Thanks, Eric. Again, we appreciate the gracious invitation to share and, as you say, extend our very collegial and collaborative partnership between our ICs, which we're looking forward to ongoing synergies and opportunity to get input from this, the expertise gathered in your council that complements and helps us in our directions just to outline a couple of things, how these programs fit into our overall portfolio of both scientific priorities and fiscal management, and then a couple of highlights about some interfaces and we'll throw in a couple other pieces where I'm hopeful that collectively we can think about and brainstorm and strategize about additional synergies and collaborations. I always sort of start with some guiding principles that relate to our NHLBI mission that kind of keeps us grounded in which a big part of our fiscal and strategic approach centers around investigator initiated fundamental discovery science really is the bedrock upon which we think about these particular institute solicited and initiated sort of large programmatic efforts and our ongoing efforts to maintain a balanced portfolio that spans basic translational clinical and population science and how this, again, fits into those enduring principles and a key sort of sacrosanct element that I always use as a touchstone is the integration of training a diverse new generation of leaders of science as part of this and again relevant to our collaborative efforts in this genomics and data science space that we're exploring and then probably actually more relevant to you on this particular point about implementation science in some sense I guess kind of what you do with CSER and insight and thinking about how this technology and our findings and our new knowledge actually penetrates to in a very pragmatic but strategic and evidence-based way into practice that influences how patients are cared for and has public health impact and I think that's that grounding that both our institutes need to continue to put forward such that we're always connecting with the public and the public impact of the discoveries that we fund and then finally a passion of mine to innovate an evidence-based elimination of health inequities which again still stirs stases of backdrop and I think is still very relevant quite frankly to the programs we're pursuing now. Just as a brief overview, certainly this council is familiar with the trials and tribulations that relate to our budget but this just goes to show some of the things that we've been doing in our multi-year perspective modeling to try to again bend the curve in promoting investigative initiated discovery science, particularly R01 funded research at our institute in which we're trying to eek up that pay line despite fiscal constraints and we're making some headway obviously facilitated by the boost up of the two billion dollars from FY16 and I guess we remain hopeful Eric as to what Congress may do in the selection year but given the unpredictability of that I'll stay away that from that in a public session but as we think about those strategies one of the elements has been a strategic planning or what we call strategic visioning process we've been embarked on for last year and a half or so to help provide greater framing and focus and strategic guidance on our institute solicitation and institute major programs that fall into these four major broad goal areas around understanding human biology reducing the impact of disease promoting translation from early to late implementation science and and then our stewardship of the workforce and resources and it was a sort of a typical process for NHLBI that use crowd sourcing and solicited from all 50 states and 42 countries around the world to help us think about what are the most compelling questions and critical challenges we should develop and indeed we're encouraged by the response we got relevant to the presentation today there were a number of things that over the course of time came in that aligned very much with a direction that I know Eric's been pursuing since your strategic plan from several years ago in the genomic medicine space and where we've been talking along since I arrived I see a convergence in this space that was really also bubbled up in the strategic visioning process around the opportunities that exist in precision medicine within our portfolio and a sense from our community that we need to leverage these new technologies for understanding individual factors that account for variances and treatment and response as strategies for both prevention treatment and incorporating that into our research agenda such that we can be more effective at predicting outcomes tailoring treatments refining our approach to clinical trials and really extending the scale scope and depth of our population science. There are some challenges that come from considering how we might implement this related to some elements of how we have typically collected data on a R01 by R01 or grant by grant or even cohort by cohort basis over the decades and where these things often remain behind isolated firewalls and yet the increasing explosion of data that we are seeing some of which are two institutes have catalyzed together particularly with all the sequencing efforts of late that particularly the whole genome sequencing efforts and the fragmentation of that data generation and accessibility and utility in moving those sorts of data sets around and so we certainly look forward to ongoing partnership with genome around some of these areas of open science and how we can get more facile and nimble data integration and movement across data set data sets that we're both are both our institutes are generating similarly again this theme of training and leveraging advances in data science and inviting them into the biomedical arena and vice versa and the opportunities that exist for our collaboration and synergies in that space and as a organ disease based institute a call out for for lack of a better term perhaps a human phenome project in which we say as a clinician scientist hope that our our phenomics catches up with our genomics technology and and and that we seize this opportunity to refine basically the clinical taxonomy that we all kind of grew up with it a much deeper and more fundamental way and I think we've gotten quite a a tailwind provided by the the president and his vision for a precision medicine which I think gave us both a boost certainly Eric and I were shoulder and shoulder in the implementation of trying to go from what a statement in February to a rollout of projects here this fall at the speed of light it seemed like at periods of time for the government to move but indeed removing and making progress and great that Eric Dishman is both here and on board and we'll detail a lot of that for you we we're excited by the opportunity that comes from a space in which folks like a terminole you'll have been around NHL BI has been having these iconic longitudinal community based cohort studies that have collected data and really set a paradigm for so many years on the ability to predict who's at risk of a heart attack and identified things like risk factors and now to overlay the the greater depth of data that we now can put together to maybe hopefully refine that original framing man risk score which helped me Terry probably hasn't changed in about 30 years hopefully we'll we'll get something that can can beat it out and it's in predictive value now we have all this data at least that's the promise let's see if we can actually bring it to fruition and hopefully one of those elements is that the ability to create resources that facilitate the more effective mining of that data the scaling of that data in ways that we can think about it as a broader resource a data commons if you will a shared resource of a virtual public good something that I think the NIH should be involved as a steward in creating that serves for knowledge generation innovation scientific advances as a sort of living ecosystem one in which there's a communal space that engages people from variety of disciplines and perspectives toward asking and answering important questions and that's open and one in which whether you're a participant in a cohort or a member of council that you can gain from those insights and be engaged so this is the vision that I think is starting to emerge I think certainly Eric and I share some of these things and are engaged internally with discussions about you know how NIH probably should be positioned to kind of create this kind of discovery sandbox of these data and data sets in a responsible way that obviously honors privacy and controlled access restrictions but as we look at the future we see the potential particularly in the HLBI space of reimagining clinical research that aligns with our mission as we know it enabling rich data collection it facilitates cohorts of some phenotypes of interest like early onset MI new onset HL for belation hypertension even monogenic disorders like sickle cell disease and potential modifiers asthma COPD etc and apply deep analytics to predict disease risk and identify novel molecular pathobiological mediators and for that to then translate into a space of launching clinical trials with predetermined eligibility predictive risk profiles and embedded long-term follow-up perhaps in existing health systems and again related to emerge and Caesar and ignited can't keep up with all your acronyms but I think there's opportunities as you do these proof of principles that the disease-based ICs can can learn and again will continue to work together toward this convergent vision certainly for us part of advancing into the space is to leverage the class cohorts that we've had and to contemplate a transomic approach for precision medicine our top med program to link the deep phenotyping characterization of heart lung blood sleep phenotypes in our cohorts with the multi-level omics that this Institute has been at the forefront in creating the techniques and technologies and approaches to and I think it's again an opportunity for synergy and partnership where we can continue to hopefully push the envelope and how to to really expand and extend these genomic phenomic analyses at a larger and larger scale and I'm sure Adam will get into the potential collaborative synergies that have come through your complex trait program but there have been some piloting if you will of this approach of linking the multiple layers of things that are happening at the epigenome the transcriptome and and DNA level even in Framingham work that Dan Levy's done even the space of our hypertension phenotype and looking at the multiple layers of omics to start to identify networks and potential mediators that otherwise we may have missed through any one approach alone taking the system strategy and so we're hoping that the top med can continue to extend this beyond a single cohort but leverage the various cohorts of over 100,000 actually a couple hundred thousand individuals that currently have been characterized and for whom we have a number of these biospecimens within the NHLBI portfolio such that we take advantage of these phenotypes and indeed continue to expand them perhaps with personal sensor data information continue to layer the omics and extend beyond just sort of the genic GWAS genotyping that's already been done for over a decade and continue to use the various modalities inclusive of metabolomics microbiome and other elements in ways that builds out our capacity to characterize the determinants of heart, lung, blood, sleep disorders and then to put this data in a space that promotes greater antelope new antelope methods and approaches and it happens in a space that is again communal in bringing together expertise that might reside clearly outside of heart, lung, blood, speed, sleep specialists and in that regard I was aware of this paper that I thought was apropos of this dialogue with this Institute and actually some of the statements made earlier about how we can work together as we develop these data sets of paper that Isaac Cohane's group put out that related to genetic misdiagnosis and a potential for health disparities in which in the case of hypertrophic cardiopathy one of the entities in our portfolio leaders like cricket Sideman at all have provided a great understanding of in terms of sarcomeric defects that now when that rolls out to patient care that unfortunately often reflects of the sort of skewed distribution and frankly your centric nature of a lot of the studies and genomic resources can be problematic when these data and knowledge are brought to bear in African-American patients and the potential to misclassify something as benign or pathogenic without really the evidence base to do so particularly given again that the different allele frequencies in the very cross various ancestral groups and really I think a call out to us to ensure that as the NIH fulfills this mission to turn discovery science and the health of the nation that we create resources they're reflective of the diversity of our great nation and to be explicit about it that's something we've been fairly intentional about in top mid as we've partnered with genome and a number of the sequencing centers to ensure that we really take this opportunity to expand that diversity of populations in which we we start to understand the whole spectrum of genomic variation and not not solely in some narrow sense of political correctness but as a matter of understanding the human family and understanding population histories and and how those have an influence on predispositions to health and disease I think it's a fundamentally a scientific issue not only a matter of doing the right thing so to speak and so far we've been diligent and and quite frankly leverage the legacy of the HLBI has had of having diverse cohorts where there's Jackson heart study strong heart study of Native Americans the multi-ethnic gross study that has captured these groups as well as the various other investigator initiated cohorts so in addition to that diversity seen on the right we also have one across the various phenotypes of heart lung blood and sleep complex traits and again I think this is where we have a lot of synergistic opportunities with what genome's been doing I'm also hopeful that we we start to think about how we can more effectively promote access to these different data types data elements and data sources to ask and answer fundamental questions typically these multi-dimensional data sets and creating that discovery sandbox where all that can come together it's obviously not a trivial matter but we're we're also hopeful that we can work with genome that quite frankly has created a number of these data resources to think about how we promote and enable and facilitate a more seamless integrative analytical strategy that is less encumbered by what is traditionally been kind of an upload download sort of world of data use and and one that can potentially leverage the capabilities of cloud computing where we move and go to the data go to tools that are accessible and as ways to again promote discovery science in this regard I was again intrigued by this a recent paper I came out of star net but again looked at heart lung blood sleep phenotypes in this case the cardiometabolic risk loci and leveraged not only sort of GWAS data but obviously tissue expression data and did that in a way that aligned the GWAS hits eqtl's with CIS trans regulatory pathways and identification of networks to get some further insights into determinants of certain outcomes and so it is always kind of reaffirming that intuitively it kind of makes sense that you might discover not only loss of function gain of function for PCSK 9 but that there might indeed be energetic regulatory regions that were identified that again are important in modulating LDL and risk and indeed are now drug targets for new therapeutic and so to me these are some of the elements of bringing those data sets seamlessly together I think we could probably facilitate in a more user-friendly way than then currently exists and I'm hoping that a data commons kind of concept helps make that more likely to occur similarly this paper that Eric shot was part of and certainly he presented some of this so when he visit us at our last council meeting talking about the work that he had done on this case in childhood diseases and the notion of resilience and a human knockout resource and as we contemplate top med that can leverage existing cohorts where we're hopeful to have whole genome sequencing with a goal at least a hundred thousand individuals and Eric will talk about or D will talk about PMI of a million plus and we already have colleagues at the VA with MVP that soon will have the kind of information in which we should be able to understand that that same example of a misdiagnosis of all those sarcomeric genes to really know that it was that really benign not just on allele frequency but what's the echo MRI and EKG of that variant of at least perhaps hundred people 150 people over the age of 60 so that when we're you are counseling that individual 25 what's the likelihood that they'll have a long QT and sudden death or hypertrophic cardiomyopathy with a little bit more evidence base and creating that capability as I think something that we'd love to see and work with genome to create and so we're starting to see this notion of bring together these multiple layers and levels of data all of which NIH has already invested in but making it not a series of one-off projects and programs but something that indeed can become synthesized integrated in a seamless digital way such that those who are great phenotypers as well as those who are great genomicists can leverage it in a way that have an impact on patients and participants and it's really with that notion that we look forward to synergies and partnership with NHGRI in helping us fulfill those shared visions and purposes and be happy to address any questions or hear any comments and feedback you may have for us thank you for your attention questions yes thank you for that presentation a number of the issues that you touched on have significant ethical social implications to them one of the innovative aspects of NHGRI has been that set aside for LC research and I'm wondering whether NHLBI has ever considered anything that would be analogous or perhaps collaboration with NHLBI on that set of issues where there's some synergy yeah that's a great point again I agree with you I think that's a terrific opportunity for collaborative synergy particularly given genomes long-track record history domain expertise in that space in the sense that a lot of these things are cross-cutting makes more sense to do that as opposed to a disease or organ basis and we look forward to that top med does include on its external panel actually some of the folks around the this table and you know at that they're in that space whether it's a Wiley Burke or Ellen Clayton and others who are thinking about those so definitely an area of interest of ours and quite frankly in one of the areas that we would love even more interchange relates to one of the cohorts that I mentioned the strong heart study and Native American populations and and so the first nation is is a an area of interest and priority I was intrigued Eric that you talked about some of the outreach efforts you've had in that space I think that's a another area where it makes sense for NIH in a collaborative and joint way in a very coherent single voice way to think about how how we address that very thoughtfully so absolutely totally agree with you there so thank you for the presentation I I really like the the vision and the way you presented this idea of this data sandbox or for mining but I noticed that one of the inputs into that sandbox wasn't information we can learn about the connection between genotype and phenotype and model organisms and how that can actually help inform our understanding of biology of variants in humans both in health and disease and so I'm wondering if that's part of your vision and how you if you want to make any comments on that as well yeah so it's a great point I definitely would agree that that sort of comparative genomic element that evolutionary perspective if you will in some ways is consistent with sort of a population history appreciation of things and I'll defer to another day and really to Eric that I think that's one of the areas that we've been in internal dialogue about clearly genome is played a leading role in a lot of sequencing across species and I agree with you there's a wealth of information there that I think would fit very well within the data comments you should be able to to look at a variant and and we're I don't know an enhancer region and be able to understand it not only across human population but across species in a very seamless sort of way with the phenotypes that they've been derived from a zebrafish as well as from a human being and certainly I think all of that's informative and understanding a molecular pathobiology of disease absolutely Gary I'm really glad that you highlighted that paper from the Harvard group on the hypertrophic cardiomyopathy and this really vicious cycle of having SES lower SES and ethnic background mixed together resulting in less genetic testing less research less information which means therefore it's less useful to them and it's just so I think we have to break that cycle quite deliberately and specifically so I mean for example I'm thinking particularly of a resource like ClinVar which is relying very heavily on clinical laboratory testing which is being paid for and is not open because of how poorly served underserved populations are by our insurance system and by a whole variety of other systems to be able to get access to this testing so I think we have to break the cycle quite specifically and deliberately yeah that's all I could say is amen brother um eric borwinkel on the phone has a question you know it's a great comment and erica you're pretty adept at having multiple ICs that support you so if there's anyone who knows the answer to that question it's you but but in all seriousness I think that's one of the opportunities we have with top med is eric used the term sort of prototype some might call us the canaries in the coal mine that I think we can probe and see how this this model is working obviously eric has done this throughout you know his tenure as did francis that I think in this space it it's only makes sense to do this as partnerships it's been clear from a lot of the queries that you've already had that the potentials are for the synergy with all the other resources that this institute has created so to me it's a no-brainer and and and to a certain extent as you know eric it may derive from the fact that the cohorts also have had that sort of approach so as you're aware NIA and aging and and dementia research leverages these same cohorts same true for kidney disease same for at least the pre-diabetic population that has outcomes as we scale these things I think it becomes almost self-evident that the other ICs need to play in the same sandbox and contribute to its ability to go across it'll be a win-win for everybody and that's where I think the data comments can help promote that as opposed to a series of IC specific one-offs and and that's where I'm hoping I think eric shares this we hope that we can create this as an enterprise approach let me answer I'm going to go to Sharon and then Dan but let me I have a direct question that relates to what there's a lot of ericsson the borewinkle just said and it relates to what dishman is going to talk about this afternoon Gary what I was going to ask and just say answer whatever you're comfortable with because recognize an open session and you and I are both individually recognizing that that how the institutes synergize and connect with this evolving precision medicine initiative is a lot of uncertainty but we're all thinking about it but relating to borewinkle's question do you so there's two parts one what is NHLBI thinking about at the moment how they're going to take a program like top med and synergize it with the precision medicine initiative and then second question is will that be an organizational framework to address what borewinkle just asked with I mean will will that become a place that more institutes will gather to figure out how to do the kind of studies that our institutes are comfortable with and I don't know the answer but I'm just curious you know I thought I both of those questions you know I I think we as both ICs and quite frankly with Eric D in play now in place I think we've at least had some preliminary discussions that PMI as you know was initiated as really a disease agnostic platform and so I think it then and and it's making important advances in that space I think the the it's it's fullest potential I would say though relates to not only be being a disease agnostic platform but being able to link to ICs to ask specific questions that are clearly more phenotypes disease specific so I believe and I have to defer to Eric uh that it'll be the synergies of those that that that will be important and so I agree with you that's on a opportune place of convergence I think for ICs around PMI certainly speaking for the NHLBI it's hard to conceive of health systems coming up with even a half million people where heart-long blood sleep phenotypes aren't going to be very common by definition and so I'm hopeful that there are things quite frankly this institute has done probably with Emerge and some of the others where there are EMR phenotypes that we can do a deep dive on in PMI as it matures that we can ask at a scale that I probably can't do through the community-based cohorts and that I think could complement what we're going to have in top mid so that would be my hope speculation and I think it's a win-win with what Eric Dishman wants to do with PMI. From my perspective a lot of this is just going to be dependent on timing you know I mean the sooner it is that there's things there that we can that the precision medicine issue that we can build a project on people will be there I mean I think people be there in a disease specific way people will be in a technology or fundamental questions we have around genomic medicine implementation a lot's going to depend on what the timing looks like okay so Sharon and then Dan. Thank you for the presentation to just follow up I think on one of the early questions one of the things that NHGRI is now doing is really looking at the return of results of genomic results to a number of subjects in a variety of these different consortia and I was wondering given really the scope of sequencing that's going on funded by NHLBI are some of these projects returning specific results and is there a group looking at that which again could perhaps synergize with some of the NHGRI consortia. Yeah so again another great point one where clear synergy has to happen where again this institute has thought about it long and hard and we'd want to lean in to that domain expertise and understanding I would certainly agree how can I put this that there are opportunities to get a strategy on this that top med brings to the surface you can imagine that was a hodgepodge of studies and cohorts we actually lack a coherent way of doing this and so even though we're generating all this data I'm not so sure that there is a coherence across all those studies and I think again there's an opportunity for NHGRI to provide some trans NIH leadership and helping us do this in a thoughtful way and clearly you guys have been thinking about it for a long time so we look forward to that collaboration. So thank you again Gary for that summary. I guess I have three sort of pretty specific questions just sort of to clarify or to help us think about so how do we can all work together better one is do you have a timeline for when when you know an initial set of results might come out of this because I think the the public is getting a little tired of the promise of genomics and and it would be lovely to and I you know I say that because there's a big investment we all know that there is progress but if you have a timeline for this that was question one the question the second question was among the cohorts that that you've accrued some of which are ours thank you do you have a sense of of how broadly phenotype they are so you know in an ideal world they would have phenotypes beyond heart lung blood and sleep but they would also have cancer phenotypes they would have eye phenotypes they would have mental disease phenotypes and some of them will have some of that and and to the extent that they do that that would be really interesting in terms of the kind of network diagram that you actually showed and then I had a third question I can't remember what it is okay but I think those those are the two are plenty yeah yeah given that both of us are over 50 I'm having trouble remembering your first over 50 that's that's trying to be charitable buddy friend but so two good points the second one first that I'd agree that that obviously these studies started off with a very hyper focus and heart lung blood sleep some of them even more hyper focused than that the the the cohorts over the years have been broad but it shouldn't speak out of school but you know even the cardiovascular ones probably could have thought about lung phenotypes better than they did and and and quite frankly given those are comorbidities some of our lung cohorts could have thought about cardiovascular phenotypes a little bit better in many ways this is an opportunity for us to to to get some greater coherence there as we mentioned with the other ICs to the degree to which they put skin in the game in the cohorts to extend that phenotyping again their synergies that I think they're things we could be doing in dimension indeed we're planning to do in dimension dementia whether Alzheimer's disease per se or related disorders they're already plans afoot to include more pet scanning for example in in our cohorts to to to tap into domain expertise in terms of dementia outcome so I agree with you this presses the issue that we need to extend beyond our classical uh phenotypic uh phenotyping regime um and I've already forgotten your first question was it was a timeline question and my third question yeah I want to avoid was the the top the oh and top med stands for omics but this is mostly genomics right now isn't that or am I not so we're so we're encouraging um trends and and obviously we went with the technology that's you know ripe and ready to go but the intent is actually built in that as um you know ability to characterize DNA methylation continues to expand or any other epigenomic analyses that scale um we're we're interested so so it's already built in that we'll be looking at that and certainly RNA seek is uh to the extent we can extrapolate from blood you know but so so we want to pursue those as the scientific question makes sense absolutely uh timeline is tough um you know um so so when are you going to discover all the variations of you know long qt and and you know it it comes back to you uh about how quick you can discover things obviously we're hoping if we get to 60 000 whole genomes we'll have a sense of you know whether this is a strategy that we double down on or not and that's almost a matter of a pipeline issue and an analysis issue is anything and as you know we have built in a lot of traits already that you'd think should yield us some information in a relative short term that's we're hoping and quite frankly in collaboration with genome Eric it's okay it's public as to what phenotypes you're starting with or no yeah so so yeah so so those are you know cardiovascular you know phenotypes and so I think there's a lot of again uh complementarity uh that we we hopefully will we'll learn some things about certainly the early in my one I'm intrigued on because if we get a non-lippid I you know I'd kiss you Dan uh Gail please change the subject no no I I'm expecting the same response although I can't offer that kind of science but I I do have a question and and I first of all thank you for coming um really interesting um I had a question about when you talk about your cohorts whether they're all already collected and whether they are existing in one space whether they're um the data from them have been deposited in dbGaP or or whether there are some things that so you're gonna you're gonna go back to some of the cohorts and ask for additional permission to do uh you know additional um both data and and genome testing so and so that sorry it seems like a really fundamental question you might have already covered it but you know it is uh important one and actually it does have some challenging nuances to it that um so so all dbGaP um to get into top mid um there was screening of the consents to to to make sure that they were uh pretty compliant and and we actually had a screen out a lot of things that uh wouldn't make the grade but that being said um as you this institute has been exploring um you know the the whole genome sequencing data set and whether that aligns with what was contemplated in a consent you know from 10 years ago even as broad as it may have been it one could make the case that that's something we continually need to think about the consent supposed to be a living process and so I appreciated the LC a component I think those are things we have to continually bring to to bear and so uh we're open and again I think it's a point of collaborative synergy to think about if you start to put this stuff in a cloud um what what do we need to do to to make sure we're doing that responsibly uh and consistent with the participant wishes and consent so I still think there's a lot more to be explored and refined okay I think on the issue of time maybe we'll get Adam Felsenfeld to come to the podium um and in a very complimentary talk that we scheduled deliberately after Gary's to describe the opportunities for synergy between our genome sequencing program and the top med program that you just heard about and again I think at the end of Adam's presentation there'll be more time to talk more specifically about those connections


So remember, you can get most things you want out of life, but don't take one or two years longer than you expected. Be patient. And that patience is one of the most rare ingredients found in this modern world. Almost everybody I meet, and I see this on TikTok, people posting their journey to financial success. In January, I was working at McDonald's, having a hard life. In February, I quit. In March, I launched my business. In April, here I am, and they show all these videos of them in Dubai or in a private jet. I'm going, a four month journey ain't a real journey. Nobody made money in four years. Money's made with blood, sweat, and tears. I had a friend, he said, he added, he said, most wealth in this world is created with blood, sweat, and violence. So depending on who you ask, it's one of those formulas. And nothing big comes from four months. In fact, if you look at the science, for example, of people who win the lottery, the average person who wins the lottery is dead broke again in two to five years. You see this in professional athletes, people who didn't grow up learning the fundamentals and the foundations of wealth. I call those the 300 foundations. When you don't learn those 300 foundations, frameworks you could call them. The average pro athlete, like an NFL football player, they come from nothing and all of a sudden, but they didn't learn the 300 frameworks of wealth. At those one, two, three, four, or five million, the average NFL player is broke again in two years. Now, some of that is from the training side, not learning. Our school system doesn't teach you, but the second aspect of that comes from a lack of patience, meaning you make your first million dollars, and now you've tasted wealth so you're like, I'm going to make a hundred million and it only took me three years to make a first million. I bet you I can make a hundred million and now I'm better, now it'll only take me two years. That's not how the game goes. In fact, if you look at log diminishing returns, it's kind of like when you're out of shape, it's easy to learn you lose your first 20 pounds of fat or 30 pounds or 40 pounds. But when you get lean to optimize that next step takes tremendous patience. You can get what you want out of life, most things, but it'll take you one, two, maybe 10 years longer than you think. And I remember being 19 years old and my second mentor, Alan Nation, said to me, he said, tie. The average millionaire, real millionaire. I'm not talking about crypto flash millionaire. I'm not talking about an NFT flash millionaire.  He said to me, real millionaires take 12 to 20 years. The average real millionaire, multi-millionaire that keeps their money takes 12 to 20 years. And I remember being 19 and going, I'm not going to wait 12 to 20 years. And sure, you can shorten that learning curve, but think about this way. That same mentor Alan Nation said, look, Ty, success building a business, creating money, it's a little bit like having a child. At the beginning, it's a lot of work, keeps you up all night. It's like a baby. Then it reaches kind of the toddler stage.  Then it starts to grow up, it becomes, you know, preteen teenager. At that stage, they're good to go on their own for a day or two, but you better keep your eye on the ball. And he said, if you wait long enough, that baby, that success you created, long enough, it'll eventually take care of you when you're old. And I remember thinking, that's a good analogy, but I don't want to wait. It takes whatever, 18 to 21 years for an adult to mature. I'm like, if that's the metaphor for wealth, I don't want to wait 18 to 21 years. And he said to me, well, Ty, I was like, I'm just going to work harder and smarter. And then I can make it all the first year. And he said, well, what happens if you overfeed a baby? Can you make it grow twice as fast by feeding it twice as fast? Can you make a baby grow 10 times faster by feeding it 10 times a calorie?  And so a lot of people, because they don't have patience, they don't understand the cadence of wealth creation. Even somebody like the first internet billionaires, Bill Gates started at 12, building his first computers. He was a, you know, a multi-billionaire, 20s and early 30s. That's a solid 10 to 20 years.  It took a while, he's the richest person in the world. I remember reading, you know, he started PayPal at 01, made some money, made solid money. I think his cut, he says, was under 150 million. Reinvest, that was like 01, 02, 03. And he's the richest man on the world in 2021. But he's a patient man. And that's what I said, you can get most things you want out of life. But it's going to take one, two years longer than you expect, maybe a decade. And you can't just feed the baby more to try to speed it up. But let's talk about, for those of you impatient people watching this, you might say, well, I just don't have the time, I'm not going to do that. Well, you're probably going to be poor. But let's say you want to try to break the natural laws of this universe and you want to feed the baby so that instead of 21 years or 18 years to grow up, you may get, you know, happen in eight years. How do you half the learning curve? How can you work half as hard and get twice the results? I'm okay with that framework. I'm not okay with cutting the framework, you know, 100X. I'm not, I don't like these Insta-TikTok reels where it's like, my McDonald's journey in January, I quit my job Tuesday. I'm, you know, January I'm broke, working at McDonald's. Friday, February, I quit my job. March, I launched my business. April, I'm traveling in jets and Lambos in Dubai, you know, and I never taught people that. That wasn't from me. Some people go, Ty, didn't you teach people to get rich? I'm like, did you ever listen to one iota of what I said?  Yes, they'll say what you taught without ever listening to what you taught. I always, I've been talking about this 12 to 20 year framework from when I started in social media back in like 2010, 11, 12. It's the same message. Now, of course, I show the Lamborghini. Why? Because people need to see the end game to stay motivated through the dark years. They call those the 10 dark years. Most greatness, whether it's a Bach, a Botticelli, a Leonardo da Vinci, a Nikolai Tesla, an Elon Musk, they had the 10 dark years. Now, of course, the TikTok age, everybody wants to be the 10 week darkie. I had my 10 dark weeks. Well, the laws of the universe haven't changed and the frameworks of wealth haven't changed. So my advice to you is very simple here. How do you cut it in half? That's about the best you can do. Give you three simple ways to cut the learning curve. So you'll still need patience, but maybe not quite as much. Well, number one rule is what Warren Buffett says. It's true you only learn through mistakes, but there's no rule the mistakes have to be your own. You only learn through mistakes, but there's no rule the mistakes have to be your own, meaning learn from the mistakes of others. Read biographies and autobiographies. The business books I read are not just, I'm not just doing it to be able to say I read a book a day, it's going, so in a 500 page book or a four hour audio book, I'm condensing the life history of somebody. All their mistakes, yeah, it's true you only learn from mistakes, but there's no rule they have to be your own. Read a book, listen to a book that condenses the mistakes and the learning curve of somebody who's spent 40 years doing it right and doing it wrong, cut what didn't work and keep the rest.  And you can do audio if you think you're to whatever ADD to read. Number two, don't get high on your own supply, meaning use social media, but don't have it used against you. The second you're consuming one to two hours a day of reels and TikToks, like how are you going to cut your learning curve?  So I use social media, I put messages out. It creates revenue for me, but I don't consume it much. Be careful what you're consuming if you want to build wealth in half the time it takes the average person. Be careful what you're consuming. That also goes with food, but we'll stick with the media side of things. So then the third thing is shadow, shadow, shadow. Why did I say it three times? Shadow three people for a year who have already gotten what you want and are 20 years ahead of you. Think it through, it'll be harder than you think, but it'll also be at the same time easier than you think. Humans don't learn through school as much as people think. You know how you mostly learn? You shadowed kids who were your peers. Most kids growing up, it's their peer group. It's their teacher's body language, how they talk, the things they don't do. It's not actually the textbook itself and the lecture on the chalkboard. So shadow, shadow, shadow, one person, two people, three people. You want to get into real estate? One of my mentors, he made $2 billion, did mobile home. One of the biggest mobile home real estate developers slash investors. He told me when he was a teenager, back in the 70s, he's an older guy now. He said, Ty, I lived in Virginia and I found, I asked around, who's the richest real estate person? And he said, I was 16 years old and I went in this guy's elevator. I found out where his office was and I kept going, took the elevator, went to the third floor, met the secretary. Hi, I'm 16, I'd like to learn real estate. I'd like to shadow the owner of this real estate investors business. And the secretary nicely said, sorry, he's busy right now. And he went three times, same thing. He went for months, he wouldn't come back every day, come once a month. Finally, he went and he hid behind the plant. He told me, he said, Ty, I hid behind the plant next to the elevator. I knew he came in and I knew that secretary was keeping me from meeting him. And he said, as the guy got in the elevator, I came from around the plant, got in the elevator with him. I knew I had three little floors. I had 10 seconds to pitch him, my elevator speech. And he told him, he said, hey, I'm 16. You don't know who I am, but I'd love to learn from you and I'll do it. I'll do, I'll get you donuts, I'll get you coffee. I'll travel with you, I'll do the grunt work, the boring stuff. If you'll just teach me what you know. And the guy took him under his wing. And he said, before he was 18 years old, he was making so much money. His parents did an intervention because they found his bank account and thought he was doing something illegal like selling drugs. And he said he was making, this is in the 70s. So he was making like $200,000 a year while he was in high school. Because he would help this guy go on the weekends. And the guy started getting little pieces of real estate deals. 200,000 in the 70s when you're 16 or 17 is like making two, three million bucks a year in today's buying power. Shadow, shadow, shadow. And if one person that you want to shadow you won't say yes, move on, there's a lot of people. But you need an in-person person ideally. Not everything can be done on Zoom, Google and YouTube. There's nothing wrong with Zoom. You could make one of those three mentors that you shadow could be online. But I'd have two of them in person. I have people that I shadow as much as I can. Some of them are billionaires. I just posted on my Instagram, I was in Texas and I texted Tom and Fertitta, the owner of the Houston Rockets, multi-billionaire, owns the Golden Nugget Hotels, owns 500 restaurants, you know. And I hadn't seen him in a while because of this whole COVID thing. So I texted him, I said, hey, can I come? And sure enough, he's like, I got 30 minutes and I showed up there. That's in-person shadowing, you know. It was last minute, so I couldn't find, there's no way to fly. So I drove three hours just to be there. I'm willing to put in what it takes to shadow people that are ahead of me. And as you become more successful, it's going to be harder to find them. The good news about being broke is it's not that hard to find shadow, shadow, shadow, three people to shadow, because everybody's ahead of you, basically, in the business world. So you can get what you want out of life. Most of the things will take one or two years longer to start working. Listen carefully. I didn't say you will get it in one to two years. You could get most things you want out of life, but it will take one to two years longer than you expected. Be patient, because in one to two years, it's not going to be done. You're not going to have everything you want, but the ball will start to roll. And the hard part of life, it's like a boulder.     Now it's not that hard anymore. Now maybe that top is for a little while. They call it the plateau. Keep pushing. Because eventually that boulder begins to roll on its own and gets real easy and you can sit back and relax. And what you want begins to come to you faster and faster with less and less effort. That's how money works. Doesn't they say the rich get richer? Of course the rich get richer. Because once that ball is pushed up the hill, just a little tap starts to bring the wealth in. That hard part is the push. That's the ten dark years. And even harder sometimes is the top of the hill where it's a ridge and it's a plateau and you're still pushing but now you're not going up or down and you don't even know what's going on. Those are part of the dark years. Be patient. Patience is rewarded eventually almost always. Like Charlie Munger said, to get what you want and life you have to deserve what you want.   So remember what the great Charlie Munger said, to get what you want, you have to deserve what you want.  You may think that a whole bunch of undeserving people create wealth. And there's always exceptions to the rule. But the saying continues, go to bed a little wiser than you were the day before. Step by step you get ahead, not necessarily in fast spurts. But you prepare for that fast spur through patience, train the mind. Everybody trains the mind. You got crossfit, you got weight, you have cardio, you have high intensity. Where's the training for the mind? Where are the people who are doing patience training? People do intermittent fasting. That was great. What about intermittent fasting of the brain? Where you're not addicted to dopamine, you're addicted or begin to readjust the brain to be addicted to the slow patience that it takes to get what you want. So good luck out there. What you want is probably a year or two away from happening. But it'll be almost in a snap of the fingers when you look back. It's hard going forward. You'll realize it wasn't so hard when you look back.


The resource and admission control function is a service provided by the next-gen network architecture to serve both the transport stratum and the service stratum, comprises certain network elements, and it has certain distributed nature. The deployment designs and options that we can have has a direct impact on the kind of services that we can get, the administrative control that we can obtain and the interoperability we can get between the policy decision and policy enforcement functional entities. We'll first understand the need to have such variety in deployment and then we'd look at the deployment architectures themselves. The modules in the RACF are basically the functional entities which perform specific tasks to realize the QoS provisioning. Now they also have a relationship between the service and transport stratum entities. The RACF performs QoS provisioning either in conjunction with the service control function or without the incorporation of the service control function. This leads to three options that can be considered as different deployment architectures. The first one is when the service control function is involved as an intermediary. The second one is the RACF performs QoS control without the intermediation of the SCF. And the third one is RACF is now common both for the access and core networks. So we'd look at the diagrams then we are going to understand them in detail. Let's look at the scenario where the resource and admission control function is performed by the intermediation of the service control function. So here we see we have the service stratum including the SCF it is being shown to you here. At the transport stratum we have the RACF. The RACFs of the core and access networks are talking to each other via SCF. It means the QoS control is actually being dictated through the involvement of the SCF. What are the pros and cons? Let's look at them. Since the access and core networks are separate domains. So as such within the RACF the policy decision functional entities of the core and the access networks are not going to communicate with each other. Only indirect communication is possible through the service control function. It actually means all the signaling which are performed for QoS control is coming via the service stratum functions. It means the application layer is spelling out its QoS functional requirements. And then the SCF is dictating the RACF to mediate between the core and access networks. The second option is when there is no mediation between the two RACFs through SCF. And these RACFs both for the access and core network are managed independently and they communicate with each other directly. It means the signaling for QoS control takes place between the two RACFs. The service control function in this case is now the scope of the core network and as such it is not communicating with the access network. That is exactly what is mentioned in here that the access and core networks are independent domains. Each domain has its own RACF. These RACFs communicate with each other correspondingly. Their PDFs are going to talk to each other and there's no involvement of SCF in intermediation as such. And then the last option is once we have a single administrative control both for the core network as well as the access network. In that case we are not going to see much involvement of SCF. In fact the RACF with single administrative control actually results into more smooth and harmonious interaction of the PDFs both for the access and core networks. Since the PDFs are part of the RACF. So as such we are not going to see two PDFs and there's just going to be one PDF. But the interesting thing is for these PDFs to implement the policies we need the Policy Enforcement Functional Entity. Now the Policy Enforcement Functional Entity actually exercises the policy or enforces the policy in relation with the Transport Radio Control Functional Entity. Now the TRCFE actually is going to be different for the access and core networks because it is dependent upon the underlying technology.


Hi, I'm Shane Harris with the Alderman Corp. Extension System. It's officially a Zaya season.  So what do you do with the Zayas once you've supposedly bought them or you brought some home for the new landscape? Today we're gonna show you how to plant those Zayas. When it comes to site selection on your new Zaya, you need to take a lot of time to look where you're gonna wanna put this particular plant. Does it need to be near the house? Does it need to be more of a natural area? You wanna give it room to grow. Zayas prefer filter sun and afternoon shade. In other words, they would prefer morning sun maybe more shade in the afternoon. They will tolerate sun, but they can get very hot in the summertime. Also look for an area that's gonna be well-drained. Zayas prefer well-drained soil but cannot have any wet feet. So an area that provides filter sun maybe under pine trees, just a few hardwoods, maybe an open area that gives a plenty of sun in the morning and afternoon shade when it's hot this summer is gonna be ideal. Zayas should be grouped together based on color or variety and spaced properly around three to four feet apart depending on the maturity size. Now let's put the Zaya in the ground. The planting holes should be no deeper than the depth of the container it came in, but at least twice as wide to allow the proper root development. One common mistake is playing the Zayas too deep in the ground. Adjust the depth of the planting hole by adding more soil underneath the root ball or under the pot to get the correct height and depth. Remove the Zaya from the container and massage and loosen up the roots along the root ball. This allow those fibrous roots to grow out properly and keeping it from being pot bound while in the ground. A common horticulture saying with the Zayas is plant them high and they'll never die. You wanna be sure that the root ball is about one inch above the native soil level. This, again, if they're planted too deep, they will not survive. Before adding the native soil back into the planting hole and around the Zaya, it's a good idea to add a little bit organic matter into the native soil to have the best of both worlds. Common soil amendments would include compost or fine pine bark or the store bought soil amendment. Almost finished. Let's add the native soil and organic matter mixture back around the Zaya. Gently pushing it on each side and pressing downward so that root ball is covered and all air pockets are removed. Be sure not to bury the plant above the top of the root ball. Gently spread it out and firming the soil with your hands. Now add a layer of mulch around the plant. Choices could be pine straw or even pine bark. This is very critical for the first year of the Zaya as it will lose moisture since its roots are not fully established. This is very critical the first year to maintain that moisture in order to survive the hot summers. The last step is to give the Zaya a drink of water. You'll want to water the Zaya at least once a week depending on the amount of rainfall and how hot the summers may be. Again, spring planted Zayas will need at least one year for those roots to get well established. So again, be sure to water them throughout the year. Zayas are one of our prized southern landscape plants because they last so many years. For more information on Zayas and other home and garden information, visit us online at aces.edu or contact your local county extension office.


So my name is Sue, and I'm a caseworker with the Victim Service Unit at the Vancouver Police Department. And this is Luca, our trauma dog who's recently joined the unit. Luca is a three-year-old yellow lab who was trained by PADS. In the Victim Service Unit, we provide crisis intervention and emotional support to people who've been either victimized by a crime or have experienced a traumatic incident. We are always looking for innovative ways to enhance how we serve in our community. We thought long and hard about whether utilizing a trauma dog would be a valuable asset to our unit. And after deciding that yes, a dog would help us in our work, we then began the application process. After nearly two years, a lot of preliminary work and a commitment from the department, we were matched with a dog from PADS, and Luca joined our unit. Luca has joined our unit to assist us in providing that kind of support and stabilization to the clients that we meet with. Trauma dogs can have positive physiological impacts on stress and anxiety. Their presence can assist in lowering heart rate, high blood pressure, and also assist in stabilizing rapid and shallow breathing. Trauma dogs can also assist in diffusing extreme emotion. They can facilitate the healthy expression of emotion, particularly where clients may be in shock, grief-stricken, or traumatized. Trauma dogs can provide healthy, positive distraction in situations of crisis and trauma. Trauma dogs can also help to ground clients who may be anxious, agitated, or highly emotional. Trauma dogs can assist in providing a source of cathartic touch and the physical comfort that a client may need. So we're so happy to welcome Luca into the Victim Service Unit in the Vancouver Police Department. If you happen to see Luca and I around in the community, please feel free to say hello. We'd love to meet you.


Don't shoot the messenger. I'm just relaying the info YouTube team keep it clean. What's going on is saying Raven here with another video within this video today Shout out to South Florida not just Florida, but South Florida We love all of Florida now, but South Florida was special because it was a South Florida takeover for Raven's press conference today First up we had missed the seven pounds lighter. Maybe it was all the hair I think that's exactly what it was. He cut his hair and then he's like, hey, I lost seven pounds That's where all them seven pounds was at Willie. We already know but Willie Snead The Raven spoke to Willie Snead and Hollywood Brown Willie Snead was up first and he said he's feeling lighter feeling fast. So he's just ready for football man He is he didn't mention anything about him getting on all them Browns fans cases though a couple weeks ago He talked about that, but it wasn't necessary either, but it's all good But Willie Snead he just said he's ready man. He said he's excited for this season looking forward to it He said everybody just got to be smart. Everybody has to be extremely responsible if they want this season to happen We can all agree there But one of the things that he talked about specifically was his quarterback Mr. Lamar Jackson and one of the things that so many people have talked about with Lamar Jackson One of the areas where he definitely needed to show some improvement on was in them outside throws But Willie Snead said hey, he's ready. He's ready. They've obviously been working together and now Everybody's at training camp For 80 man roster. Oh shout out to Nigel warrior. He's back to he got cleared. So shout out to Nigel warrior. Welcome back But Willie Snead said that Lamar he's ready man he's ready and That's what we all just we all waiting to see it man We all waiting to see like I know the other day cheers put out a tweet talking about are y'all more excited for the offense Are you more excited for the defense and I was like, hey, I can't choose. I can't choose either one Cuz I'm excited for both I'm super excited for both of them and I don't even know which one I'm more excited for but I'm just super excited for football straight up, man I know y'all are too. I am just I'm ready man I'm ready and we getting closer and closer and closer. So Right there, man. But anyway Somebody else like I said that also spoke was mr. Hollywood brown and Hollywood brown as we all know we have seen this guy This you know them pictures that people take on Instagram transformation Tuesday throwback Thursday Now Hollywood he could post up these throwback pictures of when he was small When he was just a small receiver. He ain't that no more He ain't that no more and this dude actually he said that he's looking forward to blocking people Hollywood said that He's looking that's why he bulked up because he's looking forward to blocking people because he want to set up the run game what like It's one thing about them Ravens receivers, man They are not selfish And watch somebody they listen to that part of the video and then they look at the title of the video They don't hey wait a minute engraving wall the title of this video and that those two don't go together. So it's not half Anyway, um, that was a beautiful thing from Hollywood But he said and we talked about this before about him getting up to 180 Um, he said last year. What did you say he was at last year? Uh, about I think 170 something like that Uh, but he he's at 180 now and you could you could tell the difference in Hollywood Obviously the dude is just it's like Like he's big now, man Like somebody somebody who might have pushed him last year. He might have went. Whoa Now they they'll push him. He just sit there. He ain't gonna feel it. He's so big now But he did also talk about how the Ravens gave him the um the gps tracker And it tracked him at the same speed that he was last year. So he didn't lose a step He didn't lose a step even with the added muscle And that's a beautiful thing because enough times people can add on muscle They can get bigger and they can get slower But how do you say no? It's like you gotta it's some factors that cancel each other out because yeah, he did add muscle But remember last year he was versus last year he was smaller But last year he was also hurt but still crazy fast Yikes That's scary But now he's he added muscle and now he's healthy Um, he also talked about Lamar Jackson just ready to get that super bowl, man Ready to get it and and not just wanting to get one but wanting to get multiple And that's the goal man. That's the goal. Um, a lot of players they uh, they envision the long-distance thing Getting into the hall of fame and that's great because if you in the hall of fame That means you were playing at a high level for a long time And you were amongst some of the highest levels in your uh in your era for a long time Now not everybody who played at a high level got into the hall of fame yet unfortunately um, but You were among some of your your best the best consistently Um, so the hall of fame is a beautiful thing, but my personal opinion and I've been saying this for years If I was a football player I would rather have super bowls than hall of fame Hall of fame is nice now, but I would rather have super bowl because super bowl is the ultimate goal And your team your one team because they can only be one winner Hall of fame there's five of them every year even though those five are chosen out of like 25 who are chosen out of like 50 who are chosen out of like 100,000 or something like that but Super bowls I think it should be the ultimate goal and I think that's Winning that would be better than the hall of fame But either one is a great accolades, but Lamar Jackson Ravens They got their mindset on the super bowl. They got their focus set on the super bowl And Hollywood talked about that with Lamar Jackson.  You got to be healthy You got to be healthy And Antonio brown he was better than a lot of people are doing that and staying healthy and just always being in shape But something else that hollywood said about mr. Antonio brown He said that he would fit in well in this locker room And that every time we talk about antonio brown That is one of the most popular Comments in the comments section and it goes both ways It goes both ways now, of course just to do a recap. We know about antonio brown situation We know about antonio brown situation. We know that it's a ultimately like the players can say whatever they want And a lot of them have all been on the side of signing antonio brown hollywood Lamar Ingram Um, I think who else disney say something about it a little while back. But anyway Some pretty uh, marquee guys on the ravens have been for A b but anyway, um, we know it's ultimately up to the front office And they would all have to be on the same page in order for that to happen and with antonio brown situation He's currently suspended for eight games Uh, and after I think september 14th is his next case. Um, that could possibly Add more to it But we just got to wait and see But hollywood said that antonio brown would fit in the locker room But like I said, a lot of uh ravens fans are just team keeping clean period Uh, because this is some stealers fans. So they got experience with antonio brown Uh, raiders fans don't really say much about them and patriots fans are like, uh, whatever. Um, but A lot of some people feel like hey Him in the locker room, he would destroy the locker room. Oh, it'll be chaos He would wreck it And then other people feel like oh, no ravens locker room. They strong enough, man They got some very powerful personalities in that locker room And they did just fine during the season Got earl thomas. He got a more powerful personality than we realized I calleus camber. Oh man. That's leadership all day. Mark Ingram same thing Look at Marcus Peters How has Marcus Peters been since he joined the ravens? Because we all know we all heard all the stories about Marcus Peters We heard them all He joined the ravens. What happened? Oh, well, I don't know man Haven't heard from a man. He's just getting you just getting all them pick sixes, man He did just fine, but I'm just putting it out there, man If it happens, it happens if it doesn't happen. It doesn't happen We will continue to wait and see what happens with mr. A B. I ain't mean to be spitting no bars like that My fault, but it's all good.  Well, he's gonna start complaining if he doesn't get catches I the only thing I say to that. Hey, I feel like with Antonio brown if I don't think he would complain over that, of course, he's gonna want his catches now. Who wouldn't But you would be you would be coming in on the ninth game You would be um You'll be coming in on the ninth game. You would be uh, this will be your last straw. This is this is it This will be it and this is no matter what team he goes to so i'm not just talking about raven I'm talking about no matter where he goes This is it Because it was almost it last year and again depending on how the other thing goes we see But he is on like his last straw It's a very thin straw too So we're gonna see how everything ends up uh working itself out But this was uh interesting press conference From themselves Florida boys man So shout out to west pome beach And shout out to hollywood So this was uh, we're gonna see how the season goes man But these are two receivers who are primed to have a big impact on ravens offense In more ways than one And real quick, it was just very interesting why we were watching it. I'm like wow they they mentioned that again And we talked about this before too that we've seen is the oldest receiver on the ravens But I didn't know exactly how old he was and they're like oh, he's 27. I was like wow Imagine that like That's not raven esque at all The oldest even though last year I think it was like that But the oldest receiver on the ravens team being 27 years old What what is this a fake team? Like that's crazy But hey times are changing. So anyway I love y'all. I appreciate y'all. I can't wait to see the comment section in this one. It should be a lot of fun But we out


Hands up if you passed your hardest moments alone While everyone thought you were doing just fine. I See you guys today


What does it mean to pray in the Holy Spirit? But you, beloved, building yourselves up in your most holy faith and praying in the Holy Spirit. To pray in the Spirit is to desire an agreement with heaven, to speak aloud those petitions which originate from the will of the Father. True prayer in the Spirit begins in union with God. Praying in the Holy Spirit is praying in harmony with the will of the Holy Spirit, with the guidance of the Holy Spirit and in the power of the Holy Spirit.


All right good afternoon separate traders welcome on back here this Monday July 24th shortly after 2 30 p.m. Eastern time great to see all of our students and members alike inside our live trading room Hopefully I'm good to go across the board here on social on social media Facebook live linked in Twitter YouTube Etc great to see Lawrence with me here and Grant and all this just joining in on right now great to see Michael as Well from before Andrea Dave Elizabeth Etc So hey whether you're joining us inside our live trading room whether you're on social I mean hey the markets been pushing up a little bit heading into this afternoon here But at this point now and a little bit of a pullback. So let's see if we can get support to build I feel like we can get a bit of a volatile market just across the afternoon today with anticipation of the the Fed meeting on Wednesday concluding so You know right now on the screen Dfli ended up making a nice push earlier today This stock was on a radar from earlier last week ended up making the beginning of a gap fill and as you could see here I mean I'm not only completed it back from Friday of last week, but and then some this morning So right now it's even pushing back on up once again. Let's just take a look at the highs off 325. I think it is It's a hard ask to see this try and run all the way back up to those highs Breaks at highs and keep going. I feel like at this point right now It's gonna hit resistance pullback Dfli has been a nice trade over the last week or so Maybe keep it on your side list going into tomorrow, but that that's really all that's really all it is All right, so hey we have class coming up We got the phase one stock course lined up at 305 Eastern time We're gonna continue our discussion on volume But really begin to go over level three the NASDAQ book viewer the trade station matrix here If you're on interactive brokers the book trader should you have that? But you know really introduce the order book and really show you how it all works live So looking forward to it rich is gonna post the link for class coming up in just a moment as we did earlier But you know with that let's just go right from top to bottom here. Let's see what we could put on our watch list across the afternoon BJ DX pop and drop. I think that's easy to say there Tupperware same deal right same deal for Tupperware ended up making a nice move early this morning in pre-market pop great after the open but fizzled out pretty quick broke lower Again easy to say but you know trust the cyber clock and you're gonna be avoiding a lot of those reversals around that 10 10 15 ish time MK FG MK FG nice little push I'd like referenced it earlier just kind of just scanning across the board I saw a pop-up and it was kind of lead into the run when I was at like 150 so it's pushed up about 15 cents since actually but You know what? Hey, I don't mind putting this on our main list to begin MK FG Just because you're unfamiliar with the stock does not mean that it can't prove you wrong I make a really strong trade into the afternoon or hell. Who knows maybe tomorrow morning. It's on good volume Let's take a look at the daily chart actually here. Just Yeah, stock took a huge hit across the last year and a half from 16 down to sub one perhaps Yeah, hit like 80 cents back like a few months ago So there could be more room on the way up, right?  But it's definitely not out of the realm of possibility if it could hold above. Let's just loosely say 158 157 ish looks like it closed here back at whom all right So like 159 will call it 159 if it could hold above the close back from Feb second here Then there's a pretty good chance to see continuation whether it be today or tomorrow this week whatever but MK FG Definitely when you want to keep an eye on AMC now if you're not keeping an eye on this then perhaps all of the people on that reddit channel Wall Street bets are doing it You know, you get all these people out there following the meme stocks and all that Hey AMC made a great move this morning off of five bucks dropped that first be called out the bounce off of five And it's really given us great opportunity since it pushed up pretty nicely at first But you know even after holding flat there ended up pushing back upward a bit and it's still looking pretty strong So AMC definitely going to put on our watch list here. Let me ask and I know one of our gold students here Dave T was in on the options on this I am to myself live right now who here is in on the AMC trade static curiosity Does not mean that you should be jumping in right this very second But if you were Grant Sam or Lawrence or Phil perhaps you're inside the chat board earlier Just taking a peek and saw some call outs. I'm just curious is anyone in on the AMC trade from earlier Needs to break over a 607 for this to be like a really strong trade for this afternoon I was calling that 607 you darker blue line out just earlier All right, so let's see what else we got here though folks got the AMC trade MK FG Bbi G not doing much right now pop and drop right there. We'll keep going Kscp nice little choppy trend, but it's holding strong near the highs right now This stock back from a few weeks ago a couple weeks ago popped up on our radar So from there pushed up pretty nice pulled back and hit support perhaps you can call it from Friday last week No, really strong run back up once again today So, you know, it's one that I'll definitely put back on our list Kscp Good spread good volume at the highs got an iceberg right here an iceberg right there Let me keep it going yell. I gotta make sure my water cup is filled up because The louder I get during class and during this meeting. I got to make sure I need it So I yell ended up pushing up pretty nicely earlier, but it's like such a slow-moving stock So you're more hopeful that this increases in volatility gets get sharper faster moving than anything So, you know what I'm gonna actually put it on the side list I feel like there could be even better opportunities than this right now It's like a beautiful looking level one chart, but how much could it really get you? And we'll come back to it if we need to On the other side of that spectrum though, we're not gonna put SDA on our watch list Although that's looking pretty good on the way up just bad order book. There's zero needs to be trading a stock like this right now Dfli I'm actually gonna put on the side list here. I didn't actually write that down technically on my notepad here So I'll be on the side for right now still, but just kind of skimming through see what else we got here. Oh Nice little push here QSI quantum SI another quantum Name stock QS is the other one. So you this one here QSI making a much better push Good volume nice trend across the afternoon Hope it starts trading even more volume per minute than what it's doing about six to seven thousand per minute So if that winds down, that's not a good sign But for right now makes the cut QSI not bad. All right. What else we got neo backed off from 12 earlier That was a great trade from this morning I'm gonna write that down on my side list. So I remind myself tomorrow Billy same deal. I didn't have Billy on my notepad either. So Billy side list Expev same deal. That's with neo there Redfin redfin had a strong June and into early July and pushing back up once again here today But not really trading the type of volume right now that we saw it trade. So You know again side list material nothing really too special about it But so far we got four stocks. We got the MKF G. We got the AMC trade We got the KSCP and then the QSI just before Let's see if there's anything looking just as good if not better on the loser side here folks Not much else from the gainers there. All right, so KOD took a huge hit earlier and to click on that KOD And popped up when the market opened a little consolidation first But had the larger pop afterwards and then just before it tried to make a move back up towards said highs So I had a little bit more of a squeeze here at this time, but failed to get the push and You know what? Let's see here. It's not looking terrible I'd say maybe like 425 ish maybe a 450 ish on a good side there, but You know what KOD I'll slip on there for right now I just gotta hope it holds support really soon and then from there it pushes back up If not, then actually on on my trade station platform KOD here is easy to borrow So this is tradable in both directions technically, but with the recent trend up that it's had the afternoon So let's hope to see it build a higher low and then pop higher if it fails to do that Then it could be a better short. That's kind of my thesis on it there. I forgot about this one a pph Oh 10 cents. Okay. I pass on that. All right So let's see if there's anything else looking just as good Fubo down big but You know, it's just a little too slow for a short for me Probably say the same on a lot of these cheapies that are on the loser side right now So hey, I need your help folks I mean, if there's anything else looking good up down left right more than 5% Before we wrap things up Pop the QR code up right now if you're joining us on social media here Just scan the QR code to get access to our live trading room across this entire week live workshop tomorrow Actually stay tuned for that also on YouTube at the same time But you know if you want to get the full official version of it just join us inside our live trading room Especially for tomorrow you get all the recordings to those workshops, too. All right going once going twice Let's say what for a Monday We normally do a good job of scanning. Don't we I mean there's always one or two that slip past the radar here, but Checking Benzinga pro right now really quick. I don't really see much else that looks too great Yeah, I think that we're at the bottom of this barrel here folks So, you know, hey, let me know but otherwise I think that rich just posted that link once again for class So if you're joining me for any of our phase one students here just joining me We're gonna look to go over level three the Nasdaq book viewer trade station matrix Just the ECM books entirely everything that you need to know about level three looking forward to that folks Really, this is where we begin to get more into the meat and potatoes of our trading strategy So I'm looking forward to it. Hey not a bad list to work with Let's actually just run through the side list before we wrap things up. There wasn't really much that impressed me from it But go through the yell the DFL I Neo Billy and then redfin markets dropping off a little bit more if they last peak there ended up pulling back a little bit further Right now, so just be a little careful with that Let's make sure we can get supports to solidify at this point heading into the close Best of luck trading to all and if you're joining me. Hey looking forward to that coming up just at 305 p.m Eastern see you soon


All right, so my paper is a lab So, you know that As this company Is a problem for do it for me for many reasons One of the reasons why it's a problem because it yes, it's associated with a bunch of Variety of risks also on the sort of politically on the political side of things And so when we think of inequality like that then one question is okay How do people think about redistribution and demanding redistribution right which I think both in South Africa and Colombia would imagine It's a it's a big topic So what explains support for redistribution why do some people want more redistribution than others So this is the demand side of the redistribution equation And here we focus on three On the role of three three factors one is aversion to high inequality the other one is the personal loss of a more equal distribution and Then just as a sort of sanity check the role of luck versus merit when it comes to redistribution I'll explain better in a second so the literature shows that We as humans have fairness considerations in ourselves, so we do There is ample evidence that we care about Fairness even when it doesn't involve us directly, okay and And this links to the inequality opportunity talk we heard from from Chico Ferreira the other day Inequality that arises from things that are considered Less fair is also more objective Objectionable and that means that we would probably expect to see more demand for a distribution if that inequality is considered less fair In fact, this explains a little bit the different attitudes between for instance Europe and the US Where in the US people tend to believe that effort is rewarded in Europe We think a little more that luck has a greater role and that might explain why we accept more taxes than for instance people in the US So our contribution is so we have all of this evidence, but it's mostly from high-income countries So our first order contribution is to ask these questions in a high inequality Emerging country, okay, so that's really what our first contribution is and this is a lab setting in the University of Cape Town where we have three Students and I'll explain well the sample is more than three, but there is three students and I'll explain how it works So why is this South Africa an interesting place to study these questions? Well, so Africa Speaking of fairness and how fair inequality is so that I think is one of those countries where the current distribution of income is a direct result of explicitly discriminatory Institutions so we can't just say well, you know the market is doing its thing Well, the market is doing its thing, but you're still paying the price of a system that did not allow the majority of the population to express their full potential so speaking of You know merit and luck. There is no merit here, right? Despite all of these however in the world value survey, we don't see a high demand for a distribution in South Africa In fact, we see comparable to other countries with much lower inequality less or what explains this puzzle Why why and why are South Africa not demanding more redistribution? So the experimental design works like this I'm gonna spend actually most of the presentation on this because the results are fairly simple So there is a production phase in which two players are paired and they have to complete a series of tasks And then there is a decision-making which is this third player was talking about this third party. We call it a stakeholder That decides how to split the payment between those two players. Okay It's important to understand that the third party player is not Does not complete the task does not participate in the production phase. It's just the person who decides who gets paid more. Okay Why do we need the first phase we could just make up some players and then do some hypothetical questions Well, the literature shows that having real persons Being paid real money makes the decision-making phase more binding and more realistic So that's why we we have the first phase with real people rather than just ask hypothetical questions We had a total of 335 students and we had about 220 in the workers Conditions or production phase and about 115 in the decision-making phase now our sample of interest is these guys because they Are those who make the decision that we are studying So here's the this is the most important slide Each of those stakeholders gets this piece of paper and they have to decide. Okay, listen You have 25 potential split of payment between player a and player b They just completed some tasks in the other room and now you have to decide who gets paid more One of these 25 will be randomly selected as the payment split So each of your decision is important because one of those is going to be the real payment So our sample size is 116 times 25. Okay, so that's how many decisions we observe So here we say we vary that the difference between the winning player and the losing player So this is max difference hundred versus zero But we also vary the cost for the third party stakeholder to Redistribute okay, so for instance here is zero whether I redistribute or not I don't lose anything but here is 45 which means that if I want these people to to be more equal in the payment split I have to pay 45 rents. Okay so We vary but the inequality The difference between the players. So here is 100 down here. It's only 20 the difference But we also vary the cost that the third party stakeholders in curse when deciding to Split the money equally So if I circle yes in the for instance in this line if I circle yes The players get both 50 percent and I get 100 which is my endowment payment minus the cost So 85. Okay, so they do this all the stakeholders. And so we have as I said 25 decisions times 116 stakeholders How does it change by how much it costs me? to affect a fair distribution so We see that It's decreasing meaning the more I pay The less likely I am to care about fairness so to speak So if I lose if you're touching my pocket, then I'm less likely to enforce an equal distribution And we still sorry we still have a difference Between the lack and the merit so for each cost level the lack People still redistribute more than than the the one in the merit condition, right? But it's decreasing in the cost What about by the level of inequality well the higher the split between player a and player b the More likely you are to redistribute. So we interpret this as an adversion to inequality So another important thing about this graph is that you see that the difference between the lack and merit is less relevant at high levels of inequality which we interpret as a sort of Unconditional this state this taste for excess inequality So for the cost we didn't see that for the cost it was the same essentially two parallel line here instead The source of the inequality whether it's lack or merit matters less when the difference is too much I don't care if you were more productive than player B. You shouldn't get the whole pie essentially That's what this is saying. I don't care if you were more productive than player B You shouldn't get 80 20. That's too much of a split So this is what we are calling an unconditional this taste for inequality This table. It's what I just told you but it's a linear Probability model. So essentially this is saying that higher inequality more redistribution Higher cost less redistribution and this is what I was saying earlier that there is an interaction between between In the inequality condition where sorry the inequality and the merit condition interact meaning that in What we saw here essentially, this is what this means, right that inequality is more important in As that the source of inequality is less important the higher level of inequality So this is just the regression version of these two graphs Does this matter so what is that you can calculate the genetic efficient out of all the potential redistributions, right? And so the genetic efficient that we started with we made it similar to the real g-link efficient or something a point six So what happens after people play and redistribute? Well in the lack condition the genie goes down to about point three and here it goes down to about point thirty five So you see how the redistribution changes the inequality in this Fictional world that we created So it's important to understand what determines these levels because then the redistribution is kind of the That the way you bring down the genetic efficient And that's kind of the sort of second message of our paper So the first is that the source doesn't matter at high levels of inequality the second one is Well, even in context like South Africa where there is a lot of understanding of a big a very Deep understanding of the unfairness of of the inequality in that country Clearly you have personal loss of a potential limiting factor So this experiment actually was motivated because when we started this experiment there was front-page news in South Africa about something called expropriation without compensation, so it's part of the South African debate whether the government should take land from mostly white farmers and Give it back for free to other people without compensating the white which in other countries will sound like a crazy radical distribution Idea, but within this context we did this experiment because the idea is to think okay Let's see everybody says they want more equality, but what if I start charging you as For for that higher equality and so essentially where we're interpreting this as Personal loss as a limiting factor for the equalizing power of redistribution now because this is an experiment we wanted to make sure that People were thinking the way we thought our experiment would make them think so post post experiment we had some some questions about You know what you know what made you? Decide the way you decided and things like that so what we find is so we analyze those those responses And we in a sort of qualitative way and what we find is that? first of all our sample We had some questions that are similar to the one you find in the world value survey Which is supposed to be nationally representative and we find it for those questions those questions are like the ones for instance Do you think the government should be responsible for reducing poverty? Or do you think the people should be responsible for reducing poverty? So those are the type of questions right and we find that our sample is not systematically different than And nationally represent the sample in the world value survey so that's good It means that our students are not weird in the Joe Herrick sense We also found because we didn't prime them our our questions were very open We find that they mentioned the word fairness lack Deserving good they mentioned these words a lot Which means that they were deciding about redistribution in the way that we wanted the experiment to make them think So essentially we conclude this by we we we interpret this as a sign that We were eliciting social preferences, which is what the experiment supposed to be doing And it also clear from the post-experiment survey that the The student that the players understood what the experiment was about because that a little Decision schedule the show is fairly complicated right, but the student it was clear from the responses in the post-experiment survey That they understood what they were doing So let me summarize This is an experiment in a high inequality context in the middle of a national discussion About fairly radical redistribution policies. So that's the context in this experiment And when I say front page front page, this is stuff that was still today actually it's discussed But this is something that again it's part of almost everyday discussion How do we redistribute and how do we redress the wrongdoing of apartheid? so what we find is that the higher the Payment split between The winning player or the more productive player and the losing player or the less productive players the more the willingness to redistribute result number one result number two The higher the personal loss of redistributing the less redistribution so essentially personal loss is a limiting factor for redistribution More redistribution the lack treatment, which is what I said. It's sort of very consistent with the literature And then that's sort of interaction effect that I was talking about earlier There seems to be an aversion to extreme disparities essentially meaning that Even when you think that player a should earn more than player b because they deserve it Even in that case if the distance between in the payment split between player a and player b is too much Then I'm still more likely to distribute Connect this to the discussion for instance in the US about the CEO being paid What is it 400 times more than the person working? I don't know in the in the office, right? So even though perhaps the CEO deserves a little more money does that mean they should earn 400 times more, right? so that's kind of the The analogy and then this negative impact or personal cost Which is not influenced by the source So it doesn't matter whether you deserve or don't deserve to be paid more if you're affecting me personally then I'm I'm gonna redistribute less Why is this Relevant for policy well as I showed you we have more in the paper But here I just showed you one graph it does change the post redistribution level. So like we saw was it yesterday in the policy session about the I think it was Santiago levy talking about the post The post tax and the pre-tax inequality. So as we see it's important I think he was making the example the difference between Colombia and Europe, right? So as we see it's very important if there is redistribution or not because it does change the the Gini coefficient So again, this is an experimental setting, of course But the intuitions are in our mind applicable to the real-world redistribution And essentially the conclusion is that Even in a setting like ours where fairness concern are prevalent as showed by Surveys and by our experiment support for major redistributed policy like the one I was mentioning May not be guaranteed by the the existence of this fairness concern. So essentially It's not enough for people to care about fairness. We need something that is we need a way to redistribute to that is compatible with people's personal Utility and and and not wanting to lose essentially and I think that's it