We had another Wheel of Fortune mishap and here's the context. Everyone's going bankrupt, Sean with two ends. Is that two ends, Sean? Bankrupt, Michelle bankrupt. No one's getting any chances to guess. Sean with two ends again, bankrupt. That is two ends, S-E-A-N-N. Michelle again bankrupt. She's like, geez, okay, just trying to play here. She spins again.  She gets to guess a letter. D. D. Nailed it. N. K. I'm afraid not. There's no K. Now, why did Pat laugh at that? K. Why is that so funny? K. I'm afraid not. There's no K. G. So it gets passed to Michelle. I. A. Lots of A's. S. No, no S. No S. And back to Sean and he's bankrupt. Tough break. So we're gonna go to Michelle and she's gonna take us home. B. Nailed it. R. Absolutely. Got it. Y. No. P. Where did she think the Y could have been? Day. Maybe this was like, she thought this might have been ending in day. I don't see a Y over here. I don't see a Y there. A. Yeah, maybe that's what you thought. We get a P. O. I'd like to solve. Okay. Paddle boat. No, that is not correct. Now that's not correct because paddle has two D's and L and an E. So it need to be P. And this would be an A. Because A's are already out and there'd be two D's and there'd be an L and there'd be another letter. That's how you spell paddle. You know, it could just be a pronunciation thing, which it probably is. T. He's not confident enough to solve. He wants more letters. Like to buy an E. Mm-hmm. He's like, mm-hmm, okay, why don't you just solve though? Why are you spending money to get this when? I like to solve. Yeah. Renting a paddle boat. No, that's not correct. No, you said the same thing that she said.  Michelle. That's an evil laugh. Michelle. Michelle, you have $3,000. You can spin again, but you don't have to. M. M. No. No. Crystal. I have to spin. Now here's where it gets bizarre, because obviously everyone's in their own head. They're like, how could it not be paddle boat? But they're just saying the word paddle instead of paddle and they can't correct that in their brain. So she's gonna guess. W? W. Renting a p-daw. Renting a p-daw boat. No. Listen to the crowd in the background. W? Oh. Sean, what do you want to do? I like to solve. Go ahead. Renting a paddle boat. Yeah, there you go. Yes, yes, yes, yes, yes, yes, yes. Yeah, everybody's been saying paddle and that changed you. A paddle boat's a little different thing. A paddle boat, you got those. Anyway, anyway, another bad round here and I'm gonna have to defend our contestants again for being a little bit on the not smart side when it comes to this specific puzzle. I'm sure they're very smart in their particular walk. I'm sure they're very smart in their own walks of life, but yeah, it was not paddle. It was paddle. And it was not p-daw or p-damm boat.


And now our next speaker is somebody who has been paying careful attention to what people around him are saying Which if I read the news properly is becoming a rarer and rarer thing these days the peace prize as you know was awarded for the the authors of the Study called on the reception and detection of pseudo profound bullshit. Please welcome Nathaniel Barr All right afternoon everybody.  You might know dr. Oz He claimed this green coffee would make you lose weight turns out that's bullshit There was actually an interesting study in the British Medical Journal that found that actually less than half of what they were Claiming to be true on his show was actually supported by any evidence When he was put before Congress he actually said he sees himself as a cheerleader, right?  It's Deepak Chopra He he actually won an ignoble back in the 90s for his creative interpretation of the term quantum You know, he has books like Ageless Body Timeless Mind Quantum Healing Soul of leadership and he gets called out a lot for not really caring about the truth, right? So for example, he says a lot of stuff like this attention and intention are the mechanics of manifestation Now some people have kind of taken to this and there's this interesting website that actually Generates things like this the future is the path to a symbolic representation Marvel and how they do this This site's called wisdom of Chopra, which pulls Pulls buzzwords from his Twitter feed and rearranges them into syntactically valid sentences When you actually think about the definition of bullshit from the philosophical tradition We realized that something constructed absinity concern for the truth This is an algorithm that generates this this sort of fits what we thought was the true definition of bullshit And we called it we fancied this to be a particular kind.  Not at all profound and five very profound and so we pulled these from this website We got a scale developed.   Yeah, the scale was great and then we turn to the next question Does this correlate with conceptually relevant variables?  We got serious about this Is it the case that it's just because they find everything profounders that's specific to bullshit So we decided to give people some other things.   Oh, yeah, we got interrupted.  So check out the paper.  Oh planning to expand your research into these other levels I Think it's probably important, you know like I said we focused on the pseudo profound because it seemed such a perfect opportunity Given that these websites exist and as I said it really fits well in that academic definition But we we're hoping you know, of course This is research that makes you laugh and that make you think but we're hoping that other researchers start to think about all Those levels of shit that permeate our lives and could try to find ways to Scientifically dive in deeply but yeah That was a perfectly pseudo profound question was it not Next question, can you relate this also to like conspiracy theories and conspiracy theorists? And if so, can you please talk to my mom? Actually, we did include a measure of conspiratorial thinking It does indeed correlate with finding the bullshit profound However, it was it was part of our receptivity So they found everything profound the people that were conspiratorily minded the truth The true things that really were specific to the pseudo profound bullshit were the analytic thinking and the skepticism But yeah, we do find a correlation between their profundity ratings and the extent to which they buy into conspiracy It's good question. It's in the paper. Check it out So it seems like you used a lot of kind of tweet length Statements, and I wonder if have you studied whether there's any correlation between the length of the statement and people's ability to distinguish between actually profound statements and pseudo profound. Yeah, that's a great question. We haven't but you know, there is Sort of like literary work that sort of assesses the use of vague Statements and things like that in the body of a longer work So it's it's sort of an effective literary device to get the reader thinking about things But yeah, there's no empirical work yet. You know, we're really just Beginning the study of bullshit, I'd say but yeah, it's a great question Okay, one more question now. Are you familiar with Stephen the great philosopher Stephen Colbert? The truthiness truthiness isn't this a kind of isn't truthiness sort of a non-schatological version of what you're talking about Yeah, yeah, there's lots of connections to other existing things for sure another one is Carl Sagan talked about baloney detection as well You know, yeah, if you know Colbert tell him to give us a call.  Yeah, there's that's the nice thing about this work is we think that it ties into a lot of the existing work on persuasion lying You know, it's really it's been as of yet an untapped Resource in psychological science.  So, yeah, thanks Okay, thank you If you have further questions stick around One question, I'm sure everybody wants to know the answer. What are you doing Monday night? Monday night. I don't know. I'm open to invitations. What's the first presidential debate? And I had assumed that you were flooded with invitations from news organizations To sit in and commentate on yeah, no invites Yeah, but you know, we're a team of Canadian scientists.  Please please let them know. Thank you very much


Well, every time Bimidji and Grand Rapids volleyball meet, you know you're in store for a good one. Lumberjacks, they've lost a couple close ones as of late, but the Thunderhawks, they've won eight of their first 10. Scratch those records tonight, though, for part one of the battle, first meeting at Grand Rapids. An opening set, all Thunderhawks. You have to know where Marissa Rossi is on the court at all times, a sneak attack for the point and the lead. Then later, she sets up Brianna Sutherland on the swing play, and she delivers with authority. They take the first 25-12. Jax just looking for some momentum in the second. McKenna Quinn gives it to him, finds a hole for the kill from the outside, but all Grand Rapids tonight, and Sutherland couldn't be stopped.  They would win in three straight, three nothing at the final over Bimidji. If you've enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland Public Television.


Item number SCP-602. Object Class. Safe. Special Containment Procedures. SCP-602 appears to be immobile and localized to apartment Green Street, New York City. Thus, containment of SCP-602 consists of keeping the public away from and ensuring that SCP-602 does not expand beyond or move out of. Apartment. However, due to its location in a heavily populated urban center, i.e. Manhattan, SCP-602 requires special considerations for containment. Apartment must remain locked from the outside, with both mechanical locks and concealed electronic locks. No one may enter or remove anything from apartment without Level 4 authorization. The entire first floor and basement, and all unoccupied units at Green Street, are collectively designated Containment Site 28. The remaining units in the building are occupied by civilians who have lived there since SCP-602 was initially contained. These units will be acquired by the Foundation as they are vacated, but occupants will not be directly forced out of their apartments. However, all measures, short of lethal force, have been authorized to keep civilians out of Site 28 areas, up to and including non-lethal force, and use of Class A amnestics. To date, the Foundation has acquired of the units in the building. See Document 602-S-28 for more information. Description. SCP-602 is an unseen entity that can manipulate objects within apartment. SCP-602 can exert enough force to knock people over and hold them down. While SCP-602 appears able to affect objects anywhere within apartment, it cannot affect anything outside the apartment if the front door is closed. Thus, SCP-602 can be effectively contained with external locks on apartment's door. Apartment does not have standard furnishings.  These sculptures appear to be made from a variety of materials including marble, granite, wood, metal, porcelain, data expunged, and glass. Data expunged. Two doors lead out of the entry room. A door in the left wall that is stuck and has never been opened, and a door in the back wall that is usually closed. The second door leads to a room that contains more sculptures, as well as a table, on which lay a large array of tools for sculpting data expunged. Also in this room are outside-facing windows that always have the blinds drawn. All attempts to remove any of the sculptures are tools, or the table from apartment have been met with violent resistance from SCP-602. Any person inside apartment is subject to attack by SCP-602. Through an unknown method, SCP-602 can apparently transform a living human into a sculpture, a variable material. Similar to the sculptures already present in apartment, when doing so, SCP-602 will close and lock the front door of the apartment from the inside, completely barring entry to and exit from the apartment during that time. SCP-602 will also destroy or otherwise neutralize any sensory equipment set up within apartment, and has consistently destroyed concealed surveillance equipment, carried by test subjects, before transforming these subjects. Addendum 1 Document 602-S28 Establishment of Site-28 SCP-602 came to the attention of the Foundation in late 1980 after the disappearance of data expunged. The Foundation acquired the Green Street building shortly thereafter. Overwatch determined that the interests of the Foundation would best be served by low-profile piecemeal acquisition of the rest of the building, rather than exerting eminent domain over civilian-occupied units. Once SCP-602 was officially classified as safe and containment procedures were enacted, the areas of the building held by the Foundation were designated Containment Site-28. Task Force Pi-1, City Slickers, was established to keep civilians out of Site-28 areas. Data expunged was established as a front business on the ground floor of the building. Site-28 has expanded its scope since its founding, serving as a base of operations for the Foundation in the Northeastern US, temporary and permanent housing for Foundation personnel, and a containment site for a few safe SCPs. Pi-1 was upgraded to a mobile task force, specializing in acquisition and containment of anomalous objects in heavily populated environments. Members of Pi-1 also offered training in urban operations at Site-28. For more information on the urban operations curriculum, see Document P1ERBOPS. Addendum 2 Document 602L01, Exploration Log Note, unless otherwise noted, in all procedures involving SCP-602, subjects are dressed as maintenance personnel, and all civilians who live on the same floor as SCP-602, as well as those directly above or below apartment are outside the building. Surveillance of these civilians is provided by Pi-1. Exploration Log 1 Materials Subject D-602-1 Equipped with a TV camera and two-way radio A second camera on a tripod. Procedure The subject records footage of each sculpture in the room. The subject attempts to open the door on the left wall, but cannot, declaring it stuck. Around 12 minutes after entering, the subject hears a smashing sound, turns, and sees the pulverized remains of the camera and tripod. The subject, data-expunged. The subject starts to move into the next room when the video cable is cut and the front door closes and locks. Radio contact with the subject is lost within seconds. Subsequent examination of the apartment shows no sign of the subject or any equipment brought inside. Analysis Footage shows 11 sculptures in the front room, and at least four in the second room. Also in the second room is a table, with what appears to be tools on it. Dr. Devin suggests a possible resemblance between some sculptures and several missing persons, including data-expunged. Exploration Log 2 Materials Two remote control motorized bases mounted with cameras and microphones. One camera array facing in through the open front door. Procedure One motorized camera is sent straight toward the second room, while the other hangs back in the entry room. Just before the lead camera reaches the second room, both motorized cameras are suddenly and simultaneously flattened by an invisible force. Nothing else happens for 10 minutes, at which time the remains of the motorized cameras are pulled out by the video cables. Analysis Thermal imaging shows the temperature of the apartment dropping by between 7 and 15 degrees Celsius. Moments before the cameras are flattened by pillars of intense cold, that briefly manifest above each camera. The two cameras were crushed within 120th of a second of each other. Exploration Log 3 Materials Subject D602-2 Equipped with a TV camera and two-way radio. Four remote control motorized bases, mounted with cameras and microphones, made from military grade reinforced steel. One camera array facing in through the open front door. Two thermal imaging arrays facing in through the windows. A variety of sensors, including microphones, seismographs, Geiger counters, data expunged, set up on surfaces adjacent to apartment- i.e. the walls of adjacent apartments, the floor of the apartment above, and the ceiling of the apartment below. Procedure The subject is instructed to record footage of the second room from the entry room, by zooming in as much as possible, while the motorized cameras observe the rest of the room. After 16 minutes, the subject is instructed to try the left-hand door. The subject claims the door is jammed and cannot be opened. As the subject enters the second room to record more footage, the front door suddenly closes and locks, and all of the cameras lose their video signals simultaneously. Preliminary analysis shows the cables were cut, just as an experiment won. When the door unlocks, there is no sign of the subject or any equipment in the apartment. Analysis Right before the signal is lost, one of the cameras records something on the front door. Analysis of the footage suggests that the object is a wire rack, around 15 centimeters long, attached to the inside surface of the front door. The external cameras record the expected drop in temperature, though exact data could not be obtained through the closed window blinds. Several minutes later, external cameras record a sustained spike in far UV radiation that lasts approximately 40 seconds. No other unusual emissions are detected. Note, Overwatch has suspended exploration of SCP-602 for now, primarily because we've neared the limit of what we can learn using current technology, without it becoming insanely expensive. At the very least, we would need stronger materials and more maneuverable robotics, though a cheap way to send a video signal without a cable would be nice too. It's just as well though, because I'm concerned that Mrs. Yankewicz up in is becoming suspicious again. I don't know how she knows what she does, but either way, getting that many amnestics can't be good for anybody, particularly a lady her age. I recommend she be investigated as a potential SCP. Dr. Devin Subject Interviewed 1981 No Anomalous Abilities Suspected Class B Amnestic Administered Dr. R. R. R. On 1991, Apartment R. R. was open for the first time in several years, and video footage was recorded from just outside the front door. Several differences were observed compared to footage recorded in 81. First, there is now a closed door between the entry room and the room with the table. We cannot tell whether the door has a lock on it, but as much force as 602 can generate, it's probably not necessary. More striking though are the sculptures in the entry room. They appear to be the same sculptures of the same people as before, but most of them have been changed, some pretty drastically. Lastly, and most significantly, attached to the inside of the front door is a wire rack holding a very sharp knife. Photographic evidence has proven that this knife almost certainly cut the video cables in the experiments. I'm convinced that 602 put the rack up after the second experiment, further evidence that 602 is sapient. Dr. Devin Addendum 3 Document 602L02 Contact Log Contact Log 1 Materials Subject D602O3 One Child's Wagon Model Radio Flyer 10 fully illustrated books of sculpture, including The Works of Henry Moore, The Works of August Rodin, The Works of Alexander Calder, Sculptors of the Italian Renaissance, and Medieval Gothic Sculpture. Three mail order catalogs for art supply companies, bookmarked in the sculpting sections, with attached order forms. One piece of paper, containing a half finished press release describing a gallery show by the mysterious new art sensation from Soho that everyone's talking about, and a handwritten addendum stating, this could be you. One cardboard sign with the words read before destroying, written on it in thick black 30 centimeter high letters. Procedure The wagon was loaded carefully in the following order, press release on the bottom, then the art supply catalogs, then the sculpture books, and finally the cardboard sign on top. The door to the apartment was opened, and D602-3 pushed the wagon inside before quickly exiting the apartment. Researcher Vogt then loudly announced into the apartment, here you go friend, we'll be back in 24 hours, and closed and locked the apartment. Results 24 hours later, the apartment was reopened. The wagon had been moved, but was otherwise intact. Upon retrieval of the wagon by D602-3, it was discovered the cardboard sign had been shredded, and the sculpture books had been removed. The art supply catalogs showed signs of having been intensively consulted, with several pages having been torn out and or crumpled, and the order forms had been filled out with crude markings, in an unknown fluid. Study of the order forms revealed that SCP-602 would like new chisels, new mallets, a miniature kiln, and... Lastly, the press release had been shredded, then reassembled with an unknown adhesive, then crumpled, and then flattened again. Analysis. SCP-602 is confirmed to be sapient, and to be willing to negotiate. Note, no I'm not suggesting that we just give the SCP whatever it wants, but we've established quasi-peaceful contact with an SCP previously thought intractable, and at less than a 20th of the cost of any one of the previous exploration attempts. We may even be able to convince it to trade its old tools for new ones, although giving it is completely out of the question, of course. Researcher Wacht. Addendum 4 Document 602-CP-1 Contact Protocol As a result of contacts 2 through 17, see respective contact logs for details. The following protocols have been developed for successful interaction with SCP-602. Successful is defined as greater than 90% survival rate. 1. Always announce yourself at the door before entering. 2. Do not touch the statues. 3. Do not make any negative comments about the statues or their artistic merits. Constructive criticism seems to be acceptable. 4. Do not touch the sculpting tools. If replacement sculpting tools have been supplied, SCP-602 will place its discarded tools in a bucket by the door. The bucket may be collected when leaving the apartment. 5. All surveillance devices must be announced before installation, and their function must be clearly described. SCP-602 promptly locates and destroys all hidden or otherwise unacknowledged surveillance devices, and uses the debris as projectiles. Surveillance devices which were properly announced remain intact and operational, until such time as SCP-602 wishes to create or modify a statue, at which point, it deactivates all surveillance devices simultaneously. When it is finished, it reactivates the surveillance devices. 6. Never enter the apartment alone. 7. No flash photography. 8. No smoking. 9. No spitting. 10. No chewing gum. Lesson complete. If you missed the previous orientation, go watch SCP-601, Sophocles' course, right now. Or for the complete course, watch this playlist.


Hi, this is Ruth Guggenheim with GPS for the Jewish Soul. We'd like to welcome Rivka Makka-Permon today from Wow in Baltimore, Maryland. Hi. Hi, Rivka, thanks so much for joining us. I love it, my pleasure. You know, I wanted to discuss today building a relationship with God. How do we go about that? You know, as Jews, we were already saying shema, and it says that we should love God with all our heart, might, and soul. How do we do that? That's a good question. You know, I'm speaking to young people all the time, and the most common thing I hear right before that question is I don't even know if I believe in God. You hear that sometimes? I hear it all the time. All the time? Very good. You know, we must all of us go through this period in our lives where we're not sure ourselves. Is there really a God? Is God hearing me? Does God listen? Yeah. How do we get through that barrier? Yeah. Have you found a way? Have I found a way? Well, there was a turning point in my life, and I'll tell you in terms of my relationship with God, and I really would like to share that with you. But before that, I just want to say, don't worry about whether or not you believe in God. He believes in you. He believes in you. He's there. Don't worry about believing in Him. I'm confident that all of us have a sense of otherness.  Something else is happening. It's not just conversation. You know what I'm talking about? That's the taste of God. Yeah, that's the taste of something else. We think of God as, like, up there. Well, I can't make a relationship with something that's up there, far away, looking down at me. That's not God. God is inside of us. God is what powers the whole world. It's something so infinite. You can't feel it. You can't feel it. But we all experience it. So I just want to qualify my answer by saying let's throw out the word God and what should we call this infinite source of energy? Love. Love. You know, I think God is truly unconditional love. It's the ability for all of us to feel without any strings attached. Certainly that God hears us on a day-to-day basis. Yeah. Do we matter? Do we matter? Yeah. I had a personal turning point in my life. I grew up with a belief in God, definitely. But it wasn't until I opened my mouth outside of synagogue, outside of a prayer book, and started talking to him that I really started developing a relationship with him. You know, if someone's here, you're going to talk to him. This is, what's the proof that I believe in you, Ruth? I believe that you're here. I'm talking to you. If not, I'd be a crazy person talking to myself, right?  You know, it reminds me there is a story of the altar rabbi, the founder of Hasidus, where he yells out, he literally yells out and he says, I don't want to know about your garden of Eden. I don't want to know about the world to come. I want to know you, God. What would you recommend should be the first step when someone is looking to consider if there's a belief with God, yeah? I could say what worked for me. That's all I could say. Yeah, of course. You know, maybe the first step is different for everyone, but I think gratitude, you know, whatever this loving being is, is sending us gifts all day long. The gift of friendship, the gift of eyesight, the gift of warmth, a house, a connection, a job, a great conversation. We're being showered with gifts, you know, and if we walk down the lonely road and don't address the source of the gifts, then it's not only the problem that we take them for granted, we don't get to develop a relationship. So I would start with a gratitude list and not on paper. The same way as an email is not the same thing as a face-to-face coffee day. I say, open your mouth and say thank you. And try that. Try saying thank you for five things. You know, I'll tell you something. This was a great night for me. I was waiting for my daughter to get off the bus and this bus was so late and coming and I was waiting in my car and I just was getting so impatient. So it was a good moment. I don't always do this, but I said, you know what? Instead of being impatient, I will sit in this car and say 50 things I'm grateful for. Maybe by 50 she'll be there. 50? 50! It was a memorable night. That's how it starts. That's where it starts. You know, Rivka Malka, I would like to thank you so much. I think if all of us took your idea and sat down on a daily basis and thought of five things, five things every day that we know that God has given us, that's a way of starting that relationship. I'd like to thank you for joining us, Rivka Malka and everybody else. See you next time.


We've got five games tonight in daily fantasy baseball. And honestly, despite there being just 10 pitchers, a handful of them are pretty solid options for pitching. I could honestly justify using five of these guys, five of the 10 pitchers, I think are justifiable plays for DFS. The problem is all five of those guys carry high salaries. So we're not getting to a value play for today. And so we're going to focus on my favorite three plays of pitcher just regardless of salary breakdown those guys dive into stacks with an emphasis on finding salary savers there. But I don't think that'll be too tough. I think you can get to the stacks or the pitchers you want to use along with the stacks you want to use and make things work. So not a bad slate for today. Let's dive on it and get you ready for Thursday night. Welcome on into the solo shot. That's right here on the Fandall podcast network. My name is Jim Sonnis. I am a managing editor of digital media for Fandall research here to break down Thursday's five game main slate with lock set for 705 p.m. Eastern for today. There are a couple of weather notes on the slate. There is a good chance of rain in Pittsburgh for the pirates in the Cubs. I check back on that later on as it could actually be a bit of an annoyance for this game. Maybe I'm just gun shy after the Dodgers Guardians game last night. But it could be dicey. Same thing in Baltimore for the Orioles and Blue Jays though. Weather looks like it arrived a bit later there. So I check back on that one later as well. In Chicago for the White Sox and the A's it is 90 degrees and humid with winds out to left at 12 miles per hour. Also chance of rain. But if they play upgrade batters for the White Sox and A's I know the two most splendid offenses we have ever concocted. But we got to bump up for today in DFS. We'll dive in and outline what that means and top pitching options in just one second. The first day reminder to make sure you're subscribed to the Number Fire Daily Fantasy podcast feed wherever you get your podcast two weeks from today. We'll be our first NFL heat check of the year breaking down the Week 1 NFL DFS main slate. Myself and Brandon Gedula will be breaking that down here on the Fandall YouTube page and on Fandall TV Plus. And as mentioned yesterday, Fandall TV Plus now available by going to Fandall.com slash watch. You don't need Amazon Fire, Apple TV or Roku anymore. You can watch on your desktop as long as you have a Fandall ID. You can log in, watch Fandall TV up in Adams live or you can check out our podcast there as well. Fandall.com slash watch. Get ready for the NFL season with incredible offers from Fandall America's number one sports book right now. New customers can bet $5 and get 200 in bonus bets guarantee. Plus all customers who bet $5 will get $100 off NFL Sunday ticket from YouTube and YouTube TV. Now is the best time to join Fandall. 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Visit gamblinghelplinema.org or call<PHONE_NUMBER> for 24-7 support in Massachusetts. Or call 1-877-8 Hope & Wire Text Hope & Wire in New York. NFL Sunday ticket offer ends 9-18-23. No refunds. Terms and embargoes apply $100 off NFL Sunday ticket not YouTube TV. YouTube TV base plan required to watch YouTube TV. Redemption requires a Google account and current form of payment. Commercial use is excluded. Pitching preview for this Thursday main slate. We've got Pablo Lopez checking in with the highest salary on Fandall's salaries $10,900. Followed by Justin Steele at 10-4. Merrill Kelly checks in at $10,200. Followed by Jose Barrios at 99. We have Cal Gibson at 99 as well. And then Andrew Heaney is the only other guy with a salary above $8,000. Now those five guys I listed Lopez, Steele, Kelly, Barrios and Gibson are the five guys I'm going to use for tonight in DFS. We're going to focus on just those five and outline my view of them for DFS and my top three for today. The top one is Pablo Lopez. Despite the fact he has a very tough matchup. He's facing the Rangers. They have a 116 in a WRC plus against righties, which is the highest number on the main slate for tonight. It's also very warm in Minneapolis. But I still might have to be on him here because there just aren't many great alternatives. And Lopez is good enough to overcome a tough matchup. He's been filtering in more curveballs over his past 17 starts now. And in that time, he has a 3.37 skill interactive ERA with a 29% strikeout rate. He's also letting up a 35% hard hit rate. And Lopez has had some tough matchups across that time. There's not a ton of them. He did hold the raise to one run across seven innings though. He had nine strikeouts against the Dodgers pitched well against the Mariners and back to back starts. And he's at home here. So there are downsides to Lopez. I'm definitely not as high on him as I usually would be, but his talent, I think it's clearly tops in the slate. And that does matter as well. So to me, I'm going to put Pablo Lopez one. I've got to project for the most strikeouts by a decent amount. But that's not everything. So I'm going to go Lopez one with the wiggle room to consider other guys. And to me, the top alternate consideration is Meryl Kelly. We're up to six starts now on Meryl Kelly since he came off the IL and he has had two clunkers in there, which has five combined strikeouts in those games. But he also had an 11 strikeout game and a nine strikeout game. So the upside is there and he is at home for tonight. So I don't mind putting Kelly in my player pool. He's facing the Reds and they're definitely a fun offense, but fun also translates to the fact they will strikeout. Got 26% strikeout rate against Reds, which is a boost for Kelly. He also does benefit a bit from being at home. His strikeout right there is 27% versus 24% of the road. So not a huge split, but I'll take everything I can get on this slate. And the Diamondbacks will let Kelly go deep in games. He threw 102 pitches last time out in Arizona needs him right now because their playoff odds are around 50%. And that's the kind of sense of urgency that I want in DFS this time of year. I have Kelly projected for 6.7 strikeouts that ranks second on the slate behind just Lopez at 7.2 and I'm going to rank them that same way. So to me it's Lopez won Kelly two at the top end for tonight. As mentioned, no value play for today. I can't justify anybody. So I'm not going to try to sell you on someone who I know I'm not going to use myself. Brandon Williamson is probably the closest. We'll talk about him and things to watch, but realistically, we're not going to do it. So let's talk about Justin Steele instead. Steele's salary is 10-4, so he is far from a value, but I'm just more likely to use him. So he's on the road facing the Pirates. Again, make sure you check back on the weather for this game because it could be a bit dicey, but it is a pretty solid matchup for a lefty. The Pirates have a 97 at WRC Plus against lefties in the current active roster with a 133 ISO and a 24% strikeout rate. Now the power numbers there at the low ISO, that's not an area where Steele needs a boost because he's really excelling in that department. Across the full season, Steele has led up a 36% hard hit rate with a 31% fly ball rate. The strikeouts haven't been super, super high for him, but they also haven't been low. He has a 23% strikeout rate, and this is also an important game for them, and Steele will go deep in games. So again, we're getting three pitchers on playoff hopeful teams for tonight who will go deep in games. And this time of year, that does matter quite a bit. At it all up, I have Steele projected for 6.1 strikeouts. That trails only Lopez and Kelly on this slate. So Steele won't save you salary, but I think he's a realistic option. I would say I feel pretty good about all three of these guys in Lopez, Kelly, and Steele. As far as Barrios and Gibson, I think they're both in play. I think they're both good enough pitchers to justify that. Just not as in their matchups with them facing each other. So Barrios getting the Orioles, Gibson getting the Blue Jays. I've got them projected about .3 strikeouts behind Steele for tonight. So that's why they're lower on the list, but they're at least considerations. And to me, it does revolve around this upper salary guys for tonight. Now, as we talk about the stature today, our first stack is one that does include a decent number of high salary guys, which is going to sound dumb, given what I said before about looking for value plays. But we'll get into value plays with these second two stacks. The first one to me is going to be the Cubs. And they're facing likely Andre Jackson tonight. They have not announced. The Pirates have not who their official starter will be, but probably will be Jackson or an opener followed by Jackson. Jackson getting a strikeouts in the rotation so far, but he's also letting up tons of hard contact, which to me makes the Cubs a quality option. We had two starts thus far for Jackson and his hard hit rate allowed is 52%. And it's led to pretty poor results, which is to me not a surprise because for the full season, when you include his time as a reliever, Jackson has led up a 46% hard hit rate this year. His strikeout rate is 26% with a 12.8% swing and strike rate. So he's getting whiffs and that has come with him in the rotation as well. And that might stick as a result. But I think the hard contact numbers will be there as well. Jackson doesn't get many ground balls, lets up a lot of line draws, a lot of fly balls. And he faces the Cubs tonight. They have a 115 at WRC plus against righties with a 181 ISO. They do draw walks and Jackson will issue those as well. So they should get base runners should get impactful contact. That's kind of all you're looking for when it comes to stacking. And I think that the Cubs as a result are going to be our number one option for tonight. Within this Cub stack, it does seem like they're gaining confidence and say a Suzuki once again. He had been sitting against righties just earlier on this month, but he had six against the righties just a couple of days ago and he earned that because he's been hitting a lot of home runs recently. His barrel rate is up to 12% in August. His strikeout rate is down a lot as well. So as long as they keep putting Suzuki in there at a quality spot in the order, I think we should be on him. His salary $2,900 for tonight. Totally fine with that. I think that's a justifiable for sure salary, easy access to the Cubs and means you don't have to go as bottom heavy on the other stacks that you have. You can say some salary elsewhere though, and that begins with the twins. The twins are facing Andrew Heaney. They're going to be our second stack and Heaney, not letting up as much hard contact right now as he used to, but he's also not getting as many strikeouts. The aggregate number of hard hit balls is probably pretty similar still. So I think the twins are a quality stack here. Heaney had scaled back on his slot usage for a bit. It's been back up for his past 14 starts though. In that time, his strikeouts are lower at 24%. And his hard hit rate allowed is still 41%, with a 41% fly ball rate. So he's gotten the hard contact on a bit, but it's come at the expense of his strikeout rate. He's had some especially weird starts recently. Heaney has thrown five total innings his past two starts, and he didn't get pounded in either, just like had too many guys on base early in games and got yanked. So the leash here is very short, which means we could be getting access to the twins against a lot of middle relievers. The twins definitely better against righties and lefties. Their WRC plus against lefties is just 99, but they do it for power, the 174 ISO.  So I think there are enough positives for the twins to be a good stack for tonight. Obviously, Carlos Correa has not had a good year, tough year overall, but he has been better against lefties. ISO there is 196. And his overall hard hit rate in August is 56%. So Correa checking in with a salary of $3,000, obviously I think it's going to make a lot of sense. One thing I would say with the twins is be wary of some of their value plays who might start against their leftie, but then exit. Because they've got, they're probably going to Edouard Julien, that area is sitting on the bench. They might have Matt Walner on the bench or Max Kepler, one of those guys. So, you know, people like Jordan Luplo, if he starts, I don't know how long he'll play. I'd be very wary of him at $2,200, especially given that he needs hats and short starts. So Royce Lewis, Safe, you know, Carlos Correa, Jorge Polanco, those guys to me are safer options. And that allows us to be on them, even though we to be about wary of some of the other guys in this lineup due to the fact they will pull batters pretty early in games. The White Sox are going to be our third stack. And they're not a team I really want to stack right now, but the weather in Chicago is fantastic for hitting. It is 96 degrees, which is the warmest on the slate. It is humid and the wind is out. So I think we can go to the White Sox here. They're facing Ken Waldichuk. And Waldichuk himself is fine. He has made 23 appearances since he started to lean on his side or more. His skill interactive ERA is 4.71. He does walk too many guys and live up to a chart contact, but if it were just Waldichuk himself, we probably wouldn't stack here. But it's Waldichuk combined with the good weather and with the A's bullpen. And they're still easily the worst in the league. The A's have a 4.75 skill interactive ERA in their active roster bullpen. Second worst at 4.55. So 0.2 runs worse than any other team in baseball in their bullpen. And it leads to the opposing team having high run total projections in my model literally every day. And the White Sox are no different for its net. So I don't want to stack this team right now, obviously, but I do think we should in this specific spot. So the White Sox, very much a team I am okay stacking for today. And it does help the White Sox are very righty heavy. Luis Robert, Eloy Jimenez, Andrew Vaughn, the main targets here. Yolm Moncada has been a smidge better recently. Maybe he's in play. So it's not a deep team, but we can consider them regardless for tonight. So top stacking options for me. Gonna be the Cubs, the Twins and the White Sox. Things to watch for tonight. I mentioned before that among the value plays, the guy most willing to consider is Brandon Williamson. Williamson's based in Arizona and they're a super low strikeout team against the lefties, which is a big part of the why, the reason why I don't want to be here. But Williamson can't go deep in games. He's had decent results recently. So not totally barren. Just not quite enough for me to get there. I would also say if you want another stack, I don't mind Arizona against Williamson. Roof is closed for tonight, which does decrease temperature a bit, but they don't have AC there. So it's not like it's like crazy, crazy cold or anything. But you know, I think that the, I don't know if it's going to be as a picture, even though he's probably the top value for today. Other side that White Sox game is also at least worth checking out. That's the A's offense based in Jesse Shultans. Shultans, it's looked okay so far in the rotation, but I'd expect him to come back to Earth a bit, given the numbers he put up in the bullpen. The A's, not totally devoid of talent and offense. So I'm okay with them here as being another option with stacking for tonight. Dinger calls for this Thursday slate. The boring one, Luis Robert. He has tremendous skills and he is playing in Chicago with fantastic weather for hitting, basing off against Walter Chuck, who is more than happy to let up some fly balls and hard contact. So Luis Robert, I think, will put him down for home run number 34 of the season tonight. The fun one, let's go say a Suzuki. As mentioned, he's earning playing time and earning it. He's not just getting, he is earning it by playing good baseball better than he was earlier on this year. So say a Suzuki in this matchup, likely against Jackson with all that hard contact, I think, is a quality home run call for tonight. So we'll go with Luis Robert and San Suzuki as the Dinger calls for Thursday night. That is all that we have here for today on The Solo Shot. We'll be back with you once again tomorrow for a full slate of MLB DFS to get that as it is posted. Make sure you're subscribed to the Number Fire Daily Fantasy podcast feed wherever you get your podcasts. Also check us out on the Fandall YouTube page at FandallTV+. If you got any questions for me, I am on Twitter at Jim Sonnis, J-I-M-S-A-N-N-E-S. You can also follow Fandall Research at Fandall Research. Want to thank you all for tuning in for today. Good luck to you with your MLB DFS lineups and we'll talk to you once again tomorrow to break down Friday Slate. This has been The Solo Shot right here on the Fandall Podcast Network.


Thanks for viewing another 12pm tutorial. This video is going to teach you how to use this service called DynAweb that was created by Dynamic Internet Technology, the same people who created the FreeGate circumvention tool. DynAweb is an anti-censorship circumvention portal that uses hundreds of mirror sites in order to allow users to access information that may be blocked whether using the internet. According to DIT's website, the DynAweb service is hugely popular in China because it seems to be able to circumvent the Great Firewall of China with relative ease. But you don't have to live in China to enjoy the service that DynAweb offers. DynAweb is easy to use, it doesn't require you to install any software on your computer, and you don't have to configure any settings before you're ready to access the whole internet. So let's get started by opening up a web browser. Now in the web browser's address bar we're going to type in www.dit-inc.us. Okay, this is the Dynamic Internet Technology website. Here you can read about their organization, their products, and their clients. In the upper right hand corner here you can choose your language of choice. What we're concerned with is the products page. So let's click the products tab. Here on the products page you can see FreeGate, mass mailing, and DynAweb. Since we want to use DynAweb, let's click on the green DynAweb text. This is an in-depth description of DynAweb. Feel free to read through this information in order to better understand the technology that DIT uses in order to help you access filtered information. Once you're done reading, click on the link in the first paragraph. That link is us.dongtawang.com, forward slash home underscore en dot php. What you are seeing here is essentially the DynAweb service. At the top of the page are a few links. Home will bring you back to this page if you navigate to any of the other pages. Download will give you information on downloading different pieces of software that DIT have developed. Fact will give you answers to some of the common questions about DIT and DynAweb. Support gives you information on contacting DIT with questions or comments, and the about us page will give you an abbreviated version of the information you read on the DIT website. If you have navigated to any of these tabs, click the home tab to return to the main page. Now we're going to use the DynAweb service to access the internet. It's really easy. Click in the address bar provided on the page, type in a URL, click anonymous surfing, and your web page will open up in a new tab. I'm going to type in www.google.com and then click on the button marked anonymous surfing. Alright, now I'm visiting Google. And you might be saying it looks the same as usual. However, if you look in your web browser's address bar up here, you'll notice that it does not say www.google.com. The address you see is the one that is routing you through the DynAweb service in order to access the website. I can enter search terms into Google and DynAweb will continue to route my request around any internet censorship. Let's say I wanted to know more about video editing. And let's face it, I probably should. So I'm going to type video editing into the Google search bar and hit enter. If you look at my browser's address bar, you'll notice that the DynAweb information is still there and the Google search is tacked on to the end. This means that my search has been routed through the DynAweb service. If you want to go to a different website, simply click on the tab at the top of your browser marked DynAweb and enter a different address into the address bar. I'm going to enter www.wikipedia.org this time. This will open Wikipedia in a new tab. Keep in mind that if you type a web address directly into your browser's address bar, like so, you will not be using the DynAweb service anymore. You must access websites using the tab marked DynAweb. Once you're finished using DynAweb, simply close the tab, navigate away from the page, or close the browser. Now you know how to use DynAweb.


And I've got a lot of slides. All right, good afternoon, everyone. We've got Alan here from Google, right? He's going to talk to us about all the blockchain information and how to query it in BigQuery. You've got any friends. They sold their Bitcoin. You want to know how much money they made? Ask him how to do it. Yeah, we have all the blockchain data. All right, here we go. So yeah, my name's Alan Day. You can follow me on Twitter. That's my username up there. I'm going to be talking about a data set that we released last month, co-author and I, for bringing the Bitcoin data into BigQuery. And what does that mean? What are the implications? All right, make sure I can drive my deck. Where's my mouse? OK, yeah, the agenda. Let's just go. OK, so first of all, let's start here. Take photos if you want to. This is just URL shortened links. There's a blog post that describes what I'm going to be talking about in the first half of my talk. And there's a data set as well. This is so that you can get to the BigQuery public data set of the Bitcoin data. Just to give you some sense of what's in here, here's a query looking at the number of addresses that are receiving money per day. So it's a measure of the number of transactions. As you can see, it's quite simple to do the query. And here on the right side, I'm showing visualization using Data Studio. So this is a connector that can read from MySQL or Postgres or BigQuery or CSV files, cool sheets, et cetera. We use this to do the visualization in the blog post. You can do iframe embeds. You can also embed it inside of slide shares. So just to give you some sense of why there's an importance to get the data from the Bitcoin database into something like BigQuery, first we need to step back and talk about different types of, can I turn this down at all? I've got some really bad feedback. Can the AV room turn me down? Thank you. You didn't understand that there's basically two different types of workloads for databases. One is for online transaction processing. So LTP-type systems are basically very good at doing high transaction volumes. They can ingest data very quickly. It's highly normalized. And it's designed for specific type of operations because they want to ingest data very quickly. So they do one thing, they do it really well. OLAP-type systems, online analytic processing, are denormalized so that they can accommodate many different types of queries, not trying to anticipate what the workload looks like. And typically, the data are denormalized or duplicated in various ways to support slicing the data across multiple dimensions. Because usually a row, you can consider the field as being dimensions on the ID of the row. And there's various ways you would want to aggregate, summarize, join, subselect according to those fields. And so that requires having some indexes or caches of the data to help you do that efficiently. Yes, these kind of systems are designed for flexible operations. If we add another constraint onto an OLTP system, that it's append only, that basically describes the Bitcoin or blockchain type systems with the exception that they're not particularly fast in the case of Bitcoin. Whereas we can consider BigQuery to be at least Google's product for doing an OLAP-type system. So if you want to have both of these capabilities of both having good transactional appending, transaction handling, as well as good analytics processing, you need to have two different systems to support both types of workloads. And so that's what's the motivation for preparing the data set I'm talking about today. Just to give you some example of what is BigQuery, it's basically a no operations data warehousing solution from Google Cloud. We can host terabytes. Largest data set is in the petabyte range of data stored in BigQuery. And it's quite easy to use because you can use a standard SQL interface. Whereas with Bitcoin, there's really no way to query the data in that manner. You need to optimize and normalize it in a binary format. BigQuery runs on Google's data centers. We consider data centers as being a computer. Just a bit of background as to how this BigQuery system works. We actually don't do any indexing. So the matter of speeding things up that we're doing is we're replicating the data across many different IO devices, the spindles in the data center. And so when you're doing a query, we're just partitioning up the scan and scanning across all these partitions of the data and then aggregating into some compute nodes. So we have this system called Borg. This is the basis for another project you may be aware of called Kubernetes, which is an open source project for handling virtual machines. And this is the type of compute container that's reading the data from the spindles I was just showing you. And of course, it has to move across a network. So we have a proprietary network at Google called Jupyter. We build all of our own network switches and so on, not all the shelf commodity stuff. And so we bundle all of these three different components into the system called BigQuery I was talking about. Data would be ingested in, dropped into storage somewhere, and then moved over to compute, possibly writing intermediate results into storage back and forth, ultimately giving the result out to the SQL consumer depicted here on the far right side of the graph. So that's basically how the systems work. Now as part of BigQuery, we have something called the public data sets program. And I'll tell you a little bit about this. And so the BigQuery, sorry, the Bitcoin data set is part of this public data sets program. It's effectively open data. As of October, we had 71 different public data sets that were in this program. The tables are world readable. And we have a free access tier for BigQuery. So if you want to look at these, you can query, I believe it's up to 500 gigabytes of data per month and not have to pay anything. You just have to have a Google Cloud account. In aggregate, there's something like more than 700 tables, many of which are live updated on a regular basis. The Bitcoin table is updated every 10 minutes because that's how often a block is produced. So it's as real time as it gets. We've got an access to 4 billion records in this data set or this aggregate of data sets. And the total amount of query data is in excess of 30 petabytes. And this is all exponentially growing numbers from the inception of the program. OK, so let's talk about how one might go about doing this kind of OLAP type of analysis on the Bitcoin data set. Here's the system architecture. So we can consider Bitcoin as being this peer-to-peer network that's maintaining the distributed ledger. And what we did is we built a custom Bitcoin client using Bitcoin J. And if you want to go ahead and grab the source code for how we did this, you can get it here. Nothing super complex, but if you wanted to know how a client works, you could use that. The data are coming in in real time from the peers. We're not mining. We're just syncing the data. And if somebody requests data from our node, we'll push it out. So we are operating a full node, but we're not trying to mine Bitcoins. And then every 10 minutes when a new block is added onto the end of the network, we take that block and we sync it over to BigQuery. And then that's made visible via this Data Studio tool. I was showing you earlier for doing basic time series type analysis or other analyses. And then also BigQuery has a connector to the Kaggle community. How many of you guys are data scientists in the room? OK, we've got a few. So this is the largest online data science community acquired by Google late last year. And so there's a connector to bring BigQuery data sets into Kaggle via a connector so that you can query it from R or query it from a Jupyter notebook to bring the data into a scientific notebook type environment to do further analyses.  And you can go check that out on Kaggle. Here's another example of some data that we can join the Bitcoin data set again. So this is the mining difficulty shown in orange. So this is a measure of, it's sort of an indirect measure of the price of a Bitcoin in dollars. And in blue, you can see that we have some popularity metric for the keyword Bitcoin shown in blue. Notice this figure is a bit outdated. But you might draw some conclusions as to how popularity may be an indicator of difficulty or other attributes of the network. Some other interesting kind of analysis we can do is moving beyond doing time-based aggregations or scanning type operations is to do graph analysis type of analyses because the fundamental type of data is a transactional ledger. So it's stating that some amount of Bitcoins is moving from account A to account B. And here you can see I'm depicting the first documented transaction for exchanging Bitcoins for a physical good. So in this case, the red node indicated here is the purchaser of two Domino's pizzas for the price of 10,000 Bitcoins. That was about $40 at the time. So the purchaser was actually advised not to make the purchase because he was overpaying, but he wanted to prove the point that Bitcoins could be used for real transactions. So now upstream all these blue nodes I'm showing you in the graph actually represent other wallets in the Bitcoin transaction space and the arrow directed edges indicate money flow of Bitcoins from them to this red node. So I did a recursive query up, I believe three levels from that node. So you can see there's some interesting structure in here. Here on the right is a different subnetwork. In mid-2017 there was a ransomware attack called WannaCry. It was basically a malware that encrypted many computers on the network and demanded payment of a ransom in Bitcoins to one of three addresses. They could only have three addresses because the payload in the malware had to be small. And then if you made the payment they would send you the encryption key to then be able to recover the data off of your hard drive. You can see here that I'm looking downstream of each of these three malware payment addresses into the network and I was curious to see if the money is sort of flowing toward one place or it's flowing across the network. I'm not really sure exactly what the structure is here. I didn't go further into this analysis but one might imagine that there's some patterns that could be discovered. Oh, the edges by the way are indicating the weight or the proportional to the logarithm of the volume of the transaction and my computer just turned off. I'll be right back. Okay, cool. Yeah, so that's some type of analysis you can do on this dataset. Now these were done in BigQuery which meant that the analysis was actually a bit difficult because this kind of linear scanning is not set up for graph traversals or recursive type of queries that don't follow something like a linear scan which is what BigQuery is optimized for. And so to get deeper into this kind of analysis it's actually appropriate to move the data to a graph database and I'll talk more about that later. Yes, another visualization of the same thing. This is downstream of the pizza transaction. You can see that there's a bunch of Kaggle notebooks like I was mentioning earlier so people are writing these things. It's quite active and yeah, feel free to join in, clone somebody's notebook, comment on it, request analysis. The Kagglers are a pretty vibrant active community and the Bitcoin dataset has been in the top five for the last month and a half for which it's been available. It was briefly at number one. Okay, so that's the Bitcoin dataset overview. Now I'm beginning to work on the Ethereum dataset. So the Ethereum dataset, this is the number two most popular, largest by market cap cryptocurrency today. And it has some similar attributes to Bitcoin but it has a bunch of additional features in particular something called the smart contract which is sort of like program. It basically acts as a global distributed computer not just allowing transfers of value via this distributed ledger but also keeping a record of computing operations that can take place on the blockchain. So it's not only value, it's a computer. Okay, yes, it's different in another way as well.  So you could write arbitrarily complex programs to execute against the Ethereum virtual machine. The blockchain is also quite a bit shorter. So rather than 10 minutes on Bitcoin, a new block is produced every 15 seconds. So this produces a bit more of a challenge to keep up with the data and keep it streaming into BigQuery but we're able to do this. It's not a problem. Yes, and so a lot of these ICOs and other things you hear about related to cryptocurrencies most of that activity is actually happening on the Ethereum blockchain today. So technical update of where I am in the status of bringing this project in is I have the peer to peer node running. I have a full sync of the Ethereum blockchain in Google Cloud. I've loaded all of it into BigQuery and it's updating every few seconds. It's also available via Kaggle. If you wanted to look at it today you can contact me afterward. I have my contact details on my final slide. I can add your username to the project. It's currently invite only right now. So I'm looking to when I release a blog to have some interesting analyses ready to go just to make a lot more impact for the launch to look at some interesting things we can do with the data. Yes, and there's also some auxiliary like pre-processing I've done that makes this data set a lot more interesting. So let's get into that. I created a view of the data into something that's a token transfer. So this is something like an 80 line query that extracts out something called an ERC-20 token. So the majority of the cryptocurrencies are actually based on this template called ERC-20. It's a, you can consider it like a software class or an object that's inherited from. And so because of that, if you wanted to look for activities related to ERC-20 tokens, you can see all of them and they all follow the same kind of pattern. And that's how I was able to produce this view. So here I'm looking at one particular token called 0x. This is a distributed exchange protocol. You can go check it out. I'm not gonna get further into that. And by doing this kind of query of exporting the source node, the target node, and then some measure of the value moving between source and target. So we're looking at the total token transfer moving within the network. We can export that data into a nice open source data visualization piece of software called Gefi and start to build some data visualizations of the transaction network data that looks something like this. Now I'm not a data visualization expert. Maybe this is not the best way to represent it, but I thought it looked pretty interesting. This is all of the 0x transactions of more than 1,000 tokens moving within the network. So it's a few thousand US dollars or greater. And what I did is I colored the nodes according to a partitioning of the graph. So I can basically say things that are red are nodes that generally interact with one another more than they do with nodes that are of another color and likewise for blue and likewise for green and so on. So there's different partitions within the graph that tend to interact intra-partition and not inter-partition. And the lines between these nodes, so the nodes represent an address and the lines between them represent a transfer of value between them. Now this is across all time. So I've not done any kind of time windowing, but you could also do analysis of this in a longitudinal manner if you wanted to do some kind of time windowed based analysis to look for various types of aberrations or anomalies where you see unusual spikes of activity, for example. Now interesting to note here, to produce that table, I actually needed to identify this thing called the transfer function from ERC-20. So all the ERC-20 tokens implement this function. It has a four byte method signature, 0xA9, 05, 9, CBB. So there's four billion possible addresses in the Ethereum method signature space. And by doing this I was able to find all of the transactions. Oh here's a zoomed in picture of the red node. This is actually one of the cryptocurrency exchanges. This is Binance. And so you can see there's some users who are doing like high volume transactions with Binance and then lower volume. Some of them are actually connected to other exchanges as well. So you can start to type these nodes and infer attributes about them based on their position in the network. But yeah, back to this method signature thing. The ERC-20 contract is open source and so we can compile it and we can identify what method signature it would have if you had the source code. So we know it happens to be called transfer. This is its byte signature when it's compiled and it takes two arguments. So there's the calling address. It is calling to another address to transfer the value to that address. And there's an unsigned int of 256 bits of how many things need to be transferred, how many units of the token. And there's a balance that's maintained in the smart contract. It's updated as a result of this method call. So within the open source space there's, well there's a database called 4byte, 4byte, like the number 4, 4byte.directory that indexes these things. And 4byte.directory has 6,942 methods for which there are sources available that can be compiled to determine the method signature. So we can start to type the transactions by looking at the source code for the smart contracts. And here's sort of how that works. So 4byte.directory takes these, and this is an open data set by the way, if you wanted to download these method signatures. The guy behind it, Piper Mariam, he's taken the Solidity source code, that's the language that's used to write smart contracts, compiled it, and then I pulled the data into BigQuery by mirroring it in as a part of the public data set. So this is one of these auxiliary data sets that's available with the Ethereum data. And then what I did is I actually looked at the GitHub BigQuery public data set. So we have all of the GitHub history in BigQuery. It's like 60 terabytes of data. And the next talk after mine from Felipe Hoffa will talk about some interesting analysis purely on the GitHub data set in isolation, but here I'm talking about it in the context of Ethereum. So what I can do is I can query this data set, find all the Solidity source files, okay, and then Piper gave me a web hook where I can create a new GitHub repo, copy all the existing sole source files into my new Git repo, and when I commit them, his database is aware that I made a commit, he can pull in the new files, compile them, update the database, and then the signatures get updated in BigQuery automatically. So this is effectively a serverless update of the database just by scraping or crawling, crawling the synchronized GitHub data set. So given that, and I also have this OLAP OLTP bridge coming from the Ethereum network into the Ethereum BigQuery data set, there's a possibility here to combine these things. And one of the great things about open data and linked to data is that we can take these two existing data sets, and there's not obviously some benefit to doing that, but we're actually able to give birth to a third data set that is the Ethereum virtual machine stack trace analytics data set that comes out from both GitHub and bringing in Ethereum into BigQuery. So this is the real value of having the public data sets is that we can accelerate the ability to innovate by joining, by linking the data. All right, so what do those stack trace analytics look like? I just started doing this. You can see here what I'm showing is not only transfer events, so transfer is the really big one, which is what I was talking about earlier. This is token transfers. I think I'm showing like the top 50 here. The second one by like largest volume by day. So this is the Ethereum for the last two years, and this is the number of those particular types of method calls aggregated per unit time. So you can see it's really dominated by transfers of tokens. Anybody wanna speculate as to what this pink method is from? I'm sure one of you can guess. Sorry? Yes, CryptoKitties, exactly. So this is actually a breeding event to produce a new kitten from two parent CryptoKitties. Yeah, it was really a flash in the pan though. It only lasted about a week. I don't have the zoomed inversion of this graphic, but yeah, it's pretty much dead from now. There's something interesting happening like a month ago when I made this chart in yellow, I didn't get deeper into it, but if any of you again wanna look at this, I can give you early access to the data set, do a study and tell me like, okay, what are the derivatives of changes of applications and what's the latest trend on the Ethereum network? All the data are available. Okay, so back to this method analysis. I told you there's a method signature space of four billion possible methods. We know about 6,792 of them, what the names of the types are, but for the rest of them, we don't know, and there's a lot. Here's what a typical method call looks like. It's just some byte array, okay? We can break it up because we know, for example, that the method signature is four bytes, right? And then we know that each additional argument is always 256 bits or 32 bytes. So we can start to get some information about this. Like I can tell you, argument two looks like it might be an address. You could possibly measure the amount of entropy in the bits here, like how unpredictable or how compressible is this, which gives you some sense of how address-like is it, right? Addresses should be unpredictable. Private keys should certainly be very unpredictable. You know, this third value, it's all zeros. What does that mean? It could be a boolean. Probably it's a boolean. Might be a null. It's highly unlikely to be an address, right? That's too easy to guess. And then this fourth one, who knows what that is? It has four zeros at the end. Is that significant for any reason? Yeah, so anybody want to speculate as to how you might take these data and get some more information out of there? You could do that. That'll cost you some money to do it, though. Yeah, not a bad idea. Yeah, sure, probe it. Yeah, probe it. Anybody else? I mean, I guess if you forked the main network onto your test environment, you could effectively give yourself free money and do as much of that as you want. Yeah, that's not a bad idea. That's more like moving into a penetration testing kind of angle to find vulnerabilities and weaknesses on the network. It's very interesting. I want to think more about that. Well, you could actually, this is a deep learning problem, right? So we could start to classify these data by looking for things like, typically transfers of tokens will have some kind of round number. So if we observe some byte string that represents a round number in a floating point space, ah, maybe it's a transfer event. And you could think about other such types of analysis you could do to further characterize the methods. So doing this sort of thing lets you get deeper into understanding what types of activity people are doing. And then by looking at top-level methods and then the stack traces underneath them starts to give you some sense of what types of activities are being done on chain. And given that every method call actually costs a little bit of gas or costs a little bit of Ethereum to run the method, you can then begin to attribute to any method call what is the real fundamental economic value that allows you to exchange ethers or dollars for computing on the virtual machine. So there's some interesting fundamental analysis that can be done on this type of data. But we need more elucidation of actually what these methods are. I was showing you some method call analysis. Here's a website that's starting to index these things called distributed applications or DAPS. Doing something on the transpose dimension. So we have methods on smart contracts and this is an index of smart contract interaction across the network, measuring interesting things like daily active users or how much Ethereum actually flowed through the contract. And if we start to look at interactions with contracts, we can begin to cluster games, for example, should have similar behavior in general. We could start to find new games just through the method of interaction. So this is a way of beginning to build something like, it looks quite a bit like a web portal like Yahoo way back in the day. Start to build something like an index or a search index on top of the Ethereum chain. All right, so where I am today is that graphic I was showing you before of the transaction network with the colored partitions is actually a lot easier to build on a graph database. And so there's a nice combination of something called Bigtable which is another Google Cloud offering plus Janus Graph which is an open source project that can allow one to store graph data in something that's easier to do this kind of recursive traversal query than it is to do it in a scanning type of system like BigQuery. So I've loaded some of the data into this database and the next step is to start to do these type of analysis to pre calculate things like what is the page rank of a node or how central and important is a particular node within the network possibly within the scope of a transaction or within a time bounded scope to further characterize these nodes and edges to begin to make statements about what their characteristics are. And then once you calculate these things you can put the data back into BigQuery for filtering in an OLAP kind of scenario. So we've got the OLTP, we've got an OLAP linear scan type database and then now we have a graph database for doing some like complex analysis to bring things back into the OLAP space for building reports. So this is happening now.  I would love to talk to you about other interesting things we can do with these data to bring more clarity and transparency as to what's happening on the network. Also I'm looking for more different data sources, right? So this DapRator database is curating a list of apps. That's really great. There are some other data sources that are available in the various types of document sets that have been leaked to the media where you can get some information about what addresses might be associated with what named players. So that could be an exchange, it could be an individual, it could be an organization, any number of things. I need help on this too. So if you have this type of data or like to do scraping and crawling and want to work on Ethereum or blockchain kind of stuff, those kind of data can be joined in the same kind of way I was just showing you the method signature data can be joined. So that would also be really helpful. Yeah, and just, I was planning on releasing this actually like about a month ago but some other deadlines were hitting so it's now scheduled for Q2. But I will be blocking this and letting the data out very, very shortly. That's all I've got. I do have quite a bit of time for questions like almost 10 minutes. So if you want to interact with me online, please, I'm pretty predictable and easy to find. Usually it's my name. Yeah, find me. Let's talk about this. And yeah, we've got 10 minutes to talk about it now freeform style. So I'll take questions, thanks. Okay, we have a mic. The question's up there, up in the back. Okay, shout it out. Yeah, sure. If you let me, what could happen is two blocks would be fine at the same time on two different nodes. Yeah. Now you have the longest chain. What, you have to distribute the longest chain, right? Yeah. So in this case, because there's a collision that happens, I don't know if a collision has ever happened. How will your system handle that? Because now you have two of the longest chains that have to distribute it out and then whoever figures out the next longest chain that becomes the longest. Oh, okay, yeah, yeah. So how do you handle that right now? Yeah, so each block that's loaded to the database has a, it's a linked list effectively. So a block references its previous block. And so when you have two blocks that are produced at the same time and the network's trying to fight out like which is the longest chain, we don't take a position on that. We just store both of them in the database and then eventually one of them appears to be a dead branch where it has only a few blocks kind of hanging off what becomes the main chain. Yeah, so we capture all of that. We capture all of that. Yeah, those branches in Ethereum are called uncles. Yeah, uncle blocks. Questions? So those uncle blocks, are those queryable as well? Yeah, yeah, yeah, you can see them. So is that like a Boolean flag in this egg, ignore all the uncle blocks or? Sure, well, I mean it's just a SQL query, right? So the data are all structured and ready to go for you so you can do whatever you want with that. Don't be shy, ask me stuff. Here we go. So any plans to start capturing Stellar or some of the other alternatives? Yeah, there's actually some, so I mentioned a lot of these ICOs and cryptocurrency projects are on Ethereum. There's not really blockchains for them yet, but there are some other ones where it's their chains, Stellar, Ripple, Dash, a few others. Yeah, there's interesting analysis can be done on all of those. I would say I'm a bit biased toward looking at things that have something more than just a distributed ledger and something more like a virtual machine. There's different, I guess more interesting types of insights that could be had by looking at those data sets. But I've not yet been preparing any of them. If you have some specific suggestions about what might be interesting and why, I would love to have that conversation either afterward or on Twitter we can start a thread. Yeah, it's a good idea. Here we go. I have a question about the real-time transaction. Yeah. So can it support a real-time transaction? I mean in the memory pool? Ah, no, I'm not supporting mempool. So the question is related to when a peer wants to submit a transaction to the network, it's not immediately added to the block and there's actually this queue of transactions that could be added to the next block and usually what the miner will do is grab the most valuable ones for somebody who bid to add their transaction next because it's a high-party transaction. That's what you're getting at. We are not currently monitoring the mempool so we are something like, I guess it depends on how long a transaction can sit in the mempool, but it's usually not more than a few minutes, like five blocks ahead, so something like 75 seconds. So we're 75 seconds behind real-time. But realize those transactions that are proposed in the mempool can actually be canceled out before they're executed or they could even fail. So indexing the things in the mempool, I'm not really sure how much value there is there, although if you're doing trading it could be an interesting, like, leading indicator of what's about to happen. But yeah, I'm not currently tracking that. That's a great question. No, maybe. I don't know. It kind of trickle in. Where are you going? One more. Hi, this looks all really beautiful, but is there a particular reason of why you are doing this? Why I'm doing this? I thought it was just really interesting. Like, you hear a lot of, so, okay, so take a step back. I'm a developer advocate. I'm a developer relations. I get basically marked on my performance of bringing attention to Google Cloud. There's a lot of hype around blockchain and a lot of what's being just like, a lot of the narrative in the media, there's no substance behind it. It's like somebody on some news network spouting nonsense coming from who knows where, not actually referencing any data, right? And if you look at a lot of websites like that do have a chart, it's some low res gift that came out of probably a consultancy and was resized repeatedly. Nobody has access to the real data, right? So giving people more access to data produces like a more sophisticated, concrete conversation in the public discourse space about what's really going on. So now we don't have to depend on these consultants anymore who are operating these databases and selling access to build reports and you can't really influence what report they're gonna build for you unless you pay them, right? We just give the data away for free. Please go build the report you want and talk about that. Yeah, it's democratizing the data. Google's mission, right? Making the data publicly available, accessible and useful. So yeah, it's completely in line with corporate mission. Woo, Google, Google's awesome. Yeah, right? We love open data at Google. So how big is the data set on BigQuery? Cause you said you have 500 gigs free to use. I'm wondering how many queries can I have. Yeah, so if you could select star on all the columns, you would burn it up. So BigQuery, sorry, Bitcoin. Yeah, we can do that. The primary data is 200 gigs and we do a little bit of denormalization to make it easy to query in BigQuery and so it's 500 gigs. So if you did select star on all the fields, you'd burn it up. But in reality, you're not doing that. Ethereum is a lot smaller. Ethereum is actually 70 gigabytes for to operate the full node and it's 200 gigabytes in BigQuery. Yeah, these are not huge data sets. They're just very difficult to access. Even it's public open data already uncontrolled by anyone, just really hard to get to. Yeah. Thank you. Sure. All right, one minute 36 seconds I'm calling it. Thank you very much. Woo! Woo! So thank you.


Having reached this point of development, from a modern context, if we try to artificially create community by putting ourselves in a situation where we do need each other to survive, it kind of feels fake, like you can set up your intentional community and go off grid and go low-tech and say, yeah, now we depend on each other. But in the back of your mind, you know you could probably rejoin the rest of society and meet your needs with money. You don't really need each other, you're just pretending to need each other. There needs to be a satisfying answer to why are we doing this? It has to be more than getting to know each other or, quote, having community. That's not community. You can't have community be the motivation for community. There has to be some other aim that you're all willing to commit to.


Welcome to JSA TV and JSA Podcast, the newsroom for telecom and data center professionals. I'm Laura Noland at JSA. Joining me today is Peter Bannister, CEO of Fiber Expressway. Peter, welcome to JSA TV. Thank you very much. Well, Peter, let's start off by talking about Fiber Expressway. Can you tell our viewers about the company and your role? Yeah, okay. So Fiber Expressway was set up in 2017 as a special purpose vehicle to look at building a subsea cable and data center ecosystem here in the west coast of Australia and northern territories. I'm the CEO of that company. We have a small team. We have a chief operating officer sitting up in Tokyo and the company is built around an outsourcing model. So we partner with large global organizations to help us build the project. Wonderful. We're hearing more, though, about Fiber Expressway's big initiative, building a gateway from Australia to Southeast Asia and then beyond with Project Co80. Can you tell us more about that? Okay. Yeah, Co80 is a Japanese word that literally means to go beyond. There are many subsea cables in the ocean and are many data centers. I think ours is fairly unique in the fact that we own the data centers and a subsea cable. So we have an interest in discussions with content providers who now can come to one company to get their needs for the subsea cable and the data center, whereas at the moment they go to separate companies and that can have problems around service levels agreements and that sort of thing. And our cable goes from Perth all the way internationally eventually through Indonesia, Singapore and in Malaysia where we will link up with a very large American cable that's coming the other way, which we not allowed to mention but it's coming down. And we also got the coast of Western Australia to the northern territories, which is a very remote area, but even closer to Asia. So our proximity to Asia-Pacific is what attracts our customers to Asia. Peter, you mentioned how the subsea cable and data center businesses are very competitive. You talked a little bit about the uniqueness of Fiber Expressway and Project Co80. So can you expand a little bit more about that and how that's impacting how you're moving forward? Yeah, as I say, the uniqueness is very much that we build this ecosystem as one thing. So the data centers and the subsea cable is paired to those data centers. So they're designed together. And as I say, a company can come to us for the whole raft of services. One of the companies we deal with on this project is the American company Sienna. And they talk very much about what they call the cloudy ocean about the need for data centers with its own subsea cable. And that's exactly the unique solution we've put in together here for that project. Who are some of your other target customers, verticals and partners? I know you mentioned Sienna, but who else is on the horizon there? Yeah, Sienna will be actually a partner with us. They provide some of the technology for us. But here in Western Australia, it's a very big mining country, a bigger company Sienna, BHP, also oil and gas and floats in LNG off the coast. So they're more, we call them domestic markets, but they're normally owned by international companies. But from Asia and America, we are looking at the content providers, financial services, companies who can call trading systems here in West Australia. And any international organization that's sitting in Asia at the moment is a target customer for us. So we can give them the same services as they get in Asia. And we think a better price and a better proximity to come and work as well. Here, it sounds like Momentum is really building with an anticipated live date in 2023. But let me ask you, what effect has COVID had on this project, if any? Has there been any effect in that timeline? Yes, you're spot on. I was at the PTC in Hawaii earlier this year in January and heard rumors about COVID and being typically sort of English and Australian thought that will never happen. Of course it has. So that's probably, when I say delayed things for about nine months, it's the time COVID's been delayed, because we obviously have to go out and raise a huge amount of money to build this project. That was all going very, very well till COVID struck. So the big money is still there. Some of the development capital we've had to raise, which we've now done, has taken us a little bit longer. So I think that will roll back into 2024 now instead of 2023. But that's, as I say, that's because of COVID, although COVID has been good for us because the demand for bandwidth has increased incredibly. And also the information that they have, they need to store it somewhere. So for data centers again, that's been good business for us. We'll be watching for updates for sure. So where can our viewers go to learn more about Fiber Expressway and Project CoAT? There is a website, which is www.fiberexpressway.com. You'll see a few media releases come out soon with some of the partner organizations we have. As I said, it's an outsourcing model. We're a small company. So we're engaging with Tata Group, the Indian technology company, CNR invention before, and there's a company called Verdi for around data centers. So I think we've done some joint announcements with those guys. We obviously have some confidentiality things we have to agree with them, but they're keen to get the project advertised as well. We'll go check them out and look for those news updates. We thank you so much for your time, Peter. It's been a pleasure. Okay. Thank you very much for your time. And thank you viewers for tuning in to JSA TV and JSA podcast. Happy networking.


Hi everyone, Joe for Jazzy's casewrakes.com with the Court Kings team random. So this is where for Court Kings pick your team 5 and 6, we pull those teams out, order them from most expensive to least expensive, and we're going to assign you a team. So here's the other thing, you're guaranteed two teams, one spot equals two teams. So 13 spots that were doubled up. So big thanks to this group right here. We had thanks to the people who bought their spots straight up. Congrats again to the people who won their spots in those two fillers. Look at Thomas with the sweep right here. Congrats to the people right here too. Now that's 13 spots, right? I think so. Yeah, that's 13 spots. Let's double up, like Sir Mix a lot. So there should be 26 total on that list. Let's roll it, randomize it four to six, 10 times. And we're just randomizing your names. We're matching up with a team after 10. Good luck. One, two, three, four, five, six, seven, eight, nine, and 10th and final time. Now here's the good news. Everyone's got a team. Now who's got some of the top teams up there? Adam, Daniel, Francis, Josh up there. All right, so let's assign you a team. And we'll put rooftops next to everybody's names so you know you won that in this particular team, random. Congrats, Josh, Pistons in Court Kings 5, Francis with Pistons in Court Kings 6, Daniel with Cavs in 5, Adam with Cavs in 6, Daniel with Rockets in 5, Francis with Rockets in 6, Randy with Magic in 5, Adam with Magic in 6, Thomas with Grizzlies in 5, Adam with Grizzlies in 6, Adam with the Celtics in 5, Eric with the Bulls in 5. Thomas with the Celtics in 6, Eric with the Bulls in, you've got to be in the full case there, Eric, there you go. Randy with the T-Wolves in 5, Thomas with the Sixers in 5, Sean with the T-Wolves in 6, Sixers in 6 as well. Thomas with the Heat in 5, Nolan with the Heat in 6, Thomas with the Bucks in 6, and the Knicks in 5, and the Wizards in 5, Nolan with the Knicks in 6, Thomas with the Wizards in 6, and Josh with the Jazz in both 5 and 6. So there you go. Thanks for watching. I'll see you in the next video, separate videos for both 5 and 6. Jaspy'scasebreaks.com. Bye-bye.