Live from New York, extracting the signal from the noise. It's theCUBE, covering RapidMiner Wisdom 2016, brought to you by RapidMiner. Now, your hosts, Dave Vellante and Jeff Brick. Welcome back to New York City, everybody. This is theCUBE. We go out to the events. We extract the signal from the noise. We're here at RapidMiner Wisdom 2016, hanging out with the data scientists. Big announcements today. RapidMiner version seven is out talking about citizen data scientists. We're here with Peter Lee.  Peter, welcome to theCUBE. Great to see you. Great to see you, Dave. So you got the little kickboxing. Yeah, you know, not getting better at golf. Obviously, I need a little bit of room for improvement in kickboxing. Great to spar with. You can make a lot of contact. So it's your big customer event. You got to be excited. Yeah, huge announcement today. Recent funding event. Fantastic, fantastic stuff. Give us the update. I can't say enough about Nokia. Nokia is just a tremendous investor. Did a ton of diligence. We're really pleased. They're global. We're moving so rapidly, not just here in North America, but roughly half our business is coming out of Europe. And Asia is a massive expansion opportunity. And Nokia is in all three places. We're delighted with them and our existing investor group. So the strategy of the company early on is to have an open core, a lot of users, and now you're in the process of sort of converting them into your paid model. Talk about that opportunity a little bit. Sure. I mean, we call ourselves by far and away the number one open source predictive analytics platform. And I'd say there's really three stages in which we engage with our fans. So first of all, data scientists, citizen data scientists, advanced business analysts. These guys can easily come in and start with very rapid prototyping. And then after you go through a prototyping phase, because especially in this era of big data, you don't know a priori what is going to be the best model or models that turn out to be the best predictors in a particular data set. Once you rapidly prototype, you can move to the next phase, which is you can really take, go beyond sample data size and really do validation. And that's typically where you're going to find tremendous new insights, gain better confidence. And then ultimately, and I think one of the reasons why Nokia invested is we have a very unique platform where you can move from the data science part, prototyping, validation to really the business value part, which is operationalization, where you take those predictive insights and then you embed them downstream into human or automated intervention. And so that's pretty cool. So Nokia, it's a strategic investment. I mean, they've always had a big, big data play. No, Nokia Growth Partners is a financial investor. Now we're pleased, Nokia has also become a tremendous customer of ours, and we have much to announce in that regard. But Nokia Growth Partners, a financial investor, they're backed by Nokia, and that's how we got connected. Well, time is good.  So the timing's good. So you must feel good about that. Yeah, absolutely. We were really pleased. We were able to demonstrate some pretty significant growth. We're doubling, tripling on multiple dimensions and we're able to really step up. And I think now that we've really gone through a couple hundred clients, we're well past the validation stage, and it's really time to step on the gas. So we're making investments both on the product roadmap, and I think we talked a little bit about that. We made some announcements today. Our fans are super excited about that, our customers here, as well as go to market. So you'll see a much more aggressive pace of investment as we work with our customers on high value use cases. Well, I'd say the timing's great because this business, the big data, Hadoop business, everybody went crazy. Tons of funding rolled in. And you have a lot of companies doing this that looks like they're growing, but there might be losing altitude and there's a lot of people concerned when the funding dries up. You feel like you're in pretty good position, obviously. Yeah, we feel like we're extremely well positioned. I think looking beyond the cash, I think one of the key elements as a disruptor in this market is that you can get started in an open source model at a price point that is very hard to beat. And you can continue to really grow and develop and invest in your analytics at an ROI, which is simply world class. And I think that's really what's propelled us to the number one spot. And so now we're building a much more aggressive community today, certainly a great example of that. I think you guys can see the momentum and the activity and the energy here, but we're also investing heavily in our marketplace. So you'll see that our partners, our SI partners and our other partners are really able to come into our marketplace and really engage with our community. The data analysts, the data scientists, the business analysts, citizen data scientists, and really have significant innovation. So we're extending our platform at a rate that's far beyond our core R&D and really embracing all the solutions in the field that you see with our partners out in various use cases. So that core community, that core data science community is very valuable, useful.  So that's great. Now, what about expanding beyond that? Is it time now or is there going to be a big effort to do that beyond that? Well, I'd say that if you think about the business of predictive analytics, the data scientists, that's really where the modeling is taking place. But we really engage with the full portfolio of enterprise personas. It really depends on the use case. For example, we've just heard from one of our partners, Pricewaterhouse here in a financial services context and really talking about using joint solutions, rapid miner, married to Pricewaterhouse expertise and transaction monitoring. In that use case, you're really engaged with not just data scientists who are modeling potentially fraudulent behavior, but really, and I think more substantively in an enterprise context, you're really dealing with the chief compliance officer, the chief risk officer, who's really looking to get in front of significant risk and cost inefficiencies in their business processes. And so that's a huge opportunity for us to really expand the vision and the embrace. So yes, we are moving well beyond just the data scientists and really heavily into line of business-based, use case-based discussions. And I think that's true in financial services vertical, consumer products and retail, and then asset-intensive businesses, midstream and oil and gas manufacturing. There's a number of really interesting use cases now. And I think people who have gone up the data visualization curve are now so comfortable with analytics, they now really want to move to the next step, which is really predictive analytics. And so we're in that. We've been tracking this now for many, many years, well over five or six years before people knew what Hadoop was and early on there was some big winners, particularly in financial services markets, some leading edge, typical for financial services, particularly coming out of the downturn. And then you had a lot of money pouring into experimentation. And a lot of the decisions were based on technical feasibility. Well, we can do that, but the ROI wasn't there. I'm sensing that's starting to change. There's more of an emphasis on starting with that business outcome and they're learning how to deal with the technical aspects. Is that fair? It's a great comment. I would say we are well beyond the stage of proof of concept type engagements across the board in the world of big data. I think it's a well understood paradigm. I think the challenge is really what I call a proof of value engagement. And so it's really about the end result, which is if you can operationalize your predictive insights, there's significant ROI and then let's engage and really kind of quantify how we can create a self-financing project that is one of three, that's gonna drive one of three outcomes, transformational, know your customers, so revenue-based ROI, customer and marketing analytics, radically reduced costs. So think about operational use cases or reduced risk. You know what's really seeing around the corner, not just what's directly in front of you. And cost reduction in terms of business process. Absolutely. As opposed to what the ROI in the early days was kind of reduction of investments, lowering the denominator of what it cost to build a data warehouse or whatever it was. And now you're talking about deeply embedding into the business process. Yeah, well we just had another customer really talk pretty eloquently, Siemens, just really talked about fantastic use cases around business process transformation. In audit. In audit. We had Lars, right? Yeah, Boris. Boris, yeah, Boris. Yeah, Boris on this morning. Oh, he was unbelievable. The number of questions that he got and you talk about that is what a great comment because really, to your point, business process, it's not about forming an ideal business process. In fact, one of the use cases he pointed out is in a procurement in Latin American country in Brazil, 12% according to his stats of the actual purchases that went through that country, followed the standard business process. So using RapidMiner, they were able to really isolate the 88% of the business process. So they have an ideal business process. 88% of the order flow doesn't follow it. And then you really begin getting into the predictive analytics of how do we begin altering which one are the ones to prioritize and then what do you begin doing to really move the needle around picking off the high value orders that really should follow those processes. So I think that's a whole rich new area of innovation that predictive analytics is really, I think it's been around for a long time. The legacy approaches, I think, have really been statistically oriented. Sample size, let's take the, I like to jokingly summarize it, let me take the smallest sample and draw the biggest inference from it. Let me do the least work possible. In the RapidMiner context, the more data, the better. Kill sampling, sampling's dead. Give me everything, the richer the data, the more likely we're going to have richer context and be able to make better predictive decisions. So that's something that I think is really a sea change in the way modern cutting edge data science platforms are really attacking this problem. Besides the fact that you can't, insight without action has no value. So it does no good to have a woohoo moment and you find the best predictive insight for particular customer segmentation analysis or basket affinity in a retail context and two guys in a trick duck know about that in your organization. You really now need to coordinate that insight both in the marketing area as well as the supply chain area, for example. And so I think it's that closing the loop that has significant business impact and that's what we're seeing and that's what's propelling our business. So there's a lot of action in this space. Yeah. You joined RapidMiner last summer. I did. What was special? May. May, excuse me. What did you see? What was it that really you decided to, all right, I'm gonna put a bet on this horse. Couple things, Jeff. So first of all, it's important to know I'm a Die Hard New England Patriots fan. So moving to Boston, I mean, there's nothing bad about that. No downside there as the Patriots repeat. So that was a big draw for me. But seriously, RapidMiner, I would say stepping back. I've had some experience in analytics-themed businesses. I was pleased to spend four and a half years with Tipco Software running a number of analytics-themed go-to-market product groups. Before that, I was the co-founder of another New York-based software company. I just stepped back and say really when you take a macro view of the opportunity, analytics has been around for a very long time. Now we're finally in an era and it picks up a little bit on what Dave talked about, particularly in the era of big data, we are now in an era where we can actually, nothing is impossible, let me put it this way, so you can actually take advantage of really taking all of the data in any form, at any scale, and you can answer any question. And when you think about how powerful that is and what RapidMiner can really do to propel transformation in your business, it's a no-brainer. I think for me, the opportunity to partner with Ingo and his team was just too good to pass up. He's a brilliant guy. He built the world's most recognized open-source predictive analytics platform and so we're really doing two things. We're both industrializing a product to have significant ubiquitous uptake across enterprise use cases and then we're really substantially increasing the velocity of how we go to market and we're doing that in a way that is completely disruptive, open-source innovation married to enterprise industrialization. It's too good to pass up. So what should we be looking for in the next 12, 18 months? What are your sort of objectives for the organization? What should observers like us be paying attention to? I think that what you'll see is we've been well-known to a pretty unique audience. I think we're gonna be aggressively establishing our ecosystem of partners in the big data space and I think you see some of them here today. Hortonworks, Tableau, PWC, many others will be joining us and we're aggressively investing in those relationships. I think it's fair to say that no one partner in the big data stack has all the goods. So I think it's very important for our joint customers that we're able to easily and seamlessly fit into the other significant investments they're making in data storage, in data visualization and I think predictive analytics fits neatly into a full stack concept. So I'd say that's one area that I'd absolutely call out. I think a second area is as I mentioned before our marketplace, we as an open source platform have tremendous R&D and innovation from our customers engaging with us across hundreds of clients and dozens of use cases but even more importantly, we don't have any delivery or consulting services capabilities. We rely on our external partners, our systems integrators and other partners to work with our clients hand in hand. So we're now investing in a marketplace where all of those partners can really reach out and get repeatability around their field solutions built with our product. I think that's a tremendous capability. We're already at something in the neighborhood of 15,000 monthly downloads today from a handful, 50 contributors in our marketplace. You'll see that number begin to move dramatically and you'll see the contributors into that marketplace expand pretty significantly. So I'd say that's a second area that you'll see in the next 12 months. Innovate, tap the TAM, you go deeper to the TAM and then leverage the ecosystem. Absolutely. Peter Lee, thanks very much for coming to theCUBE.  I think you just did, right? Well, it won't be pretty for you if you're Denver fan. So two or three interceptions, single digits on their side. I see a repeat of the Peyton Manning Indianapolis Colts game when we won it 20 to three, something like that. In the Super Bowl, it'll be Carolina. It'll be, again, it'll be another repeat.  It's going to be a lot of Superman action from our side of the fence. Love the confidence. I hope you're right. Peter, Lee, great to see that. Great count on it. That's a predictive. I love it. You better make it. Keep right there, everybody, we'll be back with our next guest, with our wrap, actually. This is theCUBE, we're live from Rapid Minor Wisdom 16, right back.


Don't believe or disbelieve anything we discuss in spirit science. Simply have your own experience. In lesson six I showed you an intro to sacred geometry, the flower of life. We looked at the genesis pattern and how it forms the fruit of life, the pattern that all physical matter in existence comes out of. We jumped out of the sacred geometric pool for a few lessons, and today we're going to dive right back in. I've mentioned quite a few times that within the flower of life are found the music and harmonics of everything in existence. Let's find out how that works, shall we? First I want to show you Phi and Fibonacci. It's important to understand for what we're going to talk about. I'll show you what you need to know to continue, and if you want to learn more in depth about these sequences, I will provide sources in the comments. Phi, also known as the golden ratio, or golden mean, is a very simple relationship. If you had a rod and were going to put a mark on it, only two places would mark the Phi ratio, which is here or here. The length of A plus B is equal to the length of C. This ratio is 1.618 0339 and continues on forever. If you multiply the length of C with Phi, it will create the exact same image, only bigger. C and D is equal to E. This ratio could then span on forever, going smaller and smaller or bigger and bigger forever. This ratio is infinite. It has no beginning and no end. It is also believed that Phi is the mathematical root of all other sequences. See, every mathematical sequence in existence needs a minimum of three numbers to figure out the sequence. Phi only needs two. It is the only one. Similar to how the circle and square are the source of all shape, but we'll get to that later on. The next thing that you need to know is that this ratio is found in all life everywhere. Sort of. By sort of, I mean it's really Feminacci, but we'll look at that in a moment.  Not only does each finger have its own ratio moving up each finger, which is Phi to the next bone, but it oscillates back and forth from the tallest finger to the thumb. You wonder why the human hand is like that? It's based on Phi. This relationship is found throughout the body in various ways, moving up the arms and legs in your face throughout the entire body. This is a Greek statue that accurately represents this. The Greeks were very precise when they made their art, because they understood Phi, Feminacci, and the importance of these sequences. When the Romans took over Greece, you could see the perfection in statues just completely disappear. I'm not saying the Romans were bad artists. They just didn't measure everything to the same caliber that the Greeks did. Here is the Phi ratio in butterflies. You can see this ratio everywhere, from the wing size to the body to the antennas. They're all Phi ratios. Here's dragonflies. It's the same story. Phi runs along the entire body and the relation to the body and the wings. Here it is in frogs. Phi is found throughout the body in relation to the head, to the arms, to the fingers, and so on. Well, what about fish? You'd think they wouldn't be found in fish. Well, here's three kinds of fish. Once again, the ratios are consistent. It doesn't just apply to these creatures, though. Regardless of what mammal, insect, avian, plant, or living creature of any kind, you will find this ratio one way or another. There's a reason for this, but we'll get to that in a moment. Let me show you the importance we used to place on this golden ratio. In ancient times, we built many structures based on Phi because we understood divine proportion. This is the pagoda of Yakushiji Temple in Japan. It's built with these same mathematics, from the doorway to the ball on top of the temple. It is a structural embodiment of the proportions that all life holds. The Parthenon in Greece also has the exact same mathematical structure, but even more. I recommend watching Nova's Secrets of the Parthenon if you wish to learn more about this, because the stuff that they find is really cool. The Great Pyramid Giza also has these proportions. They're incredibly precise, perfect in every way. You'd think that by building these structures using the logical and mathematical proportions so carefully, that they would hinder the creativity behind these buildings, but they really don't. In fact, the left brain understanding all of this can even enhance creativity if used correctly. It makes me wonder about all of the world-famous buildings of the modern world. Could Phi be a large factor in what makes them stand out? Let's move on to our next sequence, which is called Fibonacci. Now, the Fibonacci sequence is life's way of creating the golden mean. Allow me to explain. This sequence is continually made from adding the previous number to the current. One and one is two. Two and one is three. Three and two is five. Five and three is eight. You can see how it continues. Now, what most people don't know about Fibonacci is that it actually continually strives closer and closer to the Phi ratio. By dividing the current number into the last, you can see this happening. One into one is one. Well, that's not close at all. Two into one is two. This time, it's over Phi, but closer. Three into two is 1.5, which is under, but closer still. Five into three is 1.666. This time, it's over, but even closer. Continuing with that, it's 1.6, and then 1.625, 1.615384, 1.619048, and so on. It continually oscillates over and under the Phi ratio, never quite making it there, but continuing on closer and closer every time, until eventually you can't even tell the difference. Because Phi is an infinite number, this sequence will go on forever. Let's look at some spirals in nature, another way that Phi and Fibonacci can manifest. This is a nautilus shell. Many people will say it's Phi, but it's really Fibonacci. See how when it's in its earliest form, it's crude, not smooth or anything? One look and you can tell that's not Phi, but as it goes out farther and farther, it gets closer and closer to Phi. It becomes a nearly perfect Phi spiral by the time it's all the way out here. This also happens with sunflowers, pinecones, and many plants in nature. In many cases, such as the pinecones and sunflowers, it flows in a double spiral or more, much like the spiraling arms of a galaxy. From the microcosm to the macrocosm, spirals are always present. So Phi is basically source, or spirits, or God, in a mathematical way of thinking. The math of God. Don't forget that this sequence is an intimate part of nature itself. I'm going to call it source. It is the source of all mathematical sequences and all life in existence grows based on Phi. However, Phi has no beginning and no end. Life doesn't know how to deal with that. It's like Source says, go and replicate this, and life says, we don't know how. Because life doesn't know how to create from something that has no beginning. So it creates the Fibonacci sequence instead, which has a beginning, but starts out crude, very basic, and then continually goes closer and closer to Source, becoming more divine every step. It does take steps too, which actually has quite a bit to do with evolution. Let's move on for now, though. The only other sequence you need to know for this is binary sequences. This is a sequence, like 2, 4, 8, 16, 32. We're just doubling the last number instead of adding it to the previous one. We're all very familiar with this. Binary sequences are found in life as well. For example, mitotic cell divisions are binary. We go from being a single cell being to having over 100 trillion cells in only 46 divisions. Binary sequences are also how computers work by turning on and off chips. Computing at its core, anyways, is binary. Okay, let's move on to something different for now, but what we just looked at will reveal itself in time. This is how a polar graph usually looks, with 36 radial lines in 10 degree increments, representing the 360 degrees. Then, concentric circles are drawn, each with the same distance away as the last, creating eight equal demarcations as the one before, counting the inside circle as one. Think about what this represents, too. It's a two-dimensional drawing of a three-dimensional sphere, one of the sacred forms, by projecting it onto a flat surface. This is also called a shadow form, and casting shadows is a sacred way to obtain information. Also, a polar graph has both straight male lines and circular female lines, both male and female energies interacting at once. If you plot a golden mean spiral at zero degrees on the polar graph, it will loop all the way around before hitting zero again, exactly at the eighth circle. You'll find that this golden mean line crosses five specific places as it goes out. These places are where the female circular lines meet the male lines. It crosses at 120 degrees, 190 degrees, 240 degrees, 280 degrees, and then it jumps to 360, or back at zero, depending on how you look at it. What's interesting about this is that it creates both a binary and Fibonacci sequence. Looking at the radial increments from the center, it crosses at one, two, three, five, and eight. Well, that's Fibonacci, but it also crosses at two, four, and eight. Well, that's a binary sequence. We're going to look at the binary sequence in particular, though, because what you find is very cool. If you draw lines from the outermost circles on the lines where the binary sequence was formed, you get this image. It is an equilateral triangle. If you continue the spiral outward, it would continue to hit these exact same places, and continue to form larger equilateral triangles. Let's divert yet again to look at something very interesting. There was a man named Keith Critchlow who discovered something very important to understanding the geometry of music. First, he drew a straight line through an equilateral triangle, and then he measured from the middle of the center line and drew a straight line up to the top edge and back down to the bottom corner. Then he did the same, but passed through the center line of the top and back down again. He did this yet again on the other side. You can keep doing this on either side as well. By drawing this funny little form, he discovered something of great importance. He writes, Continuing in this way, each success of proportion will be the harmonic mean between the previous proportion and the total length, and all of these proportions will be musically significant. 1 over 2 being the octave, 2 over 3 being the fifth, 4 over 5 being the major third, 8 over 9 being the major toner step, and 16 over 17 being the half toner step. In other words, he discovered the geometries of music, or at least one aspect of them. Then he tried measuring it in a different way, starting at a different point of the center line. At 3 fourths, he found the measurements were 1 over 7, 1 over 4, 2 over 5, 4 over 7, 8 over 11, and 16 over 19. All of these numbers are musically significant. This is very interesting. It means that the harmonics of music are somehow related to the proportions of the central line moving through a tetrahedron. Back to the polygraph, you can see that this drawing has a much greater value all of a sudden. Not only that, but it becomes even easier to make your measurements thanks to the polygraph itself. You can just draw a straight line through the drawing on the graph, and it will give you the center line. This information has been taken light years beyond what I just showed you though. A research team found that you can draw these lines not only from the center, but from any nodal points inside the upper half of the triangle, and you will come up with all known harmonics in existence. Basically, this means that anywhere the straight line and curve lines on the polygraph cross from 0 to 120 degrees and start making the pattern, you will come up with all known harmonic systems. Not only the western keyboard, but the eastern, and even many unknown systems that have never been used. As I'm not a musician, there's not much more I can show you related to this, but I would love to see what a musician could really do with this knowledge. How far could you take this? All right, I'm running low on time here, so I'll wrap up with this unraveling. Remember when we talked about spirals in nature? They often travel in twos. Usually this is male and female. So on this polygraph, if you're going to copy nature, you don't just plot one spiral, you have to plot two. When you do that, it gives you this image, which is a star tetrahedron inside of a sphere. We mentioned this in Liston 7, and this image is more commonly known as the Star of David. Do you remember the face on Mars? NASA obviously tells us that it's just a random formation on the surface of the planet, but right next to the face, there are also a few pyramids and other anthropomorphic structures. I know what you're thinking. Why on earth would I bring that up all of a sudden? Well, Richard Hoagland and his colleagues have spent a long time researching and deciphering a message on the surface of the red planet. Want to know what that message was? It was a star tetrahedron inscribed in a sphere. Holy balls, right? There's a link in the comments to a page with all of this information if you want to learn more. It's pretty crazy and very eye-opening now that we have this information about what this really means. Inside the star tetrahedron, another one fits perfectly. We can continue to put more and more star tetrahedrons inside or outside of the other star tetrahedrons the same way the golden mean spiral can wrap around the polar graph infinitely big or infinitely small. You'll notice that this smaller tetrahedron also happens to fit perfectly around this sphere. We'll check this out. If you put this same size sphere centered on the point of every single star tetrahedral point, guess what suddenly reveals itself? Of life. It's back. According to the Egyptians, as well as the Ascended Masters, this is one of the holiest, most sacred forms in existence. Of course, we already learned one of its informational systems in Lesson 6, and what you just saw was the second, only in reverse order. What this means is that all of the information of music, harmonics, sound, and spirals come out of this image. Not only that, but light and the dimensional levels work in the same way as harmonics, which we've already discussed in Lesson 2, 7, and 9, meaning that the geometric information about light and dimensions are also related to this star tetrahedron pattern. So just briefly looking at this image that we looked at in Lesson 7, this is the fourth unraveling of the flower of life. It is an infinite spectrum of never-ending fruits of life within more fruits of life. This is the unraveling of dimensions, so it makes a little more sense now, but I won't have time to show you anything more today. So what you just saw was the second unraveling from the third rotational pattern of Genesis, the geometry at the heart of creation.


Before Senator and former Attorney General of California, Kamala Harris was chosen as Joe Biden's running mate in the 2020 election, she played a role in a campaign to force a website called Backpage.com to stop operating on the grounds that it was used to facilitate sex trafficking.  Good businesses such as Craigslist understood how it could be abused and mishandled and they shut that aspect of their business model down. Backpage needs to do the same. We didn't cow tail. We don't cow tail. It would give the lie to our entire lives, our entire career of being journalists.  In the course of her prosecution of Backpage's founders, Michael Lacy and James Larkin, Harris spread misinformation about its practices. She co-filed criminal charges that were quickly dismissed but succeeded at garnering headlines and photo ops that raised her political profile. In reality, Backpage.com had become a powerful tool for law enforcement to catch sex traffickers because of the cooperation and commitment of the site's founders to the cause, whom Harris and many other state attorneys general and politicians had painted as villains. Harris had supported anti-sex trafficking bills when she was district attorney of San Francisco, but it was in October 2016 after she was elected California Attorney General that she co-filed criminal charges against Lacy and Larkin as well as Backpage CEO Carl Ferrar. Though accused of running a website used by sex traffickers, the charges were quickly tossed out because Lacy and Larkin were clearly protected by Section 230 of the Communications Decency Act, known as the Internet's First Amendment, which says that an online platform isn't responsible for many types of content posted by its customers. According to Lacy and Larkin, the charges were so thin there was no reason to file them, except as a stunt to raise her public profile. She does this right before the election, and inside the courtroom there is a jail cell. They filmed us in the jail cell and then broadcast it on the evening news. So Harris gets to have her name in all the papers right before the election, saying that she's the one who helped take down these people that everyone for years has been characterizing as these big evil sex traffickers. It was a publicity stunt. Lacy and Larkin spent four days in a Sacramento jail. She knew that Section 230 barred her from bringing these charges, but she brought them anyway. And of course, a judge threw them right out. So Harris filed another set of charges against the three men. Harris was trying to say that Brauer and Lacy and Larkin buy virtue of having this site and knowing that sometimes, you know, bad things happen there, that they were guilty. These other pimping charges later get dismissed too. Journalist Elizabeth Nolan Brown writes about sex workers in the criminal justice system, and she's been covering the lawsuit against Backpage, which recently got rescheduled to 2021 because of COVID-19. Brown revealed secret Justice Department memos showing prosecutors spent years trying to build a child sex trafficking case against Backpage, but failed to uncover compelling evidence of criminal intent or pattern or reckless conduct regarding minors. Instead, Justice Department officials found Backpage was remarkably responsive to law enforcement requests and proactively sent ads containing minors to authorities. The memos revealed a world far outside the characterization Harris and other politicians, attorneys general and activists had been pushing for years about Backpage. To be clear, this is a crime. It is a crime that is rightly punishable by incarceration in prison. On January 10, 2017, Harris, who had been elected the junior senator from California, participated in hearings on Backpage. These individuals must be held accountable. These allegations must be given voice. And we have to do all that is right to make sure that we as a civil society protect always the most vulnerable among us and not take advantage of them, assuming nobody will care. These hearings have made clear we care. But as Harris and other senators characterized Backpage as complicit in sex trafficking, Justice Department memos reveal law enforcement officers the country over were working with Backpage employees, taking seminars on how to use the site from Backpage lawyers and coming to rely on the site for sex trafficking investigations. A 2012 memo described the Backpage data as a goldmine of information for investigators. So many different people put on this huge show of making them the villain in this. A lot of people in government actively made the calculation to make life more dangerous for both sex workers and sex trafficking victims in order to satisfy this crusade that they were on publicly. On April 6, 2018, the FBI raided the homes of Lacey and Larkin and accused them of running a website that facilitated prostitution. Their trial is scheduled to take place in January 2021. It's hard to make us feel guilty. We're not guilty. We're not guilty. You can't talk me into it. It's an evergreen political issue. Always works. They're waiting to be governors or senators, presidents. That's what that was all about.


Mom hears noises in the ceiling, finds man she split with 12 years ago living in her attic. It was like a horror movie coming to life. A part of her even wondered if she was having a very lucid nightmare. There was no other way she could explain what was happening. But it was. Not fiction. He had been there, in her house, for who knows how long without her having the slightest clue. And when the full implications of this fact started to dawn on her, she couldn't help but panic. Even before this incident, life hadn't been easy for Tracy. She was a single mother of five living in Rock Hill, South Carolina. Throughout her life, she had struggled to make ends meet and provide for her family. Some. Of her children were grown now, but they all lived together in the family house to cut down on costs. Despite their circumstances, they had a happy home life. But then something started happening that threatened all of that. One September day, Tracy started hearing strange noises coming from the attic. The first thing she thought was that there might be an intruder, but she was always very careful about locking all doors and windows. She did this as a precaution. Because they lived in an impoverished part of town and break-ins were quite common. She didn't see any signs of forced entry, so she chalked it all up to her imagination. But soon she began to wonder if something else was going on. Throughout the following days, Tracy kept hearing random sounds coming from up above. She asked her kids if they had been playing around in the attic, but they all said they hadn't. She believed them the attic was. Dark and musty and not a fun place for kids to play in. She rarely went up there herself, except when she had something she wanted to store. But as the noises continued, she came up with a different theory. One day, as she was cleaning around the house, Tracy realized the sounds in the attic were also moving from one room to another. Then it came to mind that the strange noises might very well be coming from a possum or raccoon that had somehow found its way inside her house. She figured she would need to call animal control. However, it was a Saturday and they didn't work on weekends. So she decided to wait till Monday. But the presence in the attic seemed to have other plans. That night, around 2.30 in the morning, Tracy was awakened by creaking sounds in the ceiling. But this time, she also heard soft thumping sounds on the floor of her own bedroom. She looked down from her bed. And in the dim light of night, she saw a number of nails scattered on the carpet. She realized the nails were popping out from the ceiling boards. Her heart stopped this was no possum or raccoon. Tracy recalls thinking there was some poltergeist stuff going on. She was too terrified to go to the attic to investigate, so she threw the blanket over her head and tried her. Hardest to go back to sleep. But she knew she had to do something about whatever entity was occupying her attic. She couldn't keep living like this. The next morning, she took action. In the morning, Tracy was relieved to find out her nephew was visiting her two adult sons in her house. The presence of the three young men made her feel comforted. She told them about the noises. In the ceiling and asked them to check out the attic. The men walked upstairs while Tracy waited right outside the attic door in the hallway. None of them were prepared for what they were about to find. Once the young men were inside the attic, they realized something was very wrong.  The old coats. And jackets that Tracy kept up there for storage were all packed up in one corner of the room, near the heating unit. And then they saw it was a body. As soon as the men started moving around the attic, the body in the corner stirred. Apparently, he had been sleeping there before they came upstairs. He looked at them, and they looked at him, and they all. Frozen surprise for a few seconds. Then the man jumped up and rushed past them toward the stairs. Tracy caught a glimpse of him as he escaped, and she had a terrible realization she knew that man. The family called the police, but the man was long gone by the time they arrived. But that was not the worst part. Tracy recognized the intruder. Over 12 years ago, he had done some housework for. The family and Tracy and him dated for a brief period of time. But he had a history of criminal behavior, so Tracy broke up with him. The man didn't take the break up well, and so he retaliated. The man wanted to get back together with Tracy, but she refused. Then one day, he stole her truck. He was later caught and sent to prison. But while he was locked up, he kept harassing Tracy. He sent her. Letters telling him he had changed and begging her to take him back. After he was released, Tracy heard the rumor that he had moved to Charlotte, North Carolina. But she found out the truth in the worst possible way. Police responded to the call and searched the attic where the man had been found. It appeared he had been living there for a couple of weeks. He had packed all the old coats and jackets into the. Heating unit and was sleeping in the heating unit, explains Tracy. They also found a number of plastic cups where he had been relieving himself, which explained the bad smell. But an even scarier discovery soon was made. Investigators discovered that the intruder had rigged the air vents on the ceiling so he could look down into Tracy's bedroom. Tracy couldn't contain her horror at the thought of his spying eyes. It's got me flabbergasted, she said in an interview. How can you look at someone through an air vent? What was worse, they still had no idea how he got inside the attic, as the only door that led there was in the hallway between her kids' bedrooms. And the threat remained. Despite police knowing his identity, the man was able to evade authorities and remained at large. Days later, Tracy thought she saw him again near her home, but police weren't able to find him. She wants justice. I want him to be charged with it, she said. It could be somebody else he does the same thing to, but she might not be so lucky.


All right, so welcome. I'm Alicia. I'm on NMDC, Montana, and Julia are here. They're also on the NMDC project so they can help field any questions. And we're going to talk about exploring neon data with NMDC tools. Can people use the Zoom reactions to say whether or not you know what the NMDC is? Montana, you know what the NMDC is? I had to find my button. Well, for those of you who don't, you hopefully will know more after. Has anyone here worked with neon data before? Does your lab collect standardized metadata? If you do lab work. And so one of the main reasons NMDC exists is reusing metadata is hard. So has anyone else, has anyone here ever tried to reuse someone else's data? Thumbs up or thumbs down? How did that go for people? They're getting a thumbs down. We're getting a surprise face. A cold face. So in general, it can be challenging to reuse someone else's data. That's part of what an NMDC is hoping to make less painful. So the agenda today is we're going to talk about what the NMDC is and talk about our data portal, which is one of our web UI applications. Then there'll be a 30 minutes, probably 20 minutes to do it and 10 minutes to go over a data portal activity where we'll look for data on the data portal. And then we will talk about retrieving metadata programmatically via the API. And then there's 30 minutes at the end for a discussion questions feedback. Since the group is pretty small, we could definitely adjust this if people have different interests, but this is the agenda that we put together. So after the seminar, you'll be able to understand how neon and NMDC are collaborating to improve fair data. So what the NMDC offers, why fair metadata is important and where to find neon data on the NMDC data portal and the NMDC API. These are the, this is just kind of a reference slide. These are the two resources we'll be talking about today. So the data portal and then the API for programmatic access. So now I'll talk a little bit about what NMDC is and what we're doing with metadata. So the NMDC is a sustainable data discovery platform. We're really focused on fair data. So making data findable, interoperable, reusable. And we're three national labs that have come together to do this. We're in the fourth year of the project and we're really focused on enabling people to find multiomics microbiome data. So the vision of NMDC is to connect data, people and ideas to advance microbiome discovery. And we're doing that through infrastructure standards and community building. There's three product initiatives underpinned by an engagement strategy. So Montana Smith is on the line and she is the lead for the submission portal. So that's a UI where you can enter information about your study and the bio samples that you've collected in a standardized format. Julia is online. She's the product owner of NMDC Edge. And she, and this is a UI where you could run the standardized workflows. I'm the product owner for the data portal. And so that's a place where you can access and discover microbiome information. We have a couple really key partnerships. So we work really closely with the Joint Genome Institute and EMSL. Those are two department of energy facilities that generate a lot of the omics data. So JGI generates a lot of the sequencing based data and EMSL generates a lot of the mass spec data. We have two engagement programs, the champions program and the ambassadors program. And we work with people to improve data standards. Sometimes these folks host workshops for NMDC tools. There can be funding to travel to conferences. So if you're interested in information about that, Julia, I can field any questions there. And then we have a number of key strategic partnerships. What we're going to focus on today is the partnership with neon. Now I'll talk about our data portal and how we're using it for data discovery. So meta meta data standards are important because data, it's difficult to reuse data from different labs if they're not using consistent field names, measurements, or units are unspecified or terms are not being consistently used. So part of what NMDC does is makes terms, field names, units, etc consistent. So data comes in and is formatted to be consistent via the submission portal and then that data, which is now consistent is then discoverable within our data portal. So this is just a screenshot of what the portal looks like and then we'll walk through some of the features to describe them in more detail so that you guys can do the scavenger hunt activity. So on the left panel is a faceted search option so there's several pieces of information that you can look on some of the popular and very basic information that you could sort on is information on the samples so things like the depth that the sample was collected when the sample was collected geographic location either by latitude longitude search or by the location name. We also have a map feature where you could zoom in on different areas and then click search this region and that would populate the latitude longitude coordinates. We have a cake search for functional search so you could enter in the name of a cake term or type in an enzyme name and then select from a dropdown. This would return metagenome metatranscriptome or metaproteomics records that have a hit to the cake term. There's two different systems that we use to support kind of habitat or environmental information. The gold pathways is a five level system that's from JGI. So a subset of the samples to have this information populated and then we also support a three level system to provide environmental context terms. These terms are required by the genome standards consortia which is a body that governs metadata requirements about genomics information. And so we also require this so this will be available this is available for every sample and you can search on this. This is really useful for searching across studies or subsetting data within a study. You could search by what type of omics data you have so there's a couple different options here. On the left panel you could search by the omics type. This is going to be an or query so if you said you wanted metagenome and natural organic matter. It would be the super set of both of those types. On the right we have an upset plot and this is going to be an and query so 134 samples have both metagenome data and natural organic matter data. Below kind of the map and the collection date filters is going to be information on the NMGC studies. So you can click on this button here to filter records that are only part of this study. Or you could click on this arrow over here and that would lead you to a detailed study page which has quite a bit of information. So if we go there. This is an example of the study page so it has a title, a description. This has what type of omics data it has and how many of those it has. There's information on who's in charge of the project, we have links out to some of the neon resources, who's on the team. There are persistent identifiers throughout an MDC so we create identifiers from everything from studies bio samples workflow runs and then identifiers for files that get created as the output of workflow runs. Information on funding sample counts. If there's things like related publications, etc. links to other resources. If you scroll down below the studies you'll see the samples that are part of that study. So similarly you could click on this and navigate to the sample details page, or you could click here and that would expand and show you the output from the workflow results from the analyzes the metagenome raw data. So here's an example of a samples page. Good see basic information about latitude longitude. When it was collected, what the environmental context terms are over here we have a field called bio sample categories. So we do have some studies within an MDC where the samples come from neon sites, but weren't collected by the neon organization so other PIs have come onto a neon site and done some of their own sampling so you might be interested in all the samples that are from neon sites, regardless of the type of omics type or regardless of who collected the samples and this would be one way where you could return those samples neon, neon soil sampling protocol pool samples at a plot level. So we have 40 by 40 meter plots on different sites and they take one to three cores, divide them by the soil horizon layer into mineral or organic, and then pool them and so what we listed here is this is the bio sample. So we have two other bio samples that are from that plot that got pulled together for the metagenomics analysis. We click to expand and see some of the workflow data. You can see what, what type of workflow this was so here we're doing read quality filtering, metagenome assembly annotation we also do a brief base taxonomy analysis. This is supposed to make the data more accessible not everyone has access to some of the compute resources that are required to analyze metagenome data. And so if you wanted to you could put in whatever filtering you wanted and then you could download download that data via the UI. So I'll walk through an example of just like what some of the counts look like and what they mean on the data portal so things hopefully make a little bit more sense as we're doing the exercise. So here we've applied a latitude longitude search for Hawaii. And 90 is the number of samples so everything here. The fact the faceted search is always first going to return the number of samples. The same in the map appears the number of metagenomics records that are associated with those samples so this should be about three to one. This is the number of samples that use that omics type or that combination of omics type so in this example we only have metagenome results down below is going to be the number of studies that have been done in this region. And then here is a separated by each study and omics type how many metagenome records are there. This appears how you're going to clear your search filter so you just click on this icon and that would work that's going to reset the data portal. This is going to be important in the data portal activity. Now, it's time for the activity. So there's a QR code, or you can follow the link. This is the link to the data portal. And then this is the link, the link in the QR code for the questions that we're trying to answer. So, we're going to probably take about maybe 20 minutes to do this, and then we'll go through the answers. Or we could kind of go through it together I know there's only handful of people here. Does anyone have a preference of doing this together versus individually. It's a group maybe it makes sense to do it together. Okay. So let's go. Pull up the questions. These are questions. And then I'll just kind of I guess toggle back and forth so there's three neon data products that have metagenomics. So there's soil metagenomes, benthic metagenomes and surface water metagenomes. And NMDC is currently hosting the soil metagenomes and the benthic samples and then we're working on getting the surface water samples in. So this exercise primarily focuses on the soil samples because that's what the science talk was on last month. So the first question is going to be how many samples are from the study entitled National Ecological Observatory Network soil metagenomes. And then this is the neon data product ID. I'm just going to highlight this go over to set this here. I'm going to type over here. See if I can find the right study. So I scroll down it has selected this, it's filtering for this study. And so this is going to be the number of samples of 4,443 samples are associated with this study. So all of the samples I think failed in library construction or whatever so the number in the upset plot here is going to be a little bit different. So there's 4,411 records that are associated samples that are associated with the metagenomics sequencing record. Can I ask a question. Yeah. What's that 1560 number that appears with the study because it looks like that's not the number of samples. This is the number of metagenome records so this is. So, if we, if we look back at the, what happens with the pooling one to three samples, typically three samples per site get combined together for the sequencing. Okay, so that's what this count is. So the system retains the fact that those came from multiple samples and that's correct. Yeah, higher. Okay. So if you, if you look at this record. This is, and you click on the sample you can see this is the sample and this is the other sample that got combined with it. So what's really on names there are samples for the soil samples is it's the site, the plot, whether it's mineral or organic horizon from the from the core. And then these are XY coordinates within the plot, and then the collection date. So you can see here that the sites the same the plots the same, the soil horizons the same. There's different, they're different coordinates within the plot. And then they have the same collection date so these are these two samples were pulled together. Yep, and the DNA was extracted a library was made, and then sequencing was done. Cool, thank you. So here you can also see that this is the, this is the analyzed data. So then we picked up neons raw sequencing metadata, sorry raw sequencing files, ran quality filtering assembly, etc. So this is the sample that this is for. But this is the other sample that's in there. Based on the NBC identifier but if you click on this, you'd get to the other. This is the other study, the other sample page, but they're linked. So this is it's kind of nice to be able to to see how the how the records tied together. Any questions on that. Okay, so we have 4,443. That's the answer to that. Let's see. What type of omics data does an MDC has have for this study. So there's a couple different ways we could look at this. We can just look here and see there's only metagenomes, or over here, metagenomes or up here in the bar chart so it filters out and there's no match for the other omics types that we host. Or you could go down here to omics type, and also see that there's only metagenome data. The next question is, what instrument types were used to generate the data for that study. So we're going to go back here. And one of the things that you can filter on is the instrument name. If we click on instrument name, it's going to show the different instrument types that were used. So there, it's been sequenced on three different aluminum platforms so that next to Nova Seek and High Seek. These are the, the samples that were most recently sequenced at JGI. So these are of much higher depth. So therefore have like larger assemblies and are going to have more metagenome bins. So we're going to look up what the environmental, local environmental context term is for one of the neon samples. So if we scroll down and we go back to one of the samples we were looking at. So we use, these are terms specified by the genome standards consortia and it uses the Envo ontology primarily, which isn't what neon uses natively. And so what we've done is we've created a mapping table between the national land cover database terms that neon uses and the Envo terms. And then that makes the habitat descriptions descriptive terms interoperable with all the other samples that we have. So here are the environmental local context is area of evergreen forest. Everything's labeled as a terrestrial biome. All of the soil samples are labeled as soil and then their local environmental context term is going to be different depending on where the sample was collected. And then we learned about the related samples so what samples are related to that sample. In this case there's one other related sample. It's the other one from the same plot. So now the next question is to get the NBC study identifier for for this so we would want to go over, as well as the funding source so we'd go over to the study page. There are several different ways you could do this we could go back to where we were to the main landing page or this, the study identifiers are listed here and this is a link out to the study details page, the click here. So this is the NBC identifier for this study. And then this is the NSF grant number. So I'll put an example of using the some of the map and geographic location features so how many samples are from Puerto Rico. So I'm going to go back. I'm going to clear all of my search by clicking up here. And then I like to use the map feature so I just zoom in on Puerto Rico. So there's a couple different places where we have samples from on Puerto Rico, but to say search this region. And you can see that there's 364 samples that are from Puerto Rico from two different omics types. So this is, we have metagenome data. We also have natural organic matter data. We scroll down we can find out that these are from four different studies. So grow was a project to catalog watersheds globally. And so there's, we have two metagenomes and 10 natural organic matter matter projects. This is a project to study carbon carbon redox in a forest in Puerto Rico. And then these are samples from both neon benthic samples and neon soil metagenomes. The next question was how many of those samples are from how many of the samples from Puerto Rico are neon soil samples. So to do that we would click back over and then just click here to apply this study as a filter. You can see it adds it as a filter up here. And then our results drop down to 194 samples so 194 soil samples from Puerto Rico. Alright, next we're going to look at some other studies so we're going to look at this study which looks at permafrost in Alaska. I'm going to go back and clear all the search terms. And then I'm just going to search for this study title. So this is our study selected. So what type of omics data do we have so this is a natural organic matter. You have 241. It's one to one here the samples to the data, the instrument data. And then if we click on one of these samples will be able to figure out whether or not it's from neon so this is not a neon this is not a neon data product. This is individual PI. But they are doing sampling from a neon site so you can see that from the biosample categories. And then the last question was just to figure out how many samples of an environmental local environmental context of area of evergreen forest. So if we go back to the main page clear all of our searches. So we would go to the info section and then look. Click on local environmental context and put in the term. And there's 1266 samples that are that have this environmental local context from a couple different studies just kind of fun. So that's the end of the training on the data portal. Were there any questions before we talk a little bit about the UI. This is great I I didn't realize that the samples that were collected at neon sites but not by neon were labeled that way. So that's awesome. Thank you. Yeah, this is something that we did for essay. And actually I'll show you. There's no way currently right now to search. To get all of these via the UI, but I will show you how to do it with the API. All right, so I'll go through the API slides and then we'll we can go around a little bit with that. So back to the back to the slides. So API stands for application programming interface. It's just an intermediate so that you don't have to know what the technology stack is on the back end. It's a pretty common analogy online from what I found that this is like comparable to going to a restaurant and talking to giving your order to the waiter and the waiter communicates with the kitchen. And then the waiter brings back your order. So it's just an intermediate layer that is consistent and that you can, you can access programmatically. This is how you can get to that NBC API. So there's a web link and the QR code. The swagger UI does have some auto generated documentation that can be pretty minimal. So we've also put together some more user friendly kind of written by human documentation with some examples that might help you if you're if you're having some questions. And then depending on what kind of endpoint it is, those are color coded. And that's kind of just automatic. So get endpoints are used to retrieve records. So that's mostly what we're interested in today. Internally, we also have some post endpoints where we can upload information. When we're adding records, our biosample records workflow records, etc. But we're going to focus on some of the get endpoints today. So a couple of the ones that we might be interested in our endpoints about studies and or biosamples. So these two endpoints here specifically like just take an identifier. And then these two endpoints are, you have to know a little bit more about how you might want to query those. The study endpoints. We can take the study ID that we got from the data portal exercise, put it in here, and then get all the metadata back about the study. So if you could come in here, there's a button over here that says try it out, you would put in the study ID click execute, and then it would return a document adjacent document. And then you can, you could download that, or you can use curl or Python request library, or our whatever whatever your preferred choices. So here's an example that's a little bit more complicated. So part of is how we aggregate is how we say that biosamples come from a certain study. So if we were looking for all of the, all of the samples that came from the neon soil study. This is what the query would look like for this endpoint. So you would say part of colon, and then the mdc study. And then you can get back adjacent documents that had some metadata and then some results. So this says what the filter is. This is how many samples there are so this matches what the data portal, what we found in the data portal. And then by default, it's going to return 25 records you can change this if you want. So you might have to do some paging so you'll see an example of that in the Jupiter notebook that will go over. And then in the results is where the first 25 records are and then you would have to keep fetching them. I'll declare this is what I was talking about. So this is, if we wanted to look at a different study, or just in general look at any samples that come from neon sites. On our end that you would use the field name of biosample categories and then a value of neon to do that. So here I've intersected it with a search on another study so I got that identifier for the 1000 soils research campaign. This was a project out of emzel to catalog some soil samples across the US. It was a pilot study for a new, a new call that they have called Monet, which is to catalog soil samples across the US. So you could do this as a, as a combined query or just use the second part of it, but how we're going to do a more complicated query here is you just connect them with a comma. So here we're looking at for samples that are part of this 1000 soils study that have a neon biosample categories of neon. So this would return all the records just from this study. If we just put in the second half. Oops, if we just put in the second half it would retrieve any samples from any studies that are from neon sites. The NMDC schema is written in a framework called link ML and the lingo, the terminology is a little bit different. So I'll talk about that a little bit, but there are some really nice documentation where if you were using the API and you get your JSON back and you're not sure what some of the field names mean you could come in here to look up the documentation. Next, come to the repositories documentation page and type in what the field was and then you could learn more about that the link ML nomenclature is slot. So that maps to what you would call like a field in a JSON document. So here I pulled up the documentation about pH so we can just see what this kind of looks like. So this is a JSON record for a biosample from 1000 soils that's from neon. It has a pH of 6.5. So, let's say we're interested in learning more about how an MDC defines pH. This is a pretty basic field but it's just illustrative so here would be what the slot name is the pH below that is the description for the slot here applicable applicable classes would tell you what type of records. This, the slot applies to so here it's a applies to biosamples. And then you could look up if there's any restrictions on what the value is under properties. So maybe this needs to be a Boolean or you know an integer or a string or whatever. So now we'll hop over and look at what kind of putting together the API with using Python and a Jupyter notebook. The question that we're going to try and answer is, do the mineral or the organic soil horizon samples have a higher pH at the Wind River experimental forest, which is in Washington. So I put a link, tiny link here. And Jupyter notebooks that was developed internally by NMDC staff there, there's not enough time today for us to kind of write this together and so this is kind of mocked up, but gives you some idea of how, how you could use the API and Jupyter notebooks. Just wanted to note that you could also do this with the neon R packages but we just wanted to illustrate how you do this using NMDC directly. And then there are going to be some things like the workflow results those are those are hosted in NMDC and been pushed over to JGI. So there are some things where currently the neon R packages wouldn't be able to provide the information. But for this you could definitely use our packages so this is just illustrative.  This is what your API request would look like so this is the base API URL. This is what you're filtering on the name study study name, you're filtering on the neon data product ID. And then here we're like looping through, remember I was saying that there's a max number of records that get returned. So we're doing this in a while loop to fetch all the records. And then we're parsing through and getting the geographic location name. We scroll down a little bit. We can get to the map. So this is this is pre populated but it's it's rather complicated. But, so if we zoom in on Washington, there's two sites so we'll have to click and see which one is Wind River. This right. Abbey Road now that's not the site we want this it is. So this is the site that we were interested in so Wind River experimental forest. And we've plotted the pH over time so by the collection date and then colored it by the soil horizon. So here you can see that in general the mineral horizon samples have a higher pH. Any questions. Okay, let me switch back over. So, here and I was able to export that plot and copy it in here. But you could look at, you know, other sites. You can do whatever you want in the Jupiter book. This is a link to the repository the MMDC repository that has some of these notebooks. So if you wanted to look at the Jupiter notebooks that are pre pre run pre compiled you could do those here or you could open them in a Google lab notebook yourself. If you wanted to make edits you would have to clone the repo and and and go from there. So that's kind of all that I had. And now we have time for questions discussion we do have a survey that we hope you'll take. Just a little bit of feedback to let us know what you learned what you thought was valuable. What else you'd like to see from the NBC neon collaboration. Yeah. So let's see who's there's a couple people here from the NBC team. On Tana's here. I mentioned she's in charge of the submission portal. Julia is in charge of MMDC edge and then Catherine and Bryn did most of the Jupiter notebooks. So if any of us could be old questions.


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Hi everyone, Joe for Jasper's casebreaks.com We did some flawless earlier today now. We're gonna do a case of NT love it 2022 panini National treasures baseball four box picker team number 39 Big thanks to this group here for making it happen. Thanks to everyone who bought their team straight up Which made the random number block? Pretty pretty affordable considering the teams that were in there and it sold out quite quickly All right, there's a now. We don't have any more flawless baseball, but guess what? We do have more NT. I'd load it up another case just before we started this video, so Get after it check it out Wasn't that a movie Carlitos way? Wasn't that a movie with Al Pacino? Maybe it wasn't Victor's asking would you rather that's a good quote would you rather have a case of NT baseball or one box of flawless baseball that's like Do you want to would you rather have a fight with 100 Duck-sized horses or one horse-sized duck? I suppose you would lean towards whatever the value is, but if I mean I guess for the sake of the argument We're we're thinking that the that the value is Priests is somewhat similar and I just confuse myself to there There's an old argument about like who would win a fight anyway I think I would go with uh, I think I would go with flawless. All right, there's Miguel Tejada It's a tough call though five out of 25 That will be for Ed P in the A's Got Hans Krauss 53 out of 99 that's for the Phillies that'll be for Phillies are a number block team So if you're not familiar we go by that digit right there, so that's Philadelphia three and that is for For Steve Herrick number three Steve H stay hey The stay hey kid. There's Jordan Alvarez 43 out of 99 Houston that's for Ed P Speaking of fights. There's a good sit-down restaurant here with wings and the hottest flavor sauce is Chuck Norris I'll bet it packs a punch Or just has a really good kick to it. There's Kyle Lewis Colossal Jersey and Otto 14 out of 99 That'll be for the Mariners Mariners are a number block team that goes to Seattle 4 And that's for Nancy with the number 4 Last Bob Mojo to mile-high city die-cut materials interest Ryan of a lot of 14 out of 25 That's for Ed P in Colorado. I've got a thick one here. That's Logan Webb 1 out of 10 Jersey and autograph Might not fit into a 180 top loader No, it's gonna fit perfectly Who's got my rivals the Giants the Giants are a number block team. So that goes to Giants 1 And that'll be for Billy got a nice patch of autos. I'm nice color here John Haseley 16 out of 25 That will be for Stacey can city. It's for Stacey and Then Ken Griffey Jr. Nice five out of 25 No, her name is Marin not Mariners That goes to Mariners 5 for Stacey the book Harry Walker 25 out of 49 legendary jumbo materials Harry Walker, let's I don't know too much about Harry Walker. Let's let's learn about Harry Walker Harry Walker is also a business management consultant in New York City. I don't know if that's related but Harry Walker for 1918 died 1999 Professional baseball player coach and manager known by the nickname Harry the Hat Played as a center fielder in Major League Baseball between 1940-1955 Most notably as a member of the St. Louis Cardinals With whom you won two world championships and was the 1947 NL batting champion. It's pretty good. It goes to Patrick In St. Louis. Nice And we got Ronald Abolanos 21 out of 25 Jersey and autograph for the Royals for Stacey All right, that is box one Watches Vince Kelly special a little bit later. I think I've seen these before already All right, we're gonna watch some PJ tour golf in the back are all right Next box.  That's for Aaron Miller in the Pirates Harry Walker is in the fake name that Sasquatch chooses when he checks the totals Doesn't want to be bothered 32 out of 99 like in it in the TV show wasn't there a TV show with a Sasquatch? 32 out of 99 Taylor Tremel Seattle That's Seattle 2 for Steve and Yuri Perez 85 out of 99 That's for the fish Kevin with Miami. Oh Was it Harry and the Henderson's wasn't it it wasn't a tee I thought it was a TV show All right more We got Eli Morgan 2 out of 10 nice big patch nice order this I don't think is gonna fit into a 180 top or those are our PAs 10 not to That's gonna go to Roger and the Guardians Cleveland. This is for you And we got some Pudge Von Rodriguez Hall of Fame signatures Jersey and autograph Rangers It's gonna go to Ed P and Texas 20 out of 49 And we got dual signature materials 17 out of 99 It's Matt Manny on one side. It's Shane Bos on the other side That's one happy person one sad person Tampa Bay is a number block team So Tampa Bay 7 is in on it Billy and Detroit Ed P last Bob Mojo We'll do that randomizer at the end. There's Melot 73 out of 99 for the New York Baseball Giants That will be for Giants 3 San Francisco 3 Steve H. San Francisco 3 you think one person will be only slightly disappointed my top might I was thinking also All right. There's Dan Vova 16 out of 25 That is a Mets edition going to John John Heasley 22 out of 25 for Kansas City. Haysley. Heasley Halsey That's for Stacy and the Royals Well, my tower wants to know what's the best card you've won or lost on a random to 10 out of 25 Melot Another giant for number zero Nancy number zero old school Jersey. They're nice An NT you won a one-of-one Ryan Sanford Frank Thomas. Wow. It's Patrick Sandoval four out of ten It's a nice penmanship there. I feel like he uh Did you know I feel like it did he have a decent world baseball classic? Draft into my fantasy team too, so Hopefully it does well Angels that'll be for James and the halos and here is Daniel Lynch 98 out of 99 for the Royals It'll be for Stacy Victor you got a honus Wagner cut auto I think Mike was talking about like a two-player card if you're on one side of a two-player card Or a multiplayer card. I guess here's field pass Juan Gonzalez 43 out of 49 the most when you're still go you lost on the random That's rough. Why I think random players because otherwise then you're just asking. What was the? What was the card you didn't get in a random team break or something like that? I like the idea of like if you were if you had a multiplayer card like what what was the best Well, what was the heartbreaking moment? What was the best moment? Otherwise someone can just be like oh, I was in a random team break And I just didn't get randomized the best team and that best team got the best hit It's Colton Walker 20 out of 25 for the Rockies It'll be Fred P Here is Paul Goldschmidt 9 out of 25 your reigning NL MVP Patrick and the Cardinals Yeah, like Vince won a 24 player treasure chest here back in 2016 nice Had Machado for the Orioles and the O's came up on top. That's awesome And we got Jake McCarthy rookie signature jumbo material 72 out of 99 And that will be for Stephen K and the Diamondbacks Oh, it was a random card break How many spots how many spots were involved in the randomizer? All right final box coming up 20 Says it's better odds and a 30 teamer. That's pretty close but in terms of a a multiplayer card For me randomizing I'm pretty sure I can't remember any recent ones But I want to say back in 2014 no 2015 well whenever the Mariota Marcus Mariota and James Winston NFL draft was whenever their draft year was So obviously in group breaks those two players were You know the hottest player in the product. They went one and two I Think I want to say it like in spectra football or something like that I pulled a It was a different break but one-of-one like dual Nike swoosh or like a dual shield or something like that I forgot what side one it but I'm sure one person was happy and one person was very sad. There's nine out of 25 Adam Frazier Seattle and that's where Seattle nine It's gonna go to Chris T. There's Jake Myers four out of 99 Houston I'll be for Ed P Didn't have to do that. I think I think that was Jason Right dealt with that drama Seven out of ten Carlton Fisk piece of his lumber for Boston. Yeah, we had a Daniel Jones Kyler Murray dual shield dual auto John G with that and we pulled that and Listen folks, we're randomizing every single time no matter what the card is. It's being randomized every single time There's Gabriel Arias nine out of 25 and One one party was in the chat. The other side wasn't in the chat. This is for Eastwood Cleveland. This is for you Apprenticing autograph and that person that was in the chat Wanted to like work out a deal or trade or split the card or blah blah blah, and we're like that's not the way we do it Your nice Henry Davis the future way of the future Way of the future For the pirates your former number one overall pick Yeah, it is to thiccc for the 180 toplers to go into a slider box. This is a really nice one for Aaron Miller and the pirates Former number one overall from Louisville. I want to say Now usually I'm not good with the whole college thing, but why do I know he's from Louisville? You just double-check Yeah, he went to play for the Louisville Cardinals and the only reason why I know that is Because I feel like Dodger catcher will Smith went to Louisville He did so some sort of catcher factory That they have it in Louisville There's Marcel Ozuna 25 by 25 Piece of the lumber and his autograph going to Kevin and the Braves. I Don't remember a Luca Trey one-of-one dual All right, at least I don't remember any drama surrounding that. I think that was just pretty straightforward One very happy person once that person got another pirate. It's O'Neill Cruz RPA 65 out of 99 for the pirates. That's gonna be for Aaron That's right. It's also a bat factory out there, too Is Dalton rushing another dodge catcher from from Lou? Yeah, they're just producing bats and catchers Marcelo Meyer 10 out of 10 For Boston that's gonna be for John and the Red Sox The book and one more we got legendary material signatures triples out of 10 and it is Dale Murphy Two pieces of the Jersey a piece of the lumber a little cut autograph in there Nice one Braves Kevin with the Bravo's It is a legend. I think one MVP two years in a row in the early 80s We learned that when we were playing who am I earlier today saw Dale Murphy autograph baseball and the last one here is John Haisley 11 out of 99 and that's for the Royals. That's for Stacey. There you go gang I'm Joe for Jasper's case breaks calm. Thanks for watching. Thanks for breaking with us everybody We got to make one person happy and one person sad before we call it We got Detroit on one side Tampa Bay on the other side So let's go get some fresh dice. There it is Detroit Tampa Bay Rays Team on top after nine We'll get the book the dual relic dual auto three and a six nine times good luck one two three four five six seven eight and Ninth and final time goes to Tampa Bay after nine Detroit Ed P last Bob Mojo, I apologize did not work out for you this time, but Congrats to Tampa Bay seven Which is Billy Billy you'll get the dual relic dual auto. There you go There you go, Billy. Thanks for getting in I'm Joe for Jasper's case breaks calm and I'll see you next time for the next one


Now let's take a look at the present continuous tense. The continuous tense is used to talk about actions in progress at the time of speaking or around the time of speaking. The first thing to notice with the continuous tense is that we must use the verb plus ing form, also known as the present participle. You'll see it in any continuous tense, especially with the present continuous. We have three different forms of this tense. First we have the subject I, used with am, teaching. Then we have you, we, and they, are, teaching. Finally we've got he, she, it, is, teaching. The am, are, and is are forms of the verb to be, and here with this tense it's used as an auxiliary verb or a helping verb. In order to form negative sentences we simply add the word not between our helping verb and our main verb plus ing. To form the questions for the present continuous tense, again what we've done is inverted our helping verbs here and our subjects here, resulting in questions like am I teaching? Are you teaching and is he teaching?


Well the internet is full of interesting things and look, we're all sort of starving for some Nintendo news. You know, news about new things rather than old. We obviously recently had all the Mario 10 day stuff happen and there was some new news in there about a Mario or at least Mario related movie, but we don't really have any new stuff for games. We got some release dates for the stuff that was announced last year, but where's the new? Well, probably in a future Nintendo Direct, but what about Nintendo's next platform, right? All the news really died down on that until just now. Something very interesting occurred that I wanna make sure we cover and talk about and for full transparency, this is something that I have verified independently did actually happen. It is possible the literal name of Nintendo Switch 2 might have been leaked accidentally on purpose, I don't know, by YouTube themselves. Why would YouTube even know the name? I don't know, but that doesn't really matter because we just have to sit here and present the evidence. Here's a post over on the Nintendo Switch right here from a few days ago, said I just got this really weird questionnaire when trying to watch a video. It says one on Earth is Switch Attach. I'm imagining this is either a spelling error or a typo of some kind, but what on Earth is this in reference to? And if it's just supposed to be a switch aside from the Joy-Cons, this doesn't make any sense.  You can see this was a mobile and turns out I got the exact same mobile survey. So quite interesting, the survey is going around. It says, which of these gaming products would you consider buying? And it says PlayStation 5, Xbox Series X, or Switch Attach. Now, again, Nintendo Switch 2 has always been just a placeholder name and not the actual name of the system. And would Attach be inferring that you could attach other accessories besides Joy-Cons? I think that is at least a possibility, at least worth thinking about. But we also need to make sure that we provide some context to this because YouTube does these surveys all the time and how much do they matter? How factual are they? Well, of course, sometimes these surveys are for factual things, but sometimes they're not. And this is where we head on over to the gaming leaks and Reddit subreddit. And over here, the gaming leaks and rumors that I guess I should say, where they also talked about this. And I want to get into the comments section on here because they provide information that might be, you know, pertain to this at least. You so, like they said, definitely something like a possible name from the next Switch console. My Google search didn't find any apparent uses of the term, including any fake console mocks-up or incidental pairings. But as you go down here, like, you know, the user, it says the user's act, the person explained in the comments, but it's probably just a made-up suggestion. Usually they do that sort of thing for marketing research. Fake brand names tend to pop up on YouTube surveys. So I don't think that's the official name. Now, I haven't really been able to verify that fake brand names appear on YouTube surveys, but that is a thing people are saying. Other people saying that, you know, until it's official news, I tend to call this successor the Switcheroo. It says probably fake, but that's just a terrible name, just an abysmal thing to call your product.  If you have the attached theming, the Switch Connect or the Switch Snap are better options. Yada, yada, yada. That's just obviously people giving their opinions. They're doubling down on the Wii U. This is a new console, a vertically overpriced accessory. Awful name. If their next console is a new Switch, I think they should steer away from using the Switch name to avoid another Wii U situation. Et cetera, et cetera, et cetera. You can see all of these things so going on just all over the internet. Now, remember, it does still use the term Switch. So what I think is interesting is that they would be sticking with the Nintendo Switch branding if this is the name, just entertaining this for a moment. And using the word attach would indicate well, there must be some new attaching functionality. Now, we've talked in the past so there have been patents around Nintendo surrounding things like maybe an attachable second screen so that you can attach a second screen to it, give yourself a clamshell design if you really want. Maybe they're, as I said, gonna have more than just Joy-Cons that can attach to the sides. Maybe there'll be other accessories. I don't really like this Switch attached name, of course. I do think Nintendo Switch 2 with an attachment like function can just be an advertised feature of it, just like you have new iPhones that stick with the numbers but then have all these other new features in addition to, I don't like the name Switch attached. So part of me is also trying to dismiss this because I just don't think it's a good name. Also, I just don't know why YouTube would even know the name of the system unless Nintendo had already taught people at YouTube. Now, to be fair, and we do need to be clear here, Nintendo does use Google services behind the scene. They use their servers with their online stuff. So I guess there is a thought that maybe in testing this new system of Google servers, Google might have become aware of the name but then would the name really leak out in this way? That just feels like to me something that wouldn't happen. Chances are this is just someone at YouTube's kinda shot in the dark at the name because everyone's using Nintendo Switch 2. We wanna use something unique and maybe that unique thing gets headlines and maybe this is just what they intended this entire time. I don't really know. So you guys can let me know your thoughts on this down in the comments below. I just wanted to bring your attention to this because I do find this to at least be interesting but maybe not wholly that tangible. Then again, I've seen this survey myself. It is a real survey being ran by YouTube. What do they know? I don't know. So let me know your thoughts on this thing. Do you think this might actually be the name and why do you think they're even doing this survey? Kind of weird, right? I don't know. I'll catch you guys in the next video.