I don't want to have favourite speakers, but Sean's one of my favourites too. We met on the TEDx stage actually a few years ago and have been sort of hanging out ever since. He's originally from New Zealand but now based in San Francisco, where he's co-founder and CTO of Quid, an augmented intelligence company. I'm going to read this list then you just see basically he's an overachiever. He's a physicist, a Rhodes scholar, obtaining his PhD from Oxford on the mathematical platforms that underline that modern war. And this research has literally taken him all over the world from the Pentagon to the United Nations and Iraq. And he's often on CNN. I always see on the American news talking about war and cool stuff. So he has had a past life, however. There's a lot of rivalry and competition between Sean and I. Sean was a fellow nanotechnologist. He used to be one of us and then he switched. Who used to work at NASA keeping the rocket theme on self-repairing nanocircuits. And therefore we have three rocket themes today. That was number two. He has a huge list of massive successes and not just in business, but also in sports. He's a two-time former national decathlon champion. Now I was like, okay, whatever. I bet you're not that good. So we went on, you know, those nice cycle renter bike go around why he can drink some wine tours. Two A-type personalities who are sporty nuts did that wine tour on bikes. I don't think we drank any wine. I think we literally raced each other around the whole island and we missed the winery. And we actually got called back by the event organizers being like, we saw you guys. And you cycle past the winery and you kept going. And I'm like, because I'm winning. So anyway, as well as his athletic prowess and quid, he's a super fun, exciting guy to be working with. And I think the thing that's made me most jealous this year from Sean was the fact that he got to work with Morgan Freeman. I know. I'm sharing his research off on the TV show through the wormhole. So if you haven't seen that Google, it's pretty awesome. And Morgan Freeman is one of those amazing people, as is Sean Golly, who is our next speaker. Sean. That'll work. All right. Let's get that there. Thanks, Michelle. I don't really know how to respond to that. But if you ever get the chance to have Morgan Freeman for a few minutes, you should do one thing. Absolutely. And that's going to leave a voice message on your phone. You really can't go past being introduced by Morgan Freeman on the thing. I would also kind of put the caveat on that bike racing.  But it's supposed to be leisurely, right? She showed up with a racing bike. So, you know, I was like, at that point it was on. I want to run through Vaughan Sean. Here we go. Brilliant. I'm going to start with this. Because this thing for me really sums up the year that we've had at Quid. It's been a year of selling. It's been a year of getting up and pitching people time and time and time again into the big companies, the big governments, the big hedge funds around the world. It's something that I think when I started Quid, I never really had the sense that that's what the company would actually be doing, would be selling.  You never realize that at some point you're just selling that thing the whole time. But it's been a wonderful thing because for me coming into it, I was like, I'm not really a salesperson, right? You know, it's like selling for other people. I don't like getting told no. So I'm probably not a very good person and I really don't like asking for money because it's kind of awkward. So for me going through this I think has kind of been a couple of things. One is you realize when you build a company, you ultimately sell stuff, which should have probably occurred at the start of it. But secondly, it realizes too, is I think we have stories that tell ourselves about what we're good at and what we're not good at, where our strengths are and where they're not. And for me it was always, well, I do technical but I don't do selling. And I think coming through this year, I think I've earned my selling badge at the very least. And so we close the year out and I get a little bit of time now in New Zealand to take a bit of a break and just absolutely thrilled we did 8.5 million of subscription sales this year with the first full year of the software on the market. And so for me that just represents kind of a huge milestone of creating software and having it out and deployed with the sales team and kind of hitting our number. Our number for the year was 8 million, which to kind of go past that was really, really fantastic. So thank you. But it was also important to come back to New Zealand. So when I was chatting with Scott about coming down here, it was the single most important thing. I said, I've got to get down to New Zealand. He said, you know, why have we got to get down here? I said, for me it just gives me a chance to take a break from that whole circus in Silicon Valley and just get out on the surfboard back in Christchurch and just think about where we've come from, think about the next year where we're going but also think some different ideas. And I think it's so nice to be able to come home to New Zealand and take that time and that space. So I want to kind of share some of that stuff that's on my mind is I think forward towards the next year and kind of share some of that with you. I thought about maybe like saying, well, I could tell you about how to build companies but I think honestly if you were looking at advice from me, it's probably the wrong person. I think I've probably made most of the mistakes and I always think it's funny when someone says, how do you do the stuff? I have no idea. I really don't but I do have some interesting thoughts I think you're like on this. So this for me is fascinating, the human brain and particularly the limits of the human brain. What it can do but also what it can't do. And I think we tend to think that it's infinite, right? We've got infinite capacity in the way we can think but there are very, very real limits in what we can do. And one of these is the speed of thought, right? So we can think only so fast and scientists got together and they measured this and they said, well, how fast can you think? And they took a bunch of chess players and they stuck them into an fMRI machine and it started to measure the time that they would react to whether the board was in check or not. And they found that the experts could do it in about 650 milliseconds and the amateurs about 900 milliseconds, right? So no matter how good you were at chess you couldn't think faster than 650 milliseconds as to whether the king was in check or not and this sort of represented the smallest atomic unit of strategic thought. So the human brain can't think faster than .65 which is about this long, right? That we don't exist below that and it seems kind of trivial, right? It seems like that shouldn't really make a big difference to anything except this is what happens because of that little limit in our cognitive processing power. Today we're looking about 65% of all US equities are traded by algorithms and they're traded by algorithms because algorithms can think a whole lot faster than that. And now instead of looking at people trading stocks backwards and forwards it's a bunch of servers co-located to be as near as possible to the source of information because the speed of light makes a difference in these equations and it's developed a whole industry around this. It's an industry now where they're laying cables between London and New York to shave 5 milliseconds across the round-trip time between the two exchanges. So for me this is $300 million spent to take 5 milliseconds off a trade that dominates the market because the human mind doesn't think any quicker than .65. So for me when I look at where the really interesting stuff is I think, well, where does the human brain stop? And where the human brain stops the algorithms will eventually take over and that has pretty profound implications not just in technology but also the physical environment. But in addition to that I think our relationship with these algorithms is going to be one of the defining characteristics of the economy in the next decade and I want to run you through some of the thinking that I've been doing about that. So there's definitely benefits, right? Like if you run this you'll get the bid ask spread it'll go down to almost zero. Really, really efficient markets, massively efficient and it's almost always efficient almost all the time except when that happens, right? And those that don't read those stock tickers for a living you'll probably know it more like that. So Flash crashed at 245 where collectively the market decided to take a trillion dollars in market capitalization for no real apparent reason the algorithms got together and decided to remove it and then give it back 15 minutes later a little bit unhurt and slightly worse for wear and they still don't quite know what went on in that period of time, right? The algorithms collectively decided that they wanted to run the world's markets and they decided they wanted to impose their own will on things and they traded stock in Sotheby's for $999,000 and stock in Accenture for a cent maybe they knew something we didn't know but that's where they got to and it's because if you look at the thinking time, right? The humans, we think if you read a scientific journal three hours watching a post article, you know maybe seven or eight minutes you get down to about three seconds, a 140 character tweet, right? But beneath that you're moving into the sub thousand millisecond the limits of human cognition and at that point it's the algorithmic ecosystem, right? And this is the, where you're looking at the time for light to travel from New York to London, 65 milliseconds you can execute a trade in about 100 microseconds on the NASDAQ and now they've got hardware executable chips so they'll do 740 nanoseconds to do a trade now nanosecond for those that aren't physicists is about the amount of time it takes for light to travel that far that's why, you know, the position of your servers inside of the co-located infrastructure is really important they actually measure out the cable so everyone has the same amount of cable but that's the kind of the world they're in, right?  Knight Foundation moving that would be strange but these guys run, you know, some of the biggest high-frequency trading and they showed up one morning they were releasing a new algorithm into the system they got this kind of set of servers that they run the algorithms on they test it, they do all that stuff and then when they're happy they release them into the market, right? They go and trade well, they did that this morning one of the mornings back in 2012 and the markets started going a little bit strange and they knew the market was strange they didn't know that they were responsible for it going strange but it was all of a sudden they're like, the market's weird and 45 minutes it took them to figure out that they'd release an algorithm into the market that was never supposed to be in the market it hadn't been fully tested in fact it was the opposite of what should have happened it was an algorithm that was used to stress test the algorithms that were supposed to go into the market so it was a dummy algorithm that would sell high and sell low and buy high, right? do the opposite and it got released and they lost $440 million in 40 minutes and then they pulled the plug and then they got effectively got bought up for distressed assets at $0.15 on the dollar right? and it just sort of shows you these things they're sort of like crazy, right? like this shouldn't happen but again, this is stuff, this is reality this is going on and it goes on because we don't think at the speed but the algorithms dominate at the speed and again, it's start thinking about well, what does this mean for our economy? what does it mean for us? so algorithms like the night stuff they read zeros and ones, right? zeros and ones, basic time series analysis really, you know driving the quant driven revolution of financial markets but they also now are starting to read news, right? they're starting to read not just ones and zeros but, you know, letters and digits and this is really fascinating because this sort of stuff happens this is a bunch of E-mini futures there are a type of thing that you can trade and you'll look at the volume there, right? that's the total volume and then you see it sort of stop and get very, very small, right? so the algorithms all leave the market for some reason, right? remember, the algorithms dominate the market and they all leave and you think, well, why are they leaving? and they're leaving because there's a schedule news announcement about unemployment data coming out and the unemployment data is coming out at 12.30 so all the algorithms get out of the market at 12.25 and they say, I don't know how to read that stuff so I'm not going to trade and what you're left with is humans and the humans read the stuff and they go, yeah, nothing, nothing really significant here and all the algorithms they say, push the button, come back in but you look at it, you think, jeez, like the algorithms decide to leave the market, the market's kind of screwed as far as liquidity goes and that's because, you know, they can't read but if they could read, what would they do? and that's exactly what they're starting to do because in a world where you're competing for the speed of light and the distance that it can travel the 10 minutes that they're out of the market is an eternity huge amounts of time remember, we spent $300 million to get 5 milliseconds on a cable, right? so trading algorithms to read news is going to open you up 10 minutes what's that worth? so this I think is going to be very, very significant over the next couple of years the algorithm's getting very good at reading news now that seems all well and good algorithms reading news, trading markets get a machine readable news system read through an article a bomb goes off and bagged out I'm going to trade the VIX index or I'm going to trade the currency, blah, blah, blah it's going to be more volatile, I'll make some money until stuff like this happens, right? breaking news to explosions in the White House and Barack Obama is injured never happened, this was a hacked story done by humans this time from the AP Newswire and when that happened, this happened the algorithms left the market they said there's a bomb, I don't know what to do and $200 billion was removed from the market and it came back and again the volatility changed and for me again is like well we've got algorithms now being able to read news, not sure what to do there's opportunities if they do start understanding it they'll start trading it, but of course if they start reading the news, won't they start writing the news? and they start writing the news how do we believe and what about us isn't the news meant for us, right? so we log on, right? we go on and we think well this is again a kind of step back, okay so financial markets are gone we don't run them anymore we can't think fast enough that the new programs are going to start reading our news and potentially writing it well when you open the New York Times you open the Herald it takes a little time to load, right? you'll notice it takes a few seconds you blame New Zealand's shitty internet for that it takes about 800 milliseconds to load and you'd be right for the most part to blame New Zealand's shitty internet for that, but you should also realize 150 milliseconds of that is built in for an online ad auction that happens so when you go to the website it takes a few milliseconds and says we're going to auction off your presence we're going to auction off your presence to the highest bidder to show you an ad, yes or no, right? so there's like a little market that evolves for selling ads backwards and forwards and I think that's really fascinating again because 61% now of the internet traffic is non-human so the internet's kind of switched the same way as the markets it used to be the internet was for us, right? we had the traffic now we don't have the traffic anymore and it's up from 51% last year or 49% last year so again the internet is slowly moving that way because there are advantages to being able to think 150 milliseconds that we simply cannot do it's not within our biology so at this point you kind of want to push the button and say stop like, you know, this all seems a little bit complicated and a bit too much, but the reality is we can't really turn back from this so how do we deal with it? and also let's think a little bit about what we're actually dealing with so, you know, Google and Facebook what they kind of think of is having massive information filtering algorithms ways to kind of separate information back out to you and we think of that and we experience them as products and we think about how they do things but we don't often think about the economics and a large part of the economics of these two companies is electricity because you get electricity to store information and retrieve it and electricity is one of the single largest costs of running these two operations if you flip it back out what you see is it costs Google about $12.90 per user per year and it costs Facebook about $1.20 to give you the product I think these numbers are just fascinating that you can have Facebook for $1.20 obviously if you've got a billion people that can join you on that you can have that but it's not a lot of money what they're spending on the electricity to give you the product at the end of the day and that's even kind of more surprising because you look at things like this Wikipedia shows up 85% of the time for the 1,000 most common searches on Google in many ways Google is sort of crawling Wikipedia and you probably wouldn't notice too much of a difference if all it did was give you back results from that so it's kind of interesting that this kind of search and filtering mechanism that exists and I think of this because you think about well we've got Facebook and we sort of accept Facebook as a social network but what else could it look like and we say well why does it look like what it does and we've got a couple of things here the identity is one axis and you take the history so am I real and do I have to be me online and if I post something are you always going to remember it and Facebook is yes you have to be real and I'm going to remember everything and they're up there because that's really really profitable that's a hugely profitable space to advertise against but we could also think of one where I don't have to be real and you'd be reddit right you can have your pseudonyms that's a really different kind of community we can think about what no history and no identity looks like does anyone think about that well that's 4chan if you haven't been there don't go there you'll ruin your day but it's a really different kind of world and then of course on the other side real identity, no history is Snapchat so you start to explore the space of different kinds of ways of being now these are algorithms the algorithm is doing something very simple do you have to be you and am I going to remember you and just by varying those two variables you end up in a difference between Facebook and 4chan and the online behavior that we experience through them is night and day and I think you should just kind of reflect on that and think what power are the algorithms having on the kinds of interactions that I'm having with the world and did I want you know the all history all identity is that what I want because that's kind of what we've got and I think it's coming back and saying well how do you design for these worlds so coming from that I think kind of splitting this out we've been treated I think in many ways as products by algorithms most of us interact with algorithms as products our identities are bought and sold online to give us advertising that we'll hopefully buy things from so we've had that but that's pretty narrow right there's a whole lot of other ways that we can interact we could actually be the owners of these algorithms so instead of the algorithms serving information and the hope that I might buy something I could actually own the algorithm and say well give me things that'll make me a better person make me a better friend, make me smarter make me learn about stuff that I probably don't really want to but I probably should and don't try and sell me that stuff so we could own them we could be a really different kind of relationship we could also be on the other side a sort of technosurf well you can't afford I can't afford to be monetized as a product but there's some stuff the algorithm is not very good at doing and it's going to offset them to me so you can kind of think of being a servant of the algorithms and that's actually happening but you can also think of augmented intelligence actually driving algorithms being in a relationship with algorithms as sort of a conversation you own them of course but you're not just accepting what they're giving you you're actually feeding back and saying yeah I want to drive it like I'll drive a high performance race car so there's a whole different range of ways of interacting with algorithms but what we've been given is very very narrow and I think to our detriment this is a graph that kind of struck me as all the it's my favorite graph for the year and kind of what it says a graph of inequality I don't know if anyone saw this when it came out but it should worry you I think because what it's looking at is the amount of income owned by the bottom 90% versus the top 0.1% and you see that just at the point where they're crossing and you'll also see last time they were crossing was this lovely time period in the 1920s through to the 1930 and so for me this I think this graph and this rise of inequality it also jumped out in 1984 New Zealand was one of the most equal places in the world over the last 25 odd years we have had the single biggest jump in inequality in the world and so the stories that we had of growing up all equal I think are kind of different but the whole world's moving that way and I think what I put to you is the large reason of this is because of algorithms algorithms are fundamentally making our world more unequal because the information and the algorithms that are operating don't affect everyone equally and I think this is something to really consider because if you can afford the high end subscription for an augmented intelligence product you'll drive and find insight in the market whereas everyone else who can't won't the difference between being treated as a product and being driving software to make trades are really really different and really distinct so something again to think about we talked a little bit about technosurfs and for those that know Amazon's Mechanical Turk this crowdflower as well as a platform that lets that run so these are systems that you log in and they're called human implementable tasks and you get paid maybe between five and ten cents to do things like determining whether that picture is obscene or not or determining what color the sum object is things that the algorithm could do if it had money for the electricity but actually you're cheaper so I can run with you instead and maybe I'm not quite smart enough and I can leverage you and so we've got crowdflower boats that have a million human hours available at any moment you can access a million human hours to do things that a few cents a pop things that algorithms can't do because of cost or can't do because of complexity this leads to some really interesting things this is a performance art piece by Aaron Koblin he paid people two cents to draw a sheep in New Zealand you have to have sheep they got seven and a half thousand people to draw a sheep they got ten thousand sheep cost them twenty bucks and that was great because then he took all those sheep and created an art exhibition and sold each of the paintings off at twenty dollars and then people complained they said you can't sell my thing at twenty dollars they said yeah you signed the user acceptance thing so he took what people did at two cents and sold it at twenty bucks it was sheep and people he said draw sheep for two cents he was like okay which you know that's why one of my favorite pieces of art here and it's like is that our relationship with these systems are we the sheep, are we creating sheep who's getting the value, where is the value going and I think you should sort of pause and think about that for a moment but there's actually some really good sheep in there for two cents augmented intelligence this is the space that I've been working in the kind of the human coupled with the machine, the center and you can think of a bunch of companies like Palantir, Record of Future and I asked they all working in that space creating these intelligence platforms that let people interact with algorithms it looks a little bit you can kind of think of that there but it looks a little bit like this this is the software that we sell but you can kind of dive in and see it in time and again go back into all the space here what we're looking at is all the all the active participants in the world of the global space industry you've got SpaceX up in top and red all its first-order partnerships that it's done business with in yellow and its second-order ones there in green you've got thousands of objects tens of thousands of things it's all been extracted out from open source unstructured information projected down to a three-dimensional interactive space that you can go and explore and figure out and understand the structure of the world that's around you so you know at this point it's not like the computer's giving you an answer of like you know I predict with probability X what's going to happen with the global space industry it's actually said here's the information go and explore it and figure out how you want it to be figure out where you want to position yourself and so for people like NASA who use the software a lot of it is about trying to understand the structure of how the space evolves and then figuring out how to position themselves within that space there another one here's is Occupy Wall Street you can kind of see this time the stories unfolding in real time as the political protest moves you can see the stories coming out and this becomes very very powerful because you start to think about it as you know if I'm putting out stories what I want to position them you know where do I want my story to end up is there a white space in the middle but I can start to connect ideas together to get resonance that no one else is really seeing and start to monitor that as that goes through you've got a topology of information that you can effectively interact with and understand you know how do I want it to change so we did this as sort of a I guess a demo about 18 months ago this midterm election we had a bunch of senators and very close races starting to use the software now from the US political campaigns and everyone that used the software actually ended up winning their races most of them are on the Republican side so I don't know what that tells you but for the first time this has actually been deployed in elections and again these platforms and if you have access to this information you can see more and see further than anyone else that doesn't and again you start to think about how that impacts and affects inequality as we drive through this different system I want to finish on the final thing which I think has been for me the most fascinating piece to think about is this idea of subscription bots things that you own things that work for your benefit instead of being treated as a product and there aren't really a lot of companies around on that so you sort of have to turn to the next best thing about science fiction and those if anyone has read Neil Stevenson's work there's a book called The Diamond Age and there's a course inside of The Diamond Age there's a book made with nanotechnology called The Young Lady's Illustrated Primer and it's a book that writes itself and it writes itself for the young woman of the story to educate them to excel and learn and be very very successful inside of the world but it's a book that conforms to the reader and kind of makes the story up as it goes along in some ways manipulating them but in other ways educating them and I think this kind of idea of a primer for people a software subscription that you own that has your benefits in mind is going to be something I think we're going to see a lot of as we go forward we're getting there again if we look forward into actual patents this is an auto generation of social status updates so it's like Google's patterning it's like I'm too lazy to update my status but I want people to know that I'm active so can an algorithm do that for me and you start thinking about it again it's machines learning to kind of write machines learning to impersonate humans and we're seeing there's sort of a crude version of this online it's a Facebook what would I say it came up with your my valet ticket which I don't know if that is either a reflection of the badness of the algorithm or just like I don't really post things that are very sensible but still it posted that for me and I was very grateful everyone looked kind of confused I got a few likes it gets a little more complex and this is a bunch of tweets so those that can't read Spanish it's coming out of Mexico City it's a bunch of tweets here it's Mexican Twitter bots alleging that a reporter was not killed by a drug cartel just think about that for a second we've got organized crime syndicate pushing out propaganda bots to convince users online that an alleged murder of a reporter didn't happen right this is again it's not this is happening today so we think about this it's around it's going to have a big big impact on what we do here's what those bots look like and actually if you run the algorithms you can kind of see it in time they all come out every 10 minutes and it's actually pretty easy to see them but they're evolving right this is what happens in China China's got a bunch of these bots this time protests that were happening in Tiananmen Square it's really hard to figure out from the temporal signatures they figured out that the algorithm the people designing the algorithms are like we need to get rid of the temporal signatures of what's going on so we're going to move into a world where algorithms are pretty good at reading and writing and they're pretty good at understanding who you are and they can think fast in you and they can read more than you and they're going to treat you as products to be manipulated bought and sold or you can own them and have them work for you and I think there's going to be a distinction that we're going to start to move in and that decision is going to come with money and some people are going to be able to afford them and they'll do better most people are not or can't afford very good ones you're my valet ticket right that could be mine people would look at me and say sure you should get a better algorithm and they're not going to do so well and so there's an inequality thing I don't see it closing because of the stuff and it's something we really need to think about and I sort of leave you with this final piece of that and this is maybe a world that might exist I hope it doesn't but it's something that we should all really kind of consider and maybe over the Christmas break as we're having a little bit of time relaxing think about that and how we want to build the companies that we're all going to be building in a world where this is now a possibility so thank you


Proudly, we hail. New York City, where the American stage begins. Here is another program with a cast of outstanding players. Public service time has been made available by this station to bring you this story. As proudly we hail, the United States Army. Our presentation is entitled, The Dragon Returns. Two returning sergeants of the United States Army, enroute to their homes to enjoy a hard earned leave, find mystery and excitement in San Francisco's Chinatown. Our first act curtain will rise in just a moment, but first, the man who measures up will succeed anywhere. For a life of excitement and adventure, join the United States Army. You see, the Army is the proving ground, the place for the men and the boys' part company, where, in a few short months, you'll learn more about how to take care of yourself and how to lead others than you could in a lifetime of civilian activity. For the Army, your opportunities for advancement and leadership are unlimited, but you've got to have what it takes. Right now, the Army has a new program in effect that permits you to enlist directly for training in the specialty of your choice. And here's how it works. You make application for the course of your choice and then take a qualifying examination.  If you're accepted and a vacancy exists, a class space will be set aside in your name. Now, if, on the other hand, the classes are filled, or if for some reason you happen to fail the qualifying exam, then you're under no obligation to enlist and no obligation whatsoever. Here's an opportunity for you to serve your country and build a man-sized career for yourself that will take you as far as you want to go. Visit your local United States Army Recruiting Station today for complete details. And now your Army presents the proudly-we-hailed production The Dragon Returns. Boy, I never thought I'd spend my first evening back in the States from the far east in San Francisco's Chinatown. Yeah, but I tell you, it'll only take a minute. Gee, I've got presents for my Aunt Ruth, well, Aunt Harry, my kid brother. Yeah, I know, I know.  And I've forgotten to get one for Grace. How do you like that? My own sister and I forget it. Well, come on, hurry it up. Hey, how about this place? No, that's only junk in there. I want something real classy for Grace. I can't let her know I didn't bring anything for her. That's why we had to come down here. I can buy something and she'll never know that it didn't come all the way from Tokyo. Well, for that matter, it probably will have. Everything around here is made in Japan. Hey, here's the place. Very exclusive. They just got one thing in the window, that J. Dragon. I don't know. Looks like it might be expensive. Yeah, come on, I like it. Let's find out. What's it good for? How shall I know? I just like it. Maybe a doorstop, huh? Come on, this green door. Let's go in. Good evening, gentlemen. Yeah, good evening. Can I show you something? The statue at the dragon in the window. The dragon. I do not think so. Something else, perhaps, but not the dragon. Well, it's for sale, isn't it? It's very expensive. Well, that's all right. It's a present for my sister. Oh, it's for your sister? Yeah. How much is it? That depends. Is it real, J? Of course. How much? For your sister, the J. Dragon. $10 on 72 cents. Oh, that's too much. $5 on 72 cents. It's a deal. Wrap it up. Very well. Hey, that's too cheap for a J. It must be something wrong with it. I'll take a look. Here, let me look at it. That is the one you want. Yeah, it's okay. Yeah, it looks okay to me, too. Real nice. She'll like it. Gee, you sure got a good price. Yeah, almost half. That's good enough. Tila? Oh, thank you very much. I don't know anywhere. Let's get out of this neighborhood. It gives me the creeps. Gee, this was sure a night. We've certainly seen San Francisco. Too bad we couldn't get a train for tomorrow, but it'll give us another day to see the town, anyhow. Yeah, I'm getting anxious to get home, though. Hey, Dick, there's the cable car we want. We need it to get back to the hotel. Come on, let's go. We missed it. Oh, got it. Ah, well, we'll ride one more. Yeah. Might as well walk from here. It's only a few blocks. All downhill, though. Yeah. That's one thing about Frisco. Everything's so close, you know. Hey, look down that street there, will you? Isn't that a view? I have a gun in your back. What? Please, do not cry out. Hey, watch the eye. Careful, Dick. He's not kidding about the artillery. I can feel it. Your wallet, please. Okay, okay. Why don't you pick on someone else? All we've got is about 10 bucks between us. And another package, please. And that's all we have. Thank you. That will be sufficient. Hey, he's heading for that car. Quick, see if we can get the license. So, you see, Lieutenant, we couldn't get the license number because they were driving without lights. No, excuse me. Don't pray, sing, Lieutenant. She's speaking. Yes. Yes, I'll be through here in a few minutes. Okay, right. You couldn't make it out, huh? No, the street lights weren't too bright on that corner. But you think he was Oriental type, huh? About how big? Like me? About. He was more slender than you. As a matter of fact, Lieutenant, he looked something like you. He just came back from the far east. We don't think all Orientals look alike. That's something. But you did get a pretty good look at him. Well, I did. When he was turning to go back to the car. He was polite, too. He said, please. Oh, that's good, too. For what I gather, anyway, you're not out too much. About $12 in this Jade Dragon. That's right.  Well, it's a good thing you left your travel money in the safe in the hotel. You can be thankful for that. You're not just kidding. Well, Lieutenant, nice of you to bother with us. Not at all. I was in the service myself, so I take a personal interest in any report that involves military personnel. I just wanted to report this in case you could get a line on this guy so we wouldn't be bothering someone else. You did exactly right. Good night, Lieutenant. Good night. I find soldiers, Lieutenant. Yes, Sergeant, they are. Wonder who Oriental Hood is. He's new to me. Maybe not to me. Well, this wouldn't be mixed up with that thing you're working on, would it? I would be willing to lay a little money on it. But by tomorrow night, I might no more. Here somewhere. I've walked this block four times already. None of these places look like it. That's the one over there, I'm sure of it. Hey, they sure changed the window then. Look at all that junk. Yeah, but I remember the door. It was green. That's the only green one on the block. Come on, let's try it. All right. Still don't see why you have to come back to the same place as last night anyway. You can probably buy a dragon in any one of these places. Yeah, but I want one just like that when I like it. Come on, let's go in. All right. Hey, look, it's a girl buying the counter now. So it is. Good morning. Can I help you? We bought a dragon in here last night. Last night? Yeah, and we lost it. We'd like another just the same kind. I do not understand. Well, it was about eight inches high, green jade. A dragon last night? Yeah. Do you have another one? This is very peculiar, Sergeant. Are you sure it was here? I'm pretty sure. I'm positive. I noticed the door. The green door is the only one on the street. But, Sergeant, you see, I am afraid I cannot help you. Well, when will your father be back? Or whoever it was who was here last night, we bought it from him. I have no father. At least he has been dead for several years. Well, who was the man who was telling the shop last night? I do not know what you mean. You see, Sergeant, I only shopped myself. I have owned it since my father died five years ago. I run it myself and I employ no one else. And, Sergeant, I am never open in the evening. Well, there was someone here last night. Impossible. I closed and locked the shop at 5.30, as I always do. I'm sure this is the place. And I am just as sure that it could not be. Of course, I will show you something else if you like. It was a jade dragon you were interested in. I have nothing like that here, as you can see. But perhaps a vase or some nice bracelet? Not interested. Come on, Sam, let's go. Yeah. That's a hot one. Are you sure that was the place? I couldn't be more positive.  She was lying. But why? I don't know. I wish I did. Hey, Dick. Look, up there. Why? That guy hurrying up that hill there. That's our stick-up artist from last night. Why? Couldn't be. But it is. I'm just as sure of it as you are about that store. Remember, I got a good look at him. You didn't. Come on, he's going in the shop. Let's go after him. Where's the guy that just came in here? In here? Oh, Sergeant, I think he almost stick him. No one came in here, as you can see. Brother, I think maybe I'm going nuts. We were following a guy up the street. We think he held us up last night. He turned in here. Unfortunately not. However, is there anything I can show you? That guy. Oh. Please, look around. We have some very fine pieces. A statue art, perhaps. Here's a lovely little dragon. A dragon? Yes, brass, as you can see. Or perhaps something more practical. Here are some very fine cigarette boxes. Yeah, they're nice, but what about Jade? Ah, Jade, Jade. Over here, please. You see anything you like? Yeah, what I had in mind is a Jade dragon. Come on, we're wasting time.  Let's look around a little. We've looked. Okay, okay, I'm coming. What are you holding a rank hole like that for? It was dragging on the ground. You know, I might have found something in there for Grace if you'd have given me more time. It was a pretty nice shot. You did find something. Look, the Jade dragon. You are listening to the proudly we hail production, the dragon returns. We'll return in just a moment for the second act. Young man, be honest with yourself. Have you reached a standstill in life? Is each day just like any other? Are you worried about your future? And most important, are you feeling sort of dissatisfied with yourself and your personal development? Well, if this description or any part of it fits you, then it's just about time you investigated the wonderful opportunities waiting for you when you enlist in your United States Army. You see, in the Army, every man has a skill. And more often than not, the Army taught him that skill in one of its fine technical training schools. The Army offers an interesting present and a secure future, with plenty of promotions along the way. And above all, the Army molds you into a man, a man whose family, friends, and country are proud of him. If you think you can measure up, drop into your nearest recruiting station and see if you can qualify to wear the mark of a man, the uniform of your United States Army. You're listening too proudly, we hail. Now we present the second act of the dragon returns. Well, we got the dragon back. Pretty, isn't it? Pretty mysterious, if you ask me. Yeah. Funny turning up there. But it's the same one, all right. I can tell by this crack on the tail here. I wonder how it got in that other store. Well, it didn't walk. Our friend of last night must have left it when he lambed through, dodging us. The other guy certainly did a cover-up fast. Well, that's that. You've got it back. We've called Lieutenant Che to tell him, and now we can get on with our sightseeing. Hey, leave the dragon here. We don't want to lose it. Yeah, okay. Oh, wait a minute, wait a minute. I've got a pair of shoes here that need heels. I'll just drop them off on the way. I'll, uh, put them in this bag here. Okay, come on, let's go. Fisherman's Wharf, let's take a taxi. It'll be faster. All right. Taxi! Hey, taxi! Even the taxi drivers are Oriental. I think we were back in Tokyo. Yeah. Hey, this doesn't seem right. Are you sure this guy knows where he's going? I don't know. At least he knows what's better than we do. Holy smoke, this is Chinatown again. Can't we get out of the Orient? Driver! Hey, hey, driver! He heard me, but he won't turn around. Probably taking us the long way around so we can charge us more. Hey, slow it down. This looks like the same place we found the dragon. Say, driver, what's the idea? Hey, he's stopping. All right, gentlemen, just about quietly. Walk in store and nothing will happen to you. What the... Dick, he's got a gun. Look who it is. The guy who sold you the dragon. Well, I guess we don't have any choice. Very sensible, gentlemen. Very sensible. Come on. Move on. All ready. My humble apologies, gentlemen. But, you see, I felt sure that it was you who had taken my dragon from the back room. His dragon? Get him. The package you are carrying, please, Sergeant. The pack? Now, if you will just accompany me to this other room, it is more quiet back there. Ah, yes. Now, I will just look at my little green Jade dragon. What is this? I, uh, looks like a pair of shoes to me. What kind of joke are you playing with me?  Well, you see, they need heels and I... Where is the dragon? The dragon? Oh, the dragon. Where is it? You mean a little old Jade dragon? You know there what I mean. Gee, whatever happened to that thing, Dick? I don't know. I think it got broken. I can't recall. Oh, well, that's life. Hey, move on. You too. Okay, Dick, do what the man says. You make a tired holding that cannon and accidentally let it go on. Yeah. And when they are secure, go back to their hotel and search the room. Anyhow, I know how a turkey feels when it's trust up for roasting. Don't you be pessimistic now, boy. He may not roast us. Well... Hey, Dick, I think I've got one of my ropes loose enough to... Keep it down for Pete's sake. You'll have everyone in a place in here. I've got my legs free. Now, if I could... I made it. Where are you? I can't see a thing in this blasted cellar. Over here. Oh, oh, yeah, yeah. See if I can get these knots loose. Friend Wang took my knife away. Guess he was afraid I might cut myself.  I'm sure he didn't lock the door at the top of the stairs. Guess he was sure we were tied up for keeps. There must be a back way out. There's no one in a little back room. We've got it made. We'll go out the same way the guy who held us up did this morning. Hey, so kind of alley. Never mind the view. Let's just get out of here. Dragon's gone again. So much of a surprise. We should have put it in the hotel safe instead of leaving it in the room. But it had no value. And have him think we're nuts? First you have it, then you don't. Besides, there's nothing much more we can tell him.  The funny part of it is that girl back at the place where we bought the thing. She didn't look like the type that'd be mixed up in a thing like this, you know? Just because she's pretty. No, no, that's not it. Just had a feeling about her. Oh, well, oh, gosh, I just remembered I still got to get something for Grace, you know? Oh, no, you don't. Not with me, anyhow. I feel like locking myself in this hotel room until it's time for our train tomorrow. Yeah, but, gee, they got back the dragon. They don't want us anymore. Still can't figure out why they wanted it. The-the-the tail was even cracked. Maybe it's an early Ming or something. Someone's turning the knob on the door. What? Hey, so they are. I got over here behind it and I can grab them. It's opening. Hey, it's the girl close the door, Sam. What's this all about? What are you doing here? I-I did not know you would be here. What did you think? We were tied up in a cellar? Yes, that is. I wanted to tell you something. Oh, come on. Now you'll have to do better than that. No, really. I can explain. You frightened me. May I sit down? Well, go ahead. You know, you had us holding our breaths too in case you don't know it. I am so sorry. I really am trying to help. You see, my brother, he is in the army too. I was trapped by Dr. Singh to leave store open with one of his men there. I tried to find out after you left today what it was about. And I did find out one thing. The dragon you bought was supposed to be sold to someone who would give a password. You must have said it by accident. Well, it seems to me they go to a lot of trouble in this town to make a sale. That is what worries me. I am mixed up in it now and I am afraid there is something wrong, very wrong. And I thought... Yeah, well, what did you think? I thought perhaps you could help. I do not want to go to police. Us? I thought you could at least find out what it is all about. I do not dare ask any more questions. There is going to be a meeting tonight. And I thought... A meeting? What kind of a meeting? A tongue. They dress up in ceremonial Chinese gowns and Dr. Singh is head of it. Now, if I could arrange for a backdoor to be left open, then maybe... Things you get me. What do you mean? Well, you started it all by buying that confounded statue. Shh, we're getting close to the main room here. Yeah, there's a crack of light over there. Must be the door. Hey, maybe we can hear through it. Have they started? Open it just a crack. Why not? All we can do is end up in another basement. Anything we're just making with the tea, sitting around the table. Well, I'll be doggone. Let me see. Hey, it's my dragon. Yeah, here comes another guy. All dressed up. Hey, will you look at that mustache? That's a beauty. What's he doing? Shh, I don't know. Listen.  Well, I've come to make a purchase. What is it for? The dragon is a present for my sister. Quite so. A $10.72. Too much. Very well. A $5.72. That will be satisfactory. My gosh, he's giving him the money. No wonder they thought you were the right guy last night. You said everything right. Just the way he said it. He's leaving. Quick. We may be able to get around the front of the building in time to catch him. There he is, coming out of the building. Yeah, he's getting in the car. Hurry. Taxi! Hey, taxi! This guy look all right. We can't be choosy. Can you follow that car that just pulled away? Yeah, I guess so. We don't go too fast. I don't want to get no ticket. We probably should have called the lieutenant. Well, it's too late now. We're on our own. Looks like an apartment house. Hey! That shit's not real. For God's sakes. It's Lieutenant Chi. So our orientals don't look alike to you. Come on, come on inside with me. You may have been followed. We'll find amateur detectives. You wind up following the law. We were only trying to help. I wish you could tell us what this is all about, Lieutenant. I can't tell you much, but I can tell you one thing. You're lucky you have not been killed by now.  What do you know about this dragon of yours? I think except what we told you. Yeah. Let me see that thing. What? I'm sorry, Lieutenant. You're crying out loud. Why did... Hey, Lieutenant. Look what fell out when it broke. Let me see that. What is it? It's microfilm. I know. I used to work with it in Washington. This may put a new light on everything. Cheespeaking. Get me Inspector O'Brien. Yes. Yes, thank you. I still don't know exactly what it was all about. Well, I don't know all myself. I saw enough of those microfilms to know they contain military information. The army and the FBI have them now. We won't touch them again and we may never know what they were. See, I was mixed up in it because I was trying to get our friend Dr. Singh on a bunco racket that I still suspect he was carrying on as a side-drying to the espionage. They were all mixed up in it. Even the girl, the one at the shop. No, you can relax. She was just what she said. An innocent duper. No kidding. Gosh, what a night. I'm going to see that you two get a commendation from someone out of this. You took a terrific personal risk. Actually, I should throw the bucket you for not calling me instead of going up on your own like that. Well, Lieutenant, we thought you'd think we were crazy or something. I suppose I might very well have if I had not been working on the case in the first place. Sam, you know, I was thinking if we get up early tomorrow, maybe we'll have time to run up and get that present for Grace. Oh, no. Here's a word to young men and women who are high school graduates. Your United States Army is rapidly expanding. Men and young women with the will to learn can get ahead fast in the Army. So why not at this important time of your life, take advantage of the opportunities for advancement that are going to be yours by enlisting in the Army right now. Just pay a visit to your local United States Army Recruiting Station and they'll be glad to give you all the facts. Be sure. Go Army. This has been another program on Proudly We Hail, the United Transprived in cooperation with this station. Proudly We Hail is produced by the Recruiting Publicity Center in New York for the United States Army. And this is Mark Hamilton speaking, inviting you to tune in this same station next week for another interesting story on Proudly We Hail.


So, I want to see who has early control of this 50-day moving average. If we open up lower and reclaim back the 50-day and start rallying. Welcome to Access a Trader, the number one community for those who are committed to taking control of their trading in order to achieve success, profitability and longevity. Thank you for joining us. Here's Dan Shapiro to help you find your edge, master your process and own your future. Hey guys, good evening everybody. Welcome to another edition of the Access a Trader.com nightly wrap up show. Hope everybody is doing well. Crazy day today, right? We'll get to that in a second. As always guys, just as a friendly reminder, please support the channel. Again, we try to give as much unbiased content as possible so you can make adult decisions on a day-to-day basis. So please, if you haven't done so, please like the video and if you are new to our platform, subscribe, right? Subscribe so you can get notified when we upload. So, let's talk about the tape, right? Number one, I'm going on my 24th year and I have every video that I've recorded on the platform.  I think that's the most important part to understand. We're all idiots, okay? We don't know what's going to happen a week from now, three weeks from now, three months from now, three years from now. The only thing we do is get prepared. We do our best to get prepared for the next day, put ourselves in a position that we are going with the win, not against it and hopefully our research from the night before gets confirmed and everything plays out, right? So, keep that in mind. Keep that in mind every single day when you are going to the day. Again, I've always said this. If you are trying to convince everybody that you are the smartest person in the room, you're only trying to convince yourself. Nobody cares. There's no brownie points. Nobody's keeping scored. We're trying to do our best that whatever capital we have, that capital comes back with some friends at the end of the day. If not, we try to figure out what went wrong, what possibly could we've done better, make adjustments and get ready, right? And get ready for the next day. And, you know, just kind of going back for the last four or five days. So, we reclaimed the 50-day moving average four days ago, right? Above this 27760s area. Everybody see it, right? That's the 50-day, which translated later in the last four days was a pretty significant rally.  But the one thing that we always talk about in a trend type of scenario, when we started talking about last year, even though we were in an 80% predominant cell bias market, you're always going to have the reverse trend days. So, basically, if we're in a down market, you're going to have updates, right? When you're in an up market, you can have reverse down days. And I said this every single video, a trend doesn't mean straight up. A trend doesn't mean straight down. It just means that the overall directional bias is going to be in that direction. And you can see pretty much that played out in the last five days. We've had one down day, right? We had one down day in the last five days. The only difference between a down day that could have been, you know, a very mini school versus a down day that closed where it did today, and we'll get the ramifications in a second, we are setting up into a very, very interesting part for tomorrow, right? Where the bulls are going to be faced with who's going to have control over the 50-day. We know we lost the 50-day here, what happened later, we know we reclaimed the 50-day, we know what happened later. And you can see here, we closed right on the 50-day, within literally within 10 cents of the 50-day moving average, which is going to be a very, very important day for tomorrow. So if we have a scenario that the market gaps up, right, and we lose today's ranges, that's not good, right? It's not good. However, in a weird way, in a weird way, it would be almost beneficial. Like if we closed a dollar away from the 50-day, then going into tomorrow and said, hey guys, let's play that 50-day bounce, and we should hold that 50-day the first time around. But the fact that we came in so close to the 50-day moving average on the close, it's almost in a weird way, right? In a very odd way, it's almost in an odd way. We almost want a gap down tomorrow so the bulls can shake off the gap down and reclaim back the 50-day moving average while taking everything red to green, right? That's what we want. If you're a bull, that's exactly what you want. The last thing you want is a very insignificant gap up tomorrow, right? Let's just say 10, 15, 20 handles on the NASDAQ futures and the NASDAQ futures confirm today's channel back to the downside. And if we get a close below 277, again, for tomorrow, well, tomorrow, there is no tomorrow, and I rest on Thursdays. But for the weekend video, we're going to have a completely different conversation or at least a completely different conversation potential for Friday's session. So we don't want that. So I think for tomorrow, I don't want to use the word. It's an important day or it's a crucial day. But I want to use that word because, again, you could clearly see just what your eyes said. How important who has control over the 50-day moving average will have a very, very beneficial idea of which way the wind is going to blow going into Friday's session. So it's super-duper important. When you look at all the other indexes, this is where your eyes start to get a little wider. When you look at the diamonds, yesterday they were down roughly 400 points. We're going to use the diamonds as a proxy for the Dow Jones. Yesterday, and I joked around about it, we were down 400 points on the Dow. We didn't feel it. We didn't feel it just because so many NASDAQ names are strong. But yesterday they lost 400 points, and today they lost another 600 points. So 1,000 points is not small. Granted, you have exactly the same scenario here with the Dow Jones industrial average just the same way we've had. We are having right now with the Qs. The diamonds broke out above 334. They broke out above 334 this whole level. Here, in this case, we closed below the 50-day moving average on the diamonds. If you look at the spies, they did exactly the same thing as the Qs. They broke out above here around this 389 level. They got down to this right above the 50-day moving average. So you're going to have a very, very interesting day. My advice, especially for the neutral, hell of a lot, for any trader, I was about to say for the new traders, for any traders, let's see how the market opens up tomorrow. Again, it's not that I'm necessarily bullish or buried. How can you definitively turn around today and say, well, I'm definitely bullish for tomorrow? Or turn around and say, I'm definitely bearish for tomorrow? If we're closing right in the Mason-Dixon line that anybody who has control of this big moving average is going to probably have control for the foreseeable future. So I want to make sure that two things we're going to do for tomorrow. Let the market play out in the first 10, 15, 20 minutes. Again, there's only six channels of the day. For all you guys who don't know who are relatively new to this channel, the PS60 theory is pivots supply via the 60-minute interval. There's only six candles for the day versus the smaller time frames. So the first channel of the day confirms at 10 o'clock. Right? So I want to see who has early control of this 50-day moving average. If we open up lower and reclaim back the 50-day and start rallying, then obviously we want to watch the opening range highs. That's obvious, okay? However, if we gap up and we confirm today's channels and lose the 50-day moving average, I just want us to be prepared on the short side as well, just in case. And there's a lot of names if you look at going through the NASDAQ 100, there's a lot of names, right? A lot of names that are mirroring exactly what the indexes are doing. So it's not going to take you a long time today to make yourself an actual watchlist on both long and short, right? So for example, a name like NVIDIA is actually holding up various. One of the very few stocks that didn't take out the previous day's low, right? You know, this and a stock like Tesla, and we'll get the Tesla in a second, right? Didn't take out the previous day's low, but there's a lot of stocks that did. And that's the most important part. So the stocks that didn't take out the previous day's low today, those are the ones you want to keep an eye on for tomorrow, right? For potential washout, rent to green, opening range high, but anything that's taking out today's lows, right? Potentially taking out today's lows and confirm them tomorrow, they're going to be on the chopping block in case the Qs lost their, lose their ranges for tomorrow's session, which, you know, tomorrow is definitely setting up on one of those days, one of those days, you know, let's listen to the market, right? Don't judge, don't anticipate, don't have an opinion tomorrow, right? Tomorrow is legitimately a 50-50 shot. The fact that we closed right on its breakout level, where we broke out only five days ago, it's a toss-up.  We don't want that, okay? That's the one thing because what's going to happen is a lot of people are going to get too anxious. A lot of people are going to start thinking and overthinking without letting the market kind of dictate to us what should be doing, right? So that 10 o'clock channel tomorrow is going to be super-duper important. I'm usually in, you know, I'm in some things most of the time before that 10 o'clock channel because the research confirms and things usually go pretty orderly, pretty uniform, but for tomorrow's session, I'm probably 90% sure that I'm going to let the first, you know, 15, 20, 30 minutes play out until that 10 o'clock is checked because we don't want to guess, guys, because if you start guessing and forecasting and having an opinion, there's a good chance, you know, higher probability than not because we are all bad guesses that we're going to get run over. We don't want to get run over, okay? This is not a game of chance. This is not a game of, let me show everybody how intelligent I am. This is a game of price action confirmation and the fact that we are going into tomorrow's session with such a definitive line in the sand for both bull and bear. It's not just for the bull case, for the bear case as well, because if the bears want to take back control, they got to close below the 50-day moving average. So yes, in the beginning of the video, I said, I don't want to over, you know, over hype what I think is going to happen tomorrow over sensationalized. But again, as we're seeing and we're chatting here and we're seeing how important these levels are, I think tomorrow might be one of those sessions that if you are patient, you are going to get kind of more clues, more validity, more clarity, especially on the 10 o'clock channel, which way the wind is going to blow. And again, we could easily have a situation tomorrow that, you know, we gap down, reclaim the 50, and just start rallying again. Because again, everybody knows that before you can have the next leg up, you know, a very, very aggressive next leg up, we do have to retest back a major level that it reclaimed on supply. And that's exactly what we did today. So hopefully tomorrow we could get a cleaner look. So again, today's session, you know, today's session was choppy. I think that's the best way of saying it. Number one, congratulations for all you guys who came in Long Tesla. That was obviously, you know, I woke up today at five o'clock in the morning, and I was tweeting at five o'clock in the morning. Tesla gapped up another $6 today. I go $138 supply on deck. If you are long equity kick out a half, two thirds.  What's better, equity versus options, right? There's pros and cons. And obviously, I'm not really, I really only feel like going into a whole discussion about that now. But one of the greatest things about trading equity, and there's obviously a lot of pros and cons is, again, well, you have four o'clock in the morning to get your, you know, to get your engines rubbing, rubbing, right? The problem is if you're trading on the option side, you have to wait till the open. However, if you are long calls, and this is kind of the whole point, you really have to learn how to kind of almost take out your position and start getting out your position by shorting, by shorting the equity versus your call so you can start pairing out your position. And that's exactly basically my comments around eight o'clock in the morning. If you are long equity kick out two thirds, a half to two thirds of your position. If you are long calls, you might want to short some equity against your position. If you're an experienced trader, there's some PBI numbers, doesn't make a difference, what came out at 830. Again, big move on Tesla, congratulations. That's pretty much set the tone for the whole day. It was about five, six points pre-market, which is awesome. Obviously, everything else stopped that break even. And then you have a scenario that pretty much everything failed, right? And that's the most important part, like bulls got tired, there was overextended move, buyers, the way the sellers were tied three, four days ago, buyers became tired today. And a lot of things really failed. You had square, 75, 80. We talked about this last night, only went up 40 cents and died. PLTR, 716, 720 needs to build. It went to 730 and then died. Doc, you never got up to the macro level. Pan W, you know, did okay, right? Pan W rallied about $2, a little less than $2, 143, 75 needs to build. NVIDIA never built above the 78 level. And the case in point, that's kind of my whole point. For experienced traders, once in the eight needs to build, stock has held, has gone on an insane four day at 17 points in four day. If you are trading NVIDIA today, scale down to a quarter or a third size, maximum one point for a potential another push. Obviously, everything got tired. Netflix had a $1.5, $2 move to the downside, snapped right back. They report earnings tomorrow and kick off earning season. Meta never got up there. Amazon never confirmed. Here is one of the very few shorts that we were looking at. NVIDIA, $74.90 if it builds below can flush. Here is NVIDIA. And again, I still like, I think NVIDIA still looks good. But for today, just kind of lost its opening range. And as the market was coming in, here's the $74.90, right? Here's $74.90. You know, went down a couple of bucks, wasn't really a lot of fear there. And I think that's about it. I think that's about it. Yeah, there was a bunch of bounces today. We bounced Tesla a couple of times decent cues, not a big move on the cues. Got down to $79.70, bounced about $0.50, $0.60, and then lost support. This is why we always harper on the idea of, hey, take money on the way up, use break even as you stop.  Please God, don't let my position keep on going lower. So that's basically it, right? That's basically it. Look, I think tomorrow is going to be important. Again, I'm not rushing out of the gate to have an opinion, to have a course of action. I really want to see who has control. I would love to see the bulls. Nothing would make me happier to see the bulls reclaim that 50 day moving average tomorrow. Fight, trap, go red to green and have, you know, resumption of this rally that we had started five days ago. But at the end of the day, guys, I understand I'm not a bull. I'm not a bear. I'm an opportunist. And technical analysis is the only thing that I trust as far as price action to come. So guys, have a great night. Stay blessed. Tomorrow, again, is Thursday. It's my normal night off. So there is no video for all you guys who are joining us tomorrow in the live webinar. Looking forward to working with you. If not, see the rest of you guys on the the weekend update. Take care, everybody. Have a great night.


Good morning, everyone. Welcome to Harvard Law School and Harvard University. Generally, my name is John Palmfree. It's a great pleasure of welcoming you here on behalf of the institution. It is a thrill that we have the ending synthetic final meetings for this round with Law.gov here at our campus and starting today with the Massachusetts-based day and heading to the broader, nationally-based concluding day tomorrow. By conclusion, I mean, of course, hurling into the next phase of getting it done, but hopefully coming to some common conclusions and consensus. I want to thank, in particular, our great friend, Carl Malin, but of course, who's been the person who spearheaded this process right from the start. I should note that when the Berkman Center, which is also affiliated here in this family-style event, celebrated its 10th anniversary, we gave out a couple of awards. And the chief award among those is the hero, really, of the movement in which we perceive our research to be situated. The hero to whom we gave the Berkman 10th anniversary award was Carl Malin, but as somebody who has embodied the spirit and the energy and the commitment to making available the world's information, particularly around the law and its connection to democracy, and to make possible what we think these technologies can do in the spirit of this great democracy and so forth. So, in the other piece of this is that Carl wasn't able to make it to our celebration team. He received a beautiful award, but arrived by video cards. I actually didn't marry both of whom were involved in important matters, trials, various other things going on. I think you were fighting more again at the time, if I recall. So, in a way, this is a chance to welcome Carl back physically to Canvas a few years later to thank him for his leadership and to stand beside him in what we think is really one of the most important conversations related to the Internet and society. Also, from the perspective of a library director, which I find myself now doing here at the Harvard Law School, I think this is possibly the most important thing we could be involved in. The notion that the basic law, the primary law of the United States in Massachusetts as well as the state level, ought to be free from copyright, ought to be available on the web, ought to be something around which we as professional librarians and information people can put context and make possible the kinds of direct democracy and broader, more vigorous democracy that lots of people are working on. So, it's from those multiple perspectives I'm just thrilled to welcome the group here. We have my co-convener is also Professor Lawrence Lessay, who needs no introduction.  I want to thank also Professor Phil Malone, who I think is here or maybe here, is working closely with the Access to Justice Commission and Judge Fine from whom we've here this afternoon. And in particular on the library staff, Michelle Pierce, who has been not only the open access librarian, a new job where we have a wonderful senior extraordinary person doing but also the driving force behind this event. So, on behalf of all of us in this broad sense welcome and for more heading into this episode since Carl Malone, welcome to the conference. Thank you. Thank you. Good morning. Thank you John and Larry and Michelle especially for putting this together. I want to give a few remarks to kind of set the stage for what LawDoc is all about. And this is a two-day workshop that we're doing and as John said today is Massachusetts and tomorrow is the national wrap up. I want to begin with William Jennings-Vryton, who in his famous Cross of Gold speech said that changing conditions make new issues. That the principles upon which democracy rests are as everlasting as the hills, but they must be applied to new conditions as they arise. Well, the internet is a new condition that has arisen. And we must once again apply the principles upon which democracy rests. For the last six months, LawDoc has been a national conversation about our legal system, about how primary legal materials are distributed. And this conversation began in January at the Stanford Law School and it concludes this week on Tuesday we were at the Center for American Progress. And of course all national conversations should end at Harvard Law School, so I'm really pleased to be here. 15 workshops around the country have involved 650 participants, as we've examined the basic premise of LawDocGov. And that is the government institutions that make the law, entities that originate primary legal materials. These jurisdictions should make their work product available in bulk with no restrictions on use. And this work product should be held in authenticated, well-formatted, and complete repositories. And this principle goes across all three branches of government and reaches from the lolliest water district through the cities, counties, states, to the Supreme Court, the Congress, and the President. Now by primary legal materials, we mean the work product of these lawmaking institutions. And that includes the documents of primary authority, but also includes the supporting documents that issue that one must use to interpret the law. This is a slippery slope, a definition that's most clear at the peaks of our legal system, and it's a little murkier as we descend the hill to the lower jurisdictions. For the Congress, this means obviously the public laws, the statutes at large, and the U.S. Code. But also the hearings and reports and rules of the House. And given the place of the U.S. Congress in our society, this means that the full archive, all the laws and all the reports and all the hearings should be available and should be authenticated. Now perhaps for another legislative body such as a municipal council, the collection doesn't need to be nearly as complete, but even a municipal council should make available in bulk with no restrictions the current ordinances at the promulgate. For the Supreme Court of the United States, this certainly means all the opinions and the briefs and the oral argument should be available as an authenticated repository signed by the court and accessible to all. And as we move down into the 7,436 state courts, or the 3,140 counties, or the 19,289 incorporated municipalities, each with their own city courts, the definition of primary legal material should obviously be adjusted. PASER system for access to our federal trial courts is a good example of inequitable restrictions on access to the law. PASER has funded $129 million in 2009 expenditures for the administrative office of the U.S. courts. And that's a revenue stream they've come to depend upon. Birch's courtroom technology, large screen TVs, all sorts of things that are arguably necessary for the courts, and they're very low to relinquish that revenue stream. PASER has over one million account holders, and the administrative office of the courts is proud that they waive fees that are $10 a quarter or less. And they say that over 50% of their users don't end up getting billed. But $10 per quarter at 8 cents per page translates into four 30-page documents. You can't do a lot of legal research with four 30-page documents every three months. So you've got to think that perhaps the demand for these materials is artificially constrained. And we shouldn't forget, if you want to be one of those one million account holders, you have to have a valid credit card. And if you don't have a valid credit card, you can go petition a judge for free access. But I'm not convinced that petitioning a federal judge is necessarily a lower barrier to access. So what uses are not possible under the current system established with PASER? In Law Doc of, we've seen several very compelling examples over the last few months. First, many valid public interest uses of bulk data in PASER are essentially prohibited. When my organization was able to audit 20 million pages of PASER documents, which would have cost over $1.5 million to purchase at retail, we found 30 district courts in substantial violation of the privacy laws. That audit of 30 district courts led to a change in the judicial conference privacy procedures. But the audit was only a small portion of the federal district courts, and our audit did not extend to the bankruptcy courts. We can't afford the price to continue the audit, a price tag of millions of dollars, and a barrier to access at stock what we think is a valid public interest function dead in its tracks. Now, I put it to you that being able to audit the district courts of the United States for privacy violations, or for discrimination in the application of civil rights laws, or for discrimination in patent litigation by districts, or any other examination of how our system of justice functions is technically possible today, and it's only a paywall that keeps us from performing these functions. It's not just applications of legal research and public accountability that suffer when the law is not available. It's our system of legal education. A survey of 66 law schools found that 63 of them do not let their law students access PACER because of cost considerations. Our law students don't learn from our federal trial courts because of the cost. And the law students aren't the only ones who must suffer. Other semi-professional uses, journalism, business research are all self rationing because of the cost. Now, there are two other effects of a paywall on a system such as PACER. And the effects are both about innovation. Innovation in the legal market and innovation in government. Innovation in the legal market has been slow and painful for the last 20 years. And that's because the law has been parceled out to a series of exclusive concessionaires, private fences around the public domain. And that means that acquiring the rules of our society, what we call America's operating system, the code for how our legal system works, is an expensive proposition indeed. The estimate to purchase rights for a decent collection of case law statutes and regulatory materials in the United States is 10 to 50 million dollars. If you want to be an internet startup, if you've got a better idea for how to get to a lot of consumers, if you have a better citator or a checking system, you need big bucks to get started. That barrier to innovation is large enough that even Google took two years searching around for a decent collection of case law before they were able to purchase the cases they needed to add their Google Scholar product. Artificial barriers to entry have that little innovation in the private sector. And the innovation we've seen is big company innovation, which is of course useful and necessary and it serves large enterprises such as big law firms. But the mind-bending startup, the innovative new business model, the previously unthought-of niche player, those are not possible today. There is a flipside to innovation in the market and that's innovation within government. Judge Jay Rich Leonard, one of the architects of PISA, says that PISA was originated entirely within the federal courts without any external requirements. But one of the virtuous cycles of the internet is that we all learn how to do things better. And external requirements are good. Judicial independence should be independence from the other branches of government, not from the public. Before coming out to Washington, D.C., and then up here to Cambridge, I spent last weekend processing government videotapes. It's one of the things that our nonprofit does. For $25, the State of California's Department of Public Health sold me a fascinating two-hour training program about the safer processing of juice. It's valuable information for those thinking is opening a juice factory and it's pretty much obligatory if you're already in the business. Now the video had segments on agricultural practices and raw materials, on processing design and packaging, on cleaning and sanitizing and personnel practices, but the longest segment by far was that on the regulations, requirements and legal guidance for being in the juice business. If you want to make juice in California, you need much more than a good supply of mangoes. You need to know about these laws. Title 17 of the California Code of Regulations deals with sanitation in food plants. The Office of Administrative Law of the State of California asserts copyright over the California Code of Regulations and contracts at Barclays to publish this document. You can view the provisions on their website, but I can't make a copy that looks differently, one that's aimed specifically at juice people. For your juice business, you also need to be very familiar with the California Health and Safety Code Part 6, which is the California Food Sanitation Act. You want to be familiar with Title 21 of the Code of Federal Regulation, particularly the standards on packaging or holding human food and on sanitation standard operating procedures. You will need to be fully familiar with the Haasip Regulations which are a detailed standards from on hazard analysis and critical control points from the Food and Drug Administration. The Haasip Regulations, in turn, incorporate by reference a raft of technical standards such as ANSI NSF standard number 7 for commercial refrigerators and storage freezers, which is $100 per copy if you want to do due diligence on your freezer. And I can't afford the license to republish that because there is no license to republish that technical document. And these documents are just a start and you will need to use the juice professional. You're going to want to be able to consult your public safety codes, all of which are only available from a designated exclusive vendor, such as a national electrical code from the National Fire Protection Association. Likewise, the building codes in your jurisdiction, the fuel and gas code, the plumbing code, the fire code, elevator safety code. You'll need your local municipal code, particularly the sections on zoning and factories and employment practices. Most of the municipal codes in California belong to one of the three major outsourcing companies, and over 50% of municipal codes in California have copyright restrictions. Now, my point is not that the ambitious juice entrepreneur is totally without resources to learn the law, but that if I want to create a new product or nonprofit site aimed at the juice people of California, and I saw that Californiajuicedudes.org is available, I have a hard time gathering the materials I need to set that site up. There's just too many copyright restrictions, pay walls and other impediments to access both legal documents. John Adams in his thoughts on government said a republic is an empire of laws and not of men. Now, if a republic is an empire, it's an empire that's been vulcanized by a complicated set of deeds, exclusive tendencies and contractual offenses. Walls and borders have split this empire, and their walls and borders have denied access to justice that make equal protection under the law and due process under the law a function of the size of your wallet. It's a tax for access to justice, and to me this is no different than a poll tax on access to the ballot box. The problem with an empire of laws is that empire implies that property implies that law is owned by the state, but the law does not belong to the state, it belongs to the people. James Madison emphasized the importance of the rights and the sovereignty of the people to access the laws when he stated that a popular government without popular information or the means of acquiring it is but a prologue to a farce or a tragedy, or perhaps both, and that knowledge will forever govern ignorance. A better geographical metaphor than an empire owned by the state to me is the shining city on the hill. Law.gov is an idea that we should all try to approach, not about who shall control the law. It's a hill we should climb. It's an idea to adopt, as John F. Kennedy said, that our governments in every branch, at every level, national, state, and local must be as a city upon the hill. Ronald Reagan called this shining city a tall proud city built on rocks stronger than oceans. A city with free ports that hung on commerce and creativity, and there had to be city walls. The walls had doors and the doors were open to any known of the will and the heart to get here. It is not often that Ronald Reagan and John F. Kennedy saw eye to eye in the role of governments. So we are going to be talking about Law.gov for the next two days. I am really thrilled to introduce our next speaker, Professor Lawrence Lesig, who has been moving out of the world of copyright for a long time, but has been instrumental in getting a Law.gov movement up and running. You saw that we've done workshops in a dozen major law schools over the last six months. This wasn't because I've been able to call up the deans of all these major law schools, it's because Professor Lesig made the introductions and introduced us to the professors that saw that this was a good idea and that's really what made this possible. I know Professor Lesig was honored last night as one of the lawyers of the decade and certainly as far as the internet is concerned he has been the lawyer of the decade so I'm really pleased to introduce him.


So, you desperately need to control your weight, not a problem. Click your mesh, shift-click the skeleton, control P, and pick with automatic weights. Then click the skeleton, shift-click the body, and go to weight paint mode. And under the tools, make sure you check auto-normalize.  And I'm not going to be able to help you because your painting is going to make absolutely no sense. Don't ask me why, just do it. So turn on X mirror to make sure that what you paint on the left is copied to the right. Now scroll to the top, set blend to mix, weight to 1, radius to 50, and strength to 1. So here's how this works. Your skeleton has bones. And your goal is to assign territory so that when that bone moves, the correct parts of the body move with it. To select the bone, hold control and left-click. The bone will glow, and from here you just left-click over the points of the body that you want that bone to control. Once a bone is selected, you can press R to rotate or G to move, unless you're using IK. If you are, you're going to have to select the IK handle first. You can tell how loyal each point on the body is to a bone by looking at its color. Red means the bone completely owns that territory, blue means that bone has no control over that area at all, green means 50% control, yellow means 80, and so on. How strong the colors are depends on the strength of your brush. So right now we have our strength maxed out to 1, which means that all the points that we touch are going to be painted in red or 100%. If we were to set the strength to 0.5, then all the points that we paint would be represented in green or 50% instead. So if we picked this bone, and all these points are red, that means that when we move this bone, all the red points will follow that bone exactly. But if these points were painted green instead, then when this bone moves, they would only follow the bone about 50% of the way. You can change the strength of the brush at any time by pressing shift F. You can also just change the radius by pressing F. One last thing, if you are doing high poly, the default brush works great, it just means that the center of the brush is going to have the most strength, and the paint will be weaker in the outer areas of the radius. But when you are doing low poly, I recommend to set the brush to flat, which just means that every point inside of the brush radius is going to be set to whatever strength you have. Okay, so those are the tools. But how do you use them? How do you know where to paint? Well, the easy way is to start with what you know for sure. Set your strength to 1, and paint a rough draft. For example, I'm pretty sure that all the points above the head should belong 100% to the head bone, so we are just going to paint this whole area red. And everything beyond the wrist is probably going to be controlled by the hand. We can do the fingers later. Same thing with the foot. Just go through all the main bones, and paint a deep red area for anything that might belong to it. Now, some of you may wish you had the ability to paint the front and back faces at the same time.  Because unlike any other 3D software, Blender's front faces only button is totally busted. And even if it worked, Blender's x-ray mode doesn't work in wait paint mode. It's been broken for years, and it doesn't look like they have any plans to fix it anytime soon, so you are fucked. Until they fix this, you are going to have to waste your time manually painting the front and back separately. Anyway, once you've done the draft, it's time to smoothen things out. Now, to do that, you are going to need my super secret family technique that's been passed down from generation to generation. From my great grandfather, to my grandfather, to my mother, to my friend, to me, and now finally to you. We call it, if at first your joints bend fuggly, click the bone next to it and apply point two in between. That's right, point two is the answer you have been looking for. In addition to your weight painting needs, point two has many healthy side effects including but not limited to increased life expectancy, cancer reduction, a six pack, a mortgage, a new girlfriend, and a C plus on your next exam. If you don't experience any of these symptoms within the first five days of using point two, you are doing it wrong. And you should consult your doctor about additional medication. So switch to point two today while supplies last. Okay, but seriously, if you're not happy with the transition between two areas, ask yourself what direction should the problem points be going. If you have a bone next to him that is in that general direction, select it and try point two. Now, if the point went too far, control Z to undo, reduce strength a bit and try again. If they didn't go far enough, undo again and increase the strength instead. Now, if you find that you are not happy with the transition no matter where you draw the paint, then consider changing your topology. Just add or remove points that you think will be more compatible with your joints. If you do all that and you still aren't getting the right results, consider adding a control bone. Place the control bone in the middle of the points in question, then paint the points to that bone so that when it moves in combination with the main bone, you get the transition you want. If you're not sure how to do those last two steps, don't worry. We'll get to them in detail for all the most common issues, like elbow and knee clipping, fingers, pelvis, and the shoulder areas throughout the week. And meanwhile, hope that helped. If you enjoyed this video, please don't forget to like, subscribe and ring that bell. Hope you have a fantastic day and I'll see you around.