionate about open source and what we try to do in their case is is get to know them and say, okay, you're going to be patching, you know, which projects matter to you and and just make sure they're putting, you know, both our best face forward but also meeting the right people and source because it's very rare but there are some projects that are very difficult to deal with as a larger company and as an employee of a larger company. And so we make sure that they get the right kind of attention. Similarly, you know, contributor license agreements have become way more popular over the last couple of years and some are completely signable and in fact are often based on the Apache contributor license agreement which is the same one we use at Google. And so that's usually very easy and so we make a make a point of making those very efficient when a Google goes to sign those. Other CLA's are not as easy to sign because they carry type right assignment and often patent assignment clauses that are too, you know, grabby. Sure. You know, and so in those cases we usually end up pushing back on the project that wants that kind of thing and they often change because they still want our patches, you know. And then in some cases we'll release patches wholly separate from our project, you know, and independent of their desire to have grabby clauses in their CLA's. So, you know, we exist in those conversations to basically protect Google and to protect Googlers and to protect open source people from Googlers who are not always so savvy. You know, so. Well, one of the other important parts about about contributing open sources or open source general security. So recently Google announced a new program to reward large security improvements to open source projects. Tell us a bit about that. Well, I'd love to take credit for it, but this came out of our security group and they're just brilliant. And they're like, hey, you know, we want to expand our bounties programs to these very popular libraries. And we had focused funding on some of these libraries in the past to ensure that they persisted. But this was a very smart approach where basically, you know, what it is is if you take a commonly used and popular library and you find a security bug in it, you know, we're happy to basically award you for finding the bug and for fixing the bug. And then we also have a program on the side where we approach those projects and said, you know, if this creates a lot more traffic for you that's hard to deal with in terms of, you know, patch traffic, let us know we're here to help, you know, and because the reality is if you look at like a library like Zlib or the OpenBSD drive open as cells and the rest, they're incredibly important, right? They're important to Google, they're important to the web of large and we can make a better web, a more secure web, if we just make sure that, you know, these patches are found quickly and dealt with. And that's the power of the open source model, right? Well, that's very, very true. And so we just want to, you know, make it very, very clear how important these projects are to the internet, frankly. Thanks to Google for putting together that program. Well, sure.  They're the ones that do their day to day work. Great. So last question here, and before the conference here, all things open, we did an interview with you on Obasource.com and you talked about Obasource being brutal, got a lot of attention. Yeah, I think that was a great quote for people really like, ooh, brutal, that's a great thing to say. But so, I mean, it sort of is, right? So what's the, you know, it's brutal. Why is it brutal? Well, I mean, it's very much the survival of the fittest applied to software, right? And the thing that people forget about evolution and survival of the fittest is that there's a lot of, you know, stalled forks out there and it represents broken hearts and broken dreams, right? And sometimes those people come back to open source and come back to the main line project and sometimes they don't, you know? And that's how it's brutal, you know?  If you're going to spend 10 hours of your day at your work, it is personal.  It kind of are. I mean, I hate to say it, if you put your heart into something that much, it is. And because of that, you know, when your work is rejected for whatever reason, you know, it's heartbreaking and brutal and all these things. And at the same time, you know, it's also how we get really good software because sometimes you have to say, this piece of software is unsuitable to the task. And that can be hard to hear, but it doesn't change the fact that people want software unsuitable to the task or insecure or broken or worthless. There's no, you know, there's no gentle way to do that. And the thing is, there are some people who over-correct the other way and make it extremely brutal. And that's too bad. And you see communities that are harsher than others. But in many of them, it's just simply hearing your software, your patch is unsuitable. And it takes us too long to teach you how to make it suitable. That's very hard to hear. It's awful, right? But at the same time, you know, I've seen it over and over and over again, both inside and outside of a corporate context. And it's like, you know, I would love to take your patch. I'd love to tell you what's wrong with your patch. But to do so would take too much time. You know, and so that's why you have better software, right? Well, that's how open source. Because it's funny, because within a corporate context, you actually, it's very hard to say that, right? So for a Googler to say that to another Googler is very difficult, right? I don't have time to help another Googler out. I mean, it happens. And this sort of goes to the nature of why some software developers are valued more than others. And it's a very hard conversation.   It is, you know. But great. Well, Chris, we'll take you off the hot seat. Thanks so much for your time today. Sure. Happy to.


In this learning activity, you'll learn the difference between a parameter and an argument. It's easy to confuse the terms parameter and argument, but they are different beings. A parameter is a variable which is part of a method's signature. An argument is an expression or a value that's passed into the method. There is a subtle difference. Consider this JavaScript method. The variables A and B are the parameters of the function AddToNumbers. Now, let's call this function. The values 5 and 3 are arguments. Think of it this way. Parameters are variables, arguments are expressions or values. Now, let's do a quick quiz. Look at this code and determine whether the highlighted portion is a parameter or an argument. If you said parameter, you are correct. Let's look at another one. This time, we're looking at an argument. Try one more. This one might be tricky, but that date is definitely an argument. What about this date? If you think this date is a parameter, you are correct. In this learning activity, we learn the difference between a parameter and an argument.


Hello everyone and thank you for joining us today. I'm Gosia Steindl, IBM Fellow and CTO of Hybrid Cloud Research. We are looking forward to a lively discussion about the latest cryptography research. Following the program you'll have the ability to submit questions to an IBM speaker. We'll save the last few minutes for questions and try to get through as many as we can. And now let's talk about cryptography. Cryptography has been around for millennia. The first encrypted messages were disordered hieroglyphs carved on tombs in ancient Egypt. At IBM we began exploring cryptography in the 1960s when IBM chairman Thomas Watson Jr set up a cryptography research group. The group created an encryption method named Lucifer to protect the data for a cash dispensing system that IBM had developed for Lloyds Bank in the United Kingdom. In 1971 Lloyds Bank bought the code and IBM worked to integrate Lucifer into its commercial product, the ATM. And today cryptography remains a key part of IBM's business and the priority for IBM research, one of the largest industrial research organizations in the world. In this session we'll discuss three critical emerging areas of data privacy and cryptography, confidential computing, quantum safe encryption and fully homomorphic encryption. Each of these is solving a different piece of the data security equation. Let's start with one area of security research that companies today are actively using, confidential computing. Confidential computing provides hardware level privacy assurance by encrypting data within a secure enclave that not even the cloud provider can view or access. In 2018 IBM became the first cloud provider to offer confidential computing for use in production. Currently clients in the financial services, telecommunications, consumer healthcare and government industries all use confidential computing capabilities from IBM. To share more let's turn to Hillary Hunter, IBM fellow and vice president and CTO IBM Cloud. Thanks Gershey, it's such a pleasure to be here today. You know to jump off on what you said, for IBM our cloud strategy has always put the security and privacy of our clients data at the forefront. We believe our clients and only our clients should have access to their sensitive data and to their data overall and one of the ways that we're making that happen in technology is through confidential computing that you just described. These capabilities allow company running workloads in the cloud or on premises to have full privacy and control over their workload even though they don't necessarily own the infrastructure in the cloud context when the workload is hosted. IBM has been working with confidential computing now for around a decade and we were the first to market as you mentioned with a commercially available solution in 2018. But we've worked since then with a handful of companies across different industries who are using our confidential computing capabilities to ensure that critical data can be processed with complete privacy and we're going to talk about a few other keywords in this space but I am delighted to have one of those clients here with us today and want to welcome Samuel Brock who is the co-founder and CTO of DIA which is an open source financial information platform. Welcome Samuel. Thanks for the warm welcome and thanks for being able to be here. Yeah welcome everyone. Wonderful thank you. So Samuel just to kick us off here can you talk me through a little bit about DIA in the space that you're working in? Yes so we are a financial data provider providing data mainly on blockchain financial markets so our main focus lies in decentralized finance and everything which has to do with with on-chain reporting on on different data sources. It's a very fast moving space and it's also a space where a lot of data is handled in a very short amount of time so we need a reliable and scalable solution while also we have obviously customers who are very decentralized and very spread out about many jurisdictions and we want to show them that they can that they can rely on our data and that our data is always with the highest protected with the highest level of integrity. Yeah it's interesting because I kind of hear you saying that data privacy is important to you because it's important to your end clients right? It's part of being able to use something like confidential competing as part of the core value proposition that you then pass along to your clients. Yes so for confidential computing I mean one of the one of the advantages in our space is that we don't have personal data in the in the traditional sense so data privacy is not a concern in the in the privacy sense that people's data is concerned so we have financial data it's public data in the end but what we care about a lot is data integrity and also the ability to to be very sure that no one else can tamper with our calculations with our database so that everything is really in a in the secure enclave but without the disability or without the the problems we would have for example when doing it completely decentralized which introduces a lot of costs a lot of latency a lot of complexity so we try to get to the sweet spot of having decentralization only for parts where we actually really need it and to use a centralized secure system when possible. Yeah I think it's such a great example because you've introduced that word integrity and I think across many different industries people understand that both privacy and integrity are important there's high value capabilities and then there's a lot of capabilities as you're dealing with across different industries where the integrity of transactions and the consistency and the ability to know and trust that process is important and that applies to many different types of industries that's great thank you. So I know you looked at a lot of different technologies can you just elaborate a little bit more on where you ended there as to why confidential computing versus general computing how did you make that decision to to leverage confidential computing and secure enclaves to establish that data integrity and privacy. So with traditional cloud computing let's call it like that there's always a problem that we have to yeah we have to trust the cloud provider in some sense that the data is or that that the yeah on one side that the data and databases that are hosted there is not tampered with or not changed on the other side that also the computing itself so the code is which is run is not changed I mean there's obviously protocols for that so you can you can run it in a multi-cloud environment and then have it synchronized but again that introduces latency introduces complexity on top of that then the question comes up who controls the system on top of it is it running on-prem or is it also running in a cloud. Obviously I mean the cost of every attack will increase with every level of security you add but also the the potential benefits are very high because in yeah in our blockchain world we essentially working with programmable money so if someone finds a bug or someone can find a way to to access and to to change our data there's suddenly a very high monetary value so there's a concept called cost of corruption and this this cost of corruption can be very it can be very even for attacks which are very expensive can be very beneficial to to to do them if you have like a monetary value directly coming out of the attack. Yeah and I know when we when we met earlier you know we were chatting a little bit about some analogies that that we've tried to help folks understand sort of those degrees of of security and the cost of attack as you said you know in our daily lives you know a hotel has has video cameras outside and a security person at the front desk and you use your key card to even get on the elevator you use it to get into your room but yet we all know there's a there's a vault there that we may choose to additionally put very particularly sensitive things into in that room and so it's always a matter of degrees and for the type of work that you're doing really you know securing the integrity of transactions and data is is that much more important to then make a specific confidential computing choice that's great thank you so so I'm going to wrap us up here thank you so much for being with us today Samuel I think that was a great articulation of the practical application of confidential computing and it's great to see your work live on our cloud and you all pursuing those opportunities in the market so thank you for being with us today. Thank you. Thank you so much Hilary and Samuel now that we have learned about the promise of existing technologies like confidential computing and just how far we've come since the advent of cryptography it's time to discuss what's ahead at IBM we believe that quantum computing is a large part of the future of computing and currently have deployed more than 20 quantum computing systems but quantum computers are really good at factoring large numbers and the strength of today's cryptography depends on the difficulty of factoring so clearly quantum computing poses a potential security challenge for more than three years IBM research the national institute of standards and technology and the broader crypto cryptography community have been examining new approaches to encryption and data protection to keep our most sensitive data safe from quantum computers let's learn more from NIST and hear from IBM researchers about our latest advances in this field. Hello my name is Dustin Moody I'm a mathematician with the national institute of standards and technology usually known as NIST I'd like to thank IBM for the invitation to come and talk a little bit about post-quantum cryptography and what NIST is doing to address this threat just an obvious disclaimer I don't speak for the entire federal government and because I'm speaking in an IBM event that does not mean we endorse any products or anything like that so over the past few decades there's been a lot of research and work towards building what's called a quantum computer a quantum computer would operate on a fundamentally different paradigm than our current classical computing technology that we use today and if such a large-scale quantum computer were actually able to be completed and constructed it would have a lot of positive applications because it has a tremendous potential for improving computational power so there would be a very lot of positive applications in science and medicine and so on but there would also be a consequence with regards to the field of cryptography and in my area at NIST we work on creating standards for cryptography which tell the government and other organizations how they can safely use cryptography for their application needs and it's been known for a while that with a large-scale quantum computer that there are some attacks which would completely break some of the crypto systems which we use today these are called public key crypto systems and they are standardized in some of our our documents at NIST and even though we don't yet have a such a quantum computer around people are actively working on building one they're actually you could already be under a threat of attack from one before one is built and this is because somebody could take your your data and information which is encrypted using our current crypto systems and they could just hold on to it they can't read it because it's encrypted but they can wait until the quantum computer comes along and then they're able to crack into it and you may not be providing protection that you hope for the amount of time that you do thus it's important to already be thinking about this project and getting to work on making sure we can counter this threat now all of this depends on when a quantum computer will be built and the answer is nobody knows for sure people are actively working on it working very hard making a lot of good progress there are some experts who have estimated that it's it's possible that in 10 years 15 years you know maybe we might have one of these around and so that's why NIST has been working on this project for quite some time want to emphasize that this is a a field called post quantum cryptography it's to search for crypto systems which would replace the ones that would be broken by an attack from quantum computers there's another type of cryptography that sometimes kind of gets lumped in with this because it has the word quantum in it and that's quantum key distribution or qkd that's a that's a different application and i'm not talking about that in 2016 at NIST we issued a we published a short report explaining post quantum crypto and talking about what we would be doing to work towards standardizing the crypto systems in essence we kicked off a large international competition and the scope of that was for public key digital signatures and public key encryption or key exchange algorithms and we pledged to run a process that would be open and transparent to select the the most secure and best crypto systems that came out of this process our criteria were number one security and number two performance besides a number of other characteristics that we hope the the algorithms that we received would have and this was open to everyone we received a large number of submissions and we posted them on our website the complete specifications as well as a code that you could download and implement this so internally at NIST we are testing these and we encourage people from around the world to evaluate them as well we structured our process to be in a series of rounds where at the end of each round we would select a smaller number of algorithms to move on to the next round and for us to focus on currently we're in the the middle of the third round we have seven finalist algorithms and eight alternate algorithms that are currently being looked at we expect towards the start of 2022 or so we will select a small number of them to begin being standardized as the first quantum-resistant algorithms to be included in our our standards for public key cryptography we'll then put those out for public comments and hope to have the the final version completely ready and published by around 2024 we definitely want people to be aware of the the threat and what's going on with what's called post-quantum cryptography and to be planning ahead there will be a transition to these algorithms and like any crypto transition it's not always it's not going to be necessarily easy and that's particularly the case here because we're dealing with algorithms that are a lot more complex in terms of the math they use and some of the characteristics that they have they also have things like larger key sizes so we as much as possible we're trying to prepare as much as we can and encourage others to do so so we encourage companies and organizations to you know do an internal analysis of this look at the crypto you're using is it threatened by quantum computers be aware of what's going on and the sooner that you plan ahead you'll be able to get ahead of the curve and not be left scrambling at the end once again thanks for the opportunity to speak and if you have any questions for me the good folks at IBM will send those my way or give you my contact information thank you very much so good morning my name is Vadim Lubashevsky and I'm a research scientist here at IBM in Zurich so we just heard Dustin from NIST talk a little bit about the importance of switching to quantum safe cryptography and he also mentioned that NIST narrowed down the selection list for the new standard to about seven finalists so I'll now talk a little bit about what IBM's role in this is and how we're planning for this quantum safe future so IBM has contributed five of the initial 69 schemes that started out in this standardization process in 2017 and four of these five are now among the seven finalists and the remaining one is an alternate so we've definitely got some internal expertise in this field and we're taking this transformation to quantum safe crypto pretty seriously so in fact IBM has already incorporated quantum safe crypto into a good number of its products so for example IBM cloud and redhead open shift and the cryptography that we've incorporated comes from a family of schemes that we submitted to NIST which we call crystals it's an acronym for a cryptographic suite of algebraic lattices and these schemes derive their security from the fact that they are based on the presumed algorithmic hardness of something called lattice problems and these lattice problems are mathematical problems that have been studied for many decades and they seem to be resistant to quantum attacks so luckily for us they're also something that lead to very efficient cryptographic schemes and what's more and you'll hear an example of this later in this broadcast is that the mathematics of lattices also allows us to construct things that can't be done in any other way so they have benefits even beyond just quantum safety so for these reasons cryptography based on lattice problems really might become very important in the future and i guess this point might be interesting to ask what are these problems what do they look like and how do they differ from classical problems upon which crypto now is based so a classical problem which maybe you've heard of if you know something about cryptography upon which some of today's cryptography is based is called factoring so i mean there for example i give you a number like let's say 713 and what you're supposed to do is to find the two numbers 23 and 31 in this case whose product is 713 right so for classical computers this factoring problem is quite difficult at least we believe it's quite difficult when these numbers are big so if the number i gave you is a thousand digits i mean i gave you a three digit numbers that's not hard but if it were a thousand digits then the best algorithm on the best supercomputer would probably not finish for billions of years now a powerful enough quantum computer on the other hand can solve this problem in a couple of hours and this is where the problem comes in for security so now what are these lattice problems that we believe to be hard even one even for quantum computers right so the easiest way to explain what a lattice problem is is as follows so suppose someone creates a random list you know for this for this example let's just say it's six numbers between zero and a hundred and everyone knows this list me you the bad guys everyone i mean in fact if you were wondering what's behind me that's the list right so here's this list and then it's completely public and what i do is i pick three of these numbers i don't tell you what they are and i write down their sum so let's say i write down the sum just you know so you see what this 130 so now your job is to figure out which three numbers i picked or what are the three numbers that sum to 138 right so i guess there's no way for you to tell me right now if you have the answer maybe you can type it into the questions and the communications team will let me know if somebody gets it no i'll wait a few seconds no no okay well anyway it doesn't matter right i mean the numbers were 28 39 71 right so it's kind of hard right but i'm sure if you had enough time you would you would figure this out um but it seems like you know if we took had more numbers uh than for classical and quantum computers this problem would be extremely hard so if we had a list of you know a thousand thousand digit numbers um then uh you know this problem seems like it would be hard even for quantum and classical cryptography classical computers right and upon this problem we can build very efficient and expressive quantum safe cryptography now as i said before some of this cryptography is already in systems today and it's not just IBM who's experimenting with the crystals library other enterprises are too and the software is open source so anyone can go ahead and use it now and so so far from these experiments we've noticed that the efficiency of the schemes is such that the end user won't notice any difference so in fact sometimes the new scheme is even faster so the quantum threat is not an existential one for cryptography we will have security it's just that we need to do the work to switch over to different cryptographic algorithms so um i'd like you to walk away remembering just a few key points so first is you do not need to do anything quantum to fight against the quantum computer there are many normal mathematical problems um which are suited to quantum to cryptography that a quantum computer uh most likely can solve and in the vast majority of cases if today's cryptography is replaced with lattice cryptography the end user won't see any negative effects uh in fact in some cases it may even lead to a speedup and uh third is there are many good reasons to start using quantum safe crypto now and these were mentioned by Dustin for example i mean the most important one is i guess that your data now can be harvested and stored until a quantum computer is built at which point it can be decrypted so all confidential data from today can become a completely leaked and insecure when a quantum computer is built and you know to prevent something like this because it's already efficient there is no really no reason not to start switching over to quantum safe crypto now and if you plan to do your switch you know you can do it in an agile fashion meaning you'll be able to later plug in any scheme that may eventually be standardized so don't hard code your scheme in but do the transition so that any scheme can be plugged in as a black box and so thank you for your attention thank you Vadim for giving us a peek into the insights of quantum safe encryption and how it can protect us against threats from future technologies we learned earlier that confidential computing is one way IBM is helping clients solve the challenge of maintaining the privacy of data in the cloud it allows us to encrypt application data when it is in use but what can be done to protect the data from the application itself that's where the prospect of fully homomorphic encryption comes into play over the past 10 years IBM has taken something so complicated that only a few people could use and turned it into 10 lines of simple code today we are excited to share the latest advancements in this technology and how IBM is working to bring it from the research lab into early adoption by clients our private information and data are being shared more widely than ever before and often we're the ones sharing it we share our data in exchange for convenience and improved services as long as our personal accounts remain untouched we think nothing of it and for most giving up our personal information is required to interact in the digital world both at work and to utilize basic everyday services so how do we know our data is safe while most of the sensitive data we share is encrypted encrypted data is useless to hackers and thieves as it's translated into complex code or cipher text that can't be read by humans that's a good thing but while encryption safeguards our data as it's being stored or transferred the data must be decrypted or translated back into clear text to be processed this provides a window of opportunity where your data is exposed making it vulnerable to cyber criminals privacy violations and other misuse IBM is combating this problem with fully homomorphic encryption or FHE which is changing the paradigm of security it's a technique that enables computers to process sensitive data while it's still encrypted for example every time you hop in the car and fire up your phone's navigation app the app needs to know where you are where you're going and any stops along the way in order to give you the best route with FHE the app could still provide those same directions without the service behind it needing to see or save that information about you maybe you don't care about an app knowing your location maybe the convenience outweighs the risks but what if this data was much more sensitive like say healthcare records or your personal banking data suddenly the stakes are much higher the ability to apply AI machine learning and other computing functions to data without exposing more private information is the essence of what fully homomorphic encryption enables first in vision in the 1970s an IBM researcher pioneered the mathematical framework to make FHE possible in 2009 but FHE was too slow for everyday usage because of the enormous computing power it required back in 2011 it took 30 minutes to process a single bit using FHE but by 2015 we could compare two human genomes with FHE in less than an hour and now through software and hardware advances the time has come for companies to start experimenting with FHE FHE will be a game changer for security in the hybrid cloud era unlocking new business opportunities with its ability to process regulated and sensitive data FHE will drive wider enterprise adoption of hybrid cloud platforms especially in highly regulated industries like financial services and healthcare FHE could also impact mergers and acquisitions where due diligence could be performed without violating the privacy of account holders shareholders and clients even airlines hotels and restaurants could utilize FHE to offer packages and promotions without giving their partners access to details of closely held customer data sets but first things first companies need to get their hands on this technology to begin developing real-world usages for FHE within their unique industries with the launch of IBM security's homomorphic encryption services clients will gain access to both the tools and cryptography expertise needed to start building prototypes for their own FHE enabled applications pushing forward on this new frontier of security is part of what positions IBM as the leader in hybrid cloud all the while protecting the privacy and trust of clients and keeping your data safe hello my name is Eric Moss and i'm responsible for strategy within the IBM security business unit part of which means getting technologies like fully homomorphic encryption out of the lab and into the hands of our clients so let's first understand FHE as you just heard it's a unique form of encryption and it's going to allow us to compute upon data that's still in an encrypted state but to better understand that let's first revisit some of the classical encryption models that we know well we have data at rest and this has historically allowed us to protect data that's being stored whether on a disk or in a database then we had data in transit and this allowed us to protect the confidentiality of data as we transmitted it between point a and point b over a network what's been missing has been this ability to compute upon data while it's still encrypted keeping the data in a protected state while a CPU can compute upon that data so let's look at an example of this let's say we have an application and that application needs to perform some type of statistical analysis on a data set well in order for that application to do its job the app first needs to decrypt the data in order to access it then it can perform a statistical analysis in the form of computation on that data but the act of decrypting the data itself puts the data in a vulnerable and exposed state with FHE we now have the ability to actually keep the data encrypted never exposing it during the computation process this has been somewhat akin to a missing leg in a three-legged crypto stool we've had the ability to encrypt the data at rest and in transit but we have not historically had the ability to keep the data encrypted while it's being utilized this is being made possible by some of the same lattice encryption techniques and mathematics that you heard Vadim discuss so again let's look at why this is important to our clients and to businesses at large first let's acknowledge the fact that our clients are facing two really large forces against their business the first is in security but the other one is a business force on the security front companies are facing multiple pressures in the form of increased regulations both industry as well as government regulations that are pushing for better privacy controls the punitive fines and damages that go along with this are significant on the flip side though these lines are looking at the business pressures that they're facing they're looking to improve the use of their data data as a competitive differentiator in the form of collaboration or monetization and they also have an increasing reliance upon that data for their day-to-day operations an example of this could be seen in the health care ecosystem the health care ecosystem relies heavily upon collaboration between health care providers insurers clinical researchers the ecosystem is is quite vast and they must have the ability to seamlessly provide high quality services through data collaboration but with that is also the need to provide trust and the ability to secure this data and the ability to secure that data is paramount to their trust in the broader public's eye in this case FHE will allow us to secure that type of collaboration extracting the value of the data while still preserving the privacy of it meanwhile FHE allows us to provide a certain type of security that can follow the data this differs somewhat from the confidential computing that we discussed earlier as it's not reliant upon any type of special hardware and it allows us to ensure that even data in untrusted environments where we have no control over the hardware can remain secure so where are we today with homomorphic encryption you heard IBM has been working on FHE for more than a decade and we're finally reaching an apex where we believe this is ready for clients to begin adopting in a more widespread manner it's been historically complex not just in terms of the calculations that are performed on the data but it requires a lot of computing power and the skills and learning curve have typically been very steep for the normal client out there but there's some good news here researchers have been working as we discussed to refine this process making FHE much more efficient than it has been in the past and we now have technologies that are going to allow our clients to more easily adopt FHE and that becomes the next challenge widespread adoption there's currently very few organizations here that have the skills and expertise to currently use FHE but IBM research has been helping in this space by delivering not only open source and toolkits to help encourage that adoption but IBM security has recently launched its first commercial offering on IBM fully homomorphic encryption services back in December this is aimed at helping our clients start to begin to prototype and experiment with fully homomorphic encryption with two primary goals first getting our clients educated on how to build FHE enabled applications and then giving them the tools and hosting environments in order to run those types of applications so how is FHE going to be used in the near term as you heard highly regulated industries such as financial services and healthcare will be some of the early adopters in this space they have both the need to unlock the value of that data but also extreme pressures to secure and preserve the privacy of the data that they're computing upon but rather than just tell you about that here let's talk to one of my colleagues Omri and IBM research who can show us a demonstration thanks Eric working on FHE we wanted to allow our customers to take advantage of all the benefits of working in the cloud while adhering to different privacy regulations and concerns what only a few years ago was only theoretically possible is becoming a reality our goal is to make this transition as seamless as possible improving performance and allowing data scientists and developers without any crypto skills a frictionless move to analytics over encrypted data in the demo I'm about to show you we worked on a use case for such a regulated industry the healthcare industry in this demo a hospital is sending private healthcare records to the cloud for analysis now this could be done to analyze DNA for genetic issues or us will be shown here to alert regarding a possible risk for certain condition now prior to FHE such analytics on the cloud were very challenging since the data had to be decrypted prior to processing so this uh interfered with different regulations and privacy concerns but now we are able to upload the data encrypted analyze it while encrypted using a machine learning model which is in and of itself also encrypted get the result of the analysis encrypted and send them back to the hospital or the patient for decryption so let's start the demo as you can see what was one what once took hundreds of lines of code and advanced crypto skills a can now is now accessible to data scientists a whom with less than a dozen line of lines of code you can see marked here can leverage the capabilities a of FHE now if we run this code give me a sec now if we run this code you can see that what was just five years ago would have taken a few hours is now processed in much less than a second if you can see here 0.069 seconds to be exact and thank you thank you omri you've just seen three crucial technologies that are shaping the future of secure computing around the world confidential computing quantum safe encryption and fully homomorphic encryption these capabilities were born in IBM research and we are working with partners and clients some of whom you have met today to commercialize and integrate them into our everyday lives thank you for joining us today and stay well