So there is this fuzzy logic tool application, there is already a similar example running on the website. Go check it out if you haven't done so already. It's over here. You can play with it. That's a human alone and has no noise options. So currently we are adding fuzzy logic features to it and it looks like this. You can add the noise level to the ECG waveforms. There are some preset waveforms generated in JavaScript. Just using basic math functions. You can turn the noise all the way down. You have the human score, so you can click on it yourself. There is instructions at the bottom. Go check it out on the website. You can play it. This one is a normal ECG waveform. So when I do not click on it, I get a reward in the shape of a points. Can't give you any other rewards. So that was a hit because that was abnormal ECG. This one also missing a bit. So when I click on it, I get a hit and 10 extra points. Same with this one. Not sure. It's the same one. I think there is a 60-40 ratio between abnormal to normal. That's a normal one. So I do not click on it and I get another 10 points. Click on it as well. Every 50 points, the speed will go up. And on the right side here, this is the new thing is a machine learning what our fuzzy logic algorithm is doing the same task. So it's not cheating. It doesn't have the labels. As I said, the waveforms are being generated in JavaScript. The fuzzy logic is actually running in the back-end Python code. So it doesn't have the labels. It's only getting the raw data in the same way as you see it on the screen. It gets the numbers for the waveform raw values. It's currently not doing very well, as you can see. That's because we just changed that earlier today. We removed one of the features that we were looking at. So we're looking at frequency, amplitude, and peaks, positive and negative peaks. And the abnormality score down the bottom here is the output of the fuzzy logic system. We decided to get rid of frequency. Well, mainly there's two reasons. So first is that it wasn't actually doing much. Second, we only look at a single PQRST complex. So there's no frequencies. So there's no, for example, peak to, what was it, the R to R distance for continuous waveforms. We're looking at each complex, QRS complex individually. So frequency didn't make sense. We are still looking at amplitude, but we give it a low priority, mainly looking at positive and negative peaks. And now we also added a R peak sharpness value. But we're still working on that. So originally, we just had normal and abnormal values. And we had just arbitrary, assuming it's normalized between zero and one, and we take below 0.5 and above 0.5. But now that didn't work quite well. I'll go into details in a bit here. These live streams, it's all about the details. So beware. So now we're adding instead of just two membership functions, we're adding three low, normal and high. We are probably not normalizing it. So the R peak sharpness, it's actually the distance halfway through the peak. So this sharp peak gives an sharpness of 26. And there is another example of not so sharp R peak that should give a larger number there. And it's not coming yet, this one. And that didn't work. Okay, so, and obviously we've noise, the whole idea is that with noise things should become worse. So then even if the algorithm is performing well without noise, then you can add noise to it and see how performance drops. One of the rules for us is not to use any magic numbers. So all these membership functions, if there are two, we just divide that 0.5. If there are three, we do a three way split equals split. So for example, in this case, it's wrong. We'll get the bots doing the coding for us. So we get GPT4 and GitHub co-pilot. GitHub co-pilot normally doesn't have much context. So it's making a lot of mistakes. GPT4 tends to be generally much better for us. Popping the code quickly. This is the waveform generation. There is only a bunch of them. There's four or six. There's essentially two variations for QRS complex, a regular waveform and examples of where one of the other waveforms in the ECGE signal is missing. So no P wave, no S wave, no T wave. And later we might be adding more examples as we go. So that's nothing. You can never increase noise and see how the algorithm is performing performance drops. Or you could add more waveform examples and see how it affects performance as well. We have the game logic. Actually it does all the scoring, measuring the score and everything. So all the measurement of the score is done in front end and all the fuzzy logic done in the back end. So the fuzzy logic, the bot, doesn't have the labels. So they isolated from one another as you would expect. So when you play against the robot, you would not be complaining that the robot is cheating or something. Okay, so this is the end of the Python script. Okay, so we shared all the code with you. We would like to fix a few things. Our peak sharpness is not working well. We get a value of 27. We always get a value of 27 and it doesn't change much. Sometimes it's 25. We need to check how that the function is doing. We'll need to improve on it. Now also the peak sharpness value is not being normalized. Yes, all of a sudden it went all the way up to 85. So there's something wrong with that calculation. Have to check it out, improve the code, go over the membership functions, also the peak sharpness, we want it to be three levels, low, normal, high. Instead of just the normal and abnormal, we'll have to modify the fuzzy logic rules to reflect that change. Okay, I mean, yeah, we could normalize it. That will be easier. I think yeah, you normally normalize between zero and one, don't you? So I think that's reasonable. So we're doing, yeah, so we're applying a basic filter to reduce noise. It's a basic butter worth. Have to check it might not be working correctly. Yeah, in this sense the port is cheating, isn't it? Because it can filter signals. So I'm thinking for the human also, you know, overlay the filtered version of the signal, you might do it later. So it's finding the R peak and then doing the distance between the right and left crossing. So it's going halfway through the peak, should be fine. But then the, yeah, so I'm getting 24 for this sharp R peak and 25, 24. Okay, that's, you know, the noise could add the variability and then I'm getting 97. So it's actually working pretty well. I don't know what, I don't know if it's changing over time, essentially becomes better over time. Is there any over time changes that are being made? I don't think so. You have to check that filter. We'll have to check that filter. Yeah, I have people, there's always someone saying, you know, when you're working on ECG, someone will say, how am I interested in EEG? When you're working EEG, someone say, you know, they want the other one, maybe we should do both at the same time. But then someone will say they want the PPG something, which is also something we are interested to look into. But this is mainly just an example of how fuzzy logic works. Instead of doing like a general, you know, like a textbook example, we actually apply it onto this synthetic data, onto this ECG scoring game that we already have running. Yeah, big sharpness issue. We want to normalize it as well. Just go with the board. It's normally does not do mistakes in the beginning of the development session. So we might return sharpness score. I just comment that out and use the new one. This should be normalized as well. Yeah, the numbers are now very low. 0.03, 0.04. And that's expected to be the same. And then 0.01. Okay, Y on Earth doesn't go. This function calculates the sharpness based on the width of half the maximum height of the RP, which is inversely proportional to the sharpness. If the RP is very pointed, this width will be small, and the sharpness score will be high. Yeah, but it's way too, well, first the numbers generally are way too small. Next, for normalization, you can use minmax scaling based on the observed range of sharpness scores or standardize it based on the mean and standard deviation if the data is roughly normally distributed. Yeah, so it's not normalizing it yet, is it? The membership functions can then be adjusted in the fuzzy logic system to reflect these three levels. You need to define the universe of discourse for the RP sharpness and set appropriate trapezoidal or triangular membership functions based on the normalized scores. Okay, sometimes GPT-04 goes into this error generating response state, and you can actually continue. So you can have a regenerate the response, which I'm happy to do, I'm just not sure it's gonna work. I'll just refresh the page quickly to continue generating, see if it's still on topic. Maybe, maybe not. Yeah, I was saying GPT-04 is better in this case because it's more because we're doing more general stuff. We can edit the last prompt as well. Now it got stuck on us. Yeah, the interface is not great, is it? At least when we refresh the page, it lets us continue with the chat. So I might do that. Okay, 0.4, 0.3. There should be one that they get something else. So we have this one, then we have the 0.1 or something. Yeah, this one. Okay, so with these two examples, it is not behaving as expected or is it? Can you double check? Also, the numbers are very low. How can we fix this? Yeah, I think it's broken. Yeah, that's nothing you cannot do in the GitHub copilot, can you? But then it's thinking forever. Doesn't look promising. Don't let us fix, try and fix the code manually. It's not gonna be fine. Okay, it's really stuck, isn't it? Right, now it's working. Okay, that's right. How can we fix it though? Other morphological features that could be more indicative of sharpness. Yeah, I thought the distance between the two should be fine. What's wrong with that? So it's finding the maximum peak and taking halfway distance. Just a pretty sure this, yeah, can we get rid of these two? Sharpness, cool. But we need that, don't we? Wait a sec. So not do the one over, just do the width, yeah. Right, so we get 97, wait, normally. Yeah, the rules are not working because that 97 is way outside the 0 to 1 range. That's fine. Right, okay, we get 97 and 91, which is not much of a difference as at 24. Yeah, there's something wrong with it, isn't it? Maybe there's something wrong with that filter. Hey, we should display the filtered data. I mean, we could do it for, you know, if the bot having access to filtered data, then the human should have it as well. And yes, that could make your labelling, human labelling more a bit easier, depending if, how well the filter is working. Consider the scale of the measure. If the sharpness values are too low, it might be due to the scale of the waveform data or the calculation method. Ensure that the units of measurement for the waveform data are appropriate and consider scaling or transforming the sharpness values to a more useful range. Okay, if we're scaling, why do we need to transform? Normalization. Normalization is crucial to ensure that the sharpness values are comparable across different waveforms. Normalization should be done based on a known range of sharpness values observed in the data. For example, if sharpness values typically range from 0.01 to 1, you can normalize these values to a range of 0 to 100 for better interpretation and use in the fuzzy logic system. Well, ideally, we would not even need to normalize. Adjust fuzzy logic membership functions. Once you have a proper range of sharpness values, you can adjust the membership functions in your fuzzy logic system to affect three levels, low, normal, and high. Make sure that the universe of discourse for the R-peak sharpness includes the entire range of observed values after normalization. That's fine. Debugging. Implement debugging statements in your code to print out intermediate values used in the calculation of R-peak sharpness. This can help identify where the calculation might be going awry. Guess we have some suggestions. Remember, these are conceptual sketches and will need to be adjusted based on your specific data and the range of values you observe. The key is to ensure that the measure of sharpness is sensitive enough to reflect the actual variation in the sharpness of R-peaks across different ECG waveforms. We're using the epsilon 4. Sounds a bit... It's just a constant number, is it? No, I'm not talking about the message. I'm talking about the actual sharpness score to avoid division by 0. I don't think that's the problem. All just max. We have a scaling factor. No, we don't want to do that. Get rid of that. Normalization. Yeah, for this, we need to know the mean and max values. No, we don't want to do it. Okay, the first suggestion wouldn't work. We don't have an issue of dividing by 0 as it is. So that's fine. A normalization. I don't want to do specific normalization. It isn't doing 1 over the value is, in a sense, normalization. The other main question is why the numbers do not make sense? Or maybe they do. Okay, in the normalization function, the sharpness values have to be saved somewhere, is that correct? So do we need to use the back end for storing these numbers, do we? Well, because it's simulating, eventually, a situation where you just connect the device. So like in an ideal sense, you'll be just taking your ECG recording device and connecting it online, and so it uploads the data, streams the data onto, well, obviously, bionicchaos.com, not any other website. No, I mean, that number actually works now that that's suggesting a major change. I'm starting to defend the previous algorithm. Yes, so with these values, what should we be scaling? Now, I mean, maybe we can do both later, but just continuing with the same, with the previous approach of the distance at the half height of the peak, looking at the current examples that I added, what should the scaling be like? Yeah, we don't want to have a magic number for the scaling. Now we don't want the 2000, we potentially can do 10. Let's just do 10 over there, right, 0.38, those numbers are more like it, 0.4, 0.41, okay, that's fine, 0.4, 0.1, yeah, 0.4 and 0.1, would these do the trick? Okay, we just changed the code to this, to have 10 instead of 1. Now the values seem to be correct.  Can you adjust the membership functions accordingly? We have it suggesting this simpler, a calculate R peak sharpness, we try it quickly, 0.4, 0.1, it's actually, it's cleaner, 0.3, yeah, we'll see how it works with more waveforms. So we get a 0.1 for this and 0.4 for normal one. That should be fine. Now, for the fuzzy logic membership functions, if you're getting sharpness values around 0.4 for normal waveforms and 0.1 for wider R peaks, you need to define your membership functions to reflect this. Here's a possible setup for your membership functions. Okay, we have those membership functions, oops, no, this bit sharpness, it's not called that, but okay. In this setup, the low category captures the wider R peaks, medium captures the normal range, and high captures the very sharp R peaks. The triangular membership functions overlap, meaning that a sharpness score could belong to both low and medium categories to different degrees, depending on its value. This is typical in fuzzy logic, where crisp distinctions between categories are not made, and elements can partially belong to multiple categories. Don't like that name, and we like this to be normal. Make sure that you define these membership functions within the context of your fuzzy logic system, and then adjust your fuzzy rules accordingly. Okay, this is better, should have a rule using this thing, rule seven, the eye all low, can it do this control eye all low? It's actually doing that, send the OR operator abnormality likely, oops, some problem, some problem with the rules, I need a GPT to have all the code anyway, no, no, no, no, that error before didn't make sense, now it's gone away, what, it's weird, we have low normal high, yeah, check those rules, yeah, this one, what do we do abnormal, that's wrong, this is wrong as well, yeah, because we changed the code, let's see if, the error message you're receiving indicates that there's an inconsistency in the definition of membership functions for our underscore peak underscore sharpness. In the code, you're trying to access a membership function named abnormal, which does not exist. To create this, you should ensure that the membership functions you reference in your rules are the same as those you defined. As per your request, you've changed the scaling factor for the sharpness calculation to 10, which seems appropriate. Now, let's make sure the fuzzy logic rules align with the membership functions you defined, low, normal, and eye. Here's how you should define the fuzzy logic rules based on the membership functions. Okay, so we have this, and what is it, seven rules now, rule one, was if peaks too few or too many, and the amplitude is not high, could be just amplitude is low, which will be different. The abnormality is likely too few, normal likely, yeah, those two rules probably could be combined, couldn't they? Okay, normal, normal is unlikely, rule five, let's read this. In the rules, we're now using the correct labels for the R underscore peak underscore sharpness membership functions. We use high and low to denote abnormal sharpness, assuming that both very high and very low sharpness values could indicate an abnormality. Adjust these conditions based on what constitutes an abnormality in the context of your application. Make sure that your fuzzy variable abnormality also has the correct membership functions defined, unlikely, possible, likely, and they're being used consistently in your rules. After making these changes, your fuzzy logic system should work without throwing errors related to undefined membership functions. Remember to test your system with a variety of input values to ensure that the rules and membership functions are behaving as expected. A couple of things aren't rules four and five are essentially the same, please confirm so I can get rid of one of them. Now the rule six that you suggested is the same as rule seven that I already had, please confirm. Yep. Both rules are indeed checking if both positive and negative peaks are within the normal range. If the intent behind these rules is the same, which is to determine that the waveform is unlikely to be abnormal when both peaks are normal, then one of these rules is redundant. You can safely remove one of them. Here's the combined rule. Rule two checks if there are too few negative peaks and not a normal amount of positive peaks, then it's likely to be abnormal. Rule seven, the old one, checks if the R underscore peak underscore sharpness is either too high or too low, then it's likely to be abnormal. They're not the same because they check different conditions. Rule two is about the number of peaks, while rule seven is about sharpness. However, if rule seven is intended to flag any sharpness extremes as abnormal, it is similar to the new rule six, which uses the updated membership function names, high and low. You should keep rule seven if it contributes to the decision making in a way that is distinct from the new rule six. If they effectively represent the same logic with the updated membership function names, then you can replace rule seven with rule six. Ensure that the rules you set up are capturing the distinct scenarios you need to evaluate in your fuzzy logic system. Each rule should correspond to a unique combination of conditions that you consider important for the analysis. The error message you're receiving indicates that there's an inconsistency in the definition of membership functions for R underscore peak underscore sharpness. In the code, you're trying to access a membership function named abnormal, which does not exist. This error would be an easy fix. You always say that and then spin an hour. Based on the area you're encountering, it seems that there may be a set of input values for which none of the rules are firing. This can happen when the input values do not sufficiently activate the term set in the antecedents of any rule. In fuzzy logic, it's important to cover the entire input space with your rules to ensure that any possible input will result in some degree of activation. Review the membership functions. Make sure they cover the entire range of possible inputs. There should be no gaps between the ranges covered by the membership functions. Review the rules. Ensure that all conceivable combinations of inputs will trigger at least one rule. If there are any gaps in coverage, add rules or just existing ones to fill them. Default rule. Consider adding a default rule that catches any input combinations not covered by the other rules. This rule would typically have a lower confidence level and would serve as a fallback. Here's an example of how you might implement a default rule. Considering the updated rules and membership functions, let's ensure they're correctly set up. After making these changes, test your system thoroughly with a variety of input values to confirm that every possible input scenario results in some rule activation and that the system no longer produces the sparse system error. Hash ensure that the input ranges for the fuzzy variables cover all possible values. Amplitude. AutoNF3 hash this automatically creates low, medium, high membership functions. Okay, I didn't know you can do that. Enable to resolve rule execution order. There's two more rules that depend on each other. So if I... that's automatically generating rules. Automatically populate the universe with membership functions. Number of membership functions to create the fully automated use supply 3, 5 or 7. Any number may be generated if you provide an appropriate size list of names. Quality, quantitative variable. That's essentially a default for impedance circles that if the error... what's up with that window? It's not great. The error message you're encountering, unable to resolve rule execution order, suggests there's a circular dependency in your rule definitions. This can happen if the antecedents of some rules are consequence of others in a way that creates a loop, which makes it impossible to determine the order in which the rules should be evaluated. Okay, the sharpness now works. Okay, so we can get rid of all the rotate type functions. Check for circular dependencies. Review your rules to ensure that there's a clear cause and effect direction. Each rule should have a distinct antecedent, cause and consequent effect with no loop back to the cause. Rule graph visualization. If your fuzzy system library supports it, you can generate a graph of rule dependencies. This visual representation can help you identify where the circular dependency might be. Simplify rules. Simplify the rules to break dependencies. You may need to refactor some rules to prevent anyone rules outcome from directly influencing its own activation in a loop. Simplify rules. Simplify the rules to break dependencies. You may need to refactor some rules to prevent anyone rules outcome from directly influencing its own activation in a loop. Order of rules. Define rules in an order that ensures that the output of one rule is not immediately used as input to a rule that would affect the first rule's input. Let's look at the rules you've defined and try to identify any potential circular dependencies. From the rule definitions, it's not immediately clear where the circular dependency might be. All rules have distinct antecedents and consequence. However, the default underscore rule is using the negation of the abnormality consequent as its antecedent, which may create a circular dependency if it affects the input star the rules in a way that wasn't intended. To resolve this, you can modify the default rule to only consider the inputs rather than the outputs of other rules. This rule is very silly. Suggested by the bot, it was a hallucination, was it? Positive peak if not normal. Positive peak is not normal and the answer is not medium. Abnormality is possible. It sounds more likely. Big sharpness. Subnormal doesn't exist. We don't actually use normal or abnormal. Should get rid of it. No, we are using it for the decision. But not for this. Yeah, we have low normal high. That's right. GitHub co-pilot can do something useful. It's great. Not actually running the app. It's a good idea to run it. Okay, now it's working again. Anyone wants to test it for me? It's not correct. Normal. That's cool. No, it's not correct. False enemies for that. It's getting better over time or something. I don't think so. It should be normal. It's not too great. Check the rules again. Please do let me know what are any questions about videos.com. Any comments are more than welcome. Yeah, don't particularly care for likes or subscriptions or clicks or whatever. I do want comments. Your feedback would be greatly appreciated. Yes, it will be great to have a better way to visualize the fuzzy logic detection. How the fuzzy logic algorithm making decisions. That would be awesome.  Go for it. But not too funny. Also, you can touch on the following. Yes, we currently working on ECG today. But if I'm more interested in EEG, we were using fuzzy logic or trying to use fuzzy logic before to detect the seizure in a clean EEG. But we're also curious about using it to ignore noise in real time. Yeah, real time should be much faster than neural networks anyway. So real time is actually a good use case for fuzzy logic. I would think. Let me know what you think and maybe a comparison to a component analysis method, which yes, in terms of what assumptions are required for each and then finding the pattern against the specific course of action. Not sure what that means. But yeah, maybe the pot has some ideas. Give some overall stuff as to how to improve what we did today. So we will do this tomorrow. And any overall statements as to how this tool might be used. Wrapping up our session in a not too funny but lighthearted biomedical engineer manner. So we've been diving deep into the ECG squiggles today, haven't we? It's like trying to interpret an abstract art piece where every line could mean normal or code red. But seriously, the fuzzy logic system we're tweaking is like that friend who doesn't overreact to every little thing. It's calm, it's collected, and it only raises an alarm when it's truly warranted a valuable trait in both friends and algorithms. If you ask me now, if you're interested from the heartbeats to brainwaves, moving over to EEG, that's a whole new ballgame. Asia detection in EEG data is like finding a needle in a haystack, especially with all the noise. But you're right, fuzzy logic could shine here since it's all about handling uncertainty and imprecision, perfect for stormy seas of EEG data. And speed. Fuzzy logic is Usain Bolt compared to neural networks, which can be more of a marathon runner. Comparing fuzzy logic to principal component analysis, PCA, it's like comparing an improvising jazz musician, fuzzy logic, with a classically trained pianist, PCA. Fuzzy logic rolls with the punches, making decisions on the fly based on the vibe of the data. PCA, on the other hand, is all about rehearsal, finding the perfect linear combination of variables that best explains the data, given its assumptions about linearity and statistical distribution. As for finding the button against this specific course of action, let's assume it means challenging the status quo. In that case, fuzzy logic doesn't just push the button, it writes a whole new instruction manual. Improvements. We're on the right track with scaling and refining the membership functions. Tomorrow, we can look at tweaking the rules further, maybe consider other input variables, or bring in new data to fine-tune the system. In terms of broader applications, this fuzzy system can potentially be a game changer for real-time monitoring in clinical settings or wearable tech, providing quick, interpretable feedback without the computational heft of deep learning. It's about making smart, fast decisions, which, let's face it, is a universal good, whether in medicine or choosing what to binge watch next. All right, let's call it a day. And remember, in the world of biomedical engineering, the only constant is the pulsing line of a new challenge. Keep your senses tuned, and let's crack it tomorrow. Okay, yeah, the pot could be a much better YouTube channel host than myself. Let me know if you want to co-host a YouTube channel. I'll see you tomorrow. Bye.


How many of you have old TV sets? You know, big boxy and annoying in every way. I had one, just one. My nice 50 inches plasma screen crapped out on me, so recently I've been watching my shows on the old television set. It really was a hassle, lugging the thing from my garage to my living room, setting it up, getting new rabbit ears, the likes. I've had it in my living room, which doubles as my bedroom because, well, I am too lazy to walk to my room most nights and I just crash on the couch. I usually stay up all hours of the night watching the tube. The last couple of nights I've noticed a very strange phenomenon. The afterglow. At first I thought nothing of it. I just thought it must have been my eyes adjusting to the darkness.  I brought my head up and the afterglow remained. There, on the screen, as given as if the thing were on. I always had irrational fears. Clowns, being alone, stray branches tapping my window. But this disturbed me in a way no fear had. I got up off the couch, causing it to squeak from the release of pressure, and walked across the carpeting floor to unplug the set. I pulled the plug from the wall and to my dismay, the glow was still there. It is a faint kind of dark light.  If you've seen it, you know. If you haven't, lucky you. I thought nothing more of it and went to sleep. I awoke the next morning and opened my eyes to the television.  I remembered the previous night and shattered a bit, but thought it was all in my head. That night I did my usual ritual of staying up late watching the TV, but I again shattered at the thought of the TV being the only thing making any noise at all in my house. I was alone, but that fear had dissipated with the years. This time I was bound and determined to make the afterglow not happen. I pulled the plug before shutting off the TV. The afterglow was there, but different. Now there was an egg shape in the middle of the screen. I thought it may have been from pulling the plug, but I thought nothing of it and laid down, defeated by this relic of the 1970s. I laid with my face away from the television, almost too afraid to look at the screen. I fell asleep, but had a terrible sleep. Nightmares plagued my slumber, their origin wasn't known. I don't even remember what they were to a point, but I do remember the background was. The afterglow. Why was it so frightening? What made it so creepy? The next few nights I just unplugged my TV from the wall after watching my shows, turned my head and laid down facing away from the set and not looking back at any time, fearing what I might see. The glow. The devilish horrid glow. It isn't scary. Why am I afraid? I thought over and over. I slept like this for weeks, until one night something bothered me deeply. The sound of breathing. It was labored and harsh.  I almost cried when I could still hear it. I decided to face my fear and look at the TV. That was a bad choice on my part. I should have just slept and ignored it, but no, I had to look. I turned to the glowing screen, and in horror I realized what the avoid shape on my screen was. It was a face, egg but there in the glossy convex screen, one of pure terror. It looked as if it had seen something truly terrifying. I closed my eyes and I could still see it in my persistence of vision. I couldn't escape. I picked up the TV in my hysteric state and tossed it out the window. It crashed through the glass and broke with a loud bang. I don't watch TV anymore at night. And if you have an old boxy TV, don't sleep near it. Ever.


Now, unfortunately, in this game against the Phillies, the first game of the NLCS, his first pitch is a fastball, middle, middle, 92 miles per hour, and Schwerber is going to crush that and ride the wave, ride the horse, ride something, ride everything. Yeah. You gotta be up in the zone. You gotta be down, especially the first fastball he's seen. You can't make that 92 dead center. Schwerber almost looks like, really dude? I wanted a challenge.


Sometimes a light I carry inside feels light. Sometimes I can't see past the shadow of my shame. If you enjoy watching Backroads Online, please consider making a tax-deductible donation at lptv.org. Backroads is made possible by the Minnesota Arts and Cultural Heritage Fund, with money by the vote of the people November 4th, 2008.


All right back here live in Austin for Linux Foundation open source summit. We've got our J frog folks We're back-to-back here. We're gonna be doing a few interviews. I want to introduce you. He's a new frog You tell he's not that green yet. Yeah His name is Peter McKee and and Peter welcome. Thank you. I'm Kind of honored to be breaking you in here on on the texture on devops.com first time Yeah, your first time. I think we've only lost Well, no, we haven't But Peter why don't you introduce yourself to our audience? Yeah, my name is Peter McKee I run the developer advocacy team at J frog hard word to say I should practice it more But yeah, I came from Docker was there for about five years ran the community and DevRel teams there Super excited to come over J frog great people great products. Absolutely It's funny. We were just talking that our last guest was Jeff from IBM And we did like a quick history of Kubernetes and talked about Docker and swarm and all of that stuff No, boy, you know, there was some history there But anyway, you know a lot of people look at this and say yeah dev dev advocacy a Lot of us think that's the new sales people. Yeah, because we don't do sales people We do dev rel and dev advocacy and and your job is to just make sure the software is delivering delight. Yeah Yeah, yeah, I tell people I tell my advocates. I want people to know like and love you Right and else or no, no like and love too. Well, yeah, okay. Okay But yeah, and I think it's one of the best jobs in the world, right you still get to Talk and speak and connect with the community, but you can still also write code contribute to open source Yeah, I think I think nowadays software is eating the world, right and software engineers are the new king makers No, not in my terms. Absolutely Yeah, and is it liquid it better be it should be it will be if we have our way You're gonna be here, man. You got to be saying it will be that's a wheel. Yeah, um, I was just kidding with you But you know when we talk about Jay frog it it's look I will tell you is I started DevOps.com, right? There are a lot of software companies that I'm fond of right who I think do a good job Jay frogs one of in my mind dollar-for-dollar does the best job of balancing being a for-profit company While nourishing a thriving community and if you do it, right you can do both well and be successful at it And I think yeah show me and Fred and yove and the whole team there have are a shining example of it I'm interested to know you coming from Docker Like what do you know about the Jay frog software? What attracted you to this position? You know, it's not that they pay. Yeah, a lot more than everyone else does they do now. I'm just kidding Well, well number one the team is the phenomenal and then we had a factory at Dell I was at Dell many years ago. I think in 0809. We had a factory which was completely a new concept Yeah, and to be honest, right? It took a little bit. Why are we doing it? What do we and until you get it then you get it, right? And I think it was that a combination of the products the people and then their open-source initiative, right of Persia and the in a different cone and and different projects. We're doing like you said I think they have a great pulse on the community. They basically started the DevOps movement, right? It's kind of like Docker started containers movement change how we run our run times and DevOps has changed the way we deliver software Yeah, and I really it's a great stable company that I want to be part of take it to the to the next level, right? Yeah, and so it's interesting. I think of Jay frogs mission Especially as it relates to open source There's there's like two sides of that open source coin one is Jay frog does a really or tries to and I think does do a really good job of Securing open-source software, right? So a lot of the stuff in Artifactory is open Yeah, right and and using x-ray and other tools, you know, they're securing these open-source software At the same time Jay frog also and and I think more recently than in past has been a Progenitor a producer of open-source software, right with some of the projects you just mentioned And we're gonna dive more into them with our next guest even but It's interesting. You don't see a lot of companies that play both sides of that street. Yeah I don't think most companies understand that right they I think they feel if they give away their technology They're they're they're gonna lose right there lose their advantage. Yeah, I think Jay frog going back to the dev advocates too Right, it's give back to the community Make people happy and then when they have a choice, they're gonna come to you right They start to see you as leaders in the industry thought leaders. I hate that term, but it's true, right? And I think Jay frog does a fantastic job about that especially around dev ops and other things is hey We want to help you wherever you're at and if you want to come to us and pay us we'd love that also But we know eventually you'll find the right product and hopefully it's ours, right? But we want you to be successful first Got it. Yeah, I think that's given and it's that open-source mentality to give back to the community, right? Excellent, so, you know, I forgot to hit the star button here, but I'm gonna assume about where we are Let me ask you what maybe seemed like an obvious question, but not what are you doing here at the open source summit? I'm just here to support the community and yeah support our open-source projects. I'm looking over at Steve But yeah, I live here. I'm here in Austin local, so I can't can't miss the conference Oh, yeah, well, yeah, you're here and come down and I call it You know shaking hands and kissing babies and building relationships with folks. Are you? Up on what's going on with this offer a supply chain security and I am but I'm not a security professional So I got to be careful, but I am a developer right and it's interesting You know back in the day We were just talking last night So I worked on Dell comm we were on HTTP Right, I've written software where you log in you're passing the the password and the username in the URL unencrypted, right? That's and I did yeah, yeah It's in so I think developers we caused a lot of this for you know trust first kind of approach And now we're all now we're all need to go back and fix it. So I love the shift left because I Think we caused a lot of it the developers and we need to be an integral part of fixing it Right. Yeah, but you know something I've so so I was never a developer I come from security I'll make a confession.    Yeah It's just a question of what your priorities are and what the state of the art is yeah, you know You talk about passing stuff in in the URL, you know change That was the state of the art then yeah people weren't thinking about Wow, man in the middle of tax. How do I jump that you know know all of these things and in IE not to cut Sorry, no, no, just think about the Internet Explorer, right when you used to download the demise the Internet Explorer They should have blown that thing out. But yeah, and yeah, well down something just automatically execute it because it's good for the end user That was great for my parents, you know, 30 years ago when they weren't computer people Now it's horrible right and we again set ourselves up for it. But yeah, I agree. I think the honestly I didn't give to pennies about security when I was you know 15 years ago frontline developer I was worried about hitting my features and my deadlines and then then the security then you folks will walk in We're going to production the day of the launch, you know, go. No, you're not wait a minute We didn't do all the security stuff compliance issues here. Yeah, and you want to go to jail. Yeah Yeah, it was one of those guys and it was an adversarial type of very much roles, right? And yeah, now I think that's starting to blend and we do software differently to your point. We have well I think that's been the yeah, so that's you know When we look at what's going on at this show and it's a little quiet now because it's later in the day But look every person we're talking to is talking about software supply chain security in the OSSF and and all of these things In my mind none of that's possible without what DevOps is done to change the way Yeah, we built software we went from people like you just sitting on coding Like building what we call let's get called bespoke software right custom written software for a given Project to a factory to an assembly line to a pipeline Right where we we just add in third-party parts like we're building a car Yeah, right Deming and and and all of that, you know, we night and lean manufacturing if you didn't have all of that You wouldn't have an open SSF you wouldn't have You didn't have a software supply chain. So what do you got worry about so white chain security? Yeah, no, it was me. It was me launching into production and then fixing it well into production I was selling security back then and you know We had a vulnerability management tool that I was trying to convince people That you should scan your infrastructure once a year once a year And it was a hard fire. It was a hard. It was a hard sell. Yeah dad You know because they just thought it was a bad news generator. They didn't want to know about it.  Yeah, and I I think it's a good thing Yeah, it accelerated it made things easier and then it just then it exposed. Oh, wait a minute We got to get better at plugging holes attacking security. But yeah On some sense software engineering's come easier, but then on the other sense, it's become way way more complex Well, I think this was straws on the developers back today. Yeah, yeah, right this morning production code code the cloud, right? Yeah, no, it's it's a big name We haven't even look you're gonna start seeing edge stuff come in and then all this other stuff Let me ask you another question. How long you with JFrog? What about eight weeks now? Okay? What is if I'm talking to you six months from now, what does success look like for beyond saying? Oh the company sold more software or something that's obvious But yeah, what is success for you personally look for for me personally right now is to have our free product Everybody using Artifactory go try it out get a free trial use it understand what why you should use it and Bring that into your DevOps practices it right try it out and eventually you're gonna love us You're like us and you're gonna come purchase But just use the software as you do now if if I can help get more people to know like and love our products Get to use them and maybe not in pay yet The sales folks will take care of that down their own right but if we have really good technology and people are using them They're gonna stick around and pay right and so I think my team's job is to show people that right So if we can do that and I can help raise the weekly users of our free tier Success from that's what it's like one of that. Yeah, it's one of the key things After eight weeks biggest difference between the culture of JFrog and and I'm not asking a bad man But differences between JFrog and darker be friendly to everyone. Yeah, I mean I mean Dockers a phenomenal company right phenomenal people. I didn't stay there as long as I did I mean the technology was incredible, but yeah, the folks were wonderful. I mean smart Empathetic people and I found the same at JFrog Probably even more so J-Frog folks are awesome.  Then you will be productive, right? It's it's a subtle difference, but I think it's key, right? Yeah, everybody I've met at the company is fantastic. Cool, man Yeah, all right. Peter was a pleasure meeting you. That's the block with JFrog man. You're with some good people Yeah, thank you appreciate it. We're gonna come to have you come back in six months and tell you So you did see if I hit my KPS You know, whatever makes whatever makes you happy or show me one or the other Um, all right. Thank you so much new developer advocate here at JFrog


Hey everyone! Good morning! I didn't realize you guys were here yet. Hi Meg! The question of the week. What are your genealogy goals for 2024? All of the profiles of the week are actresses who have played Mrs. Claus in various incarnations. We have a tip this week. What's happening around WikiTree in December 2023? Let us know in the comments below.


The following is a presentation of TFNN. The TFNN Bull Bear Trading Hour. Every trading day, live at 10 a.m. Eastern. Call now, toll free at<PHONE_NUMBER> or internationally at<PHONE_NUMBER>. The TFNN Bull Bear Trading Hour. Now, Tom Ant, Tommy O'Brien. Welcome folks, appreciate you growin' and prowlin' with us. We have the Dow Industries down 21. You get the Nasdaq up 19. S&Ps are up three and a half. Gold contract up a buck, 90 trading at 1310 an ounce. You get Silver Flat, $15.19 an ounce. Light Sweet Crude, $64.46. We're gonna have those numbers this morning. Half hour from now, we'll see what happens, man. Higher prices. It doesn't want to back off, man. No way. This is just... Higher oil for sure. Doesn't want to back off. Notes and bonds. Now, notes and bonds caught a bid once again. Bottom line is that you get the 10-year up by seven ticks, $123.28, 30-year up a half a point at $148.14. And that just came out of the gate. Bottom line is that they were trading flat this morning down four or five ticks. King Dollar. King Dollar up 134 ticks, trading 96, 745. That battle's still on. In both sides, the bulls in the bears are actually weak. Dolls at the high. But guess what? You don't have buyers nor sellers. Euro. Euro's at 112.44. The year is trading at 111. And the British pound is at 130.62. And it looks like the British pound, well, the U.K. in general, are gonna kick the can down the road. Why not? Politicians love kicking the can. Hey, listen, man. When I look back and see the Greece crisis and the Italy crisis, man, everyone forgets about those things. That was like four or five years ago. I guess it's just... They all get money now. They're not broken anymore. I guess so. I'll let you, man. It's totally wild. Let's go over to our man, Mr. Kevin Hinks at TD Ameritrade Think of Swim, as we do each and every Tuesday, Wednesday, and Thursday. And don't forget, folks, right here, every trading day, 11 to 12 Eastern Standard Time, you want to understand the option market, option strategies, the future market, great program. If you haven't test-driven yet, the Think of Swim platform, really easy to do, just come over to our website at TFNN, hit the Think of Swim banner, bring it up. They'll allow you to trade with paper money. It's a great platform.  It's real simple, folks.  You be the market. Kevin Hinks, what's going on? Good morning, Tom. Good morning, Tommy. Great to be out with you guys. How we doing? We're doing good. We're coming up to... I know you're not going to sleep for another 48 hours. We're coming up to the most wonderful time of the year. Congress has all... Finally, it's here. Yeah. Congress has all the banks right now, Kevin. They're asking them all the hard questions. Tommy and I were just talking. We were just listening on the way in. I'll turn the music on afterwards. I don't need a 15-minute spiel about how great your bank is. You know, I mean, that's what they're getting. They get their opening statement, though they should, but it was like, man... I was watching it as well. I mean, it's must be TV right now, only because I'm really waiting for the question-and-answer period. You kind of knew what the prepared statements were going to be, right? They were all going to say how good they are. And I appreciate that. And probably since the 2008 crisis, they are in pretty good shape and much better shape. And of course, they're coming this Friday, folks. That's when the earnings are going to be coming outside. Right. We'll see how these interest rates and the trading and volatility, in particular, basically affect their bottom line. So... Pretty interesting things going on this morning, Tom. I mean, I thought the CPI data, obviously the less food and energy was, you know, a 0.1 that's lighter than expected. But the headline number, the, you know, the full number was 0.4. It's warm. And I broke it down here. Gas? Yeah. Now, less food and energy, though. Right? Use cars and trucks down. Kevin, it just doesn't look like it's really intriguing, man.  I mean, this thing, from December 24th, as the market went straight up... Crude, yeah. Crude, and gasoline did, too. I mean, and it just doesn't look like it wants to back off at this point. It's like, okay, man, we're going to be spending some money here. I don't know about you guys in Florida, but in Chicago, you're starting to see a difference in the price of a tank of gas. It's not... It's, you know, it's significantly higher, but for sure. Yeah. Yeah, no, it is here, too. And you know what happens, and this is really... And this is the point, folks, that we're all making here, is that I look at my gas tank now more. Just coming in, I can't believe I'm almost empty again. I mean, just that thought process. I says, oh, man, okay. That means more. I'm going to go spend another $50 or $70. Yeah. Right? Yeah, I mean, to fill your tank, you know, six months ago, it was in the $30. Now it's in the $50. Yeah. That's not insignificant. No, no, it's not. It's not. There's no doubt about it. And, you know, I don't know if you saw this Lyft yet. I mean, Lyft is getting smoked this morning, and I'm not quite sure whether it's just because Uber's saying, okay, they're going to file tomorrow. Uber's going to file... Well, Uber... Let's put it this way, guys. Uber's lowering their price probably because of what happened with Lyft. Oh, is that what they're doing? I see. Okay. That news release is probably hitting Lyft a little bit more. Yeah. I see. Okay. So Uber's sell $10 billion in stock at a valuation of $90. Okay. Right. I mean, they were talking about as high as $120 billion on that valuation. Now it's $90. That's not insignificant either. Oh, I agree. I hadn't seen it. $90 billion. I had heard $120. Right. Exactly. Yeah. So that's a little haircut. Oh, my God. That's... Yeah. And remember something, guys. These firms, they don't make money. Yeah. Right? And they don't have a clear path to make money anytime soon other than the obvious, which is they need to raise prices. Right. On this.  The question is how do these guys get the profitability without just raising prices significantly? Yeah. And it's tough, too, when you have a lift and you have an Uber. So it's not just like an Amazon where you're just leading the way in losses, but you really don't have a competitor. So no one's super worried about you just turning on... That's right. I mean, these guys, man, who's going to, you know, you're going to start taking profits and let the other competitor just start plowing to AI, self-driving, all that. Right. That's when you start... A duopoly is not a crowded space. Right? With only two real ride-sharing firms. So this is something Uber should do. Oh, definitely. And just the opposite. Yeah. It's not a clear detail here. Right. Lift is only in the U.S. Uber is... No, no doubt.  I'm sure McDonald's is cheering on Uber. I mean, because, you know, at McDonald's stock, that took off like a rocket chip once they really started delivering with Uber. I mean, it's just amazing, right? Yeah. Uber Eats is still a big... That new thing that they're going to. So there's a lot of moving pieces here, guys. I was going through my Uber Eats yesterday, Kevin, and I was showing them how many times I've ordered from specific restaurants, even ordered an ice cream, and I said, man, why is it so... The numbers are high. I am an avid customer. They got a good product for sure. Folks, right here. 45 minutes to now. Kevin, you have a great one. Safe one. We look forward to the program. Thank you, guys. Have a great day. Thanks, Kevin. You too. The Taz Profile Scanner is the most revolutionary piece of trading software that you will ever try. 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Check out the new tfnn.com now and experience all the upgrades. tfnn.com Educating investors. Call now. Toll free at 1-877-927-6648. Internationally at<PHONE_NUMBER>. That is now 39. That is like it's up 17. S&Ps are up too. And Mike, it's a little tough time holding any type of price out here. You get the bulls and bears fighting inside the infuse as well as these futures. You can see and put this a little bit closer. There's a lot of things jumping around today, man. I saw Tesla getting a pop. We had Snapchat jumping around. We can keep going, but there's a lot of... And then we get the Fed meet and Fed minutes at 2 o'clock this afternoon from the March 20th. Yeah, the ECB this morning with Draga having a press conference. It still might even be going on. And that took the euro. So watch this. When he was talking, you'll see a little down there.  This was a quick down draft. Look at that thing. Where is it on the chart? Show me. Seriously, folks. We went from 1-1287 and 20 minutes later at 1-1233. Yeah. It doesn't seem like a lot, but it actually... No, definitely. Half a penny's a lot. Yeah, half a penny, right. Then... So let's go just inside the Dow. Sure. See who's moving things here. Boeing, huh? Yeah. So Boeing's putting 31 negative points. Home Depot 15, 3M6. Bring it up. You get Chevron. Six positive points. Visa 5, Goldman 5. Boeing's going to be approaching that 361 low, maybe? Yeah, it is. It is. This is the danger point for them. This is the danger point. Yeah, 361. 361. We hit 362.92. Okay. What you want to do out here today, would you be watching, folks, this is big volume already, because we're going into 10.1 million.  And that was day one, when everything got grounded, yeah. Right. It'll do more than 10 million today. So the real question's going to be, does it hold at this 361.57? And I wonder if you're getting some of that Delta had their earnings, like that could come into... I heard it. I know. And the Delta didn't hold price. The Delta didn't hold price. Oh, look at that, though. It opened at 59. Yeah. Right. Open at 58.97, which is the high, and just sold right off. Man, you know, well, what's going to happen there, too, is that, you know, when you take a look at it, I've got to get this new somebody... GLCO. I know. This is kind of cool. It is. They assemble it nice and organized. Because when you look at it this way, you have to get into... Let's guess. I think, now, where's the diesel? Interesting. Heating oil. That's going to be the diesel. Okay. So, as we're talking energy, and you're talking alloys, that diesel price is a monster. Yeah. You know. Definitely. So, when you're looking at the charts, folks, well, when you look at my Bloomberg, the heating oil and diesel is the same thing. That's how this is shaken up. Okay. But that's what allons use right there. So, you can see, if we brought that chart up, too, you're going to see that. It goes up pretty dramatically. So, just to dig into the actual numbers. So, they had earnings per share, 96 cents. Compared to 90 was the estimate. Generated revenue, 10.47 billion. Quite a number, man. 10.42 was the analyst's estimate. Companies' profits jumping 31% to 730 million. So, that explains why it was so much higher coming into the open, man. But what happened on the sell-off, right? So, investors were expecting a strong quarter from Delta, especially after it raised its earnings and revenue guidance just last week. Okay. Exciting, healthy demand and high record performance. Can you pull up that chart again of Delta? Yep. I just wanted to see. Yeah, so it already had its run. You know, I believe that was when they came out. So, it was trading at 52 before they guided up and they're trading at 57, but a little bit of a sell-off. So, let's go to the oil market. Speaking of oil numbers out here, 10.30. That's right. So, it's Wednesday, 10.22. We get those numbers in about eight minutes. There's our crude oil chart. We're trading at 64.33. To jump around here to see what kind of action we have, we'll start it off with the 11 a.m.s. So, the 11 a.m.s have 64.25 as a price point where you can get an exposure upward, downward. Not bad, right? Yep. You're only eight pennies away. The bullish spread would be the one that has some intrinsic value because you're eight pennies above. You're looking at about 20 bucks on the bullish side. Your bearish spread is going to be the same thing minus the intrinsic value, right? So, about $11.12, $11.31. So, $31.31 away from 64.25. And those are your 11 a.m.s. So, you're only going to have about half an hour after we get that news. Jump in to see where the noons line up. Okay, exact same price. Oh, no, wait. I had 64.25, right? 63. All right. So, 64.50. Yeah, different level. I thought it was 65.25. 64.25 was what we're using. Now, this is a great example with, okay, we just did the 11 a.m. The 11 a.m. has exposure from 64.25. You'd have a little bit of a bullish head start. What if you said, you know what? We're at, like, the 65 level. I'd rather have, like, a little bit of a bearish head start. Maybe it won't get above this 65 level. Well, there you go. Now, you have 64.50, where instead of having, on the other side, Now, you're positive, you get the 18 negative. Exactly. So, this is going to be your bullish spread, which is completely out of the money. Now, the cheap one, so about 12 bucks. And on the bearish spread, that one's going to be the intrinsic value. $40 instead of 31. But again, this one... And that's what it's in 50. Right. Yes, yeah. So, 40 cents away from 64.50 becomes your break even. And let's see how the dailies... Okay, well, that's nice. And the 230s, these line up the exact same way. 64.50. That would be the bullish spread. And I always like to see, so you can see the market. Not that big of a difference, right? Right. Number one, this one's still noon. This one's still 230. And you also have exposure to 67.50. And you're only paying... Look at that. Two ticks, three ticks, right? Yeah. Difference. Not bad for that extra hour. So, there's your bullish one. Going to be about 15. Close this out. Your bearish one. Going to be about 30. So, 45. So, went 30 bucks basically at 11, right? 40 at noon and 45 at 230. Take a look at this. So... It seems like in recent weeks, as you pull it up, we've gotten huge misses where you could have seen the price plummet, right? No. We had a build of 7 million barrels, maybe last week. I don't even think the estimate was that much of an increase, if not a decline. It wasn't. It didn't move. And we still go higher. Yeah. So, like out here this morning, that's the first down one. Interesting, man. Okay, so that's down to... Yeah. Well, guess what? You know... What are you doing? I think it's going to go south, man. South, okay. You know what's interesting here? Yeah. And this is wicked, folks, because when you take a look at this, you know, it's pushed higher with volumes. You can see this volume right behind it. You know? That's the good volume here, those last few days, right? Yes. Now, that being said, now watch this when I break this down intraday, and you're going to see that your two cells, you know, are really down. You know? That's what I'm looking at. Sure. You know, the sell down yesterday at 9.40, you have another one with volume. There's this little one right here. You know? So it's like, okay. Yeah. That looks to me like that's where I would like to go first. So that's going to be intriguing, too, because what we do have here is that the oil market has been going right along with the S&P. Okay. I mean, you know, we look at that, they're both the 7.24 blows. Oh, for sure. Quite a turnaround, yeah, from Christmas Eve blows. They're both up at highs right now. Yep. You know? They're moving together. We're complaining about the price of gasoline. Yeah. They're going to get up. If you just wanted to go bearish, right? I mean, there's still great trades, man. We always look at both sides. But here's one, you get the market trading at 64.37. Yeah. You're selling at 15 pennies below the market, all right? Yeah. That's the sacrifice you make. But your losses are kept at 64.50. And you're putting up 20 bucks and you have exposure all the way down to 61.50. That's pretty good. Not bad with those numbers coming and that's until 230. Yeah. All right. Yeah. So you have an idea folks. Tommy and I are coming right back. Our phone number is<PHONE_NUMBER>. We have the Dow Industrial Trading down 12, down 33 rather. NASDAQ is up 19. S&P's are up 2. Come right back. Hi, folks. Tom O'Brien here. If you'd like to get my daily newsletter and market insights, then now is a great time to sign up for a 30-day free trial. 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Seems like every week, there's been more of a bill than they think that should cause prices to pull back, more supply, and basically a non-reaction in terms of sitting at 60% and in terms of sitting at 64.31. We were sitting at 64.31, right, as we were coming into this number. Right. See what happens. They're going to come up with a lot of numbers. Gas inventories falling 7.71. So they were talking about this as well. I'm going to scroll down a bit, right, because I was mentioning that and part of the... They give you kind of a what to watch for here. Crude unit outages at refineries. Now, that's the head of the number, right? Just talking about our still trending high. Last week, we saw 1.5 million barrels a day offline talking about refineries. That's a bullish signal for gasoline. Right. And that number kind of reiterating that news, right? Yes. You have a huge inventory fall of 7.71 for that gas market. Crude oil inventory is rising 7.03. Yeah. We'll put that back up, and let's just check back to the price one more time. Oh, we're going higher, baby. We're going higher. Look at that. It's got to be tough if you're short there. That's why it's nice to see some of those trades, right? You lost a cap to 64.50. Oh, it's huge, man. Not bad, yeah. Because this market is crazy. You can be trading an inventory number. The estimate on Bloomberg's 3 million barrels. We'll pull up the median analyst estimate as it pops up there, and nonetheless, 7 million barrel build. Right. And the market's like, we're trading higher, man. Right. And that's one of the targets saying there. You know what? We use gasoline. We don't use crude. Gasoline uses crude, to be fair, but that's where that comes in. Oh, yeah. But it's still a crack, do you know what I mean? Yeah. There's a lot inside that barrel than gasoline. Oh, for sure. The plastic market is a lot of different markets. That's the refinery. Hey, the refineries are offline, man. No gas is getting made from that crude. Yeah. Let's go take a look at the gold market.  Now, we need more volume. Yesterday, you know, we had 194,000 contracts. Oh, it's going to be good today, 135. Okay, so we got a lot more out here today. I think we did 194 yesterday. 200. We got to 200. So the day before was 208. Yes, there was 200. 135 is good right now. 135 will get us into the maybe 210 area. Okay. And real question's going to be, how long can it stay over this 1309? Because this is going to be a good number. And what happens, if you know, if you're watching Tiger TV folks, you're seeing we're at the top of the range right now, right? Yes. So when you get to a top range, or a bottom range, it's like, okay, what are you going to do? Are you going to make it a break? Sure. Who's going to take control of him, man? You know? Are the bears going to sell right into it again? Are the bulls going to basically turn around and say, okay, give me 200 contracts. Hit that button and say, yeah, we go top side. Let's go over to the dollar. Because the dollar index just does not want to give it up. Look at this. It's just hanging at highs. Anything over that February high of 96, 685 is in the higher range. Well, that sell-off on the euro definitely popping the dollar. It did. It took it immediately. 60% of the dollar index, I believe? Yes, it's 60%. So quite a sell-off. Yeah. Of course, that's going to pop that dollar off the lows. There you go. And then you got... Almost the same move. Almost half a penny from 96, 4 to 96, 8. Yeah. Except in the 96, 7 now. And then the pound. Whoops. This is just amazing how the... they just can't get it together, you know? It's like... And the thing that's amazing, it doesn't look like they're going to get it together. I mean, if they give them a year, the next time we talk about it will be seven or eight months from now. Oh, yeah. And the flip side of that, though, which is why it was so almost hysterical that they were extending it by two weeks, is that they couldn't get it done three years. Why? It was like three days going to do it. I know. They have a lot of issues still to go through. I know. So that's why some of those people are saying, don't want it two weeks a month. There's not the deal here. We need like a year to really go through all these issues if you want us to be on board with what you're doing. And unfortunately, she has very little leverage now on her side. So you've got to make those concessions. Zero leverage.  No doubt. So let's see, inside the heaviest trading equities for this time of the day, anyway, now you get Lyft is sticking out. That's about the only one. Lyft is down three and a half dollars. You got Olivaistros. That's a new IPO. That's up a box 10. Yeah, not bad. And the limit. Trading 22 bucks. We're just looking at some of this. Some of those numbers over here. So you first earnings since release since their IPO. So they came out 37 cents on revenue of 1.44 billion and they're up 25% year to date the stock. So people, they like their genes, right? You were in genes? I got some genes. I am. Exactly. And when they came out, I think they just went public last week. Okay. And I think that when they came out, what their mantra was is that, yeah, they're the gene people, but they evidently have been making a huge amount of money just on shirts also. Okay. And there it was. So March 21st. So they've been out a few weeks. That was their IPO. Yeah. And they began trading at $22.22 a share after having priced at $17. So quite a little game they're playing, saying it's up 25% on the year, year to date. But if I'm correct, I believe that's off of their IPO price. Yeah. That's off the 17. Yeah. Which is remarkable to say that when in reality they're trading basically at their opening price. Right. Yeah. But first earnings they delivered. So that's probably quite a hump to get over in that company in terms of coming out with your first earnings. Oh, yeah. Listen, you know, there's plenty of these companies that they push, push, push to get IPO'd out there. All of a sudden, they spent all the money the prior year to push, push, push. All of a sudden the sales are like, oh, the losses are more because we spent more on marketing to get to push this baby out the door. They build up to that moment and then they can't deliver on basically the expectations they set. So let's go take a look at that bond market because let's see what put fire underneath this thing. This was when I was on the way in, this was a flat market. There it is. Okay, so what time? Probably some of that same time we saw the currency action, I guess. 8.30, so CPI data. That's, there you go. That's when the run begun. Now, what's going to happen out here today? This is going to have volume. This is good, man. If you want less expensive interest rates, this is going to have volume today. We've already done 791,000 contracts. Yesterday we only did 1.2. This will do, this is going to do a couple hundred thousand contracts today. So these bonds are on the way again. That's the third, that's the 10. U.S. 30, probably, oh, 122, that's good. I think we only did two something yesterday. So the 30, yeah, we did 223 yesterday. We're already at half of that, 122 right now. So these are moving, man. These are going to go right back to the highs. They just peaked their head over the last five days. Last five days we were testing the strength from the 22nd of March, did it with light volume. Had a little volume yesterday, but you're going to have to pick up today, which is going to be pretty well-watched. So we have on the 10-year, 2.474, so we ducked under 2.5 again. It's pretty amazing when you actually just think of, oh, I heard an analyst today on, this is a pretty cool stat, folks. So I checked this out. An analyst was on Bloomberg, and he was saying that, hey, listen, we think that the Fed's going to go down, cut twice in 2019. Okay, wow. Cut twice. Yeah, I had to adjust my head first. Yeah, exactly. I had to adjust my head when I was listening to it, too. Cut twice. Yeah. Hikes are off the board. And what it was about, folks, is that, he was saying that, well, they had historians that once that they stopped raising rates, they cut very quickly after that, and they always claimed that they're not going to. You know. They're right there, folks. Come back when I'm in. Teddy Kegstad. If you're in the CD market and looking for a secure investment, tying a first mortgage program may work for you. The security for these first mortgages are building lots in the tax opportunity zone in St. Petersburg, Florida. 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We do each and every Wednesday at 40 past the hour. You can reach Teddy every trading day, folks, at 4x-trading-unlock.com. Teddy Cakes, what's going on? Good morning, guys. Pretty interesting action of currency markets today, I would say. Yeah, you got some big movements in that year, oh man, that was a fast move, no doubt, right? Well, you know, the ECB not doing anything with rates, I think that was probably one of the biggest things. It kind of got the move. Now, if you guys look at the US dollar, Swiss, that's like above parity again and right now the market's bid, at least it was the last I checked at. Okay. So right now you have the US dollars above parity with Swiss. That's a nice reason the dollar index is high. The euro is selling off, but interestingly, if you look at the sell-off in the euro, it was much lower before and now it's coming back. Yeah, interesting. The other ones are still bid. Now, I was kind of wondering, I'm like, why is it looking like that? And then I looked at the euro, excuse me, the euro of Swiss and the euro of Swiss has been nothing but rallying for the past month. So it's pretty interesting to see how the Swiss is falling to the dollar more than the euro actually is today. Yeah, that's interesting, man. So what do you think, you know, when I was looking at that, it almost looked like the euro wanted to move higher the last few days, Teddy, right? And then I'm trying to correlate with, okay, does that have anything to do with Brexit? Non-Brexit, do you know what I mean? The euro seemed like it was going to be happy when Brexit was going out for a year, do you know what I mean? Then Draghi came up with small and said, okay, I'm not that happy, man. You know, I want to get to a lower price because that euro at that 112.16 is kind of a dangerous place for it. Absolutely, absolutely. Because it's flirting with that 11.5 area, which seems to be the bounce point for the market right now. So I agree with you. I think that a couple days ago, I was looking at the euro and I'm just like, this really seems like this slow creeping little bull may try and extend itself, and then of course over the past couple days, it fizzles. Yeah, exactly. And I think that that has more to do with some of the numbers coming out and then you had the deal, I mean Brexit's supposed to happen Friday, right?  And I actually had an interesting conversation over the weekend with someone who's from Switzerland and they're actually a trader, but they live in Dubai. So I'm like, what would be if they just did the Brexit Friday and just said, okay, Brexit's over, but we're just going to deal with these things on a day-to-day basis and just address them as they come. Wouldn't that be a seamless way of moving on and making everything happen? And he said that's what people wish would happen because that would be common sense. But the thing is the EU doesn't want to let go of the UK. That's ultimately what the thing is. Listen, man, power never likes to let go of anything. You have to take it. It is what it is, right? They're part of the organization. You want organizations as big as you can be if you're a bureaucrat, right? Sure. And the thing is the UK has always maintained the power. So their ability to leave the EU should be actually a seamless one. And it's not being one. So that actually I think is also scary for the rest of the EU countries, which also starts to weigh on the euro because not coming to a deal is not good for the EU either because it means that they're not willing to compromise. Right, right. And even inside of the couple of press releases they put out, it seems like the EU's worried that even if they give them the extension, I don't mess with that business when I give it this extension for the next year. And I'm not quite sure how they can mess with their business, but... Well, they get to vote, man. They're active players. That's what I remember of the EU for that year. Right. And look at the pound dollar right now. Today, with the dollar rally going on, it's pretty neutral. It's not doing anything. Right, right. Yeah, I know. Just laying there at 130.73. Yeah. And it's just like a flat line, just a little range trade. So it'll be interesting if the dollar Swiss stays above parity when it's higher and can continue over the next couple of days. Well, obviously the trend is pretty solid and there's a bull in place. But I think really it's kind of skittish. I think it's just a little news reaction, trying to figure out what's coming out with Brexit where nothing really is there.  They're basically stuck in range trades. Yeah, just as you were speaking, man, I just brought the Swiss franc up, you know, going back to 2000 and FOA. And this thing's been in the same place for what, 2011? Man, that's a tight range for that, isn't it? Right. Exactly. So it's just because the ranges have gotten so used where things look valid over where they're at now. But if you really, like you said, look at that, they haven't been going anywhere. Look, so at one point, that's amazing actually. So at one point, the Swiss was $1.80 to the dollar? Yep. Wow. And then 2000 happened, right? 2000.  Holy cow. Right. That's, man, the Burgers then must have been worth a fortune. No, no, it's just the opposite, right? So $1.80, is $1.80 to $1.00 But is that stronger or a weaker Swiss? That would be weaker. That's weaker, okay. So the Burgers will, so now the Burgers are more expensive. Right. Oh my God, yeah. Right. $50 for a big Mac over there, right? You know, I'm exaggerating a little, but you hear the stories. The stories are pretty amazing, right? Right. Sure. Sure. What else do you think we should be looking at in the next couple coming weeks here? Actually, I got a trade for you. It's setting up. Yeah. New Zealand dollar, US dollar trade. If you look at that chart, they stamped below a few days ago, and then over the past few sessions, the past two days, they settled slightly higher, just a little bit. And today it's flirting with just being slightly negative, slightly positive. So if they can get a slightly positive close today, and then tomorrow, if you are near those lows, if they can take out that low from three days ago with a sell-off, which is possible with some numbers that are coming out tomorrow, there could be some action in that market, actually all the currencies. So if the bears come out and take that out tomorrow, then you're probably looking at an extended bear trend for probably the next week or so, maybe even two weeks. So you can really see it take out some heavy support levels. Yeah. You can see going back there, so at 67, going back there, what, in December or January, it's 65. Yeah. This whole currency market is so intriguing, man. It's a lot of variables. There's always a trade somewhere. Yeah. Yeah. Now, the Chinese won, though. That's not tradable, right? Is that because they have such controls over it? Well, no, you can, there's FX products on that. You can trade the one. Absolutely. I was just curious. Yeah. Pretty wild. I would do it. I'd stay away from that. No, for sure. I just wanted to know more than anything. Do you know what I mean? Do you have an insight track in the Chinese government? You know what's coming next? No. That would be good, right? That would be the ultimate. Listen, folks, you can check out, Teddy, every trading day, 4x-trading-unlock.com. Teddy, you have a great week, safe week. I'm sure you were later that it's spring up there. Can I look out at Lake Michigan? Get a little bit warmer for you. Absolutely. Have a great one, man. Have a safe one. Thanks, Teddy. Thanks, Teddy. Stay right there, folks. Tell me how you come right back. We have the Dow Industries down 14. NASAC's up 38. S&P's up 5.5. We'll come right back. 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Right now, you can get a two-week free trial to the opening call, Basil's daily trading newsletter, by visiting the front page of TFNN.com. Cancel at any time during that trial and pay absolutely nothing.  So, we get a little action in this oil market. We sure do, man. These are five-minute bars we're looking at. Just making sure they show us. So, 10.40 a.m. 10 minutes to digest that news, right? Yeah. We trade from 64.40 down to 64.06. Now, sitting at 64.10. See what happens. We get a lot of time left in the day. Not even 11 a.m. yet, and it looks like that inventory has been quite a build, 7 million plus barrels. Maybe wait on that price a bit for the first time in a while. And we were looking at the 64.25 and 64.50. Correct, yeah. The 64.50s were the ones we looked at more often. They were the bearish ones, yeah. And the 11 a.m.s are the ones that had your 64.25 as your price point. Right. The noons in the 230s were going to have 64.50 as your price point. See what happens. Yeah. And, you know, as we were doing, was it, let's see, is that, yeah. So, this gets interesting. NQM. Yeah, quite a spike, right? When we were talking with Teddy, yeah. Take a look at the spike inside the NQs. We'll see what, put some juice inside. Look at that thing. Definitely. So, get us a little bit closer for us. That's the spike. So, when we were just talking with Teddy, folks, the NQs just went from 7601 to 7624. These things love to move. No, it's only a third of a percent, basically. No. In the span of no time.  Taken away from it, Baidu 2.5 down, NetEast 1.8, JD 1.8. Let's go look at AMD and see if... That was steady all the way up there, yeah, exactly. That was a quick hour. Is it over? It's over. Oh, man. That's it. That's really quick. Oh, man. TD Ameritrade and Basil. That's right. Steve, Dave, we're rocking this. Stay right there, folks. We've got some great programming coming up. Thanks, Bill. Thanks, man. We'll get them, folks.