Motivation, this one's a bit different than what we typically think about when it comes to motivations.  We can just end the lecture there. Just that's enough, right? The point is is that these traditional definitions of motivation Let me qualify that before I go on they suck in terms of like from a scientific perspective They may make sense on the surface and of course they make sense on the surface Otherwise, it wouldn't be around we call that face validity. The problem is they have no experimental validity They're just completely circular, right? So traditional definitions focus on these internal drives You have this internal state and that is what is motivating you to do the particular task your Your low in this one Thing in this one, you know, whatever it is So you want to do it and you have this and you have that and it's this internal thing that's Moving you forward, right? And it's like, whoa, okay. How do we observe that? Well, we can't What we can observe is a few other things, right? Again, those are typically circular and why are they circular? Well, the idea is that well, why did I do X because I was motivated to do so? Well, why were you motivated? How do we know you were motivated to do so because I did it Why does the child learn to you're gonna hear my cat? my cat just decided to climb into a Suitcase and he got into a spot that's gonna be very hard for him to get out But we're just gonna let him hang out there.  So we'll come back to that topic later. I Guess there's something reinforcing about that. Anyway, so again, why does the kid learn? Well, because he's motivated to learn. Well, how do you know that he's motivated to learn? Well, because he's actually learning yay nice wonderful circular argument completely useless for science completely useless for a Further understanding of what motivation really is So we need to look at motivation from a more scientific a more empirical perspective and of course behavior analysis has taken a more empirical Perspective now it gets kind of odd I'll grant you that and talking about motivation from this perspective can be a bit challenging So but it works right and there's a lot of evidence to support that this is a very parsimonious and clean way to present What motivation really is? But I do want you to realize that this doesn't fit very well with our society It doesn't fit very clearly with the views that we typically have and I'm not talking about scientific views I'm talking about the views that we have as a culture And if you start spouting off things about CMEOs and EOs and NEMOs and all this stuff people are gonna be like You're just crazy So this is one of those frustrating things is that our culture is Loves these circular arguments because they sound great on the surface right so an internal drive in an internal state Which motivates you to do something?  That's what what sounds good in our culture But that doesn't necessarily mean that that's actually what's happening Just remember think about it from this perspective at one time the world thought the world was flat, right? Everybody thought that the earth was flat. That was what was culturally appropriate to say and saying something else got you in trouble Right that sort of thing happens when you talk about motivation believe it or not It happens when you talk about a lot of this behavior analysis stuff people just freak out That's okay, you know, it's it's part of changing the way we view the world and that's not a fast process So from this other perspective Motivation relates to something in the environment that can be observed to measure So something that influences you to do something right so we you might go oh reinforcers They're what influenced me to do something. Yeah, that's part of it right and in fact, that's a major part of motivation But we're gonna talk about things that modify reinforcers We're gonna talk about these things called motivating operations and we're gonna break them up into four categories and those four categories are actually Back up and we're gonna break motivating operations into two categories those two categories And they're gonna break broken down into two more categories each So four categories overall to deal with the motivating operations that have been directly observed These are not inferred. These are things that have been directly observed There are two categories right off the bat establishing operations and abolishing operations establishing operations Increase the effectiveness of a reinforcer and more accurately they increase the value of a reinforcer So if we're thinking about the three term contingency and you have the SD the response and the SR are the consequence, right? Establishing operations and motivating operations in general modify the consequence They're not something that act directly on your behavior They modify the consequence of the behavior so they change the value of the reinforcer or the punisher, right? So establishing operations are going to increase the value of the reinforcers Abolishing operations are going to decrease the value of the reinforcers Again, they affect consequences both punishers and reinforcers got a hauler for the fighty knock it off. Hey He's still playing in the bag. Anyway, there's something motivating about that Probably because he never gets to do it. I'm recording this lecture in a room that the cats typically don't get to play in so They're going crazy in here and having the time of their life and that's because Appropriately we have established the the value of this room to be greater. Why? Because they don't get to come in here very often There's stuff I don't want to mess in with in here They have a tendency to knock the books off the shelf and those types of things So there might be all sorts of noises that are going on but They're in here now and they're playing around so it's we definitely increase the value of this room It could decrease the value of this room. So I've changed the change the motivating operation By letting them hang out in here all the time, but there's stuff they can get into that. I don't want them getting into so anyway That was actually a really good example of this situation I could just kind of finish the lecture, but we're going to go ahead and move forward to again The idea is They affect the consequences they change the value of that of that consequence of the reinforcer the punisher And I'm going to talk about this in terms of just reinforcers, but you can apply this to punishers as well There's the condoms again, right? Let's just tend to pop up everywhere Anyway, it's a changing value an abolishing operation will decrease the effectiveness of a reinforcer This goes really well with the picture, right? I mean really think about it What's the reinforcer for having sex the feeling you get, right? Um, that's at least part of the reinforcer. Well, guess what a condom does Decreases that value it decreases the feeling right it makes things less sensitive. So When you're using condoms you're decreasing the value of the sexual baby Have the brain for sure that's available for sex And it makes absolute sense why someone would be less likely to choose condoms Over having sex without a condom If they've experienced both right because when you put the condom on it is going to decrease the value of that sexual act For both people now there's a way around this by the way and it's Has to do with deprivation of sex.  So deprivation is one of those things we can use We'll talk about that more here in a moment Okay, so again, so the condoms are actually an abolishing operation For the value of the sexual behavior When something increases the effectiveness of a reinforcer we call that an establishing operation So again, if I deprive you of sex or if you deprive yourself of sex then Sex becomes much more valuable. You know, there was an interesting study Wasn't even a study. What was it? It was it was like the social change thing that happened in in a couple of places and though I think it started out in hilly and then it got picked up in kenya and It was absolutely hilarious and it worked perfectly and it was a great example of an establishing operation and What happened was is that these ladies all got together and they were like we've had enough of our husbands being assholes And by assholes, I don't mean they were like beating them or things like that But they just weren't taking care of things. They just weren't being a good husband. So The general idea is that the ladies were like fine. No more nicky for you until you start doing the things you're supposed to do So what did they do? They made the value They increased the value of those other things like completing their chores, right? Because if they were able to complete their chores for a month, then they were able to get that to have sex so They they increased the effectiveness of the various reinforcers by abolishing everybody Withholding it, right? So they deprived their husbands of sex which then made sex more reinforcing for them And of course they put some other tasks on that use some great behavior modification techniques I mean that that's just hilarious when if you start to think about what all the different things that they used In terms of doing that, I mean they were using rules. They were using goals. They were using motivating operations Reinforcers effectively. They were changing the environment. They were selecting for new responses They were they got response generalization going on. They got stimulus. It is actually a great little technique You can look it up and see it on the internet There's an interesting story about how that all worked out and there was a large number of women that got together and did that And the basic idea is that they're just trying to change their husband's behavior The trick with motivating operations and what makes them motivating is that they happen before the reinforcer is delivered So you put the condom on that happens before the reinforcer, right? And that immediately changes the value of that reinforcer So These things I mean in that three-term contingency I don't like to put them in front of the sd's but some people do I kind of put them off to the side And put an arrow directly towards the consequence because that's what they're doing They're really affecting that they don't affect the discriminative stimulus They don't affect your behavior directly. They affect the reinforcer, which then may in turn affect the behavior And again, it's only changing the value. It doesn't that doesn't like get rid of it It's not a consequence and into itself. It just changes the value of that consequence Interestingly enough these do not depend on learning learning history at least one category of them doesn't That categories the the unconditioned ones, right? So you have uncondition motivating operations uncondition Establishing operations and uncondition abolishing operations, right? So those are the ones that don't depend on learning history and the condition motivating operations They only depend partially on learning history. They depend on the fact that those CMEOs and CMAOs are They've already been conditioned for those reinforcers to work or those punishers to work But again, it doesn't the changing the value of those things Is not Learned sort of thing. It's just literally through deport deprivation and satiation and other techniques Right poor kiddo and tears, right so deprivation We deprive you of something generally anything that we deprive you of it increases the value of it We talked about that before right so we talked about With holding access to a reinforcer to make that reinforcer more valuable what we were really talking about was establishing operations There may be some others out there that you can think of okay, but deprivation in general is a very effective technique so you want to make Accident you want to make one behavior more reinforcing than Or more likely to occur than withhold access to it for a while And we talked about this with the premac principle right the low probability behavior and high probability behavior stuff So I can even make low probability behavior reinforcing by preventing you from doing it And by preventing you from doing it for a while that Basically means that you're not going to get the reinforcers for that and as a result it increases the value of it Okay Abolishing operations satiation fill you up guess what so if I've got you completely full on something So if I let you eat all the m&ms in the world that you want You let me eat all the chips in the world. I want that type of thing then Guess what it's going to decrease the value of those reinforcers And in fact, you know I have this search in a group of students that are reinforcing my behavior For showing up for class on time and what what they've done is Use Cheetos or various chips in order to reinforce my behavior Well in order for that to work I continue to work one of the things that I actually self-manage here is making sure that I don't buy chips at other times All right, so you're not going to see chips in my house You're not going to see chips in my office unless they're the ones that I'm getting as reinforcers The idea is is that I'm not satiating myself on chips because if I satiated myself on chips Then the ones that are brought to class to reinforce my behavior Are the being on time are not going to work. In other words, I will have abolished the effectiveness of it All right, there may be some others your job to think about that So let's look at the condition versus unconditioned stuff pretty straightforward With uncondition motivating operations of value effect value altering effect is innate if I deprive you of food You don't have to learn anything about that that will work right off the bat Okay, in fact, this is one of those things that we use When we're doing animal research as we Deprive them of food. We get them to a particular free feeding weight And once we achieve the you know, so they're at their free feeding weight Let's say I don't whatever number of grams that that would be for a squirrel or chipmunk whatever that is their squirrel Then within withhold some food for a while We deprive them of some food until they drop below their free feeding weight At that point food is a very very valuable reinforcer And we have established the effectiveness of that reinforcer and the animal will work hard for that So but the behavior that is affected by this value altering effect is learned So think of the chipmunk person or the the squirrel person the lever or the rat person lever Whatever it is in the operating chamber that lever is learned, but the value of the the reinforcer is not It's something that it's absolutely innate With condition motivating operations the value effect is due to learning. So The example I gave earlier, right About in previous lecture about that imagined pressure, right? It's the guy doing the golfing thing. So he's adding that imagined pressure to himself The idea is is that that is some sort of Value altering effect. So if you imagine that yourself's under pressure imagine He hopes like it's the 18th hole the u.s. Open and you're tied And you got to make this one putt for birdie in order to win And you what you're trying to do is alter the value of the Reinforcer in other words alter the value of making the putt to make it more likely that you'll do it make it more valuable when you do But that's something you had to learn to do, right? That's not an innate sort of thing One of the other ones that we talked about is money, right? So deprivation and satiation of money is actually a condition motivating operation It may seem unconditioned, but you had to learn what the what the value of money was in the first place How are these things different than sd's and s deltas? The idea is that a discriminative stimulus is a signal that tells you that a reinforcer is available for a particular behavior So the sd's are connected to a response, right in the sense that that response will be reinforced That's what an sd is saying Cmo's are events or conditions that alter the effectiveness of the consequence So these things are targeted at the end. They're not targeted at a response, right? So they're changing the value of the reinforcer, which then could be used for any response So they're not the discriminative stimuli. They're not signaling what to do. They're not signaling any of that stuff They're just saying that all they're going to do is change the value of the reinforcers They are very very temporary You don't get stimulus control developing with cmo is like you do with a discriminative stimulus The you know once they once you've been undeprived so to speak once you're back to your free feeding weight Then food is less valuable This is an interesting one to think about Oftentimes rules and goals are not really discriminative stimuli. We kind of talk about them as being sd's They kind of are they kind of hurt but some people have argued that rules and goals are actually conditioned motivating operations The idea that especially with goals the idea with the goals that by stating that goal i'm Altering the value of doing the behavior that is being set up in that goal All right, because then now I have achieved it in that achievement Um, it is more important than like reaching the goal, right? So I've reached the goal rather than just oh, yeah, I did the behavior Oh, yeah, I was um successful today at not smoking a cigarette. Yay Okay, but if you say hey, I've been my first I achieved my first goal my first step and getting rid of Getting rid of smoking cigarettes Um was today and I did it right so it increases that value you set that goal and it increased the value of the reinforcer So I do believe that's it. So we'll talk to you soon and I hope you've enjoyed this set of lectures


Genuine Health formulates products to nourish and inspire a truly remarkable feeling of health and vitality. To nurture the health of people and our planet, Genuine Health sources sustainable ingredients, plants trees to replenish the planet, donates their nutritional supplements to animal rescue sanctuaries, and funds research to protect the endangered bee population. Some popular products from Genuine Health include fermented organic gut superfoods. This no bloat whole food formula provides 22 fully fermented organic plant based ingredients, including organic greens, superfoods, and prebiotics to help nourish a healthy gut, ecology, and supportive overall wellness. Fermented vegan protein spars. For the ultimate on the go snack, these fermented vegan protein bars provide a full spectrum of amino acids from seven plant based protein sources. Each bar provides 14 grams of highly digestible protein in support of maximum bioavailability and gastrointestinal health. Fast joint care with fermented turmeric. This powerful formulation provides research supported natural eggshell membrane and bioavailable fermented turmeric. These concentrated ingredients provide nourishment to joints and connective tissues and support a healthy inflammatory response. If you have any questions, please call, visit, or email the professional supplement center.


in this UPSC civil services examination. I thank my family for this without their support this would have not been made possible. I also thank Shankar IIS Academy because all my basic foundations in this preparation was laid off in this academy. I am a PCM student of Shankar IIS in their 2017 and I have been most fortunate to have studied under Shankar sir. Those concepts in geography and the math reading classes helped me till this day. Thank you Shankar sir. I am also very grateful to the faculties of Shankar IIS Academy especially our Rajitha man who is my sociology teacher not only a teacher she is also a mentor, moral supporter during that low phases of my life right from fleeing my taff till the day before my interview she has been with me she made me say to this process thank you so much man. I also thank the other faculties in Shankar IIS Academy whose our teachings were very helpful for me. I also thank everyone in Shankar. Thank you.


Today we're going to talk about BERT. So let's jump into it. This is the transformer neural network architecture that was initially created to solve the problem of language translation. This was very well received. Until this point LSTM networks had been used to solve this problem. But they had a few problems themselves. LSTM networks are slow to train. Words are passed in sequentially and are generated sequentially. It can take a significant number of time steps for the neural net to learn. And it's not really the best at capturing the true meaning of words. Yes, even bi-directional LSTMs. Because even here they are technically learning left to right and right to left contexts separately and then concatenating them. So the true context is slightly lost. But the transformer architecture addresses some of these concerns. First, they are faster as words can be processed simultaneously. Second, the context of words is better learned as they can learn context from both directions simultaneously. So for now, let's see the transformer in action. Say we want to train this architecture to convert English to French. The transformer consists of two key components, an encoder and a decoder. The encoder takes the English words simultaneously and it generates embeddings for every word simultaneously. These embeddings are vectors that encapsulate the meaning of the word. Similar words have closer numbers in their vectors. The decoder takes these embeddings from the encoder and the previously generated words of the translated French sentence. And then it uses them to generate the next French word. And we keep generating the French translation one word at a time until the end of sentence is reached. What makes this conceptually so much more appealing than some LSTM cell is that we can physically see a separation in tasks. The encoder learns what is English, what is grammar, and more importantly, what is context. The decoder learns how do English words relate to French words. Both of these, even separately, have some underlying understanding of language. And it's because of this understanding that we can pick apart this architecture and build systems that understand language. We stack the decoders and we get the GPT transformer architecture. Conversely, if we stack just the encoders, we get BERT, a bidirectional encoder representation from transformer, which is exactly what it is. The OG transformer has language translation on lock, but we can use BERT to learn language translation, question answering, sentiment analysis, text summarization, and many more tasks. Turns out all of these problems require the understanding of language so we can train BERT to understand language and then fine tune BERT depending on the problem we want to solve. As such, the training of BERT is done in two phases. The first phase is pre-training where the model understands what is language and context. And the second phase is fine tuning, where the model learns, I know language, but how do I solve this problem? From here, we'll go through pre-training and fine tuning starting at the highest level and then delving further and further into details after every pass. So let's go deeper into each phase. So pre-training, the goal of pre-training is to make BERT learn what is language and what is context. BERT learns language by training on two unsupervised tasks simultaneously. They are mass language modeling and next sentence prediction. For mass language modeling, BERT takes in a sentence with random words filled with masks. The goal is to output these mask tokens. And this is kind of like film the blanks. It helps BERT understand a bidirectional context within a sentence. In the case of next sentence prediction, BERT takes in two sentences and it determines if the second sentence actually follows the first in kind of what is like a binary classification problem. This helps BERT understand context across different sentences themselves. And using both of these together, BERT gets a good understanding of language. Great, so that's pre-training. Now, the fine tuning phase. So we can now further train BERT on very specific NLP tasks. For example, let's take question answering. All we need to do is replace the fully connected output layers of the network with a fresh set of output layers that can basically output the answer to the question we want. Then we can perform supervised training using a question answering data set. It won't take long since it's only the output parameters that are learned from scratch. The rest of the model parameters are just slightly fine tuned. And as a result, training time is fast. And we can do this for any NLP problem that is replace the output layers and then train with a specific data set. Okay, so that's pass one of the explanation on pre-training and fine tuning. Let's go on to pass two with some more details. During BERT pre-training, we train on mass language modeling and next sentence prediction. In practice, both of these problems are trained simultaneously. The input is a set of two sentences with some of the words being masked. Each token is a word and we convert each of these words into embeddings using pre-trained embeddings. This provides a good starting point for BERT to work with. Now on the output side, C is the binary output for the next sentence prediction. So it would output one if sentence B follow sentence A in context and zero if sentence B doesn't follow sentence A. Each of the T's here are word vectors that correspond to the outputs for the mass language model problem. So the number of word vectors that we input is the same as the number of word vectors that we output. Now on the fine tuning phase though, if we wanted to perform question answering, we would train the model by modifying the inputs and the output layer. We pass in the question followed by a passage containing the answer as inputs and in the output layer, we would output the start and the end words that encapsulate the answer, assuming that the answer is within the same span of text. Now that's pass two of the explanation. Now for pass three, where we dive further into details. This is going to be fun. On the input side, how are we going to generate these embeddings from the word token inputs? Well, the initial embedding is constructed from three vectors. The token embeddings are the pre-trained embeddings. The main paper uses word piece embeddings that have a vocabulary of 30,000 tokens. The segment embeddings is basically the sentence number that is encoded into a vector. And the position embeddings is the position of a word within that sentence that is encoded into a vector. Adding these three vectors together, we get an embedding vector that we use as input to BERT. The segment and position embeddings are required for temporal ordering, since all these vectors are fed in simultaneously into BERT and language models need this ordering preserved. Cool, the input is starting to piece together pretty well. Let's go to the output side now.  But with training, we need to minimize a loss. So two key details to note here. All of these word vectors have the same size and all of these word vectors are generated simultaneously. We need to take each word vector, pass it into a fully connected layered output with the same number of neurons equal to the number of tokens in the vocabulary. So that would be an output layer corresponding to 30,000 neurons in this case. And we would apply a softmax activation. This way we would convert a word vector to a distribution. And the actual label of this distribution would be a one-hot encoded vector for the actual word. And so we compare these two distributions and then train the network using the cross entropy loss. But note that the output has all the words. Even though those inputs weren't masked at all. The loss though only considers the prediction of the masked words and it ignores all the other words that are output by the network. This is done to ensure that more focus is given to predicting these mass values so that it gets them correct and it increases context awareness. So that was a three passes of explaining the pre-training and fine-tuning of bird. So let's put this all together. We pre-trained Burt with mass language modeling and next sentence prediction. For every word, we get the token embedding from the pre-trained word piece embeddings, add the position and segment embeddings to account for the ordering of the inputs. These are then passed into Burt, which under the hood is a stack of transformer encoders and it outputs a bunch of word vectors for mass language modeling and a binary value for an extended prediction. The word vectors are then converted into a distribution to train using cross entropy loss. Once training is complete, Burt has some notion of language. It's a language model. The next step is the fine-tuning phase where we perform a supervised training depending on the task we want to solve. And this should happen fast. In fact, the Burt squad, that is the Stanford question and answer model, only takes about 30 minutes to fine-tune from a language model for a 91% performance. Of course, performance depends on how big we want Burt to be. Now the Burt large model, which has 340 million parameters, can achieve way higher accuracies than the Burt base model, which only has 110 parameters. There's so much more to address about the internals of Burt that I could go on forever. But for now, I hope this explanation was good to get you an idea of what Burt really does under the hood. For more details on the transformer neural network architecture, which is the foundations of Burt itself, click on this video. Subscribe and stay safe, a lot more content coming your way soon, and I'll see you soon. Bye-bye!


Hi everyone, Joe for jaspyscasebrakes.com. We did it. We knocked out 2023 Bowman Draft Baseball Super Jumbo Case Break number two. We're doing all six boxes. All card ship, a lot of cards per pack, a lot of stuff, five autos a box. Let's get after it.  This is Pick Your Team 2. Gary, you ended up with Last Spot Mojo with the White Docks before I pulled the remaining teams and we gave them away in that blaster break. So if you have Blaster 1 next to your name, you won those teams in that break. Thanks everybody for getting your team straight up or joining that blaster box. I appreciate you. All right now, this is for the awkward size case here, so I'm going to just open it here. We've got the whole run right over there and I appreciate it. Once again, everybody making this happen. We do have more in the store if you want to get after it, but I think we don't have time for any full cases tonight, but we do have time for that. There's a two box break loaded up. Another two box break of Super Jumbo from a fresh case, a different case than this. So if you want to do that, we do have time for that after this break. TP is excited. This is, this, you must be Todd, Todd, what, what teams do you have or team or teams do you have? What are you, what are you expecting? What are you looking for? Let's go to everybody. Who's, who's in the break? Let's do a little roll call. Who's in the break watching live? What are you hoping for? Metz and Tiger is nice. Definitely hoping for a lot of Max Clarks for Detroit. Gilo, Gilo will just be happy with anything. If you want to spot through the blaster break, got the Astros, couple autos, some low-numbered cards, some color would be awesome. Yeah, that would be cool. We have not seen one of those yet. Of all the, a lot of breaks, I think on Instagram, Teddy did a bunch of this Bowman draft. I did a bunch of this Bowman draft, so did Jason and Mike. I just feel like we've, none of us have seen a Tom Brady, just even just a regular, just a card, let alone Otto, but we haven't seen anything like that. So it'd be nice to see one, Gilo, I agree, just to say we did. All right, there's Alex Ramirez for the Metz to 199, Todd. With the Metz, Wyatt Langford, all of these will go to Tristan and all of these Max Clarks, Paper and Chrome, all card ship, but these are the sort of prospects that we're highlighting. On that list is also, is also Paul Skeins, obviously your number one overall pick, number three overall pick, Max Clark, Wyatt Langford, Jacob, Wilson, Matt Shaw, Colt Emerson, some of the key players that we're highlighting. And if I happen to miss any of those, don't worry, our sorting and shipping team also have the same list and they'll be, they'll do their best to pull and top load those. And there's Cam Fisher, Gilo with the first Otto, won the team in the filler. And before the video started, he was just like, you know what, I feel like this guy always hits. There you go. Decent penmanship too. Right. Got him. And there's Dylan Campbell for my Dodgers, 96 out of 250. That'll be for, for Mark, Mark L, and the Dodgers, there you go Mark. I threw some of this paper and there's Isaiah Coupette, 68 out of 499 for the Rocks, that's going to be for Darren. And there's Maui Ahuna, that will be for the Giants, Mark B with that one, to 499. Are you? You're having a better time. Yeah, it's always, like if it's slow, it's always better to have someone else next to you. Yeah. Yes, this is true. That's the whole morning. That's, that's kind of rough. Like what is Joe gonna, or what is Jason gonna do? So when someone's going to be here, hang out with me, or how close are we to that 20? Okay, sir. That's like tantalizingly close. I know, you know, like I'm supposed to leave in 15 minutes. Just grind it out. Uh, Ledbetter will go to the Rays, that's for Mark B, and then that's Dylan ahead. I think so. That's for the Padres. Those glass cards are pretty cool. Chris Lindsay with that one. I'm not bored. I'm just tired. I've been here for 12 hours, you know, I don't know, five hours of sleep. Oh, five hours of sleep. I tried to go to bed early last night. And then it didn't happen. It's hard. Like once your body's adjusted to like a weird schedule. It's like I'll get in bed at like 11 o'clock and I won't go to bed till two. Right. You know, if you pop on a TV show, you watch a documentary, I'll lay down and I'll be like, all right, I'm actually going to try and fall asleep, no TV, nothing.  Right. There's Garrett Forrester, Garrett Finding Forrester. That's going to be Chris Butler and the Pirates, the buckos from Roseville, California. You think there's anyone from the South Bay in this set this year? They're kind of cool, though. I'll just start looking through every card. Yeah. Start looking at the back of every card and look for, you know, Torrance, Alameda, El Segundo, Redondo Beach. I don't think Stanford can. Ah, that's too far from here. Yeah, what happened? You don't want to bring it to me? It's an XL. I'm like, I like swimming it. Are we giving away now? Yeah. Joey Juarez. We're giving it away. If it was like, if it was like size Joe, then lines of double X. I didn't ask for a double X. I gave Jason a Dodger or a Z. Mookie Betts, actually. All right, Jacob Wilson for the A, Steve H, Matt Shaw. These will all go to EA and the Cubs. We'll find some South Bay guys here. Alberto Rios is from Bellflower. Where does who does he play for? Oh, the Angels? I feel like that's why it curled. Our guy, Jesus, Chewie works here and he went to high school. I think he went to Downey. There's a ball player that's his year that is in the Rocky system, I think. There's Felonin Celestin to 499. You also get that Colt Emerson paper too, Walter Seattle. You saw some paper autos pulled today. That can't be too common, right? And there's Paul Skeens. Nice. Pirates. That'll be for Chris Butler. The Butler did it. It was the Butler. Your number one overall pick. Wish there was some color to it, but a lot of box go to start. That's right, Hitchburg, Gilo. Welcome to Hitchburg. Well, this guy's kind of close. That's right, Paul Skeens is from Fullerton. Ooh, Edward Little Teaser here. Langford and Skeens pair a lot in Super Jumbo. All right, let's keep an eye out. See some color coming up. Autograph wise. And it's a Ralphie Velazquez. Nice. Aqua Lava Autograph. For Brian and the Guardians. Cleveland, this is for you. 115 out of 199. Nice. So, Albert O'Reo just went to Bosco and Belford. I'll play for Stanford afterwards. Nice. And is he in this set?  And it's Tai Pete Glass and Michael Carrico. Four out of 10. Nice low number for EA and the Cubs. It's in the game. Nice to see those low numbers right there. Those look pretty cool. These right here, we'll do a little recap later. All right, one box down. And here's another one. He is. All right, we'll keep an eye out for... for local guy, Alberto Rios. All right, Tommy Troy. And Rios are the two Stanford guys. Tommy Troy, Diamondbacks maybe? B-backs, right. Someone, someone Diego is looking for. He's on our Our Honorable Mention list, but top six or seven for Ed.  All right. Onwards, another box. And another search for... Monsters. All these Wyatt Langfords going to Tristan in Texas. Here's a Missouri guy, Geelo. You should look him up. We've got time. We've got time in this break, Geelo, for you to look up your Missouri guy really quick and see where he is. There's Teddy McGraw. Almost a Tim McGraw. That's not Tim McGraw. That's Teddy McGraw. Seattle. That's going to be for Walter. 10 out of 4, 99. And there's a Max Anderson. Not a Max Clark, but a Max Anderson. 19 out of 99 for Detroit. That's going to be for Todd. We're looking for more color from this guy, Max Clark. Ooh, I don't want to see any mon stars in this. Bracks out. That's not what I want to see. You guys are in the wrong set, guys. That's supposed to be here. And we've got gold paper, 26 out of 50, Rainer Arias for the Giants, Mark B. And we've got a Wyatt Langford base autograph for Tristan. There you go, your fourth overall pick. Nice. Ah, so Geelo's guy from Missouri is Zantello on the Red Sox. A tier two prospect. Yeah, Ed, you were right. Ed was like, if you see a Skeens Auto, a Langford Auto isn't too far behind. I'm sure the other way around works, too. See, a Langford Auto, Skeens Auto isn't too far behind. So in super jumbos. That's good to know. Yeah, as you watch more of these breaks, ladies and gentlemen, you'll start to see some patterns start to emerge. Personal criteria for picking a player to chase whether, like, as it pertains to Bowman Draft, unless it's, like, number one guys like this, you've probably got to think hitters.  Probably want corner infielders, to be honest with you, like, first or third base. Maybe even, you know, some of these shortstop guys can be pretty popular, too. Guys that hit for power play for big market teams. At least early on, those are the sort of criteria that I personally look for. Now as time goes on, as they start playing in the minors more, then you start seeing, then you start looking for, I mean, that's the criteria, like, if you're just day one of Bowman Draft. But as time goes on, you kind of want to see, obviously, how are they doing in the minors? Are they raking in the minors? Here's Grayson Hit, purple chrome autograph for Diego. Diego Lopez and the Snakes. 243 out of 250. But yeah, again, obviously, as time goes on, you want them to do well in the minors, kind of move up the ranks, year to year, and hopefully have, like, a personality. You know what I mean? Can't believe Upper Deck never capitalized any Space Jam Relic cards. Do they? Probably a licensing thing. Probably didn't have the license to create trading cards for the motion picture. And for the Metz, yellow parallel of 51S95, Austin Troser. That's going to go to Todd and the Metropolitan's. Yeah, what do you like, Diego? Consistency and a good environment. Yeah, I did see that. I did see Ronnie Mauricio tearing his ACL. Was he supposed to get... Was he going to be a starter this year? Was he a starter last year? Was he a starter? I think it was a shortstop in Francisco Lindoro's in the way. And there is a Mac Horvath. Specolotto for Joe Howard and the O's. There you go, Joe. 25 out of 71. And a white lane for paper. Some glass. Jacob Wilson glass, nice. These can be autographed, too. We haven't seen one yet, but the potential is there. A's Steve Herrick. And we got A's Zach Levinson, 22 out of 125. Awkaw Wave for the Cardinals. Michael with that one. Yassir Mercedes, 22 out of 4.99. So Jake Wilson struck out only five times in the season once. Does it say that here? Wow, struck out only 31 times in 620 career at bats. Geez. That's like a throwback to like... the players in like the 70s and 80s. And there's another Oriole. Jackson Beaumeister. Jackson Beaumeister. The Beaumeister, the Boester, the Beauminator. It's going to Joe in the Orioles. See you tomorrow. Ah, no power. I don't know, with that kind of... I don't know. That kind of contact, though, could power emerge? There's Alberto Rios. We were just talking about him. There he has some bellflower. That's near here. Nice third round pick by the Angels. Hopefully does well. And there's Zach Thornton. 134 out of 250 for Todd and the Mets. Alright, another box down. And here comes another box. Ed, what are you looking for when you're... when you're prospecting? Gila was asking this question a little bit earlier. I think it's worth exploring. It's generally hitters, right? I feel like that's what collectors seem to like. Hitters, power hitters, corner infielders, especially third basemen maybe. Maybe with the way they've changed the rules to allow... yeah, hit power combo with some flash. I wonder if with the new rules, do you think speed becomes sexy again? Maybe we'll see some 100 steel guys and that's gonna get people excited. But yeah, I guess if you could see... right, it would have to be like electric speed. If speed is to be sexy again. We're talking like stealing home kind of thing, which I think L.A. Della Cruz has done. Stealing home type electric speed. Like we're talking like... we're talking like Willie May's Hayes. I've even heard some Reds fans suggest that maybe... maybe you sell high on L.A. Della Cruz and the Reds organization should... should try to trade him for a giant haul. Who do I think has the most ridiculous career stats in baseball? That's easy, Shohei Otani. Someone who could hit and pitch at a top tier level. If it wasn't for the fear of injury, he could probably steal a bunch of bases, too. I think in his early years, they would measure Otani and Trout going down the first baseline. Talk about how fast Otani actually is. Faster than Trout. Trout's pretty quick for his size. There's Luis Guaniba. 122 out of 499. James Wood is faster than L.A. Sell the team, saying... But does he have that L.A. Della Cruz exit Velo? Retired players? Babe Ruth. He's got pretty ridiculous stats. See how many homers he's hit? This pitching in the early years wasn't too bad either. Tommy Hot, Guardians. 111 out of 499. That's for Brian. Cleveland, this is for you. I wonder who's trucked out Jacob Wilson. Is that the pitcher chase? Yeah, maybe. There he is. There's Jacob Wilson. He doesn't strike out a lot. Look it up, Gilo. I'll bet you can go through some game logs of Jacob Wilson and see who's trucked him out. I feel like a lot of times that could just be like... Just a handful of pitchers. Just a few pitchers who has his number for whatever reason. I'll bet it's not a bunch of different pitcher striking them out. Or maybe it is. I don't know. But I wouldn't be surprised. Just a handful of pitcher striking that multiple times. Crew's speed and power is a good prospect. If I need to see another, it's out there like him. There's Razan Zenatello. This is Gilo's guy. He went to Missouri. That would be for Boston. That's going to be for Kirk. And Drew Hackenberg, 22 out of 75. Yellow Lunar. You can kind of see the Lunar landscape. Parallel, which I think is kind of cool. That is for the Bravos. That would be for Patrick and the Braves. Salah Thiem thinks that I think Ricky Henderson tagging home more than any player ever. Or that the current player with the most normal base can still 100% here, still not catch him. That is kind of wild. You think that's still an unbreakable record, all-time steals? Because Ricky did play for a long time too. So someone, a player in his rookie year needs to just pun intended, hit the ground running. There's Cole Young to 499 for Seattle. It's for Walter. And there's Dylan Campbell. Dodgers. Mark. Mark Elv. Nobody will even come close. I think he might be right. I think that's one of the unbreakables. I mean maybe unbreakable in our lifetime. Maybe long after we shed this mortal coil then maybe that'll happen. Yeah, but I feel like guys like Ruiz, while they steal a lot of base, I suppose I feel like they don't get on base enough. I mean, Ricky Henderson could proper hit too. We got Mike Boeve. Boeve? 36 out of 1. Boevee. Eva. From that Disney movie, Wally. Wally. Directive. Should be looking for three more autographs out of this box. And we got Quinn McDaniel. That is for Mark B. And the Giants. Yeah, I'm with you Rex. I think that's another set of records that won't be broken. Nolan Ryan's No Hitters. Not too many managers in modern baseball that allow players to go deep enough No Hitters. And yeah, consecutive games, forget it. Speckled non-autos, not numbered. Indeed, Malcolm Vince, Coleman, Tim Reigns could run as well in the A's, but Henderson, Ricky was definitely... Yeah, I think anything in the pitching category, right? Are we ever going to see 500... We're barely going to see 200 wins for a lot of these pitchers coming up. And relatively speaking, that's probably by the end of their careers, 150 wins are going to be maybe haul-worthy for a future generation of pitchers, you know? And if you trickle that down just because how starting pitchers are deployed these days, I think if you just go down the rankings of those records, you know, like a number of complete games in a season. There's Johnny Formello, 53 out of 199. I feel like even in the 80s or 90s, there are still a lot of pitchers. Hey, we were just talking about it. Alberto Rios for the Halos. Jeremy with the Angels, won that team in the filler. A local guy. But yeah, I feel like even in the 80s, maybe even 90s, there are still a number of pitchers who would get, you know, of their 28 to 32 starts. There would still be a number of guys getting double-digit complete games. I think there's a lot of max effort pitching too, right? A lot of pitchers are going max effort more often, so I feel like an injury at some point. Definitely derail some players. And there's Luke Kashal. I'm going to go with that. Luke Kashal going to Mark B and the Twins. 35 out of 250. One, two, three, four, five. Those are five autographs. Let's see if we can find some parallels.  Maybe. I mean, I suppose there could be a time where, or a point in time where pitchers will be max effort, but because of that, they might be extremely efficient. Maybe that needle can be threaded. Power pitching. There's Colson Montgomery at a 150 for the White Sox. It's for Gary and the very noble Meyer for the Marlins. That's for Chris Butler. I wonder if you could thread that needle. Thread the needle where you can kind of do, like Greg Maddox used to do, like sub-100 pitch complete games. And then still rack up strikeout numbers. Maybe when there's a generation of pitchers that can do that, you might see the complete game come back. When androids get into the league, all records will be destroyed, says Rex. Unless we create a separate league for androids, but would that be racist against androids? Or maybe a time a thousand years from now where that might be a, or a hundred years from now, with technology going exponentially, that might be a thing. Maybe that is what will cure the virus of racism in society.  If all humans can hate androids together, this is like the humanity will come together if an alien invasion happens and for the greater good. There has to be a transitional point where that happens, right? At what point, how many, that's going to be in a future collective bargaining agreement. How much of your body can be mechanical parts? This will be in the 30-10 collective bargaining agreement. All baseball players must be at least, you know, 60% flesh and blood to be eligible to play a major league baseball.  Is that an unfair competitive advantage? You know, if he's like, oh yeah, I'm just going to swap out my right arm with a stronger bionic right arm. You know, instead of throwing, instead of my infield throwing speed from shortstop, being, you know, 95 miles per hour, I'm slinging that 150 miles per hour. At that point, players like Matt Shaw, the eighth, will be like, well, you know, I'll just get bionic legs to outrun that person's arm, you know, and get bionic eyes to be able to track pitches being thrown at 150 miles per hour. Where does it stop? Scared Forester to 199, but those are 30-10 problems. We'll let our great-great-grandchildren worry about that. There's Jackson Wiggins. In 2024, we can worry about pace of play in games, the size of bases, sticky stuff on baseballs. Jackson Wiggins, Cubs Auto, going to EA. If a 100% Android player signs a card, would that be a real auto or a facsimile? That would be a real auto, Rex. A facsimile would be if they copied that auto and then reprinted it. Your question should be, would it be a real auto, or would it be like using an auto pen, which is frowned upon in the hobby? There's Johnny Formello and Paul Skeen. Some color, 188 out of 250. That's for Pittsburgh. That's going to be for Chris Butler. Got the pirate straight up. I think I'm going to write some future sports sci-fi. Explore some of these issues. Much like Isaac Asimov explored those issues and such stories as iRobot. There's Luke Schilder. Use the false, Luke. It's going to go to Mark B. and the Giants. Blashield down. How am I supposed to fight? There are like three different wilds. There's like Wyatt Langford, Wyatt Hudful, and there was like a Wyatt Crowell for the three different wilds in this set. I don't know how there was a run in the 90s of a lot of Wyatt Earp movies. I think there's a movie called Wyatt Earp. And there was like Tombstone. And then there was like a third movie, I think. Maybe another Tombstone movie, but I think Val Kilmer was... No, no, Val Kilmer was in Tombstone, where Kevin Costner was Wyatt Earp. Tombstone was the better of that era of westerns, right? Why Wyatt?  There's Rhett... Louder! Louder! For Adam Cupperman, Cincinnati Reds. A little bit louder now. A little bit louder now. A little bit louder now. A little bit louder now. Has anyone been to a wedding where the wedding DJ has not played a shout? Zach Thorne 196 out of 199. You got to think that 95% or more of weddings in the United States, there's the other Wyatt right there, that has a reception with live music or any kind of music, DJ, band, otherwise, they're playing shout. 86 out of 99, Jackson Beaumaster. The Beaumaster. The Boester. The Bonator. They're playing it. They're playing shout. Nice. Christian Campbell. Gold Wave autograph. That looks sharp. That's going to go to Boston, that's for Kirk. 13 out of 50 on that one. Nice. All these Max Clarks going to Todd and the Detroit Tigers. Skeens. Max Clark. Have a nice scene on there. I feel like there's not a lot of, I guess we haven't seen a lot of Colt Emerson's. We have seen them. Not as much as some of these other guys. Shout. It gets old people, young people on the dance floor. There's a, gets people, there's a song that tells you what to do. People like that. You know, they can get louder. They can get softer. They're telling everybody to shout. The Isley Brothers version is usually the one that they're playing. Telling everybody to shout. This song, that's becoming more popular at weddings. Everybody clap your hands. Clap, clap, clap, clap your hands. It's not just a baseball stadium. Brick House. Play that funky music. That is at over 90% of weddings in the United States. Chris Butler. That's absolutely true. Oh, Max Anderson. Class of 2023 autographs. This is the first one of these I've seen. Class of 2023 autos. Not Max Clark, but Max Anderson will have to do, Todd. And it's 32 out of 50. Journey. They're always, everyone, I would say Journey. Just a small town girl living in a lonely world. It's usually at the end. She took a midnight train going anywhere. Just a silly boy. Born and raised in South Detroit. Born and raised in South Detroit. Born and raised in South Detroit. I know. That's unfair, Todd. Having two Max's on the same team. Come on. It's Colt Emerson. And Jason. Buffering. 27 out of 75. Yellow Lunar for Toronto. That's for Omar. And there's Colt Emerson Glass. They call me Mr. Glass. That's going to be for Seattle. Walter. Alright. We're in the final third of our break. Two boxes to go. Two of the six, final two. About another half hour to go. I think my timing was right. I said about an hour and a half for this. We're at the hour mark right now. 58 minutes. Rex, you're talking about the tears for fear. I'm talking about shout by the Isley Brothers. A popular wedding reception song. I'm talking about shout from tears for fears. A song that I would argue you're not hearing too often at weddings. Wedding receptions. I mean, unless it's like I don't know, the part where it's like everyone's gone home and it's not too many people left. I do not mean twist. I mean what the you know shout. The song where they say you know you make me want to shout. You know you make me want to shout.  Shout. Twist and shout. I feel like that should be at more weddings. I do not hear that often enough. Right, yeah. Like shout from Animal House. Not like twist and shout from Ferris Bueller's Day Off. Or the popular cover by the Beatles. Last song, please, please me. Alright, the penultimate box. Five more autos. Good level to little auto recap at the end so you can see what you got. If anything, hopefully we've got things to send you. I'm shaking baby I'm shaking baby Twist and shout Twist and shout. Johnny was shouting earlier.   Blake Mitchell Blake Mitchell Aqua Lava for the Royals That's their big prospect, Kirk Arnold. 41 out of 199, their eighth overall pick. Nice, Johnny. Grats on that. They make me shout. Even Twist and shout. Sacramento Kings are getting smoked here. Clippers are up 110 to 79. And we got a Matt Shaw glass, nice. Rex is asking what's the best wedding related movie? You'd say Wedding Singer and Father of the Bride. No, no Brady's, Johnny. Not yet. Kevin Perot of the 99 though for Todd and the Mets. Wedding movie. I don't know if I watch a lot of wedding movies. Wedding Crashers, there you go. That's a good one. That's better than Wedding Singer or Father of the Bride. Some may argue that my best friend's wedding is up there. Aren't some of the Mama Mia sequels about weddings? I've never seen them. But the trailers lead me to believe that they are wedding related. Here's Jay's buffer in again for Toronto. Godfather Part One has a great wedding scene. And then the sound of music has a wedding scene that I could do without. Don't need it. We got Emmanuel Bonilla, 89 out of 125. Scouting since he was 14. Oh, Rex knows are there quotable lines from the Wedding Singer? I've maybe seen that twice in my life. Kill Bill, that's right. There's a good wedding sequence there. It's a pretty good movie. I feel like Tarantino has opened up some restored and reopened some old single-screen movie theaters in Los Angeles, in the Hollywood area. I think he played screen-pult fiction at one of them which I heard was really cool. I wouldn't mind seeing Kill Bill 1 and 2 double feature in a little intermission in between. Grayson Hit 64 out of 150. Blue Wave that is for Diego. Nice. These are what are they called again? Mood Rings. This is a short print. And that is a nice Mood Ring. That's Matt Shaw. Your 13th overall pick for the Cubs. EA and the Cubs. Nice. Wait, only once in a blue moon do Scots find players driven as detail The former Maryland star eats two spoons of sugar or two spoons of honey 12 minutes before every game to get his energy level perfect. He's meticulous about his sleep and his pregame routines. All trades I should ease for his transition. Honey? If he makes it to the bigs people should throw honey at him? No, don't throw things at him. There's Hunter Haas, 91 out of 250 maybe have him sign bottles of honey or maybe send bottles of honey to him. If I saw him in spring training and if I was a Cubs fan and a Matt Shaw fan I would bring him a bottle of honey. I don't know if that was his choice. Maybe he mentioned that in an interview and someone's like we're gonna put that on the back of a baseball card. I don't think it's on the back of this card though. Any honey talk here? No, no honey talk back here but on that mood ring card you've learned something new. Oh absolutely Johnny, very happy it's gonna be harder to get to Dodger games these days but very happy about Otani on the team now if the Dodgers can address the real problem with the team which is starting pitching that would be that would be excellent. Can add two starters to start ahead of the youngsters and a Walker Bueller coming off Tommy John I would love that. Here's a 10 out of 10 Johnny Farmello. Nice that's paper 10 out of 10 It's late first round picked by the Mariners that's gonna go to Walter and we got Kevin Sim that is for Diego and the I'm in backs, the snakes, the D-backs and a cold Emerson yeah I would love to see I mean the way Otani said he would do his contract was for situations like this Chris where the Dodgers could still afford to spend money and be competitive I mean if we got Yamamoto at the front of that here's Enatello 90 out of 250 if we can have him at the front of the rotation and then maybe trade for another guy like a James Cease or a Glasnau type then you back that up with a recovering Walker Bueller you don't want to put too many innings on Walker's arm so coming back from Tommy John plus Bobby Miller towards the back of the rotation he doesn't have to worry about too much to learn his craft and then your fifth or sixth starter could be some combination of you know Gavin Stone or Tony Gonslin or you know a mixture of that and then you've got then you've got Otani in 2025 and there's Luke Schilder use the false Luke it's from Mark B just feel like Yamamoto what do you say Tuesday he met with some teams yesterday beating with teams throughout the week apparently and here is Camden Minacci 109 out of 125 that's for the angels that'll be for Jeremy so I suppose we'll see the Yamamoto Domino fall this week ideally and after that I think you probably see probably see Bellinger go off the board somewhere maybe he starts seeing trades happen more often there's like another Japanese picture that's been posted that I'm sure those who are out on the Yamamoto sweepstakes might go for him the next thing you know a couple months pictures and catches are reporting Jason Jaspi already talking about I think here I think Jason was smart I think the day the morning of Saturday morning or something like that he just had a sense that Otani was going to announce with the Dodgers he bought spring training tickets to a game in early March or something like that all that there'll be a lot of people in Los Angeles who are going to go to spring training this year it's going to be a zoo also who has numbers what do you think Otani's number is going to be or did Joe Kelly oh I guess it's already happened not Miguel Vargas at 70 I guess Joe Kelly had 17 but apparently he's going to give that to Otani I wonder what kind of deal transpires or you think Joe Kelly is just like thank you for choosing the Dodgers he's not going to try to ask Otani for like a million dollars 1.7 million dollars for 17 last box ladies and gentlemen I'd love to see Otani joke about how like joke about like how he can't afford team dinners because he's deferred most of his money sorry guys can't do the team dinner remember I deferred most of my money sorry Joe Kelly I can't pay for that number remember I deferred all that money it's Colin Hawk Mets it's for Todd there's Dylan Questead 007 out of 125 do the angels retire Otani's number that's actually kind of a good question you mean like after all is said and done with Otani's career I wouldn't be surprised if they did you know after he's in the Hall of Fame I'm sure the angels would love to keep claiming Otani and use his name and likeness for marketing purposes another paper Paul Skeens going to to Chris Butler that Dylan Questead that sort of is this Aqua looks a little different like a forest green from here but might be Aqua 125 way for the twins that's going to be for Mark B one auto four more to go and we're done with this break thanks for thanks everybody for hanging with me spending time with me goofing around getting weird helps the break feel like it's going a lot a lot more quickly so I appreciate that thanks everybody yeah five or six seasons something like that right if he number does get retired yeah probably be the only player in history to have his player number retired with only five or six seasons without winning without going to the playoffs or winning a World Series title I mean if I was the owner I wouldn't want to put up the number but the angels playing Artie Moreno Calvin Harris do-do-do-do-do do-do-do-do bounce do-do-do-do-do bounce do-do-do-do-do 85 out of 150 blue wave autograph for the White Sox Gary last Bob Mojo 70% of the time last Bob Mojo hits 100% of the time according to Jaspie Math around here no Otani has not had one playoff game Trout has had one playoff series and I think the angels I think that was sort of earliest in his career and I think it was just I think they got swept I think it was 0-3 no wins something like that which is kind of crazy if after the first year of Otani's career if I said you know Will Otani and Mike Trout reach the playoffs over the course of Otani's career everyone would have said yes I think I guess it was a little touch and go when he would suffer those injuries early in his career but once he kind of rebuilt his body to handle the rigors of major league baseball season it seemed like up until this Tommy John surgery it seemed unstoppable and he still might be unstoppable he might just focus on hitting and be like I'll just hit 6C this year here's Jacob Cravey to 125 for the Orioles that's going to be for Joe got Jace Young, Josh's brother to 199 Tigers that'll be for Todd ooh and we got a Jack Mahoney red that's out of five one out of five and a Jack Mahoney red chrome autograph that's a train whistle for Darren Mackenzie DMACC out of fives and under get the train whistle all aboard the Big Hit Express who are the what should have been teams so many of those Trout with Otani Cubs after 2016 Dodgers in 2017 Dodgers in 2018 the Dodgers two years ago half Dodgers last year that's starting pitching I knew that that was going to end in tears at some point we've got Christopher Toran there's so many of those teams I mean you can just look down the list of in baseball history especially in the last 20, 30 years how many times the best especially as the playoffs have expanded how many times the team of the best record has gone on to win the World Series so there's a lot of shoulda coulda woulda teams look at the Mariners that team that won 120 games or whatever there's Nathan Detmer to 499 and we got a gold Ethan O'Donnell autograph we're on to Cincinnati Adam Kopperman 27 out of 50 gold pops nicely there a lot of nice color in this box we've got another glass here that's nice that is Enrique Bradfield Jr nice Orioles Joe Colton Ledbetter to 99 and maybe in the White Sox last few seasons right on paper with some of the names that are that are there I think a lot of people thought for the White Sox we've done a little bit better with what they had and there's Luke Keisha for the twins I think this is our fifth auto Mark Beap with that one one top load of despair right here let's see if we could be for a nice low numbered car that would be nice and we do have some color here it's Cole Young 177 out of 250 that's what it was 116 games apologies to the West Coast apologies to the Seattle fans who are probably listening right now alright nice break everybody that was Super Jumbo Pick Your Team 2 we got tons of color tons of parallel right here that our shipping team will sleeve in top or they're already sleeved they'll top load before these get shipped out here's an autograph recap that out of 5 we got the mood ring Matt Shaw was really cool for EA Blake Mitchell some nice color that's out of 10 paper Class of 2023 Max Anderson Paul Skeens Purple Chrome some speckle some purple some white Langford is nice that's out of 10 chrome Paul Skeens based autograph along with this future teammate Garrett Forrester Cam Fisher for the Astro started things off for us that's it boys and girls thanks for watching thanks for breaking with us I'm Joe I'll see you next time for the next Bowman Draft Break bye bye


Sometimes people don't understand open source from a commercial point of view because if they don't see it as a singular product with a singular entity then they believe it opens them to some sort of risk whereas we believe that there's always risk in every situation but actually many ways the risks are a lot less because you're not glued to one particular provider and with a healthy project like Moodle for example if you're not happy with your partner you can change to another partner and there's no concept of all partners sort of suddenly disappearing and the code is open so no one's ever going to come and knock on your door and say you can't use this.


Oh, welcome folks, this is Tom O'Brien of TFNN, we go five days a week, we go 10 hours a day, we go 24 hours a day on the internet at TFNN.com, always remember folks, whatever you think about, you bring about whatever, you focus on growth, hope everyone's having a great day, safe day, it's making a great night folks, don't take anything personally, your truth is personal to you, your own opinions and point of view reflect your own agreements and our personal to you, it's no one's truth but your own. Not gonna lie, let's take a look at it out here, we had the Dow Industrial's finished down 162, you had the NASDAQ off 45, S&P's off 24, you know, not bad numbers folks, you know, in the context of what we're talking about, those indices are only about down about a half a percent, you had the Dow down six tenths, the S&P down six tenths, NASDAQ down five tenths, that being said, however, with that when you do look at from the highs to the lows, now you get some action, S&P out here, the futures, the futures went from 2961 to 2924, so you can see from the highs to the lows, that's some big action, no doubt about it, we're gonna take a look at the NDX 100, same type of setup inside the NDX, NDX had a high out here today of a 7851, and you got a low out here of 7751, 100 points, yeah, oh man that's a hit, that is intense, okay, so let me pull this back again, yeah, 100 points, and what you have now at this high too, if you happen to be into candlestick charting, that's quite a, that's a little bearish engulfing, what a bearish engulfing is, is that you start at the high, you close at the low, you know, you're taking out about, in this particular case, we're taking out six to seven days of trading, small caps, what do we do with the small caps, small caps continue being weak, small caps down to buck 50, trading 156, 76, the XLE also basically gave it up, XLE down to dollar 32, you did 20 million shares, yeah, you get ABC down, oh man, watch this, they put some volume in this at the end, let me see this volume, yep, there it is, so you can see at the end of the day, that's would be the 1600 hours, which is a four o'clock, 1.7,949,000, another 60,000, they did it, they broke, they broke that swing and they broke it with volume, so that's saying the XLE next stop down to a 6330, and this is not a big ABC down, it was 68, 65, three bucks, that gives you a 6385, that swing that's going after is 6330, I expect we're going to get down there, Exxon Mobil, we take a look at Exxon, Exxon probably gave it up to, yeah, Exxon's one of the, that was, Exxon's probably the culprit, down to buck 61, Chevron didn't handle price too well also, Chevron, they popped yesterday, today down to 225, gold contract, okay, so we have the gold contract, gold contract, power comes out, first move in gold goes top side, second move in gold goes downtown, what we have out here, you close, end up closing down 840, you've done 260,000 contracts and not a bad setup, still hasn't broken any swing lows, you actually did push into the last swing high with volume 268 versus 279, notes and bonds, you get the 10-year note, 30-year bond, they both continue to want higher price, pretty amazing, it's not amazing in the context of the, when Powell was speaking folks, the bottom line is that the market in general does not expect, out to January of 2020, no rate hikes, and if we take a look at the aspect of the rate cuts, it does come in with over a 50%, even with the context that Powell was saying there's not good one way or the other, but what you have here is that you can see, if you happen to watch from my screen, in December it goes over 55%, well it goes over 50%, it's 55% for rate cut, rate hikes, they're just not in there, so what's surprising is that the market itself looks like, I guess, the market itself wants some more rate cuts, if we go take a look at that E-mini S&P before they close at 415, you're going to see that it went right after the lows of yesterday, broke the lows of yesterday, this looks to me, now you're going to get a structure that you really can get some action on the way down, I wouldn't be too surprised if this S&P gaps down to about the 2900 in the morning, which would be about a gap, well it wouldn't be a gap in the S&P, we end up having trading down to that level, if we wake up in the morning, we're down to that level, because you're getting a lot of, well let's put it this way, you had Apple come out with numbers that market liked, Apple ended up closing up $9.85 was up as high as $12, right, it was saving the Dow industrials and saving the S&P in general until the Fed announcement, that's how this thing shook out, once that was done, guess what, there was just the market was saying okay, I'm going to sell into this, let's go take a look at Square, Square closed at $73.62, that is trading right now at $69.28, let's see what they have to say money wise, their revenue, they expected, the expectation was $556 million, that's first quarter, one second, okay the earnings per share, they expected $0.08, they made $11, so they made it there, revenue they expected $479 million, they made $489, that's your first quarter, second quarter, yeah, here it is, okay so this is going to be a second quarter going forward that they're missing their numbers, they made their numbers, first quarter was there announcing, second quarter they're guiding down, second quarter the estimate had been $556 million on a revenue basis, now they're saying $545 to $555, so the top end is still underneath their estimate, their earnings had been $0.18, now they're looking from $14 to $16, their payment volume is expanding by 27%, so bottom line, that's a decent expansion of volume, there's no doubt about that, Qualcomm, let's go take a look at Qualcomm, Qualcomm come out with numbers, Qualcomm has been a rocket ship by the way, Qualcomm closed at $86, trading $82.92, but this stock here went up $35, I think in the last two weeks, yeah, we're up from like $57 to $81 even backing down the $5 when they just came out, stay right there folks, come right back.