workers that we needed about 50 years ago for our economy and our primary education system really feels to me like a really well-tuned machine to turn out people with fairly basic skills they can read they can write they can do basic math but I think more fundamentally they get trained to sit in the same place and obey authority all day every day and I think you want that if you want to turn out a workforce of payroll clerks and assembly line workers we don't need those kinds of workers very much anymore and our educational systems I believe are really poorly matched for the kinds of people the kinds of skills and attitudes we need for the second machine age talking with parents is a fascinating experience we've also had some great chances to talk to politicians all over the world at some pretty high levels one of us got invited to the White House to have lunch with President Obama and I don't want to brag because it wasn't me but we get to talk to politicians and the good news is that they're willing to engage with the ideas in the book the discouraging news is the typical conversation is they ask you to lay out the ideas and you talk to them about the the the thesis of the book and they say yeah got it okay now more than ever we need the policies I've been advocating for my entire career you don't see a lot of mindsets getting changed you see people doubling down on their prior beliefs so the politician the fact that we're having conversations with politicians is encouraging I wish I sensed a little more open-mindedness among a lot of them in contrast the happy news is that when we talk to pretty senior business leaders around the world they've been really willing to engage with the ideas in the book not just to make their own companies run better although there's absolutely a lot of that they really are catching on to this idea that as Eric points out if median income is stagnation is stagnating if job growth is tailing off that's not really great news for their markets and for their societies so instead of coming across this group of heartless capitalists toasting the demise of the workforce we're experiencing something really different which is the executives that we've been talking with really grappling with the ideas and trying to figure out what their role is as leaders of the private sector what are they what what's incumbent on them so we're seeing the rise of you can call it conscious capitalism is something that we've heard of a an emerging different mindset among some leaders and I think it's fantastic news I want to talk about two final constituencies that we've been talking with and a really interesting contrast between them most of the discussions that we're having with our academic colleagues and in particular some of the smartest economists that we work with they have a pretty interesting critique they say you guys you're being kind of wildly provocative and you're way out there with the things that you're talking about and it feels to me like they take a lot of comfort from the pattern of history which is we've had a lot of economic growth we've had a lot of technological progress and we've had something pretty close to full employment and constant wage growth to the point that economists now have a when they really think that something is set in stone they ascribe a fallacy to it so there's a thing called the Luddite fallacy or the lump of labor fallacy which is this idea that tech progress can race ahead and leave people behind a lots of folk consider that a fallacy so they look at the ideas that we're talking about and they say come on guys we've seen this before Marx was worried about it Cain's talked about technological unemployment there's this long history of people being wrong about this the trends that you're seeing are they a blip or are they for real you guys are being a little outrageous with your claims most of the professional technologists that we talked to the investors and the entrepreneurs and Silicon Valley say something pretty different they say you guys are being way too conservative with your claims the things that we're building the things that we're investing in are going to continue to transform the work face they're going to continue to advance and acquire new skills and capabilities that used to belong to people alone we think they're going to diffuse not over the course of decades but they're going to diffuse pretty rapidly over the next few years and the labor force the workforce implications that you guys are talking about again we ain't seen nothing yet so you guys are being way too circumspect people are way too calm about the waves of change that are coming I'm not sure who's right between the two of them but the technologists say something else that's pretty interesting to us they say we're sensing a broad danger out there in public perception and the danger is we really don't want Silicon Valley to become the next Wall Street in other words a next focal point for for popular ire about the economy and the next easily demonized set of bad guys out there so a lot of the very prominent technologists we talked to are seeing a danger out there I don't think they're crazy to think that I was stunned to learn that out in the Bay area out in San Francisco in Berkeley there are active violent property damaging protests against the buses that take Google and Facebook employees down to their jobs in the Valley and we were talking to a pretty senior executive at Google about this and he said think about this if you had told me a couple years ago that the zero carbon footprint buses that we make available to take our employees down to work and therefore less in traffic jams on the 101 if you told me that those things would be the target of public protests and smashed windows I would have thought you are crazy but there's a changing conversation about technology out there I think it's actually really troubling news the economists love to talk about pie and as Eric discussed and as he showed a picture of a pie we believe that technological progress grows the pie like nothing else it is the only free lunch that economists believe in and I think it's the best single best economic news on the planet so the fact that some people are trying to demonize or starting to demonize technology it's a little frightening to me in some cases we technologists I believe are contributing to the situation and making it worse than we need to Stephen Hawking here is talking about how the deep the dire dangers of artificial intelligence and some technologists are hopping on this as well Elon Musk is a first rate technologist by any measure he's using pretty apocalyptic language we're summoning the demon with the kinds of progress that we're making with artificial intelligence I really I don't agree with this and I find this really unhelpful because it's contributing to the popular unease about technology let me let me try to explain why I don't agree with this very much the reason this this concern is rising among people like Stephen Hawking and Bill Gates and Elon Musk is because just in the past couple years artificial intelligence has started delivering on the promises that it's been making for about half a century the discipline is let's call it a half century old and artificial intelligence has been promising human-like reasoning human-like abilities when you look at some of the things that Eric described when you look at Watson in Siri when you look at demonstrations of computers that can play video games better than any person you start to think maybe we're getting there so it's a really important question are we summoning any demon or not my favorite way to think about this there's an amazing company called Deep Mind started here right in London was bought by Google last year and one of their founders is a guy named Demis Hassabis who is just one of the stars young stars of academic of artificial intelligence work he's got a lovely way to think about this he says it for as long as we've been trying to get computers to do human-like things we've realized there are a number of really really hard problems how do we understand how memories are stored in the brain and how do we do that in a more in a more brain-like way in computers how do we do object recognition how do we give computers common sense so the field has realized for a long time that there are let's call it roughly 10 fundamental really really thorny challenges for half a century we've known that we've made rounding error no progress on those 10 fundamental challenges what Demis says is we're now on the first rung of the ladder we're starting to climb up that ladder so call it rung number one of a 10 rung ladder so I did a little math and I said Demis if what you're saying is correct we have nothing to worry about because it took half a century for the first one if that's our pace of making progress on these fundamental challenges we've got nothing to worry about for hundreds of years right he said aren't you the guy that talks about exponential progress if what I'm saying is right the rate of fundamental innovation and fundamental learning is about to increase a lot with technological progress and the deep challenges of artificial intelligence so the hits the breakthroughs are going to come a lot more fast and furious I don't know if that's the right way to look at it I don't think anyone knows if that's the right way to look at it but when I've looked around and I've talked to some of my favorite technologists about where we are and how quickly are we summoning any demon it's not right around the corner by any stretch of imagination and my favorite way to try to prioritize the challenges that are coming up in the wake of the second machine age if the trends in the workforce that Eric talked about continue the people are going to rise up way before the machines do we're learning that as we as we try to make computers and robots and artificial intelligence do more and more human things there we're learning that some paradoxes are vanishing and other ones remain really really thorny these are a couple of the fundamental challenges out there and it's a nice way to encapsulate where we are making progress and where we are where we're not making progress is on a long-standing challenge called Moravex paradox pointed out by the computer scientist hands Moravex a while back he says it is a lot easier to automate most of what a PhD mathematician or physicist does than it is to automate what a three-year-old does object recognition physical dexterity the ability to walk across a room and not trip we still don't have technologies that can do these kinds of things despite working on them for a long time I mean this seriously there's no robot anywhere in the world that can do that that's really far off in the distance we're manipulating pliable materials it requires a great sense of touch and feedback and fine motor control we're getting better we're still not there we are a long way away from any technology that could clear any of the tables in this room so whether or not restaurant busboy is a well-paid job or a prestigious job it's a job that's going to be around for a long time to come exactly because of Moravex paradox so we're not making massive progress here where we are making ridiculously unexpectedly fast progress is on another really long-standing one this is Polanyi's paradox and it was brought up by an absolutely brilliant scientist and philosopher of science of the 20th century and I'm Michael Polanyi who summarized in one sentence this really weird situation where we know more than we can tell and what he meant by that is if you go query a human especially an expert somebody who's really good at her job and you ask her to fully describe how she's able to do her job so well and let's say she wanted to help you out she really couldn't do very much she could describe some things that would be helpful and accurate but there's so much of what we know how to do that we can never articulate we that it remains kind of locked up in our heads called tacit knowledge and all of our attempts to elicit that are just really underwhelming and really frustrating and it provided this you can call think of it as a digital ceiling a hard digital ceiling on the that distinguish the kinds of tasks that we could automate versus the kinds of tasks that we could not automate that we could not put into technology or software one of the clearest examples of Polanyi's paradox was the really great Asian strategy game the board game of go a go is the strategy geeks favorite board game by far because the rules are if I surround your stone I take it off I've just told you all the rules of the game of go no one can tell you all the rules about how to play the game of go well people study this for decades you rise up through the rankings and as you get better you obviously can beat most other humans what you can't do is in any deep way explain to somebody how you know what you're doing or how you know what move to make next to the point that as recently as June May of last year this article was published confidently saying that human dominance in the game of go was going to remain for long for years to come as far ahead as we can see humans were going to be the planet's best go players exactly because of Polanyi's paradox and they had a great quote from a go master in the article said look I look at the board I know what the smart next move is I could not tell you how I know what that smart next move is Polanyi's paradox was alive and well the new approach in artificial intelligence the dominant approach the one that's just taking over the world is called deep learning and the way deep learning works is you don't even try to understand the rules as the programmer or to tell the computer what the rules are you just show it a lot of examples and you let the network that's inside the system figure it out for itself you're not doing any feature engineering is what they call it so a little while back a team again here in the UK took a look at go and they said hey what's fascinating about go there it's been around for so many hundreds of years there's a large library of really top level go games here's what we're gonna do we're gonna show that library to the computer and we're gonna let the computer the deep learning system absorb the insights from that library in a way that we the programmers never ever could we don't know what to do then we're gonna start playing games against a real human a decent go player and we're gonna see if the computer learned and the way they tested that was fascinating they said if the system makes the same move that the human did the human expert did in the actual game we'll say that's the system getting pretty good at the game of playing go more than 70% of the time now that system is making the exact same next move as would have been found in the library so I tweeted out earlier this year a con a prediction that I'm actually pretty confident in I think by the end of 2015 the world's best player of go will no longer be a human being I think that is going to go digital and it's an example of how quickly the progress is happening here it it's it brings up this broad insight that I had even after writing two books with Eric and immersing for years immersing myself in this world of technological progress I still get surprised about how it seems to keep on accelerating so the cute way to say this is that objects in the future especially technological ones are closer than they appear and Eric and I have noticed over and over again even over the past year when we go to conferences when we hang out with our favorite technologists and geeks and we ask them how quickly their companies or their disciplines are advancing we keep hearing the same thing which is well quicker than I ever would have thought I want to give you an example of that and I'm going to go back to the autonomous car one more time Eric talked about the experience that the two of us had riding in the car and he said at that time there was a lot the car could not yet do it was really good at driving down the 101 in northern California we had a comment from the floor could it handle driving on the craziness of Storo drive in Boston let me show you where autonomous cars are right now this is a talk that Chris Ermson gave at Ted this year Chris is the head of Google's autonomous car project and he gave a really vivid illustration of how far these technologies have actually come and how quickly he said that they have completely autonomous cars driving around the streets of Mountain View California a lot and they're encountering some situations they never would have anticipated they certainly never programmed into their technology he showed a video I'm actually not making this up he showed a video of what the car saw when it was driving around downtown Mountain View and saw a woman in a wheelchair come into the street and chase a flock of ducks with a broom this happened right what the car did not do was run over the woman what the car did not do was run over the ducks the car did not even say to its human occupant I really have no idea what's going on here you would you please take over from here instead the car said I got this waited for the ducks in the broom in the wheelchair to go off the street and then picked up and accelerated smoothly down the street a situation that weird presented no problem to the kinds of technologies that we have now so answer to the question about Storo driver almost any place else yeah I think these cars are ready for prime time even way before most of us who are looking at this technology thought we would ever get there the last learning I want to share is one that you've heard over and over today probably shouldn't surprise anybody Eric and I sit in the best place on the planet to do this kind of work and I want to say that well let me actually make this a pop quiz for everybody would you please shout out what you think the most overused word in academia is pair that's a good one in a massively overused we've been guilty of that today could probably no MIT is the most underappreciated word in academia I heard it over here interdisciplinary everyone at every university talks about how interdisciplinary their work is it's usually not the case we love to stick in our little disciplinary silos and publish work in the same old journals and go to the same conferences and talk to the same people we're just we're deeply siloed industry it's one of the things that I hope will be disrupted about academia what what what we've been seeing at MIT over the past couple years is just a really happy exception to that Eric and I and Marshall and and Rigoban so I guess this is not the perfect example of our lineup today we hang out primarily at the Sloan School of Business at MIT but we're joined by this this constellation of amazing people from throughout the Institute one of the MIT's great resources is the media lab and I have to share one more story with you I want to show you some data that Joey Ito gathered Joey's the head of the MIT media lab and I think of the lab as this this collection of kind of fiendish geniuses who keep on poking at the rest of us and showing us fairly uncomfortable truths so Joey shared a pretty uncomfortable truth about education these days and he did it he and his colleagues did it in a really ingenious way they just put a simple skin electricity sensor on a student and then left it on for a week and it turns out that the the electrodermal signal is a really good very quick shorthand measure of engagement with the world so they put those sensors on one of their students they they they let her go on about her work for a week and I need to highlight for you this is when she was in class you see that she's almost dead right there is it really hard for anything less to be happening in her brain while she's supposed to be absorbing the cutting-edge knowledge of science and engineering the blue there is sleep look at sleep compared to be this is a joke right this so but part of the reason I love Joey in the media lab is they keep on doing things like this to us and confronting us with these kinds of facts we also have just look I'm sorry this is not hyperbole we have the best economics department in the world there was just a quick study published they've been giving out a medal called the John Bates Clark Medal for the best economist under 40 for Eric when did that start 40s or 50s they've given they've given scores of these medals out about 40 percent of the recipients have some MIT connection or other it's just it's dominance like you would not see any place else on the planet so we have our economist colleagues if we want to understand labor economics or why nations fail or any of these really big topics we've got the world experts in the econ department and something parallel is going on in the computer science and the artificial intelligence lab where we've got some of the people who helped it literally invent the disciplines of robotics and artificial intelligence and we have a couple different seminar series going on there's one that brings together the roboticists the business school people the economists and the artificial intelligence geeks it has been the most consistently well attended fascinating seminar that I've ever been part of in my academic career and all of us keep showing up because not because we've got tons of idle time but because we're so fascinated by the topics that are going on here in the second machine age so I know you're sick of seeing this slide I want to put it up one final time and just reemphasize that the strengths the disciplinary the interdisciplinary strengths at MIT that we have to go tackle these kinds of questions exist absolutely no place else on the planet and I was an undergraduate and a master's student at MIT I strayed I spent years down the road hanging out with a different sort of crowd I came back home a few years back and nothing feels better than being in your place and being among your people and that's how I feel at MIT let me stop there I would love to I would love to take some questions yeah please to what extent do you agree or not about the disenfranchisement of people who do oppose the Google buses for example because they believe that their data is being given away for free and somebody else is making billions with it I always ask the real cause yeah I always ask them if they refuse to watch TV for the same reason right they were giving away their eyeballs in exchange for getting something for free in return I want to be clear I do think there are privacy concerns that come up in this world of extraordinarily big data and powerful sensors and governments who are telling us one thing and doing something else I think there are legitimate concerns about that what I don't think though is that the companies like Facebook and Google are duping us into some kind of some illicit or some kind of unethical bargain I understand that Google takes my data and shows me ads based on it I honestly get that what I don't think is that everyone else who uses Google is such a moron that they're not aware of that bargain so when I listen to those activists I hear this kind of this almost a paternalistic concern for those poor people who aren't astute enough to realize that they're being shown ads yes they do the ads are there on the page all the time so I do I do think that we have privacy and security concerns absolutely the principle that I fall back on is not let's have some let's have some Politburo let's have some bureaucrat decide what is and isn't okay let's instead rely on the principle that sunlight is the best disinfectant let's get knowledge about what is going on and let people make informed choices for themselves yeah please can you wait can you wait for a microphone please do we have one oh I'm sorry to take it away we'll give it right back sorry for that just just further on that point have you mapped it when you look at the impact of second machine age the impact of regulation either around data or maybe around things like net neutrality and so on and how those I wouldn't say external factors because they're all part of the one thing but how those big factors are impacting what you're predicting the single best piece of work that I know of on that exact question was done by our MIT colleague Catherine Tucker who looked at what happened to the online advertising market in Europe after the European regulators decided that there was too much tracking going on and that they had the that the all the operators had to scale that tracking back it was done for perfectly good intentions I think the effect was really clear the advertising became less effective which meant that we had to take up more of each screen that all of us looked at with advertising to maintain the revenue so in the wake of that legislation our screens became even more of an unpleasant mishmash of ads and blurring nonsense and what not simply because the effectiveness of it went down we had to get our revenue elsewhere I take I take some insight away from the fact that after the publishing industry in Spain successfully lobbied the Spanish government to force Google to stop showing snippets from Spanish newspapers on Google news surprise surprise traffic to those newspaper sites went down and then they lobbied to have that ruling overturned in general I'm not saying there's no need for regulation in any areas in general I'm a big fan of permissionless innovation and I'm a big fan of making sure that we know what the problem is and what we want the remedy to be before we start wielding our fairly blunt instrument of regulation yeah I'm now we're back to you I'm sorry thank you so I think Eric talked a bit about labor arbitrage around you know that which is essentially kind of how I mean China and India the growth there really really started so given you know what we're talking about second machine age and the differential of that going down would you see that to happen less so the offshoring that has really defined kind of economic growth in other countries with that stop you know after this has all happened would it come back I mean what's your view now so one of the happiest phenomenon of the past couple decades has been the movement out of dire poverty around the world of the people at the absolute base of the pyramid and it's just I think it's probably the second best economic news on the planet is the reduction in terrible poverty because of markets and trade and because of companies like countries like India and China realizing the benefits of markets and trade and globalization so the so that's been a wonderful phenomenon the question you ask is what happens to be a little bit cute about it when the rising wages at the bottom of the pyramid meet the declining costs inherent in Moore's law that's gonna be a very very interesting collision what we're already observing is a phenomenon that some people call deindustrialization and what they mean by that is the classic route to prosperity in the 20th century and we can think of the countries that became prosperous Taiwan South Korea Japan they did it in by following almost the same pattern they went through a period of pretty heavy manufacturing pretty heavy industrialization were a big popular percentage of their population was basically working in a factory then they developed a service sector that went down but the hump was a pretty high hump what we're seeing more recently as companies are trying to come out of the bottom of the pyramid they're not going through that same period of heavy industrialization so that peak is a lot lower than it used to be what's the new path to prosperity that's a lot tougher question but if you're looking at global growth and improvement in living standards industrialization was a really really good pattern we're seeing less of it than we used to and another cute way that I've got to talk about this is when I think about the problems here in the developed world and we've got our share of economic challenges medium termish I would rather have our challenges than China's challenges for example yeah please yeah Andy you and several of your colleagues have talked about the pace of progress and how it's gone very fast and it appears to be speeding up exponentially or at least at some very rapid pace do you see or have you seen in all of your conversations a conflict between the pace of technology AI change and what people actually want to deal with yeah yes is the short answer there's there's a pretty big conflict I'm supposed to do this for a living and once in a while I find myself muttering under my breath like would you give it a rest for a while so I can catch up with everything you've done in the past week and feel moderately on top of the situation again so I do think individuals have a hard time keeping up with the bounty that's coming in the second machine age I think that phenomenon is dwarfed by the difficulty that organizations and that institutions and that policy have in keeping up with the second machine age and and we really again the solution I believe is really clear we can't slow down nor should we try to slow down the pace of tech progress we need to increase the clock speed of ourselves in our institutions to respond effectively I guess what I was trying to get at was do you see any pushback coming from the sort of the conflict between the pace of innovative change on one side and the pace with which normal everyday people can keep up with that I do and that's why I tried to be explicit about the protests that we're seeing in in San Francisco in Berkeley and some of the resistance that's rising up to technology I think some of it is this kind of generalized anxiety that a lot of us have that you know stop the world I want to get off things are just moving a little bit too quickly I wish there were an easy answer to that I think responsiveness and and receptivity is our only real way forward trying to trying to fence off tech progress we've got plenty of evidence about how well that works you can do it if you want to immiserate your people yep thank you where was our where's our mic next Justin go ahead right there thank you I think you mentioned your book the way the winner takes it all tendency I think she's probably human nature how you see I mean with with the Google's on the Facebook's and or the company how you see the future and the role of startups the the pattern that I think has held true in the high-tech industry is one of dominance and then disruption and the creation of one or a small number of incredibly valuable incredibly powerful companies think Microsoft think IBM beforehand and a lot of us worry that that company is so powerful that we need to roll out antitrust regulation we need to be concerned about that we need to go after them in one way or another the market tends to take care of fat lazy monopolies in the technology space and tends to take care of them and sometimes with remarkable speed so when I look at today's really powerful tech companies I can't imagine what's going to unseat them on my imagination is just not good enough to know what's is Google's death knell out there and if so what is it is Facebook pass a I honestly don't know I'm a little bit less concerned than a lot of people that these are the new industrial giants that are going to dominate our lives for all time going forward because I'm pretty sure there's a group of I have dozen weird 20-somethings backed by somebody or else and that's that that's what's going to keep that kind of sustained dominance from happening I want to be clear I'm not saying that we don't need to worry at all because all great concentrations of power require vigilance and require scrutiny so I'm really happy that John Tyrol got the Nobel last year for his work on market power and antitrust I think that's incredibly appropriate some of our technologists colleagues have a little bit of a go you silly antitrust me don't you worry about technology they tend to love monopolies a little bit too much especially if they're early stage investors in them but but but I'm I'm calmer than than a lot of other people that I talked to about the pattern because I think we know what happens in high tech getting complacent stop it not scanning the tech landscape not taking brilliant care of your customers you're going to go away very quickly in this world you do we have a yeah go ahead carrying on from your comments on Michael Polanyi and the principle that what is codifiable can be automated while tacit knowledge cannot my question is why do the majority of companies seem to make hiring decisions based on candidates codifiable skills it's such a great question when you when you look around with with kind of a second machine age lens on things you are amazed at how many antiquated practices you still see how much of our industrial era mindset still applies over and over and over you bring up human capital management and talent management as one way to do it think about the way most of us still hire people we get a transcript and a cover letter from them which lists primarily their codifiable skills in addition to some nonsense about how there are people person in a self starter which is completely unverifiable and then we sit down and we have a short interview with them the research is really clear the point of that interview is for me to figure out if you remind me of me and if so you got the job we don't need to do more research about this this model is broken it's still the dominant model what one of the encouraging things is we're looking around at what some of the more innovative some of the leading firms are doing and they're walking away from that model and they're doing some really weird different things some of the tech companies say I actually I don't care about your resume or your transcript where you went to school and your GPA has no value beyond more than a couple years after you graduate I want to look at your github score are you actually coding out there in the world are your contributions valued by other people Eric is the one as an advisor to this weird company called knack that has you play video games literally has you play games to try to assess those those in those unquantifiable those more tacit things to see are you going to be a good salesperson in this organization so we're we're coming at this problem in lots of different ways one of the ambitions that Eric and I have in the wake of this book is because we don't learn our lessons very well to go write another one and to try to surface the the the post industrial business practices that make a ton of sense we're going to draw heavily on Roberto's work and Marshall's work to try to incorporate measurement and platform dynamics and things like that but we I feel like the business world needs to a clearer view of what the second machine age means for them and human capital management is absolutely part of that we have time for one more question well was that was that the one sign or not okay so I don't mean to put pressure on you this needs to be an absolutely bang up final question because it's the it's the last one of the entire day so please bring us home make us proud we talk about educating the students and the children of today to meet the demands of where technology is my concern isn't about where technology is today I'm looking at 10 year olds 11 year olds coming through and we need to be educating them for 50 where technology is going to be in 15 years time in 20 years time what needs to be changed what policies need to be changed what how we educate the children specifically what we're teaching them what's your view on what we need to change in order the for them to meet where the economy is going to be in 20 years and I see we're just about out of time thank you offer this is a fantastic question the reason I'm trying to dodge it is as you point out it's such a hard question our 10 year olds are going to be heading into a workforce in a decade take the kinds of things that we're seeing project them forward a decade nobody knows where we're anybody who tells you they know what the economy looks like in 10 years is lying to you or lying to themselves what it's just becoming too unpredictable so what is what's a smart educational policy in that world we need to make our best guess about where the human value still is and I want to be clear I mean human value in an economic in a workforce sense I don't mean it in a deeper sense a more moral sense although that's important too so if we just focus on what kinds of things will humans be doing in 10 years that will still be economically valuable I still think there is a list that we can see with at least some clarity we are still going to be engaged in creative work we're still going to have that edge over technology and absolute Eureka I think is still a human skill but you can say that look that's for that's for the geniuses the Steve Jobs the crazy outliers out there I think that empathy and taking care of other people and making them feel good and getting them to comply with their medication 10 years out 15 years out that's still a human skill I think negotiation is still a human skill I think as you know as tired as we are of these words management and leadership when they're done well are still very very human activities I don't think many people want a purely digital boss I don't think anybody's going to want a human soccer a digital soccer coach in 10 years to motivate them and make them better at any level now I think all of those professions are going to have a lot more technology than they do now but when I look ahead all up and down what we think of as the classic skills ladder or the educational ladder even after a decade more of this crazy progress there's still a lot of room for humans to add value we just need to stop educating them and stop thinking about the situation like it's 50 years ago and push ourselves toward the future I want to end up with one of my favorite favorite quotes about about how we should think about things and it comes from a colleague at Harvard Larry Lessig and he's just got a beautiful way to summarize it he says with our policies and I think more broadly with the choices that we make as individuals and as people we've got a very stark choice we can protect the past from the future or we can protect the future from the past I'm such a huge fan of the future I want us to do all the work we can to protect the future from the past I think that's a good note to end on thanks very much so listening to that looking at the faces in the room here I'm sure if we had Joey it is engagement meters on all of you they would all be off the charts and so it is sad that we have to bring this to a close but you can see why I work love working so much with Andy and the rest of the team at the IDE and the benefits it comes from interacting with all of those people and I want to sort of maybe close up with one of my favorite stories which has to do with trying to date when this remarkable set of changes really started happening and you could pick a lot of different dates but but one iconic game in addition to go is the game of chess and as you guys may know for the first time it back in 1997 a machine beat a human in the game of chess Gary Kasparov lost to deep blue and because of the exponential progress and the other progress in in actually in software in other areas computers have continued to get much much better at this point it turns out that there's a chess program you can run on a cell phone that will beat a human grand master in fact it got so bad that at one point Jan Donner the Dutch grandmaster was asked what strategy would you use against a computer chess program and he looked a little trouble and then a smile came over his face he said ah I would bring a hammer and we've heard about that strategy a little bit but I think it's it's it's not the strategy that we're going to pursue in fact I want to take solace from another lesson we learned from computer chess and that is that today the world chess champion is no longer a computer nor is it a human the best chess player is actually a team of humans and computers that play together Gary Kasparov invented a new kind of chess after he lost to the computer and the new kind of chess is the same basic rules except that instead of it being either a human or a computer he said why we let the humans and computers work together as teams is that more natural so teams entered together and what was remarkable was that the winning teams were not necessarily the ones with the most powerful supercomputers or the best chess programs or even the most powerful grandmasters the winners tended to be teams of humans and computers that work together sure good chess players and decent programmers but they really had this knack for figuring out how to divide up the problem how to allocate what humans can do well and what machines could do well and that combination has proven more powerful than just a pure machine or pure human approach and I think that's a inspirational way to think about how we can use the technologies of the second machine age to do things we never could have done before and not think it was a competition either or but rather cooperate together and in particular the reason we created the initiative on the digital economy was to help bring together lots of people lots of technologies but especially lots of people Andy mentioned the people across MIT in the Department of Economics the Media Lab C-Sale Computer Science and AI Lab the Sloan School of course and the broader community of people like you and the initiative on the digital economy convenes these different minds together and the technological resources that are available to try to address not just great research but the other things that David mentioned also we have a convening function where we bring together people from all over the world at our annual conference and our other events we have an educational program we have a prize in fact a specific prize and run inclusive innovation that we're developing right now to help invent some of those new business models and we're hoping all of you will be part of that team and contribute to our ability to solve these kind of problems and more importantly think of them as opportunities to create a much better more prosperous more successful kind of a world so there are a lot of specific ways you might be to get involved let me just turn it over to Andy I think you may have some additional closing comments on ways they can get involved or yes come have a drink with us as we say in America it's beer o'clock I think it's the weekend here we'd love it if you'd come out and ring in the start of the weekend with us thank you all so much for coming we appreciate it. Thanks very much.


Live from San Francisco, California, theCUBE, covering MarkLogic World 2015. Brought to you by MarkLogic. Here are your hosts, John Furrier and Jeff Kelly. Okay, welcome back everyone. You are watching theCUBE, our flagship program. We go out to the events and extract the symphony noise. We are live in Silicon Valley from MarkLogic World 2015. I'm John Furrier with SiliconANGLE. I'm Joe Mike Coase, Jeff Kelly, big data analyst at wikibon.com and our next guest is Jeremy Bentley, CEO of SmartLogic Entrepreneur, growing company in the fast emerging space around metadata, cloud, search, finding stuff in the enterprise. Welcome to theCUBE. Thank you. So what a better way to jump right in, talk about what cloud and what agile, what unlimited compute, flash memory, flash technology, basically technology to make things go faster and faster. Add to fingertips. Which might speed up the content type market. So explain, we're going to get into that, but I want you to explain a little bit about SmartLogic, what you do, because it really is some innovation going on in how things can be surfaced, the discovery. You know, information discovery is not just a consumer, but it's also for systems. I want to get into that, know the deeper way, but first start with what you guys do. Okay, well, I might start just with a business scenario, which is I think that the, you know, the users, the people who run businesses, they don't say, oh, I'm really glad you put all the data to do with the balances of my customer in this database, and then I put all the documents and information to do with my customer in this content management system. So you already now start to see an unnatural separation between what people refer to as structured data sitting in a database and unstructured content sitting in a content management system and being surfaced by a search engine. And of course, as you get into the restrictions of that, you know, you can ask a database a question and we'll talk about the changes there, but actually you can't ask a PDF a question. So you already start to see that information that's held in content is not available for analysis or processing by another computer. You actually have to read the PDF. You know, content is very, the information in content is very valuable, but it's unavailable. You have to give it to someone and say, you know, go off and code into a database the information that's in this content. So what smart logic is about is it's about unlocking the data that is in the content, right? And you know, when you do that, you start to, it's hugely beneficial. Why? Because 80% of the company's information is in content and yet the content itself is so restrictive that you can't use it for analysis. You can't process it. You can't automate content-based processes. And that really comes back to a little bit of history, which I think is part of the data versus content argument. We started life with hierarchical databases. Well, actually we started life, Gramercy III had information and he had it in paper. At some point in the 50s, we started to code really useful bits of information into databases. They were restricted. They had the eight bits, 16 bits of memory that he had. And so you could only take the really top pieces of information and put them into this Harkane system called a hierarchical database. 30 years later, we invent and the massive $40 billion market that databases are today is to do with the concept of self-description. The hierarchical database gave way to SQL. SQL is a self-describing, has a self-describing nature. Other computer systems can talk to that database. You can write reports. And that really was the beginning of what we call modern IT. By doing it, you've got this benefit, self-description and therefore automation, but you've also got a still a restriction which is that the schema or the way the database is structured means that you have to presuppose the question before you ask it, right? And then of course we now move to the post-relational and we move into no SQL. So that's the data side. Now let's look back at the content side. Well, as data was moving off reports into databases, the reports themselves were still in finding cabinets for at least another 15 years. They then moved into image management systems. They moved from image management systems into file shares. They moved out of file shares into, you know, content management systems. We invented enterprise search to sit on top of those. But actually it's all batch and brittle systems. If you, by batch and brittle means you can't change these systems and they're not self-describing. And until the information in content becomes self-describing, we don't get the same data or information facilities over that content that you get over data, okay? So self-description is the basic art, is the basic- Because data can't talk to each other. Data can in databases talk to each other. But if they're not in different databases, if they're in different databases- Well, content can't talk at all. Yeah, fine. So our smart logic's job is to make the information in content or to make the content self-describing. So it's addressable. So it's addressable. Okay, got it. So once the content, the information that's locked up in content becomes self-describing, you can start asking questions of it. You can ask your PDF, what are you doing? It's kind of like an IP address. Once it's addressable, you can do things with it, right? The data, so this is content, right? I don't know what this is. This is a report, right? And this report- You hold up a little bit. This report has a huge amount of information in it. But in order to access it today, you have to go and read it. And if you want to know who signed off the minutes of the meeting, you actually have to go and read it. But what if you could query the report like a database and say, who signed off the minutes of the meeting? Who was present at the committee at the hearing? What date was the committee found? Well, it was organized. Were there any dissenting voices? Well, you know, this is data. This is data and valuable as the information that's sitting in the database. So the thing is 80% of the information is in this form. It's not in the database. So as we move into the, if you like, the true information era. Is that because the content management systems are so lame and old? That's because they are designed to hold on to pieces of paper. And the best they can do is find the piece of paper and I'll make you read it. But I think, at the time, technology has come. There's a conference of technological change. And the first is that the, if you like, the ability to process language, right? The ability to read and understand the meaning of the information in the report. That's moved on significantly. I mean, this stuff didn't exist before 2007. The volume of content that is going into these content management systems, even if they were self-describing, which they're not, means that they're all beyond spec because they were never designed to hold on to terabytes of content. And if you start to look at, you know, big industrial processes and the compliance tasks and, you know, the paper trails that organizations have, which they've now automated into content management, this data is not available for analysis because it's stuck in paper or virtual paper because it's in a content management system. So yes, the answer is content management systems are batch and brittle applications, right, that don't self-describe. So how does smart logic go about actually breaking down those barriers and actually making it accessible, making content accessible and the ability to tie that to structured data so you can make better decisions? Well, I think this is part of the confluence of technologies coming along. So we've moved now into post-relational era and we have some, you know, we have the concept of a fact, an RDF triple, which is, if you like, the atomic level of fact. So what Semaphore, which is our product does is it goes through the information, the content and it turns the facts in the data, in the content into data in the form of RDF triples. So if you've got data coming out of your data warehouses in going into post-relational systems as RDFs and you can take the 80% of the information that's in the content into the RDF format, now you've got a common format for all data to sit in a unified information store, if you like, which is incredibly valuable. So you can start to answer questions like, which very few, you know, no banks can answer, which is give me a list of all my customers who've got a balance of over $20,000 and who've written a letter of complaint last week. That is an impossible query to ask and it's only the opening statement of so much content-based information that it's not available. So the semaphore's job is to apply intelligence, that's why we call it content intelligence, in order to pull out the data in content and what does that mean? It means you have to be able to model the subject matter of the business and words associated with models of things like taxonomies and ontologies. The reason why they're important is they're a very good container to put in, to put, to model subject matter and that sort of stuff. You then have to interpret those ontologies. You then have to classify the content as it goes past, flies past the system and able to be able to classify the content. You need to be able to extract all the facts, the entities, the potentially the sentiment in order to extract that. And then you need to be able to visualize that information and co-mingle it with stuff that might be in the database. So the conference then of post-relational information stores to give the improvement in natural language processing and the ability to actually do this stuff that I've been talking about with content. And I think the last one, which is the concept of the semantic web, the concept of open link data where people are sharing their ontologies with, you know, make them available, where the information itself possibly doesn't become so valuable, but actually the question that you're asking over the content, over the information becomes the biggest piece of value. And that also is philosophically really quite big, right? So most people think about locking down their information, their data. Actually, as you get into open link data and open shared information, it's not the information that's the most valuable, it's how you use that information and what questions you ask of it. And that becomes very, you know, it's the insight, it's not the data. Chairman, we've got to get the hook here, we're getting the poll here from the producer, but I want to get one last word in, give you the last word, share with the folks out there real briefly. What about MarkLogic? Should they know about? They might not know about. What's the key secret sauce in MarkLogic? What makes them so good? Well, MarkLogic, like smart logic, a lot of logic's here, they're hugely successful at providing no-SQL databases for enterprises.  It's volume, it's security, it's speed, right? It's reliability and all those things. And so very similarly to MarkLogic, smart logic works on the same principles. We are well known for speed, for enterprise-ness, if you like, and the ability to deal with the volumes and the speed and the reliability and the security and the things for that. So we make a great combination, the two, and we've done lots of projects together and we're looking forward to doing more. Okay, we are here at Live in Silicon Valley at MarkLogic World 2015, this is theCUBE. I'm John Furrier with Jeff Kelly from Wikibon. We'll be right back after this short break.


Slush, I hope you're having fun. Let's talk about Lilium. We live in an urbanized world. In 2025, 8 billion people will inhabit this world, this planet. 630 million will live in mega cities. The mega cities will be on a rise. Also mid-sized cities will rise. Everything that we see is will put incredible pressure on society as it exists and you know the way we live, the way we consume and the way we move around. But that's that you know as fast as the world seems to move, other parts of the world seems to come to and hold actually getting slower and slower. We're talking about traffic. I think we all know it because we are sitting in it and we are not enjoying it. So it seems like we go back in time even to a time of horse courage. So we need new paradigms. We need new thinking, new ideas, a step change. And Lilium wants to do a contribution in this conversation by creating an innovative end-to-end urban mobility concept that will be launched in 2025. So we believe the future moving upwards is the way forward. So I started seven months ago at Lilium and I was very impressed by the company and the four founders that put a lot of vigorous, a lot of dedication into this business, extremely dedicated and supported by some really world-class investors that are making our world also much easier and pushing us forward. So they're all aligned to this ambition and I was I think employee number 70. At the moment we are 250 people. So in seven months we grew quite a bit. We're people from, you know, with backgrounds, quite impressive backgrounds that are exports in their fields and we are all aligned to one vision which is enabling a world where everybody can fly everywhere at any time. So what's this promise that we want to bring to the market? First of all we believe that this air mobility service is potentially the most the most effective one to travel in mid-range distances that ever really existed. So we make an example, for example LAX to San Diego in 30 minutes or let's say you don't have to build a tunnel Helsinki. You can come to Tallinn in 16 minutes. So this is quite an amazing speed and also we are creating a world that is much more connected. So you are more or less independent from the big transportation hubs, from the airports, from the train station. You can live wherever you want to live as long as you're close to a lily pad. So that is really an amazing scenario as well as the fact that we want to be clean. Of course every new business that wants to be successful in the 21st century needs to be clean. We will be fully electric and with zero admission in our operational system. So in the end of the day we also believe that we are not creating something just for the rich. It should be for everyone. It should be affordable and it should be actually an alternative for people that would like to take a lilym jet to commute to the city to commute to work. So this is quite a mouthful. So how are we doing it? We are developing manufacturing and operating the world's first entirely electric take-off and landing jet aircraft. It's a five-seater that you can see here, this baby. It's built just with one purpose in mind to create the center part of hopefully and possibly the best urban air mobility service in the 21st century. So it has 36 electric engines that are actually fastened in these flaps that you can see. I can see this, you can see the little animation behind me. You can see there are kind of moving up and down. This gives an incredible maneuverability to the plane. So it moves like a helicopter. It starts vertically and it moves really nicely. And due to this possibility it can actually land in urban areas and it's very little infrastructure to actually do that. So it's a five-seater electric air taxi business model that we have. 300 kilometers per hour is the speed, quite an amazing speed, and 300 kilometer range, which gives us a great opportunity to create a point-to-point on-demand service. So when I talk about on-demand, it's of course built in your phone. It's of course an app-based booking system that you can actually use. People are asking me when can I buy the jet? The jet is not for sale. It is actually part of the system. So you don't have to own a jet to actually fly one any time when you need it, every time when you need it. So the system is operated by Lilium and it works on your phone. Like when Elon Musk said we're already a cyborg because we're using this phone, so soon we will be cyborgs that can actually fly. So how will this work? Just a short demonstration here. We have the app so you can say this is where I want to go. The app shows you the next lily pad.  So we want to do this in very affordable price points and you know most of us have been in this scenario already sitting in the taxi on the way to the airport trying to catch the plane, not knowing exactly how long it will take to get there from New York to JFK. Very stressful sitting sweating in the cab. This time it only takes you five minutes with the Lilium jet and it will be with comparable price points to a cab. So this will also be linked to a infrastructure of pads, of landing infrastructure that will look a little bit like what you see behind me. It is it can be built in every city. It can be built on buildings. It doesn't have to be huge. It doesn't have to be it's very compact. It can be very compact. The plane can just need 12 to 15 meter diameter to start a land. There will be a charging. Maybe there will be a lounge and this will be actually possible also outside of the city in sub-urban areas as stand-alones. So that's that's the basis of it. So now you're saying wow all sounds fiction but let me show you a video that is already from January 2017 where we started our prototype which was demonstrating the technical aspect. So you can see this is the plane as our two-seater. You see that it's kind of pushing down the engines are pushing down pushing the engine up the plane up as it as it now does what it now does is actually what the real innovation is. So it turns in forward flight so the engine the plane will actually fly over the wings. So it creates our aerodynamic lift via the via the via the wings. This is very important is very different to any drone that you actually know and it is because it takes much less energy. You can see how maneuverable the plane is and also unfortunately you cannot hear the sound. I'm not not sure why. You could actually see a very gentle sound not necessarily this flapping sound that you have with with a helicopter. Here it is here it is here it is and you can see how it's landing quite cool. I find it always I still find it fascinating how it turns around like like in Star Wars or so and then it comes down slightly. The jet is unmanned. This is an unmanned flight. It will be also managed by a flight computer and you can see here it's actually nice how it actually then lands safely on the ground. Here it is. So why are we doing this because I think it's always questioned you know what is it doing for me what is doing for the individuals and I think the the easiest way to describe it is creates an incredible radius of your life. It gives people the opportunity to actually drive or fly or move five times faster than than a car. So it gives you five times more opportunities to actually go around and you know use your time in the best possible way. So let's bring this to for example Los Angeles the service. We have here you know the city that we all know it's quite significant in terms of traffic. 15 15 minutes will it take you to actually cover the whole area of Los Angeles County and if you want to go first further you can go 30 minutes into Palm Springs, San Diego and so on. So an amazing possibility for you every person but also and creative credible for the society. There is minimal infrastructure needed for this service as you can see that's the normal infrastructure that you have. So but in for the for the pets that we have we don't need that much infrastructure. The cost of the maintenance that goes into this concept is of course not comparable. We're 10,000 times cheaper than the normal infrastructure that you have and so the infrastructure at Lilium looks a little bit like that. So because you have two lily pets in one point and the other point and in between there's nothing there is no tracks there's nothing and it will allow us to actually save the environmental impact that will be tremendous you know when you build railways station railways or out of bounds or whatsoever. So in the end of the day we'll also connect an incredibly connected world it create a world where everybody can decide where they want to be where they want to live if you want to live in the south of England and actually commute to London you can do it it might even and I think we're all waiting for that rebalance the real estate price points. So my time is up I have much more to say I would love to see you all up here and please apply to Lilium.com. Thank you very much.


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 morning everybody, and welcome to another edition of TheAxisTrader.com. Weekend update, shall hope everybody is doing well. If you are brand new to the channel, guys, welcome aboard. Thank you very much for tuning in. All we ask is take a second to like the broadcast, share, subscribe, and we will try to continue to provide the most unbiased technical outlook that we possibly can. You guys remember last Friday, the previous Friday, the big story was Moody's downgraded the outlook of the United States? Yeah, me either. Right, me either. That really shows you how good this market has been. That was a little bit of a blip in the radar or a fly on the elephants behind, but it really does show you how incredible the run in the last three weeks have been. The euphoria continues, right? Euphoria definitely continues. There's always been periods of the markets going throughout the years. I don't want to go through a whole history lesson now, but you'll see euphoric periods and the euphoric periods always end because the market, again, is never as good as you think and it's never as bad as you think. So there's no difference, right? If you think about it from the logical point of view, there's no difference in what happened a month ago or two months ago when the market basically went straight down. And the queues went from 373 all the way down to 342, right? The market was never as bad as people thought because what happened? The sellers got tired and then we rallied up 45 points on the queues. So the market's never as good, never as bad, especially if you are an active trader and you're doing this on a day-to-day. Again, if you are a long-term investor, my channel probably does nothing for you because we talk about the next day and we're not here to try to predict what's going to happen before that. Well, I'll pass that, excuse me. But what we're seeing is continuation of really good, maybe holiday vibes. Okay, we've got Thanksgiving coming up next Thursday. It's a short week. You're probably going to start seeing a little bit of a slowdown in volume somewhere around Tuesday just because it's always the busiest holiday travel time because a lot of people will be traveling that time. But honestly, market's good. Market's very good. Friday we have half a day and obviously Thursday we close. About three, four days ago, I started getting a little bit more defensive, basically saying that I felt like a 45-point move on the queues was kind of a lot. And I've been kind of looking, I've been sitting there and watching for a potential reverse. Obviously, I'm not guessing. I'm not putting bets to anticipate a reverse. But I'm watching every single day for that possible reversal. And I tell you, we just continuously put in higher lows on this range here, which is amazing. If you see this whole move here, it was all on higher lows. The one day that the market could have reversed, never followed through, right? Never followed through the one higher. And now we're just sitting on this channel here. It's very, very tight. Now, here's where the big part comes in. And when I mean good, it doesn't mean bullish or bearish. It just means good from the trading aspect. The longer we go sideways, right? The longer we go sideways here, the bigger the more aggressive the next move is going to come. And for us, I trade both sides of the market. It doesn't make a difference to me long, short or indifferent because the value is the value. The channels are the channels. And the mega cap technology names are the only names you could literally trade every single day, no matter how good or bad a Tesla chart is. And we'll get to that in a second, right? You could still trade it every day because there's a big expansion day. Whether it's down in the day, up in the day, it'll give you a bounce level, give you rejection levels. It'll give you sneaky pivots to the upside, sneaky pivots to the downside. So that's where the majority of these 10 to 12 stocks that I trade every single day are.  And the most important part is what happens next. So we're pretty much done with earning season for technology mega cap cult names, right? The last one that is going to be reporting is NVIDIA on Monday, right? That's on Monday. Excuse me, on Tuesday. I'm sorry, the 21st, right? The 21st, that's the last one. Everything else is kind of sprinkled in stocks or companies that I really don't follow, don't even trade. But this is the last one, okay? If you look at the options market, the betters in this stock, despite 110 point run up from the lows, and the lows were only October 31st. So we're talking about 18 days ago, 17 days ago for as of yesterday's close. So in three weeks, right? Three weeks, NVIDIA ran up 110 points. There are people still betting for the weekly, okay? For the weekly, this week's coming up 525, 535 calls, right? This is after 110 point run up. Is it possible NVIDIA destroys their number and continues to go higher? Absolutely. However, there's a flip side to that as well. The conversation as always is, well, is this move a direct reflection of potentially the run up is already tied into this move? We don't know, right? We don't know. And if anybody can sit here and speculate and guess what's going to happen, you're delusional, right? You're absolutely delusional of how you think the stock is going to react. I've been saying this for years. This is what goes into earnings. You can literally have the report. Listen, I can literally sit here and have the report in my hand. Read it and know exactly what's going to happen. And you still don't know how the market is going to react to the price action after its release. You still don't know what the stock is going to do after the conference call. It could gap up initially and then sell off later. It could get hit initially and then rally later based on comments. So earnings are one big guessing game. And despite that everybody has an opinion, remember, there's only one shot at price action. We're going to find out exactly what that is on Tuesday. Obviously, the big numbers continue to be on NVIDIA, the August highs and the bottom here channel. And you see how tight it's getting? The bottom channel is here to play as well. Because again, if NVIDIA does miss or it's at least deemed to be priced into their quarter, then this could be a potentially two-sided aggressive move. Because remember, the rest of the market is just waiting for NVIDIA. Just think about it, this is why we're going sideways now for the last four or five days. This is going to be day five on Monday. We're just going sideways right now. We're holding the five-day moving average. And that five-day moving average, guys, write down this number. This is going to be a big, big number in case the market finally gasses out. Again, we don't know if it will every single day. I'm prepared for a washout and it just never comps. But I'm prepared. I know the levels and that's the most important part. Don't go into any single trading.  The market's going to go up again today. Yeah, because you want it to go up again. Doesn't mean it will. Just the same way you were hiding underneath your bed, screaming, mommy, please help me. Mommy, please help me when the market looked like it was about to implode into the 200-day moving average. Again, buyers get tired. That's what we might be seeing here. Sellers got tired on the October 26th lows.  I'm doing this for nearly 25 years.  I'm not saying on one trade, on one candle, on one interval. So be very, very humble. Really understand the levels. And that lesson and that level for a potential, at least the initial aggressive back test, could be this 383 level. Guys, write this down. The queues are sitting for four days in a row. Monday will be five. So that's a full week of trading. This 383 correlates with the rising five-day support. We've been talking about this five-day support now since this whole market rally. Again, if you can see every single time it hits this orange line, it balances. It balances. It balances. It balances. It balances. It balances. It balances, right? So that's the point. The lower it sits sideways and it doesn't go up. If there is a potential back test, if NVIDIA decides to kind of miss on their quarter or the reaction is negative, guys, watch this 383 level. They held 383 on November the 14th. They held 383 on November the 16th. And they held 384 on Friday. So that 383 level is the line in the sand, at least for a short-term potential back test to kind of reset prices. Nobody's calling for a top. We're just calling for a potential if you are prepared, right? I'm telling you what the number is. If you are prepared that 383 level is going to be the line in the sand. But again, the longer we go sideways and the market can't replace, excuse me, reject the potential sell-off, then eventually we'll start moving high. We'll see. We'll see about that. If you look at all the names, again, market continues to shine, right? Amazon, despite two days of selling, kind of reclaimed back the five- to ten-day moving average looks absolutely great. We saw 147, 150 calls coming in. A name, for example, like Apple just continues to be chugging along. Microsoft had a little bit of a run-in on Friday. It got pulled in the day, in the middle of the day. And then you saw the news. I think the CEO of, what was I kind of doing? The CEO of, was it open? I'm not into this whole open AI. That's it. I just looked at it right now. A CEO of open AI, I guess his name was Altman. I guess he was asked it from his position and considering that Microsoft is the biggest shareholder of that, they took a hit. And after the close, they're getting hit as well. One of the biggest stories and what this market continues to do is the data we saw this week. We saw the CPI data come out, the PPI data come out. And it really is showing that there's a strong sign now, really a strong sign that they're potentially, I don't want to use the word they're taming inflation, but at least there's a reason, there's a rationale behind it. They potentially, what the data is telling is they potentially could start cutting rates as early as March. Or may I remember them saying, so that's a very big key. As you can imagine, bank stocks got a really big boost on this news. You can see JP Morgan, Morgan Stanley, Citibank, Bank of America all having big, big runs. Also a big deal, kind of a big deal this week. We saw kind of what Elon Musk did, which was a little bit staggering, which is very odd, especially from his point of view. So if you guys follow this, and I couldn't figure out what was going on. So Thursday night, I was long. We caught this really nice move on Thursday. So I was long Tesla overnight. As you guys saw the headlines came in on Thursday session, and that Elon Musk apparently promoted an anti-Semitic tweet. As you can imagine the stock got killed. So yada, yada, yada. I wound up on Thursday session, Wednesday was the big run up on Tesla. So I came in long Tesla, had a pretty big move on Tesla. And then because of that tweet, there was obviously a negative reaction. And I basically gave back 70% of my gains from the day before on Tesla, which was fine because on Friday we got it back on a short, a really, really aggressive short at the open here. We caught this beautiful, beautiful short on the previous day's range on Tesla. But because of this, I guess, anti-Semitic promotion of a tweet. Well, you got a lot of big advertisers either stopped or pausing doing business on Twitter. You saw Apple, you saw Apple, you saw Disney, you saw IBM. And then you go, we'll see, we'll see exactly what happens. And over, I think yesterday, I think their spaceship, right? I think their spaceship got destroyed or sculpting in midair. I think it was something in midair. So it's going to be very, very interesting to see what happens with Tesla this week. And ironically, as much as Tesla came back in on this tweet, it reclaimed back a lot of levels. And now we're kind of stuck in this range here. So I definitely want to see which way Tesla breaks this week. So going into this week, guys, again, the same game plan. The same game plan goes. The market's going sideways right now. The rangers are contracting. That's a good thing.  That's a good thing. The longer something goes sideways, the higher probability the next move is going to be an explosion or an implosion. We just have to understand which way the market's going to break. So we already know the bottom channel here is 383, right? The bulls need to defend. And the upper channel here is 38775 that the bulls need to reclaim. Other than that, you can continue. And this is kind of what we've been doing the whole week. Even though I'm prepared for back this, all we've been doing is buying dips, literally buying dips in the strongest stocks into rising 60 minutes support. And if you look at the charts, they're holding really, really well. That theme is going to be continued at least the start of the week. Obviously, NVIDIA is going to give us a whole lot of clarity of what happens next. I do assume, I have to believe, I do assume that once NVIDIA comes out with earnings because the semiconductors and they've been on just on fire, right? The semiconductors are predominantly the stronghold on the Nasdaq 100 along with biotech names. We will get a very, very aggressive move one way or another, either below the 383 on the Qs or above 388. Other than that, guys, again, stay away from the overextended names. The overextended names, they're up 12, 15, 20 days in a row. They're the toughest names because if there is a pull in the market, they're going to be the ones who get taken down first. And you can see what happened with Microsoft. When these things turn, they get very aggressively. So let me give you guys some ideas for Monday. Let me give you guys a couple ideas. Look at Coinbase, right? Bitcoin has been very, very strong. If you guys remember the last time we talked about Coinbase, it was this October base, right? And once it got about October base, it exploded. All this base is now playing out again. You're talking about now in two weeks of a new base, Bitcoin continues to look pretty good. And obviously, this is one way to play Bitcoin the whole thing. So Coinbase, watch the top of the channel here. If it starts building above this top of the channel here, maybe finally wakes up this week. Look at a name like FSOLine, right? A smaller name, but look at this base here. It has a really, really tight base underneath supply. First close above the 50-day moving average. All it needs to do now is get above this 100-day EMA. And this thing looks really, really good. Keep an eye on that. Let me see what else I want to talk about. Amazon looks great. Amazon continues to look great. Obviously, Black Friday is around the corner. And speaking of retail, speaking of retail, Target, right? Target had a really, really good quarter, right? Which is surprising because if you look at what the stock has been doing, this is a monthly view. This is from 2021. I mean, this has been on a death spiral. So considering that Target had a really good quarter, maybe there is an uptake of optimism that the retail cost consumer is back. We'll see. And that's why Amazon is writing as well. Also, watch Target. Watch Target after its earnings gap. It's kind of going sideways as well. Keep an eye on Target for this week as well if it starts taking out the earnings highs as well. Other than that, again, it's all about Nvidia. It's all about to see how the market continues to deflect bad news. So far, again, the market has done its job. Negated completely. The Moody's downgrade has really embraced both the CPI and the PPI data that we saw this week. We had some more data on Friday. I think it was jobless.  You can't remember anymore. But the point is it does show, at least from the recent data, that inflation is being tamed. And maybe there is going to be some sort of rate cut in our foreseeable futures. Guys, have a great night. God bless. Have a great weekend. Right now, it's about a little bit before 11 o'clock in the morning on Saturday. So you guys will probably get the video sometime either Sunday or it's either Saturday afternoon, Saturday early evening, or Sunday morning. Guys, God bless. Have an amazing, amazing trading week. Have a great weekend. And God as well. I'll see you guys all Monday. Take care.


Welcome traders to another tick mill weekly market outlook for a week commencing Monday the 5th of December Okay, let's jump into the data slate for the week ahead this afternoon in the US we will get services PMI data and non-manufacturing ISM Which is looking to come in at fifty three point five below the last reading of fifty four point four But still technically in the expansion zone. We also get October factory orders looking for zero point seven percent print there Really S&P global materially weaker than the ISM pointing to clear downside risks for the manufacturing sector Capital investment is also likely to be subdued through the third quarter heading in to Tuesday we get the October trade balance looking for a negative seventy seven billion their import prices and demand are starting to Heading into Wednesday Q3 GDP Sorry Q3 productivity 0.3% final estimate for that reading and on Thursday We will get October consumer credit looking for twenty six point five there high rates to weigh over the coming year on the appetite The consumer credit in the US will get a vision jobless claims Remaining at relatively low levels around that 200k mark and then rounding out what we come Friday November PPI Looking for zero point two percent there annual producer inflation is easing from those record highs We'll also get October wholesale inventory spinal estimate zero point eight percent I'm running out the week with December University of Michigan sentiment looking for a fifty six point eight print there pressure from inflation and Rates still dominates the headlines From a technical perspective dollar index has traded through our target We were looking for a test last week of that one oh four forty We hit that in the overnight session and what I'm looking for now is three-way Corrective move back into the trend channel resistance So something in this one oh five fifty area watch for bearish reversal patterns there to redeploy shorts looking then for a test of this Weekly projected trend line support in the midpoint of the broader channel that we've been trading in Looking for one oh two ninety as the next downside objective at this stage We'd really need to get a close back through the 107 90 area to suggest a more meaningful low is in place moving to the Eurozone In terms of the data for the week ahead Don't have anything on tap tomorrow. We have Wednesday then Q3 GDP In the eurozone looking for zero point two percent as the final estimate And that's that runs out really a pretty light data slate for the eurozone this week We have had some PMI data out this morning And that's coming brought in line with expectations October retail sales negative so far this year weakness is broad based in that sector with Recent rising rates in eurozone pressuring consumer at the time. We still have obviously the ongoing conflict In the Ukraine so from a technical perspective the euro dollar We're still looking for a test of this one oh six twenty area Which coincides with this weekly projected trend line resistance from there. I'm looking for a three-way corrective move Certainly think about retest of one oh three sixty potentially down to one oh three at this stage And we take a close back through one oh two to suggest a more meaningful high in place For now, we're looking for further upside in in the euro here Once we get this initial test of the there's one oh six twenties and we look to reload on the long side after a three-way corrective move Into the UK in terms of data for the week ahead what we have Again pretty light slate in the UK Services PMI final lesson at forty eight point eight Out this morning and that is the only tier one piece of data. We're going to see from the UK this week There is some the British Retail Consortium will on Wednesday release their unofficial first indication first look at retail sales For November obviously important as we're heading into the festive shopping season So this will give the first indications potentially of what? What markets can look to expect in terms of consumer sentiments and consumer appetite for spending as obviously still dealing with this cost of a living crisis in the UK and Recent rate rises continue to weigh on housing and the consumers wallet So to be interested to see what that's that survey gives us so from a technical perspective Sterling trading through our target last week. We're looking for one twenty two fourteen We have achieved that so what we're looking for now. So as we test into this one twenty three sixty I'm looking for some consolidation here three-way corrective move and we're taking another look at this trendline support Trend channel support these prior highs back into that one twenty one fifty If we find more buyers stepping in there Then we'll be looking for bullish reversal patterns to engage on the long side next target on the outside It's going to be this one three four ninety and one twenty five should be should become the magnet then at this stage Really need to close back through this daily trendline support 1890 suggests the potential for a more meaningful high in place Moving to Japan In terms of data for the week ahead Tuesday October household spending Centage year of the year last time two point three percent market anticipating a zero point nine percent print Real spending capacity is under significant pressure Into year-end and then on Thursday we get the October current account balance 605.4 billion yen versus last time 909.3 billion Surplus under pressure from that weekend which has been Correcting in recent weeks. So from a technical perspective with respect to the dolly and we have achieved the one thirty three ninety eight target So our next target on the downside now. We're looking for a test into one thirty two fifteen So I'm looking for any pullbacks initially into this one thirty six twenty watch a bearish reversal patterns there to engage on the short side But people have moved down towards one thirty two if the pullback extends I'd certainly be paying very close attention to any test of the one thirty seven seventy and Any reversal patterns from there would also be an opportunity to engage on the short side at this stage We really need to see a close through trend channel resistance coming in one thirty nine fifties to suggest a broader corrective phase to develop Down under in Australia we will get The Q3 current account balance On Tuesday looking for a six point two billion balance their trade surplus narrows after reaching record levels in Q2 of this year And then we will have the all-important RBA policy decision with the markets anticipating another rate rise tighten cycle continues responding to the inflation challenge looking for a three point one three point ten percent level on On Tuesday from the RBA policy decision and into Wednesday we get Q3 GDP looking for zero point seven percent print there Versus a zero point nine percent last time out domestic demand growth remains robust in In Australia and then into Thursday October trade patterns looking for twelve point one billion versus twelve point four last time Out another sizable surplus supported by the LNG export revenue We're also here from RBA assistant governor Jones speaking at an FIRN conference in Sydney on Thursday and that runs out the data Down under for this week in terms of the technical setup We have We've been training around this target zone that we have the 1676 770 broke out into the back end of last week. We're consolidating again What I'm looking for now is a test of this 6890 from there I'm looking for any pullbacks back into the trend channel support and the pivot here 6760s to Reengage on the long side and we are looking now for a test of the 70 level But weekly projected range resistance coming in just below there 69 95 and that concludes the weekly market outlook for week events in December the fifth as all the traders plan the trade trade the plan and most importantly manage all this Until next time. Thanks very much


Hei ychydigwyd. I'n dweud eich gweithio, eich gweithio'n dweud eich ddefnyddio'n gweithio'n fwy o'r ffordd o'i cwmwyllfa arlaeddol. Plwswch, fwy o'r cymwynt, fwy o'r cymwynt, a'r cymwynt mae'n bwysig o'r dweud o'i ddweud o'i ddefnyddio'n gweithio'n cymwynt o'i ddweud. A oedd yn fwy o'ch dweud o'i gweithio, mae'r ddeu llyth o'r ddweud o'i ddweud o'r ddweudio'n gweithio. If you are interested in one-on-one coaching, you can email me at nagsfevercoaching at humour.com How to neutralise the narcissist attacks. Narcists are dependent on your emotional reactions. They are dependent on your response to what they have said or done. When you are reacting to the narcissist, it starts off as a thought and then becomes a feeling which you express or an action. This is feeding the narcissist and regulating their emotions. It's giving them satisfaction or relief. When you engage or interact with a narcissist, they are only interested in getting you to react to them. They will plant the seed to cause an idea or feeling to be in your mind. Your thoughts are like water to the seed. Your thoughts allow the seed to grow. If you continue to think about what they have said or done, it will eventually produce a reaction. They know what they are doing and they know the reasons why they are doing it. They understand the effects that this is having on you, but they do not care. All they care about in that moment is getting a reaction out of you to regulate their emotions and give them satisfaction or relief. When the narcissist is trying to attack you, whether verbally or something that is more under the radar, you need to recognise it and then neutralise it immediately. Most of what the narcissist says to you are lies. Narciss or pathological liars. Most of what they say is thought out or planned before they even interact with you. Most of what they do is orchestrated. They have had years of practice and they know what they have to do or say to make people react. They know how to plan or coordinate the elements of a situation to produce the desired effect or the desired reaction from you. When the narcissist is trying to attack you, whether verbally or something that is more under the radar, you need to ask yourself, what are they trying to get me to do? This is when you should identify that they are trying to get you to react. This is all they really care about. They are hooked on your reaction to whatever they are saying or doing. They want you to react to them. Ask yourself, why are they saying this? Why are they doing this? Why are they displaying this to me? And then tell yourself that they are trying to get you to react. Remind yourself that this is what they are trying to do. That's all you really need to know. That's all you really need to understand. This is the only reason why they say what they say or do what they do. There is no other reason for it. Narcys are obsessed with control and dominance. They want to measure how much control they have over you. Your reaction lets them know that they are in control of you. It feeds them. It regulates their emotions and gives them satisfaction or relief. When you are watering the seeds with your thoughts. Watering the seeds that they have planted in your mind. You are giving them the ability to control you. Stop overanalyzing the situation and wondering why they said what they said. Or why they did what they did. And identify that everything they are saying or doing is designed to get you to react. Thank you for watching. I hope this video resonated with you. Please like, comment, share and subscribe. Click the bell icon to receive notifications for my future videos. We have a private Reddit community where survivors and frivers can share their experiences and knowledge. If you are interested in being a part of this community. You can sign up for our Patreon page. The link is in the video description. Check out the Narcys5EmojDice store. Where you can purchase your own Narcys5E t-shirt or mug. We have a variety of designs and it is a great way to support the channel. The link to our Narcys5EmojDice store is in the video description. Thank you for watching and I will talk to you soon.