So, I wanted to start off today, actually, with a little poetry. This poem was written by a very famous American poet in the United States, and it turned out that she went to my high school, so I feel a particular attachment to it, but she also said something in 1939 that I think was rather prescient. She wrote, upon this gifted age, in its dark hour, rains from the sky a meteoric shower of facts. They lie unquestioned, uncombined. Wisdom enough to leach us of our ill is daily spun, but there exists no loom to weave it into fabric. And I think that this is really one of the great challenges of this coming decade, is to build that loom. And by a loom, I don't mean just the technology, just the machinery, but also the societal, the cultural, the human aspects of how do we bring these facts together? How do we weave the measurements, the daily work of neuroscientists, into a coherent picture? And so, as you know, in neuroscience, of course, we're studying very many different brains. We're studying zebrafish, drosophila, mouse, cat, rat monkey, human. And it's the challenges that we need to understand how do we learn from each of those systems in order to build an understanding of the human brain. And it's really that that excites us, right? We're interested, what is it that drives us in these uniquely human aspects that underlies our creativity, underlies our passion to discover, to go to the moon, to entertain and what underlies our emotions? At the same time, there are a broad range of disorders and diseases that afflict the nervous system and therefore affect us, affect who we are. And the challenge that we face today is that we simply don't understand how any of these diseases actually manifests at the cellular level, the systems level. What is happening to the brain in these, in many of these disorders? And we simply don't understand how to treat them. The treatments that we have found, we don't understand how they work. Seventy percent of those treatments don't work in fifty percent of people. The pharma companies are leaving, they're giving up on the brain, pretty much wholesale. It's too complex, it's too risky, it's too expensive. Also, two studies came out that showed that in the biomedical fields, seventy-five percent of the big findings, these are the discoveries that people get tenure for, science and nature publications that discovered something important that the pharma companies would take and go work on, but seventy-five percent of those were not reproducible. So we've got some challenges here, some pretty fundamental challenges to building this loom. So we're at a bit of a special time in terms of science. The last thousand years has really been about science being very empirical, collecting observations, describing them, trying to derive insight from these observations. The last few hundred years theoretical, the mathematical branch of building models has emerged, and in the last few decades the computational branch has emerged to facilitate running simulations and analyzing complex models. And so today, pretty much all domains in science are undergoing a transformation to what's called data intensive science or e-science, where they're taking advantage of the technologies, the information technology branch, to manage data, to process it, to analyze it, to build models, to run simulations. And this is happening broadly across all of science. And our challenge at INCF is to help transform neuroscience into an e-science, into a science that can use information technology to facilitate multi-scale data integration. So really taking the data from the molecular level, the neuronal level, synaptic circuit, macro-circuit, whole-brain, cognition, behavior, and even the clinical, and be able to facilitate the integration of that data. Now we're not going to solve all of that at once, but what we want to do again is build the loom that can help scientists put these pieces together. It's not a new problem. 13th century Buddhists wrote a story about this, that this is the parable of the blind monks and the elephant. Now each monk came to this object in front of them, came to this elephant, and each of them could describe just a piece of what they were encountering. They could find that the tail was there and he described it as a rope. The trunk was described as a python. Another one described the tusk as a saber. And each of them encountering just a piece of the elephant and describing it in their individual terms meant that none of them together could see that it was an elephant. Now in neuroscience, we're not that bad off. We know that there's a brain there, but we're not putting the pieces together. And we're measuring more and more data all the time at many different scales. So from the subcellular to cellular to tissue to whole-brain and in many different modalities, many different protocols, many different methods we're capturing so much data and it's growing all the time. And in fact there are some large-scale initiatives that are planning to gather even more data. We're entering a new decade of the brain. Now you all may know that the 1990s was declared the decade of the brain in the United States and I think in Japan it was the launch of the century of the brain. So I think they understood a little bit better the scale of this. But now we've had some announcements from the Allen Institute committing virtually a billion dollars over the next 10 years. The Human Brain Project was just awarded about a billion euros over the next 10 years. And the Brain Initiative in the United States was just announced which will be at least 100 million for 2014 and presumably much more over the coming decade. And we had a president of a country stand up and actually talk about hundreds of billions of neurons and trillions of synapses and point out that we can identify galaxies light years away and we can study particles smaller than an atom. But we have not unlocked the mystery of the three pounds of matter the one and a half kilos of matter that sits between our ears. And we also have to recognize that no one group can do this alone. That the U.S. is not going to solve understanding the brain on its own. The Human Brain Project, the European efforts are not going to solve it on their own but this must be a global collaborative effort. And some examples of data integration what it means to bring together this data and weave it together is for example building a model neuron taking morphological data, gene expression data, electrophysiology and building a model that can predict the electrical behavior of a neuron and running simulations to analyze and compute that. Model microcircuits taking information about the cell types within a volume of the brain, their distributions, their electrophysiology morphology and also synaptic connectivity and dynamics and using that to predict network dynamics understanding fundamentally the electrical basis of neural microcircuits and whole brain circuitry. Now it's possible with the data that's coming at whole brain scale that we will be able to actually integrate data across these many levels at the scale of the whole brain in order to start developing some insight to whole brain dynamics and of course this is the goal of some projects. Another aspect is multimodal brain atlasing. Now if you can bring together different scales of measurement including the structure at various levels of detail and functional characterization of whole brains into a common space you can analyze that and come up with a new way of characterizing the organization of the brain one that isn't just based on traditional anatomical boundaries due to cell density or other landmarks but one that really integrates both structural and functional aspects. So INCF was launched really with the idea that we need an organization that can act globally to facilitate this integration. So it was the Global Science Forum of the OECD that launched this discussion and came up with the plans to create INCF. In 2005 the plans were endorsed and August 1st 2005 INCF was launched. The mission is to coordinate and foster international activities in neuroinformatics to contribute to the development and maintenance of databases and infrastructure to support neuroscience, to make everything that we build or contract freely available and to work closely with government, academia and industry to make sure that this is as fruitful as possible for the advancement of neuroscience. So some of the activities that we do are to promote best practices in neuroscience in relation to informatics, to advocate open access and data publication. We work on scientific, technical and sociological issues around data sharing and integration and we work with government policy makers, funders, publishers and scientists to promote data sharing, collaboration and open access. The secretariat as I mentioned and as Stan mentioned is here, it's hosted at the Karolinska. There are 15 staff currently. This staff is really responsible for coordinating the scientific programs, the node activities for each of the member countries, manages the infrastructural developments and it organizes an annual neuroinformatics congress. At NIDESC we have actually many of them present if the INCF staff can stand up. Then you get some faces to put to, so you see it's over half the audience. But they're here, you'll see them around campus and feel free to talk to them and ask them other questions as well. There are currently 17 INCF member countries including Japan, South Korea, India, most of Europe, United States and we just recently had Victoria Australia join. So not quite the full continent there but we're planning on that by 2015 we get the rest of Australia. So the INCF programs are really a core part of the process of engaging with the community and this is how our activities are determined. We hold community workshops and those workshops can be proposed by members of the community. And those workshops bring together expert scientists from around the world, they don't have to be within a node, anybody from around the world on a particular topic that the organizers think can contribute to defining specific activities and make specific recommendations to the governing board or what product, services, standards, guidelines are needed to attack specific problems. They bring those recommendations to the governing board and the governing board makes a decision about allocating funding to those activities and those recommendations. They also appoint an oversight committee which is expert scientists to oversee the deployment of task forces that bring in again scientists from the community to work on particular problems, challenges defining these items and if they're unable to achieve that work from volunteer methods alone we can issue contracts that are targeted to get that work done quickly in the idea to really accelerate these developments. We currently have four programs, the digital brain outlacing, multi-scale modeling, ontologies of neural structures and standards for data sharing. And I'll go very quickly through some of the products that have been developed and made available from these programs. For example, a scalable brain atlas. This is a service that you can embed in your website to provide images of brain regions and allow you to hook in services to look up information. The Vox home space which is a standardized coordinate system for the mouse brain. If you register your data to that you can use the digital outlacing infrastructure to make queries to other atlases and to other systems like the Allen Institute and do transformations between Paxinus Watson and the Allen Standard Atlas, for example. So it gives an infrastructure for doing spatial integration. The program on ontologies of neural structures has brought together so Gordon Shepard has led an effort to bring together 40 scientists around the world to define neuronal properties, neuronal classes and properties and register them in a public online wiki. There's developments in defining pan mammalian reference structures, the delineations and definitions of brain regions for the Vox home space and also a common upper mammalian brain ontology. The program on multi-scale modeling has developed some standards for describing mathematical models of neurons and synapses and networks but in a way that is independent of the simulator that's needed. So this gives a tool to exchange one common model description between different simulators. The connection set algebra is a way of describing connectivity in large-scale neural networks. Multi-simulation coordinator is an API and a library that allows coupling at runtime of different simulators specialized at different types of simulation and they can communicate while the simulations are running and exchange information to coordinate those simulations. And there's also a computational neuroscience ontology for naming and categorizing classes of models. The program on standards for data sharing has two task courses, the electrophysiology task course and a neuroimaging task course. And both of these are really concerned about all the issues of metadata and data formats but also fundamentally the issue of provenance tracking and of reproducible results. How do you ensure that enough information is captured at data acquisition and then along every step of the way of your analysis so that by the time you come up with a publication and a figure in a publication you want to be able to track back through all of that process and know exactly how to reproduce that figure. We also have training activities. We've had a hackathon with the Allen Institute, worked a course on statistical modeling of neuronal data and modeling across scales of analysis. This year we'll actually have a course in Havana, Cuba, a short course on neurogenomics and brain disease and also multi-scale integration of imaging data. We also have a very active project with the Google Summer of Code. So basically we help match projects to students and Google pays for it all. So it's a very nice collaboration with Google. The question is how do we approach integrating neuroscience data? Because I think that if we share data alone without thought to its integration, it's not very interesting. Sharing data, I can hand you a hard drive of data, but you won't know what to do with it and there won't be any meaning derived from it until you can relate it to your data. But we want to integrate this data and we want to build a culture that can do this so that we can ask new questions. We can use that data to teach. We can replicate results. We can analyze, visualize, model, simulate, understand the data and build a new model for publishing. So to start along this path, we've been building a collaborative research infrastructure for neuroscience and that is to enable sharing of data, publishing data, preserving it, federating it, making multiple sources of data accessible through a common interface, searching over that data. We want to be and provide the capabilities of Google, but for neuroscience data, ease of use, making it sure that it can integrate into a neuroscientist's lab, making the data accessible for analytics, and also supporting the building of data analysis, workflows, provenance tracking, and so forth. So the first step to this is an international federated data space. I'll explain what that is in a moment. The next step are sets of services that build on top of that, including a semantic community encyclopedia for standardized vocabulary, digital atlasing services using the Voxholm space and registering data to standardized coordinate spaces, and data access query and provenance layers. So these are services for accessing the data. And upon that, the community then can use that to build workflows of various types to visualize, analyze, model, simulate those workflows. And specific applications for each subdomain in neuroscience, for example in neuroimaging, can build a specific application for searching for brain images and for doing analysis on top of that. So in general, data sharing is difficult. We get a lot of questions. Where do I put my data? So a number of funding agencies are now requesting that you have a data sharing plan or that you make your data available. Well, how do you do that? It's not always obvious. How can I share data in a collaboration? I don't want to make it public yet, but I want another group to have my set of data and it doesn't work easily in Dropbox. How do I make that data available? Where can I back up my data if I want to have an off-site backup that's maybe with a collaborator or somewhere else in the world?  If somebody says, there's data out there. There's data shared about that. Where do you go? Where do you look? So we wanted to do that and we wanted to make it easier. We're modeling it on the idea of a Dropbox for scientists. You should be able to drag and drop any type of data, text, or images. And you have the control over access to that data. So we held a workshop. So this is part of that whole process of INCF. We held a workshop that brought together big data scientists, that brought together people from the CERN, and that brought together people from Zincotrons, from the Allen Institute, all over the place that had experience already dealing with these issues. And they came up with a specific set of recommendations that told us how to move forward and how to build the first step in an infrastructure for data sharing. We call this data space, the INCF data space. And this really allows you to make your data public, collaborative backups, and gives the whole infrastructure for doing that. So the first use case is basically if you want to take a collection of electrophysiology traces, images, maybe a cell reconstruction, maybe a model, it's a folder worth of data. You drag and drop it and you can make it public worldwide. Another use case would be for collaboration. Say this site is generating large amounts of data, big data. You want to replicate this to this site. The data space gives you that infrastructure to do it. High speed in parallel. And also international in terms of an international infrastructure. So for our Japanese node wanting to make sure that their infrastructure is replicated to another continent, should there be another earthquake or nuclear disaster. We provide the European mirror of the Allen Institute data. So we can use the infrastructure as well for replicating the data between these sites. And also in Europe particularly, there are a number of national infrastructures that provide storage to the scientific community. But there's generally no easy way to access this. If we get them hooked up to the data space, we can easily provide access to those resources. This is what it looks like to log in through a web browser. You can log in. And then you've got the different machines that are around the world. So what this is doing is it's basically hooking up data resources, data repositories from all around the world to a common interface. So it's not that we're bringing all the data together to one central location. We're basically making it all accessible as though it's one big virtual hard drive. And you can drag and drop your data into or out of the browser. And so the web is one way to access it. You can also have a Java client, which gives you high speed parallel transfers. And then of course for the advanced users, there's a strong command line interface for accessing all the properties and replicating and synchronizing data. So this is built on existing technology. We basically contracted to get it all assembled and put together and refined for our need. We deploy it on the Amazon cloud. So it's replicated. The metadata for where this data is and all these servers is replicated in four zones around the world. So it's very fast, low latency to do searches and queries and then get routed to the specific data servers wherever you are in the world. And what's important is it gives us, at one level it gives us this drop box like functionality. But fundamentally it gives us a whole layer to manage all of the future requirements in terms of very large scale data management, workflow tracking, provenance tracking, arbitrary metadata annotation, all of the things that we need to do the next generation of applications. But we first want to get scientists with an easy to use infrastructure for sharing their data. So there are a variety of ways to join the data space. First, we are providing five gigabytes of storage for free for those of you who have data sets to make available. We also, if you have an individual data server already running, we provide the software packages that install onto that and then hook up to the Amazon cloud for making that data available. And if you have a larger organization that has your own set of users that you need to maintain, you can create your own zone in the data space. And we support you in doing that so that you can manage both the federation users and your own private users. You can also install a server that's solely in the Amazon cloud if you're willing to pay the cost. So Rafael Ritz is here and feel free to contact him for further information. And we also have a competition or contest going on right now. You can win $10,000. It's American dollars, but it's sort of close to euros. And if you show us, give us a good shining example of a large-scale, powerful, reusable set of data. Data that others can access and use productively. Let us make that a publicized case and we'll give you $10,000. So the next steps for data space, we're working to build in even more capabilities, making it even easier to use, even more Dropbox-like integrated document previews. We could even... One of the future things that we can do is add a plug-in so you can visualize, for example, your brain images remotely but just within the browser. So you don't have to go and copy the data out but start to add in services on top of this that are specific for different data types. Ultimately, we'll also add in capabilities to do analysis where the data sits. As the data gets larger and larger, you don't want to move the data to analyze it. What you want to do is you want to run your service where the data sits. So this is where we're headed with this. And of course, we'll also support tagging with semantic tags, linked data principles, community ratings, collaborative analytics. We're an associated partner with EUDAT, which is a European project to build a data federation and a collaborative research infrastructure, and we are contributing our experience with building this to their group as well as testing out some of the services that they've developed. Another service that we're developing is actually built on an existing site, Neurolex.org, and this is a site that was developed at NIF in San Diego, the Neuroscience Information Framework. It contains the ontologies, a large number of ontologies for neuroscience. So standardized vocabulary and classification in relationships of brain structures and of diseases and so forth. And what we're doing is we're going to take this to the next generation. We're going to build it on top of semantic wiki technologies and turn this into a community encyclopedia that we call Knowledge Space, which will be used to maintain living review articles. It will link to the latest data models, literature, and be a tool to maintain these standardized vocabularies and keep the community going back to that. And those are the vocabularies that will be used to annotate the data in the data space. So it's searchable. We also have a program, and it's kind of an emerging area in clinical neuroinformatics. And this came about through a partnership with an organization called One Mind for Research. They're based in the United States. This was launched by Patrick Kennedy, who's the nephew of John F. Kennedy, and it was seen as a new moonshot, but a moonshot for the brain. It's an effort to reduce and improve the treatment of brain disease. So they have a vision of building a platform, a neuroinformatics platform, that can build a common, shared understanding of disease. One that's accessible not only to researchers, but to patients, to clinicians, to technology partners, and to patient advocates so that there's different views on the clinical data for these different audiences. And we have partnered with them specifically to coordinate the development of a platform for a large-scale study that was just recently funded under FP7 funding for traumatic brain injury. And so this is a large-scale multi-site, multi-country study. Seven years, greater than 5,000 patients, and it really is about providing a standardized informatics platform for that clinical data acquisition, for managing the brain imaging, for managing the biomarker data, high-resolution ICU data, and so forth, so that it can be brought together and analyzed. And this will also be made open source and open access to other groups wanting to deploy similar infrastructure for their studies. And we'll use, for example, the data space to manage that data, the large-scale imaging data, biomarkers, genetic, and high-resolution ICU. So as I mentioned before, the digital addressing infrastructure enables spatial integration of neuroscience data. And one of the things that we see coming in the future is these atlases that really consist of large amounts of data that are still remaining distributed around the world but are registered both spatially and semantically and become searchable. So you have an interactive atlas for a given brain, for data, models, and literature. These are some of the identifiers that we see as useful for bringing that data together and aligning ontologies for describing the protocol, the experimental protocol, the metadata, the animal, the brain structures. Space, so we have a common reference system. And time, both in terms of development but also behavioral events and stimuli events. The genetic identity, if you're looking at populations of genetic variants. And for patients, a globally unique identifier, one where if a patient participates in one study and they also participate in another, you have the possibility without personally identifying that patient of bringing that data together and understanding comorbidities, for example. So data integration, what we really want to provide is the ability to link your data through standard object models which give you the informatics ability to access many different types of data but link them to ontology, to standardized names and standardized spatial locations. If you have a favorite neuron, say a layer 5 pyramidal cell, you've got a standardized name for it and the location of where these cells can occur would be described in standardized coordinate spaces and then that would all be linked to various data types including morphology, electrophysiology, ion channel, gene expression, protein distribution and also models and literature. So this is what will happen after you get your data into the data space. You'll be using the community encyclopedia and the tools for annotating and curating that data into these entities that then can be shared, exchanged and analyzed where you can search for data that was generated according to a specific protocol on a particular species. You can look for the community rating. How well was that data set, annotated and curated by the community? Making these things pieces of the puzzle that you can bring together, analyze, integrate, visualize and model. And we're using the latest W3C standards for describing semantic relationships and provenance to make that data and its relationships to other data searchable and tracking the provenance and analysis as you saw in the task forces for neuroimaging. Now there's a group that we're also working with Sage Bio Networks which is really in the clinical space but they have developed a platform for taking those objects that I'm talking about, the curated data and sharing not only those data but also the analyses that are done on them. You can share those with other groups within a social network type of environment and what they're seeing now are the coalitions of collaborating scientists that take one model that's been developed fork off, split it, start doing new models and as a community, as a collaborative community producing new and even better results more prognostic disease models and what's important is that this system keeps track of everybody who contributed to every step of the way so the attribution will give you credit if you developed one key analysis that sits in the middle of that you're going to get credit for that so it's a whole new way of thinking about working collaboratively, sharing and getting credit and we see that this is really growing as a possibility as an opportunity for neuroscience and related to that is using the same type of system to produce reproducible digital publications so we see within the next five years the ability to go to a journal article and for every figure you can open it you get the full provenance change and you can trace back the whole analysis to the original data and actually re-run that analysis changing a little parameter in the analytics to see how much does it affect the final outcome so this is coming a relationship with a whole brain catalog at UCSD that is built a system for taking these data and visualizing them in 3D and navigating them like a Google Earth for the brain importantly I see INCF really in a role helping to link these large scale brain initiatives now we're already working with One Mind for Research we will be partners on the human brain project coordinating some of their infrastructure we're already working closely with the Allen Institute and we're already discussing with some of the leaders of the brain initiative how we'll be able to facilitate data sharing and access through our work on infrastructures and standard vocabularies and so on so this is really the future for INCF and these are some of the partners that have helped us along the way to where we are now we also have an annual congress and this year you're very fortunate it's here on this campus August 27th to 29th we'd love to see you there and we're going to have a special session on these large scale brain initiatives so it's really your opportunity to learn firsthand from Tom Insel from the National Institute of Mental Health on the Obama Brain Initiative from Carl Heinz Meyer who's a co-director of the EU Human Brain Project and Clay Reid from the Allen Institute on their work on Project Minescope so I would definitely welcome all of you to come I want to, since we're also webcast and some of you are INCF community members here I want to make sure that I emphasize our deep appreciation for all of the work, effort, volunteer labor that the members of our community go to making INCF successful and we're very interested in learning more from all of you as to ways in which we can help ways in which we can facilitate your work so thank you, I'd be glad to take any questions Don't be shy so we'll get you the microphone first so the webcast people can hear you It's a question about the information technology and how it can be used for robot technologies and a combination of brain interfaces and so on Right, so of course by learning by being able to bring the data together build models and learn some principles about the brain, those principles can be used in building neuromorphic technology controllers for robots and this type of thing so there's the potential there and we do have some partners that are working in that space that we're glad to work with but we don't have any specific program activities on that at this point So could you develop a little bit more the relation to the human brain project? Sure, so as many of you may or may not know the human brain project is really about building informatics platforms for managing and integrating data about the brain in order to build models and large-scale simulations So there are a number of different platforms that are part of the key deliverables for that project One of them is a neuroinformatics platform and that includes things like being able to federate data have standardized vocabularies and we'll be working closely with them on such efforts to make sure that they're integrated with the community standards as well And the ultimate aim? And the ultimate aim? But the ultimate aim is really to... it's multi-fold So for the human brain project there are three aims One is first of all to integrate all of our knowledge about the human brain into a common place and be able to build models and simulations of it Another is to develop new ways of building an understanding of diseases and identifying ways of developing treatments and the other is to extract principles from these models and simulations to derive new technologies new brain-like technologies for neuromorphics and neurorabotics And ultimately to understand the brain? And optimally very much I mean all of this is very much to understand the brain but in many different aspects to understand it both in terms of how the brain functions what principles can be derived for computing and also how to treat disease First the more or less standard ways of dealing with data has been that you perform a meta-analysis of some kind of field where experiments have been done data collected, etc And so then this goes in two ways that first of all you have to collect the data you have to see whether the data are compatible with each other use the same terminology use the same methodology and so on and so forth Then I guess this is the stage where you're going to help, right? to collect data on this standardized kind of platform Then the next step is what do you do with this data? So are you going to make a model? Are you going to extract some kind of information? Is your help coming there as well? Absolutely, I mean that's by making sure that as you're saying first of all at the level of being able to bring that data together and do the meta-analysis having standards for the way that data is described and the brain structures are described and the data formats that's already going to help there But to build models if you have an infrastructure where informatically you can make a query you can get the data back with sufficient annotations to know I can run this analysis script and extract some features from it and use those features to build a model and then when I build my model I run a simulation for example and say well what's the data that I can compare that against that's also available so it's part of that whole process and also managing those workflows so that it's all reproducible so that you can share that with somebody else and they can rerun it easily And say to what extent is this kind of analysis protected because you obviously you want to share but not necessarily with your universe So we take the position of you can decide completely if you want to make it public private or not So we give you full control some people think we should force everybody to make it all open we think let's give them the time to decide when Other questions It seems that there should be an advantage in having some standards for doing the experiments Who will develop those so that results can be So I don't think that many people are going to accept that a standards committee sits down to decide a standardized protocol but what I do think is that by making your data available and other if a population makes their data available annotated with the protocol that they used so a description of that protocol that if you want to build another data set that you can integrate with that you'll follow the same protocol and by being able to share many different data sets that can be integrated you'll know how to follow which protocol in order to build a data set that's compatible I think that should only be done as long as it's useful as long as it's valuable to keep integrating that together but you'll still need innovation you'll need new protocols you'll still need an ongoing exploration and the innovation that the scientific community is known for but the value is is that we can have the data and we can search for the data that has been captured by the same methods Other questions? All right The simplistic way of formulation of Google Brain so that you can easily move between levels of formulation from the molecular and cellular to the disease oriented or more global nerve function I think it's an instrument to facilitate exchange between different neuroscience communities and you have after all so very many differences in your science community from linguistics from psychiatry to structural biology and it's very important to facilitate the interaction between these groups so one can realize why the defect in an ion channel would give a symptom given disease or cognitive etc Good All right, well thank you very much for coming


What is love anyway? Is it just a chemical reaction? Or is love something deeper? Something that can't be explained by science? Maybe we'll never know. But for those of us who have experienced love, we know for a fact that it exists. And maybe that's enough. But how do we know if we were ever truly in love? Here are eight signs your feelings were real all along. You shared your deepest secrets. True love is all about trust. You never put up walls. In fact, you usually do the exact opposite. Lovers are desperate to show their true selves, wearing their heart on their sleeves, and holding nothing back. So if you two shared your deepest, darkest secrets, there's a good chance it was true love. You didn't gossip about your love. True love feels incredibly special. All of a sudden, the entire world fades away into a blurry backdrop. You become the sharp focus of each other's lives. As cheesy as it sounds, love is all that matters. That's why true lovers don't really gossip about their relationship. Your partner is the only person who understands what you're going through, because no one else understands your unique connection. True lovers strive to keep that special feeling alive and private. Don't you agree? You never tried to control them. There's an old saying which perfectly sums this up. If you love something, set it free. If it comes back, it's yours. True lovers don't try to control or constrict one another. Although this sounds like a pretty simple idea, a lot of people don't fully understand what it means. True love isn't about ownership. When we try to control someone, we grab on tight, not letting it out of our grasp. When we love someone, we completely let go. Why? Because we want to see them fly. You never used ultimatums. Here's another big cliché you've probably heard a million times before. True love is unconditional. But what does that mean? As Shakespeare put it, love is not love which alteration finds. This basically means that you don't look for excuses to end things if you're truly in love. If you have relationship issues, you see them as hurdles to overcome, not reasons to back out. Obviously, there are always legitimate reasons to leave an unhealthy relationship. Violence and cheating are just two examples. But if you threaten to leave unless your partner caught a better job or stopped dressing a certain way, your love probably wasn't the real deal. Before we continue to the next point, we just want to say thank you for watching and supporting our work. If you've been a long time fan, we are truly grateful for your continued support in making our vision possible. Now on to point five, love and hate. You probably think that love and hate are exact opposites, right? Well, that just isn't true. The real opposite of love is indifference. Why? Because both love and hate require you to care about the other person. Love and hate are entwined in a way that few people fully realize. This concept was explored in a 2017 study called The Deeper The Love, The Deeper The Hate. Researchers found that when people experience intense love, they are more likely to experience equally intense hate after the romance ends. In fact, research suggests that the brain circuits involved in love and hate are the same. You can refer to the sources in the description later. Things Never Became Routine. Clinical psychologist and marriage counselor Randy Gunther once laid out nine signs of what she believes to be true love. Surprise and intrigue were right at the top of that list. She explained that true love never becomes routine. It never feels like you're just going through the motions.  It never gets old. This idea also extends to sex, which is an important part of most loving relationships. The physical aspect of true love is always rich with excitement and possibilities. This guide does become bluer. The feeling of home. At the bottom of her list, Randy Gunther wrote one simple word, home. For true lovers, this word really hits the nail on the head. So, what does it mean? When you're with someone you love, you just feel completely at ease. But it's more than just feeling comfortable. The feeling of home means safety, trust, and warmth. Being home means you can let your guard down. In many ways, it's an emotion that we can't really put into words. But we know one thing. We really resonate with Randy Gunther's final point. What do you think? You see a future with them. Maybe as you're watching this video, you're looking back and realizing that your love was real all along. This could be a beautiful revelation, but it might also be painful. Before you lose hope, ask yourself whether or not you still see yourself with your ex-partner in the future. If you answered yes, then there's no doubt about it. It really was true love all along. And who knows? You might still have your happily ever after. Do you agree with the points we've mentioned? What other signs of true love have you experienced? If you enjoyed this video, why not leave a like and subscribe? There's plenty more content coming soon. Also, if you haven't already, we made a video on signs you were not truly in love. It got over a million views, so you might want to watch it too. Thanks for watching.


The benefits of having good rapport with students It is important to establish rapport with students within a classroom for a variety of reasons. It builds trust between students and teacher, insights confidence in students and allows for a fun learning environment. All aspects of teaching require teacher to have some sort of rapport with students. Students will retain more information and do better in classes when the teacher is engaged and shows love for their job as well as an interest in their students. Most students will not learn well from a teacher who comes to class, does not greet the students let alone knows their names and just reads through the lesson without showing any interest whatsoever. It is far more beneficial for a teacher to have a good rapport with his, her students as it will make not only learning more enjoyable for the students, but teaching will become more enjoyable for the teacher as well. No rapport equals classroom disruptions. Trust between the teacher and the student is crucial as there is a lot of time that is spent in the classroom. Students need to be able to feel that they trust what the teacher is teaching them and trust that the teacher wants them to succeed. A teacher that has a bad attitude or little to no rapport will not be an effective vessel of learning for students as the students will most likely not trust or respect the teacher. This makes learning difficult for the rest of the class. Students need to be able to trust that the teacher has his, her students best interest in mind when teaching lessons. If a teacher chooses favorites in class, does not follow through with disciplinary actions or makes promises that he or she never keeps, students may view these actions as untrustworthy and will give less respect to the teacher. This could lead to more classroom disruptions and thus less learning. Good rapport equals confidence students. Another important reason to have a good rapport with students is that especially in an ESL classroom where confidence may be lacking, students need to feel safe and secure. A teacher that shows no interest in his, her students will only show students that he or she does not care enough about their students and is just trying to get through the lessons. Many students will already walk into an ESL classroom feeling less confident as this is a completely new realm of learning and vulnerability for them. This may be more true for older children and adults rather than young learners. A teacher must have a good rapport with his, her students in order to build confidence within them to attempt to speak a new language even if they need help with it at first. They need to feel like it is okay for them to make mistakes and to look to their teacher for guidance. A teacher who pokes fun at student pronunciation or refuses to assist a student when asked may show students that he or she does not care or respect the class. This could lead students to reciprocate the disrespect and can lead to classroom disruptions. It could also lead to students refusing to attempt to try because of fear of failure due to the lack of confidence created in the classroom. Good rapport equals fun classroom environment. Lastly, it is important to have a good rapport with students as it creates a fun classroom environment. When students feel like their teacher is happy about coming to class it, in turn, makes them feel happy about coming to class. Generally, the teacher's attitude will translate onto the students. Teachers who give off the impression that they hate their job, their students, or teaching in general, will only make their students uncomfortable and tense in the classroom. Although learning can take place in rigid intense situations, it is in more flexible and fun environments that learning really takes shape and student goals are met. Good rapport is essential. Teachers need not be best friends with each student in his, her classroom but building relationships and rapport with students is a large part of teaching in general in the greater rapport built with students, the greater their learning. If a teacher's greatest goals are to help their students achieve their learning potential, then showing concern and building confidence and trust in the classroom is a small feat to accomplish. We as teachers need to have our students excited to learn and to come to class and we need to build a good rapport with our students in the process. Are you ready to teach English abroad? Speak with an ITTT advisor today to put together your personal plan for teaching English abroad. Send us an email or call us toll free at 1-800-490-0531 to speak with an ITTT advisor today.


Hey everyone, today we're going to talk about the possibility of Cyberpunk 2077 coming to Nintendo Switch. I know it sounds crazy, but we'll talk about why it's possible after I remind you guys of our giveaways going on. We have six winners potentially this month. All the winners will be announced on October 1st. What exactly are we giving away? Well, we have two separate giveaways. The first one is for a Nintendo Switch Lite. That's the grand prize. And then two second-place winners will get a Game of Choice on Switch. To enter that, go down to the description. There's multiple steps there and multiple ways to enter to maximize your entries, including joining our Patreon at patreon.com slash Nintendo Prime for as little as $1 a month and then you'll get additional 15 entries into that giveaway and our second giveaway. So the Patreon gets you into both. Our second giveaway is for three copies of Super Mario 3D All Stars, baby. Three copies of that game and a separate giveaway. There's a Gleam.io link for that as well as the additional entries from Patreon. So I wish all of you guys luck and let's get into this video. See, CD Projekt Red is widely considered one of the best game developers in the world right now. Throughout this video, you're just literally watching Cyberpunk footage that they have put out there over and over and over again this year, various events, and the game looks absolutely incredible. It looks like something that is next-gen, if we're completely honest, even though it's coming out on PlayStation 4 and Xbox One and PlayStation 4 Pro and Xbox Series X, it's also going to be really seeing probably better updated assets for the Series X and, well, the PlayStation 5. And they did say, they said several times publicly that the PC version of this game and the PC version of all of their games will always be the best looking version. That's not too surprising, although there are cases where some people that bring their games over to PC hold it back for consoles. CD Projekt Red is not a company that does that. Now they had Cyber Interactive in the past bringing Witcher 3 in 4K to PC and they did a fantastic job doing that. And Cyber Interactive is the company that brought Witcher 3 to Nintendo Switch, aka the Switcher. They made that version of the game and it's widely considered one of the best triple A port jobs to Switch in the entire industry. I mean, we've seen Panic Button and other companies do a fantastic job porting things to Switch where the Witcher 3 is the most impressive Switch port to date and that was done by Saber Interactive, a company that works closely with CD Projekt Red to provide their games on other platforms that they are not currently developing the game for, typically handling PC ports and all of that jazz. So Cyberpunk is going to look fantastic. It's going to look next-gen. It's going to look like something that isn't possible on Switch. And I'm going to give you one big reason why it might come to Switch anyways, even if obviously we're talking a year from now. It's not going to be there at launch. We're talking about next year. And the reason is because of something that recently happened. I actually put it up on NintendoPrime.com. For those who don't know, NintendoPrime.com is the official website of this YouTube channel where we put up news and occasionally articles, but usually news that we might not cover necessarily on the YouTube channel, including the news we do cover at the YouTube channel as well. But we put up a few extra stories there a day that aren't reported here, just because it's impossible for me to keep up with all of the news in a video format in a way that is sufficient. So over there, I put up a report about CD Projekt Red talking about the last disco quarter and the first six months of this year because they had incredible profit margins. They saw a 70% increase in revenue and they actually credited the Witcher 3 and Switch. Here are the exact words. So CD Projekt Red Group posted 364 million PLN in sales revenue for the first half of 2020, which is a nearly 70% more than the corresponding period in 2019. So 70% increase over the first six months of last year. Notice that they didn't really have anything major release in that time. Compared to the first half of 2019, the group's net profit increased nearly three fold, reaching 147 million, so this is after everything that's their profit margin. This improvement in our earnings compared to the past year is due, among other things, to unceasing popularity of the Witcher 3, including excellent sales of its Nintendo Switch edition, as well as releases from other games in the Witcher universe on new hardware platforms. The late 2019 Gwent was made available to users of iOS devices with the Android release following in the first half of the current year. We have also released Thronebreaker for Nintendo Switch. The mobile editions of our games, another first among us, have met with very positive reception among gamers, et cetera. So essentially they released a mobile game, including some on Switch, but the Witcher 3 is mentioned specifically with the sales of the Switch edition. They didn't mention the Witcher 3 sales on any other platform. It's the Switch edition that's blowing up. Now we know back in April, it sold around 700,000 copies on Switch. That was back in April. As of now, it's been a few months. You know, it could very well be over a million if that sales trend has continued and obviously we know the Netflix series on Switch or on the Netflix series of the Witcher probably helped the sales a little bit as well. So yeah, and there's a new season coming. So the sales could just keep going as the Netflix series continues.  I know we're not talking about, you know, two, three, four million, but CD Project Red is developing a reputation for providing excellent games no matter what platform they put it on. And they are developing a fan base on the Switch audience with that Witcher 3 game. Remember, the Witcher 3 came over and we didn't have the Witcher 1 or 2, so there was no pre-built, established Witcher audience on Switch. People bought it on Switch. Some people as their very first Witcher game, others as a way to play a game they already own on other platforms, portably. So they need to look at this as a potential audience for Cyberpunk 2077. And I know there are some caveats we have to mention. Cyberpunk 2077 is not made on the same engine as the Witcher 3. Well, sort of. The Witcher 3 is made on their red engine. The Cyberpunk 2077 is also technically made on that engine. But it's made on a next-gen version of that engine that they, you know, I think it's red four or something like that. So it's built upon the same engine, but it's like the next version. So it's going from like Unreal Engine 4 to Unreal Engine 5. That kind of, that kind of change here. And Saber Interactive has not worked with that engine on Switch to try to get it to run. And you might be like, well, why did they change engines? They talked about all this over the over the past year or two, why they had to switch engines, you know, going back to 2018 about some of the verticality they want in the game wasn't necessarily possible. And the way they wanted night to work wasn't possible. And obviously we know Cyberpunk 2077, you're seeing it on the screen. It looks like this would, if there's ever a game impossible to run on Switch, it would be this, but that's what we thought about the Witcher 3. So I propose to you that dial back just right. This game could run on Switch. And we've talked in the past about how any game, if you're willing to dial it back enough, can run on Switch. But as we saw with the Witcher 3, which was dialed back, Saber Interactive still made it feel and look primarily like the Witcher 3 on every other platform. Yeah, lower resolution. Yeah, you know, blur your textures. But it looked and played fantastic to the tune of probably over a million people buying it and enjoying it and getting really high reviews and tons of praise with Saber Interactive, kind of in the back pocket of CD Project Red for something like this. It's entirely possible that this game could come to Switch because CD Project Red is not going to want to bring Witcher 3 to Switch. Have it sell incredibly well. I mean, their own words, you know, their own words of how excellent the sales were for Switch. Why would you want to want to offer that? Why would you not want to bring your next game to that platform? Now, obviously, Cyberpunk 2077 was not developed with Switch in mind. It was developed with NextGen in mind, developed with Series X, PlayStation 4 Pro in mind. It was it was developed with powerful hardware in mind. And obviously, we had the RTX 3000 series cards coming, Big Navi, RDNA 2.0 is coming as well from AMD. So obviously, they're looking at those future technologies as well, making these games even better and better. And obviously, the massive progress that's being made in the CPU space. Thanks primarily to AMD, but now Intel starting to catch up as well. It's it's kind of getting crazy out there with where technology is going. We got PCIe 4.0, we've got the SSDs coming in the next gen systems, even though SSDs have been around a while. Hey, it's still cool that we finally have it in home consoles. I do feel that CD Projekt Red is going to bring this game to Switch. It's like this gut feeling I got because if they are this happy with the sales of Witcher 3 and Switch, why would they want to stop? Sure, you might say, well, they can just bring Witcher 1 and Witcher 2 over. Yes, that's a good start, but is that where the buck stops? Because Witcher 3 was their most recent triple A release when it came to Switch. People are going to love Cyberpunk.  If they can somehow get cross saves to work on PC, PlayStation 5 and Xbox Series X, and they can make that work with Switch or, hello, a next gen Switch, are we going to forget that Bloomberg has put out there that there is a 4K capable, likely through RTX Core, likely through a new Tegra chip, likely through DLSS 2.0 Switch with a better screen and all that coming next year. Are we are we forgetting all the reports about a Switch Pro or a next gen Switch, something coming that supports 4K? This is Bloomberg.  This isn't some YouTuber spouting a much a nonsense like Nintendo Prime here. This is literally a legit outlet in Bloomberg, stating that a 4K capable Switch is coming next year. And again, for those that think that's just impossible, DLSS 2.0 has been proven to be able to take a 720p image and make it almost indiscernible to the naked eye over native 4K. So it can upscale 720p to 4K so well that you can't tell the difference between native 4K and DLSS 2.0 4K. That's the kind of tech that keeps Switch right in power with everyone else without needing the same power to natively hit those resolutions. Crazy, crazy world we're living in, right? So with that in consideration, a new hardware in consideration with the success of the Witcher 3 in consideration and with the fact that CD Projekt Red is clearly pleased with the sales to even specifically mention it and that they are likely going to want to bring Cyberpunk 2 Switch even a year later. So people that already own the game can now take it with them anywhere. I think that's an amazing thing. And I would love to see this happen more often, even if next-gen games come a year late to switch. I want to see this happen. I already talk about how 2021 is going to be packed just from Nintendo side of things. But Cyberpunk 2077 will be such a huge get that it really starts to eliminate excuses that other companies have for not bringing games to Switch, because all CD Projekt Red had to do had had to do to prove that games can sell on Switch is bring one of your best.  And if other companies followed suit, I think they could see equal sales on Switch as well, at least a million, if not more. I wouldn't be surprised that 20, you know, Cyberpunk 2077 comes out next year on Switch and it sells one to maybe even three million on Switch, just based on the faith people have now in CD Projekt Red that might be more interested in this game over the third game in a series they maybe haven't played. Anyways, folks, you guys, let me know what you think about this down in the comments below. I'm incredibly excited about the prospect of this because I legitimately think this can happen, even if it's exclusive to the next-gen hardware or if it's like, you know, still workable on the Switch. It doesn't matter with Saber Interactive and CD Projekt Red behind it. Damn, damn, this is happening, folks. I firmly believe it. And the rest of the industry, the Ubisoft of the world, who Ubisoft has shown consistent support for Nintendo for a while. I want to see your best of your best games. I want to see your Assassin's Creed games. I want to see the Watchdog games. I want to see more and more of your content brought to Switch. Get a hold of Saber Interactive and see if they can handle it. I don't know how. I don't know how after The Witcher 3, they aren't your first phone call. And stop going to Virtuous. No offense to Virtuous, who has actually ported quite a few Switch games. Some of the bigger triple-A games they've tried to port, they've done a really bad job. So, uh, no. Panic Button, who handled the Doom stuff, who was supposedly handing Doom Eternal. I'm starting to wonder, Doom Eternal is ever coming out on Switch. But Saber Interactive, man. I think they're officially the best porting studio for Switch in the world. Alright guys, thank you guys for tuning in. Catch you in the next video.


Three steps to get instant success using TubeBuddy Keyword Explorer. On my channel, I teach you how to start, run, and grow online businesses. In this video, I'm going to show you three simple steps to get instant success using TubeBuddy Keyword Explorer. Check it out. My video comes up first and it's got 95,000 views. Now, why is that? I bet you thought the number one way to get views in your video was to do a great video. You know what? It's not. That's not the way to do it. You have to optimize the title of your video and I'm going to show you how to get your YouTube video to the top of the results in this video. So stay tuned. Stick to the end because I'm going to give you a free e-commerce course at the end of this video worth $97. Hey, J.R. Fisher here and I've sold millions of dollars of products online, both physical and digital products. In this video, I'm going to show you how you can use TubeBuddy to actually get more views on your video using the Keyword Explorer tool. Okay, let's jump right in. Step one, I want to show you a super cool tool that you can use that's absolutely free and a little bit more if you want to get some pro things in there. But it's absolutely free and I'll show you how you can get a 30% discount if you want to bump up and get a higher level of it. Okay, so let's check it out. The link is right there on the screen to get the discounted price. It's www.tubebuddy.com. You've got to put that in there to get the discount. So when you click the link, you're going to end up right here. Let's check it out. Now I use the paid version, which is still less than $10 a month. Okay, so all you got to do is click the link and go. Step two is really simple.  Okay, so when you click on the link, you're going to end up on this page right here. And what you want to do is go right here and click Install Free on Chrome. Now there are some paid versions, which I highly recommend. If you go up here to pricing, you can get a discount if you use the link that I provided to you. And you don't have to pay that. You're going to get a discount on this. But I would definitely go at least with this pro level right here. You can access all the productivity and video optimization tools. And as you can see right down here, you're going to get upload checklist. You're going to get the quick edit. All these things are going to come with the free. But if you bump over and you check out the pro right here, this is what I would recommend. This way you're going to get the video topic planner. You're going to get the thumbnail generator. So you don't have to worry about, you know, artwork and Photoshop and all that stuff. You're going to get the playlist actions right here. You're going to get the default upload profiles right here. You're going to get the comment filters. And this is really cool because what you can do is you can go in and filter any comments you have not responded to yet. So you don't have to sort through all of them. And then you can also put in canned responses right here of, you know, people who are saying that's a great video. I appreciate it. You may want to have some little canned response for that. You can also put in your in-screen templates and card templates right here. And that all comes with the pro version. So I highly, highly recommend you doing that. If you look over here on these free ones, all this stuff is limited, maximum five video topics. So it's not going to give you everything you need. This is limited also. It can only add one custom image. So the free one's okay. Don't get me wrong. I would definitely go with the pro. All right. Let's get back and let me show you how to use it. Okay. So once you've got it installed, you're going to need to actually sign in right here. And once you sign in, you can start using it. So let's go over and look at some of the tools you can use in it. Okay. Now, as long as you are signed into YouTube, which I am right here, okay, you're going to see this little TubeBuddy thing at the top. You want to click the three lines on it and it's going to give you a whole lot of options. You've got dashboard. You've got my videos. You got playlist. You got live streaming. You got comments. You got subscribers. You've got your analytics. Now, down here is what this whole video is about is this keyword explorer tool. So let's go to keyword explorer first off. Okay. Then you're going to come to a box like this and it has a search box. Now, our goal here is to optimize our title. And the way we're going to do that is we're going to search for a title that everybody's already searching for. And then we're going to try to find low competition for the keywords. And that's the title we're going to do. So let me walk you through all this so you can see exactly how it works. I'm going to start off with online business. Okay. So I want to talk to people about online businesses. Let's see what I get. That's a nine score right there, which means it's poor. Now, why is it poor? Let's take a look at this. It's poor because the search volume is pretty good. The competition unfortunately is just just crazy on this one, right? And the optimization strength is just kind of so so. So if it gets in that yellow right here, you know, they consider that, you know, fair good, but we'd love to get into the green if we can ever do that. And you can't do this with every single title. So let's put how to start an online business. And we'll search that. And it's still saying it's poor. Now, there's some other things you can do. You can look at, they're going to give you some related titles over here. How to start an online business with no money. Let's take a look at that one. Let's see what that gives us. Ah, still four. It's a poor one. Okay. So we're not getting anywhere there. So let's play around with this title a little bit. And we're going to go how to start an online business in four steps. Of course, you can adjust your steps. Still poor. How about we're going to put in here, they're suggesting how to start an online business in one week. So, oh, look at this. 44. So now it looks like if we mess around a little bit with the time on here. And let's let's look down here. Why? Because there aren't that many videos it looks like. Well, no, there are a lot of videos. What is it that's given at this? The optimization strength. Okay. And this number represents how well optimized the top ranking videos are for the search phrase. So what does that mean? That means that this search phrase here is a good search because the ones that are using this title right now have not optimized their videos very well. So what you're doing is you're going up against a weaker competition here. So right now we're at 44. That's certainly good. We're in this yellow. We could certainly do a video on that. I wonder if we could improve it at all though. Let's see if we could improve it. We got one week. How about let's put in here and little things like this can make a difference. Seven days. Let's do that. Seven days is 42. Still not bad. So we're heading in the right direction. Let's try five days. Down to 27. Okay. Let's say three days. Oh, that's really bad. Let's go down. Let's go down to two days and see what we've got. Still very poor. How about one day? Very poor. Let's try 24 hours. Let's see what we get there. We're up to 33. What if we did 48 hours? Oh my God. Look at this. We got a 70 on this one. That is incredible. That means that if we put this title on here, we have a really, really good chance. The optimization strength is going to be good. Competition is going to be good. Search volume is going to be pretty darn good too. So we're probably going to get a lot of views on this video. And you know, I had that one video that I had for the homeless in San Diego. And I got to tell you, I put it on another channel and it did awful, just awful. And I couldn't figure out why. And then I realized I had changed the title and nobody could find it. I didn't get hardly any views in it. One of them I got almost 100,000 views. Another one I got a couple of hundred. So this title thing can make a huge difference. So this is what I would do in this case here is I would actually take this title now and I would save it. And I would start building some variants of it down here. Because if this title is good and people are interested in this subject, then I could make other videos about that subject. And the videos could be a little bit different. But you know, you want to make what they're searching for. I was talking to somebody today and they were saying, well, I don't want to make the videos that everybody else is making because everybody else is making these videos. And you know, I want to do something different. Well, first thing you want to do is you want to check and see if the reason everybody else is making videos from that subject is because everybody is searching for it. And they're getting a lot of search volume. So that's what you want to do. And the truth is once you've built up your channel and once you've got a lot of people there, yeah, you can pretty much do any title you want because you've got hundreds of thousands or millions of subscribers. And they're going to click on your videos and they're going to go to your channel and, you know, they're going to look at a video every time you upload it. But in the beginning, the only way to get traction is for you to make videos that people are searching for. And I know because, you know, I tried a few years ago and I couldn't get any views and I switched over to, hey, maybe I'll make a video of what they're looking for and then I did a whole lot better. So that's what I would recommend you do. Now, you've got to understand that video views, that's only going to be about 3% of your income off YouTube. You have to have other products to sell. And I want to give you a free gift, a $97 course, absolutely free. I've put the link in the description and you can get my e-commerce course and learn how to do that. Now, don't forget to subscribe to my channel. I need that, okay? Don't forget to like and don't forget to turn on the notifications. You'll need to click the little bell to do that and that way you'll be notified every time I do a video. See you next time. Subscribe to my channel and click that little bell right there so you can be notified every time I do a new video. Also, click on one of those videos there. Keep watching on my channel.


Hi, I'm Andy Gojie of Investor Intel. We're here at PDAC 2018. I'm joined by Bryce Bradley of Thunderstruck Resources. Welcome. Why? Thank you very much for having me, Andy. How's your PDAC experience been so far? So far, I've been pacing myself. I've been in bed early every night, but it's only Monday. I still have two more days to go. It's been highly productive though, highly productive. I can definitely see that there's an energy in the air. That's wonderful. Can you give us some update on your projects in Fiji? Yeah. We just announced recently results of our copper porphyry. We did some work on it just before Christmas. All the results came in showing that it's at least a kilometer in size and open at depth. We don't know how deep it is. So we're going to go back in in the next month or two and do some mapping and IP on the porphyry. The two high-grade zinc copper assets that we have that were drilled by Anglo, we're in talks here at PDAC to do joint ventures on those two assets, as well as the copper porphyry, in fact. The gold asset that we did some work on recently, we're going to go back in again in April and do some, we need some more surface work. So everything's going, our season runs from April to November. So we'll be back on the ground very soon. That's wonderful. How is the gold market chats here at PDAC this year? I haven't really been to, it's been more about zinc, I'd say. Gold. Touch on zinc. Yeah. There's been a lot of the Japanese and the Chinese in particular have been approaching us for our zinc assets and copper, but primarily the zinc, actually. So that might be the first deal that we do would be on the zinc assets. We all know that there's a supply crunch and there's a lot of demand for zinc and it's probably going to go on for a long time. They need the metals and we have them. And that's what your shareholders are looking to hear? It is, yes. So I think this 2018 is going to be our year, finally. We have all the permits and place we can sign a deal tomorrow as soon as a group does their due diligence. We're ready to go with landowner agreements and we have our license renewals, we're completely set, as soon as we can get on the ground right after Easter. Wonderful. For Thunderstruck, what do your shareholders expect in the next quarter or two? The next quarter, I know they want to see us do well drilling, currently we're not going to do the drilling ourselves. It's very expensive and the copper porphyry is very deep and we don't know exactly how large it is yet. So it needs some real love on it. So we do want to get a drill program underway with a partner, hopefully. And we'd like to drill off one or two ourselves after the share price so we can get a healthier share price as soon as we get some more momentum going, which is 2018, I believe. So there's a word that there was an announcement that you made on your advisory board? Yes, I'm very excited to say that we now have Tookie Angus on our advisory board and we're very technically sound. We have two new board members that are geologists, Lawrence Ralston and Linnea von Hessert. And we have Chris Ravell from Apex Geosciences, a qualified person. But on the capital market side, Tookie Angus has done seven billion or more in mergers and acquisitions since 2008. And he runs, he's chairman of K92, a company that's in Papua New Guinea and San Marcos in South America. So he knows everybody and he gets deals done and it's exactly what we need at this stage is Tookie.  Okay, that's wonderful. We appreciate you stopping by the booth today. Thank you very much for having me. This is the great show. I'm really happy that I came as usual. It's wonderful here.


be a great chance for us this week. Just a whole new challenge, you know what I mean? Kevin, I know everybody's talking about, you know, the scoop and score that wasn't for you the other day. I mean, when something like that happens and the official may or may not have blown the call, how hard is it to flush that and just go on with the game or is it? I flushed it during the game, honestly. We see it all around the league every single week, you know, some calls on one game is called one way and it's not always uniform based upon, you know, what official you have. Sometime it actually works in our favor, this time it didn't. And I just, you know, once it happened and we didn't get the call, obviously I was kind of upset about it, but you know, you just moved forward. You were talking about, you know, the Chargers offense and no Echler's a little banged up, but he can do so many different things.  Yeah, Echler's one of the best backs in the NFL bar none. What he can do, running the football and also catching the ball in the backfield, he's been in the league running back for a while. He's a guy that you don't really see guys get clean, big hits on him because he's very, very strong.  It's very reminiscent to Derrick Henry, but just on the offense, especially short, kind of compact, but that guy is strong. I've seen him doing pull-ups with one arm or something like that. So like I said, very elite back and if he plays this week, he's going to be a big footballer we have to stop. Your quarterback obviously is taking a lot of heat after what happened on Sunday with the three interceptions. You've been around him for a long time. Any doubt in your mind, you know, he's going to bounce back? Yeah, I don't have any doubt. Ryan Taylor has played really good football force for a long time. He's had some bad games. He has some really great games. And I think just for him being a veteran, being in this thing a long time, I don't think he's going to let one game determine what his next game is going to be. And if you watch around the league, it's a lot of really, really great quarterbacks, really great quarterbacks, has some bad games, you know what I'm saying? So I would definitely expect him to bounce back. Nah, not at all. I mean, that's a whole new year. I don't think it wears on us at all. I just think, you know, in this league, it's hard to win games. We got really close to winning one and didn't happen. I think this week's going to be a whole new challenge.  I don't think the losing streak is anything that plays on anybody's mind, from the players, even the coaches' side. To be able to stop the run first, because they ran the ball pretty well last week. They have more balance this year, you know, so they actually are going to run the ball a little more.  We like to get in the rhythm. We have to be able to stop the run first. But I would say we have to be able to affect the quarterbacks to be able to win this game.  Those games you guys run up front now have an ardent key in the mix. How was better, is that for you guys? It was successful with that last one. I want to say just, it's the guys. I think it's the willing to work together. You know, no matter if you're running a two-man game, four-man game, we all have to be on the same page. We all have to work together to be able to accomplish that goal. And that goal is to run a great game and get the sack. But, you know, everyone's just not being selfish. Everyone working together, we're trying to get to one goal and that's win. And I think last week showed that, you know, no one being selfish and everybody on the same page. I think the game part of this talk about how it may not have always been a call, a stunt, or whatnot.  What makes you able to do that so quickly? I mean, the timing and the camp, you know, that's what we work for, OTA's camp, and so forth. I think that's the practice for it, being able to learn your teammates. Like I know, like right now, I know what Artin's going to do. I know, if I see this matchup over here on the right side, I know what's there. I know he's going to take it in the same thing with me. He knows if I'm rushing to Instagram and not tell him, I got him, like he knows that we're going to work together. He's going to cover me, I'm going to cover him, whatever it may be, you know, just that feeling, knowing that you can trust your guys on the field that he'll make you right. He's going to be just fine. He's going to be fine, and I talked to Harold, and I told him, just let it come to him. You know, when you miss a whole year of football, and I didn't miss a whole year of football, but I know that mindset. I need to make a play. I need to get a sack. I just told him, let him come to you. Saw him in the hot tub Monday after the game, and that's what my message was to him. And I know he'll be just fine. Obviously, two really good players on the edge, two for sure. So, you know, he's got to be aware of that and two really good linebackers. So, just got to be ready to attack that and be ready for all the different looks of the show. First communication, you guys working together. How do you think all that went and how much better should it go with the week? Yeah, I was pretty happy with how that went. I think, you know, especially given the environment, I think we did a nice job. But, oh, it's tough to work on and improve on things. We're just going to get more complex this week. So, it's got to be on top of that. Yeah, you know, I was really physical. We did a really nice job against the run last week.  Yeah, yeah. I think the only people who really know what the actual grades are, the people in this building, to be honest, and you can know what plays and know what techniques you've got to execute. So, you know, obviously, definitely stuff to work on and stuff I wasn't happy with. So, just kind of making, being intentional about that this week and working on it. What was the team here last week? Yeah, you know, obviously, you want to get one, but just got to keep going. It's a long season. You know, they're great opponent here. So, got to move on and get ready to play. You're going to not dwell on too much in the past game. They'll learn from our mistakes and get ready for the next opponent, which is obviously a really good one. So, are we ready? Is that hard to do? Not really.  So, you have to, you have to, it's kind of forced you to move on, almost. I have a son the other day. He already says, you know, I mean something to you when you're getting that kind of praise after one goal. Yeah, for sure. I think that's, you know, my first goal is sort of proved that I can let belong and I can play in the league. And you know, I don't know if that's so it happens in one game, but that is kind of my first goal, first and foremost. And so that's what I want to be able to do and help us win. So, I'm going to expect that. But, you know, I got to be able to, us corners have to be able to show up and tack on the edge, you know, to stop the run.  I'm kind of the passing side of it. Obviously, Herbert, a guy that can move around and he's got that rocket arm. You know, he can pretty much throw from anywhere on the field. How cognizant do you have to be, you know, when he gets out of the pocket, does this thing? You have to be varied, you know. Like I said, he can make, like I said, he can make all the throws. But we just want to make sure we make sure he throws the ball in front of us, not over the top of us, you know. And I feel like if we do that, you know, eliminate the edge plays, we'll be in good shape. I mean, it's a challenge every week in his league.  So, it's going to be on us, you know, to identify what their strength is. And obviously, we think that's, you know, throwing the ball. They can also run it.   So, and most quarterbacks, you know, they can make every throw, but he is like accurate with every throw, you know, and he can make throws on the run.  That way, we don't let them have X players.