Wow. That's fantastic. Hey, Bully Buddies, thanks for watching. Amazing, right? All right, let's get started. Hey, Bully Buddies, thanks for watching. All right. In this video, I am going to talk to you about over 30 Big Money Bolos items that my Facebook group members sold in July for Big Money. This is what the post I posted in my Facebook group and this is what they responded to. They told me where they got it, what they paid for it, and what it sold for. And I'm going to show you guys these Big Money Bolos. Definitely items that we should be searching for when we are out at thrift stores, estate sales, garage sales. If you are not in my Facebook group, I will link it down below. We are cutting very close to 70,000 members. That is absolutely crazy. This is available for anyone in the group to share a Bolo and then I put it in video format to help everyone learn. So the first Bolo, he said, I picked this up at a yard sale along with four others, four other ones for a dollar each a few weeks ago. One already sold last month, took about two weeks to sell, sold at full asking price on eBay. It is a Flash Leopard 2 Beyblade Force Hasbro open box, $79.99 on that. Picked this up at a yard sale a few months ago for $3 and it took about two months to sell at full asking price. It is a Frigidaire Whirlpool Ice Maker and it sold for $64.99. Picked this up at a yard sale a couple weeks ago. I got this in a lot with other Arbonne, I think that's how you say it, Arbonne stuff for $3 all together. This took a little over a week to sell at full asking price. So it is the Advanced Instant Lift Gel, discontinued $79.99 on that. Alright, so this is a set of large antique cast iron ornate ball and eagle claw feet. For a bathtub, how cool is that? He paid $5 for it and sold it for $75. This is an electric chicken bucket. I bought it at an estate sale auction with various kitchen items. I really only wanted a wooden tater box, tatter tater box for myself that was in the lot. No idea what that is. I paid about $2 for everything. So excited to see what these were worth. There are some that are not electric that aren't worth as much, but lucky me this one was electric. It sold for $150. It is a wherever electric chicken bucket. How fun is that?  Buyer already paid vintage military lot. He said the buyer paid. Wow, that's fantastic. I'm wondering how much he would have got if he would have parted it out. It's probably a reseller buying it, but a lot of times people just want the quick flip. Got this heavy silver painted piece of concrete, mounted on a black painted wood piece and a lot of three items for a dollar. Was an online auction, so in it for about $0.33. Did a seven day auction and sold for $99 plus shipping. How fantastic is that? Okay, quick flip on eBay. Not big money, but it was a porch pickup and free. Sold in less than three hours. I listed for $45 and took a best offer of $40. New Canon black ink cartridge. Mercari sale paid $19 on a local selling site. Person does not have good reviews as a seller and only two reviews as a buyer, so I'm hoping all ends well. KKW diamonds, Courtney yellow fragrance perfume spray. Sold for $199. She said yes, delivery today. Got rated today and got paid. Score, awesome. I'm glad she gave us an update. Number one, got a huge lot of stamps at a local thrift on half off day. Whole lot, 30 plus stamps about $1.60 a piece. Total $60 to $70. So far, gross $365, all full price except one. Had listed for $60 and took a best offer of $55. These stamps are Holly Pond Hill and House Mouse. And I do have a video on Wood Rubber Mounted Stamps to be on the lookout for. House Mouse is one of them that I talk about in that video. This is what the video looks like. Definitely go check it out. Holly Pond Hills I have not heard of, so this is new to me. She said, the Holly Pond Hills have been going to China through freight forwarders. I am sure I will sell more by the end of July. Bought these last week of June and all of them were listed from first week of July last week. Let's see. She said another 130 worth sold today. Again, all going to China. So, hmm, wonder what's going on with that? You know, sometimes I know that happens with like the vintage toddler dresses. A lot of those go through a different company in our ship to China. I am going to pop up this. She's got a, she's showing us six of them, but you can see one sold for 130, 40, 55, 50, 55 and 55. So, Holly Pond Hill. Hmm, all right. 1962 Barbies friend, Midge, found at the Goodwill Benz, took an offer of 135 plus shipping going to Canada. So, this is what she looks like. That is fantastic. At the Benz. Wow, bought this for a dollar at the Salvation Army and because of your great channel, I knew it was a Bolo. Oh, thank you so much. Sold within a couple days, listed it for $89.99, but when I got the $80 offer, I grabbed it. Thanks for all your information, so helpful. Thank you so much for the feedback. I appreciate it and thank you for sharing that you learned about this from the channel. I love it when you guys share with me how you, that you learned something from the channel. Unfortunately, I cannot see what the listing is. Oh, it's a jock strap. I did share that before. Oh my goodness, so funny. Yeah, vintage jock straps are definitely a Bolo. Found two at a small town thrift store, 50 cents each and went back and found a third and they sold very quickly. It looks like they are Boy Scouts pants. This is what it looks like. Purchased for $1 to $3 each, I collect these over several months, decided to try my hand at selling as a lot. Listed for $124.95, took a best offer of $105, even though it took a larger box than anticipated. My label cost was only a few cents more.  This one comes from Loreen's, I think it's Books and Things. I'm going to post it right here and I will also link her down below. She is a Bolo buddies member. I did post about something similar to this a long time ago. I haven't seen anybody do it recently but they collect these little vases and these are white and they're great for weddings. So people that are looking to decorate their tables at their weddings, they will buy these in a lot. So great idea. I have seen it done before from other people but definitely something to keep in mind. Kind of a pain to ship but it all adds up, right? I know a guy that does this with brass, like candlesticks and stuff like that. Got this at a parking lot yard sale for a dollar, sold for in about two weeks. Auction resulted in no interest, took a best offer of 25. It is a rare bobble head mascot, Texas Roadhouse, Andy Armadillo. Got this grateful dead vintage t-shirt from a girl cleaning out a storage building, paid two dollars. Put it on auction and buy it now of 74. It got several bids and someone paid to buy it now within 24 hours. I thought once it had bids, that the buy it now what didn't work. Hmm, if anybody can let me know, that would be great. These were free to me. They were my grandfather's snake skin boots, sold in about a week, listed high at 90 and took a best offer of 50. They are vintage ACME Western Snake Skin Cowboy Boots. My favorite Bolo for the month. I bought these at a local salvage store for a dollar 59, a bag. Buyer paid $32.99 for three bags. They sold within hours of posting. I sold 24 bags total within three to four days for $277.43. They are Cheetos, Sweetos, Cinnamon Sugar Puffs. That sounds disgusting, but somebody likes them. Paid $10 for three vintage PlayStation magazines on Facebook Marketplace, and this rare Resident Evil 2 magazine sold for 98. Anything Resident Evil is highly collectible, so be on the lookout, right there. Sold this vintage DMX magazine for 60. I paid 26 months ago on Facebook Marketplace for three huge totes filled with vintage wrap and hip hop magazines. I've sold multiple magazines for 100, and the total so far I've made is 2,000 gross sales on this deal. Be on the lookout for XXL, the Source, Blaze and Murder Dog magazines. Awesome. Okay, I was lucky enough to be on a random Friday. There was a yard sale, fill a bag. I ended up spending $30 for multiple bags of goodies. This was one item. There was damage to the silver area, paint missing. I disclosed all in the listing. I was very happy with the outcome. It is a 2010 WWE Divas Wrestling Championship replica title belt adult-sized collectible, $87. Found this at Park Avenue Thrift while visiting my son in Georgia. Paid $5 and sold for full asking price in two months. It's a William Sonoma Open Box Harvest Pumpkin Platter. And it looks like it sold for $119.99 plus shipping. This one comes from Wear Pigs Fly Farm, and is a nonprofit. Definitely go check out their eBay store and YouTube channel. All of the money that they make from those things go towards their nonprofit farm. Hello, my name is Cindy. I'm the owner of the Wear Pigs Fly Farm out in Lynn, Missouri. We are a farm animal rescue here. And to help us pay the bills, we actually sell things on eBay, things that we purchase at auctions. I purchase storage units, and then some things we have donated. My Bolo this month was very unexpected. A lot of times when I get things in, I'll throw the smalls into a box or in the baggie, set them to the side, try to list my bigger things first, get them out of the way. Anyway, I ran across this, a little poker chip. Now, I have seen on other Bolo videos where poker chips could go for pretty decent money. I looked this one up, couldn't find it on eBay. Found it on Worst Point. The last one sold for over $300. There might have per auction, and boom, it sold for over $400 to a collector. So keep your eyes open for these poker chips. This one comes from Jody over at YouTube channel Toy Attic. Definitely check her out. She knows so much about toys, but she sold these stickers for big money. She said, I went to an estate sale and did a filibag for $10. I got hundreds of stickers and other ephemera. I have about five cents into each of these. The gingerbread sold before I got the email notification that it was listed. And one sold for $125, and this one sold for $100. We go to a little Saturday night junk auction from time to time. We bought a clear tote with a lid for $2 because nobody else wanted a bunch of dishes. I've been on the lookout for totes. We found this little four and three-quarter inch plate in there, and I haven't seen one like it, and it may, and I may never again. So aluminum, he still has a $6 price tag from Sears on the back, and when doing research, a little research on it found out it was made from the wings of butterflies. Apparently this was common in the 60s, so we put it on eBay for $54.65 and turned on best offer, sold in less than a month for full price, and this is what it looks like. Got two of these vintage turkey blow molds by Union Dawn Featherstone at a garage sale. When I walked in, they stated everything was $5. I racked up. When I saw these, I was so excited because Bolo have sold both of them within two days of listing, and they sold for $124 each, it looks like. Bought for $70 on a local selling site. It was actually listed for $75, but she forgot about our meetup, so because I had to wait 30 minutes for her, she felt bad, so she gave them to me for $70. Best sale I've had probably could have gotten more, but I was glad with the sale. I had it listed for $599, $599 and took a best offer of $400. I think it was less than five days to sell. It is a Lego EV3 Mindstorms Education II Core Set. Wow, that's what it looks like. Blink 182 Stomping Rabbit Long Sleeve Shirt Picked up at the Benz, my Benz is $1.19 a pound, paid $0.50 for it, sold for full asking price to Canada, and this is what it looks like. Stead fast and true Bolo that never fails to sell quickly, bought for $2 at a yard sale, accepted an offer of $51, sold in two hours. It is in a Texas Instruments TI-84 Plus graphing calculator, tested and working. All right, you guys, that was all of part two. So if you didn't check out part one yet, definitely go check out part one. These are big money Bolo's from members of my Facebook group. If you are not in my Facebook group, definitely go down below and join and go under the featured. It's featured or announcement section of the group, and you will find a monthly post where you guys can share a Bolo to have it featured in a video like this. If you would like a shout out to your YouTube channel or your eBay store, you can join memberships at level two and you'll get that shout out. Thank you guys so much. There's going to be videos popping up here and here, a subscribe and a video down below. Definitely subscribe if you haven't already and check out one of those videos. I also have links to the members that were featured in this video down below, along with other things that I use for my business. So check out the description of the video and thanks for watching.


Hello, thank you for coming to this talk. Today I'm going to talk about OpenFL, which is a project related with federated learning. It was initially developed by Intel, and now it's part of the Linux Foundation. But before I start talking about federated learning, I would like to talk about the models. So when we are training models, we need more data to improve the performance of those models. So even if the model is large, even if it's a large model, or if it's a traditional machine learning model, we need more data to improve our accuracy. But the thing is that even if we improve this amount of data, we can have the problem that the data could be biased in our model. So we need to have a lot of data, or multiple data, and also this data, it has to be diverse. And this is the challenge. Suppose that you have a bank, or if you are working in a health care system, you probably would need to use other information from other banks, from other health care systems, and so on to improve your model. You can try to do it with your own data, but it would be even better if you can use other data. But if we would like to do that, we can have challenges, because probably, like in this case, let's suppose that we are here in Canada, and we would like to use data that it's in Europe, or it's in China. And we can face some problems, because if we are working in a centralized way, we need to download all the data to the same point. I mean, I suppose that we are in Canada, and we need to download the data from Europe to Canada, from China to Canada, and so on. And it comes with challenges, because we have just to mention one of the problems that we can have. The data could be legally protected. So if we talk about health care, for instance, you cannot move the data from one country to another country. So it's a challenge if you would like to use this data. Or if the data is sensitive, if you are working with different banks, probably you don't want to share the data to other banks, because it's your data. I mean, it took years for you to join this data. Or it's too valuable. Or we have the data silo problem that if the data is huge, let's suppose that we have terabytes in one side and the other side, and if we need to download this data, or if we need to put this data in one centralized place, it could be expensive to download this data or to move the data from one silo to another one. So fortunately, what we have is federated learning that it comes to solve most of those problems. So instead of using a centralized way to train an algorithm, we can do the training in a federated way. Instead of training in one place, you can train the model in multiple ways. But it also comes with a problem because we need to be aware of the security. If we are moving the data from one country to another country, we need to be sure that the data is safe. I mean, it's not modified. So it's not just distributing the training. It's also about trying to secure this process and try to have additional mechanisms to make it more safer. If we compare, and this is how we, if you are working with machine learning or with AI, this is the way that you probably are training your models today, right? You have the data, let's suppose in free institutions, or in free countries, or in free banks, and you have to centralize the data in one place, right? So you have, let's suppose that you are in the aggregation side, that is your data center, could be right here, and if you'd like to train models, you need to download the data, right? So the data will come to your model and you will train it in a centralized way. So you can imagine that we can have a problem moving the data from institution one, institution two, and institution three to the centralized side. Which federated learning does is instead of moving the data from the institutions, we just move the models. So we train the data in each institution in which, and the model travels to the aggregator. So it's very important because now, if data is not moving, the data is in the place where it resides or where it lives, and the only thing that is modifying or is moving from the data, from the places to the centralized server is the model. Technically, it's the weight of the model, because if you have a, let's suppose an algorithm or machine learning to detect something in computer vision or whatever, you have the same model, so they may share the weight because they are trained in the same way with the similar data. So this way you can share the data between institution one, institution three, and also from the aggregator. How you can do that? We have, well, this is the open FL, which is a framework, and that is basically, it comes to help in that process, because you can do it, you can start thinking, okay, I would like to train in a federated way, but of course you need a framework to do it, right? So open FL is one of the frameworks available, and now it's part of the Linux Foundation. It was transitioned from, it was in March, I think. As I said at the beginning, it was initially developed by Intel, five years ago, six years ago, and when Intel decided to donate the project to the Linux Foundation, it was always a community-driven project, right? But now it's part of the Linux Foundation. So since we are Intel, we are embracing the open source concept and the open source mindset. We are doing that with these kind of projects. The main difference between, or the main value that open FL can bring is we have three main pillars. The first one is the privacy. So it adds or it provides additional mechanisms to make the conversation between the aggregators and the collaborators, or when you are moving the weights from one side to another side, it adds additional mechanisms to make it safer. I mean, it's not just TLS encrypted, it's TLS plus another more things that are also added here. I don't wanna go in details because it's pretty technical, but think just keep in mind that it's providing an extra layer of security. And the other one it's pretty easy to use. Easy to use, it's scalable. If probably if we as a data scientist is if you are working with a new framework, you don't want to learn a new language to learn everything, right? So if you have an API or if you have a framework that's pretty easy to use, it may help you to start adopting those kind of algorithms, right? And the way to use it is you can download in GitHub, pip install, and we have also our containers version, so you can download the containers and everything. And talking about security is these are the main, I just wanted to mention the main two problems that we can face when we are working in a federated learning environment. The first one is an attacker could poison the weights while they are traveling from 1.8 from 0.2, they can attack the weights and they have a way to access to the data. I mean, they made poison in the weights, they ingest that in the model in the process, and they have a way to access to the data. So even if we are using the vanilla way to use the federated learning frameworks, we are vulnerable to this kind of attacks. And the other one that is pretty important is that, as I said, if the model is going from one collaborator to the aggregators, we have the same model present in all the points of my federated learning, on my federated framework. So we can have the risk to someone who could probably steal our model in a collaborator because the weights are presented in all the points of the federation. So this is another process that is very important that we need to be aware of when we are working in federated environments is that we need additional processes to try to ensure that. How it works, it's a good animation, I mean, I like it, I just wanted to show you is like to see how it works, right? So we have the data, the data, it's encrypted, and it goes from the collaborator to the aggregator. The aggregator puts together all the weights, made weighted average of the weights, and has a new version of the model. And when they have the second round, and when I like to retrain the model in a second round, they send the model again to all the other collaborators. All the processes, it's encrypted, and the important thing is that whilst processed, it's also encrypted, it's also in a secure way, right? So this is enabled thanks to a feature that Intel chips provide, that is LGX, that is the part of the Confederation computing, that it's not just about the, protecting the data while it's in transit. So it's also protecting the data while it's processed, right? So it's not in the same, it's an additional layer. So I wanted to show a demo, a really brief demo, to show how it works. Just to explain what I will be showing is that we will have an aggregator, that the aggregator is the main part of the federation. He's capturing all the weights from all the other nodes or aggregators, and it's doing the weighted average of the model to get it updated. So what we'll have is an aggregator, and we have two nodes that can be, now they are running in my PC, but the reality is that in a real environment, it could be in different countries or in two countries or three countries, right? So let me, it should work. I should make it higher, right? It's okay, yeah. Here we go, this is right here. I need to change the fonts. So let's see, we have in the left, right here we will have the aggregator. Let's see, let's see here. And right here we will have the collaborators, and that's it, oh, it's not so big, but as I said, what we will do is, I will just pick the aggregator, which is the team that is centralizing. So what, how we will work in the beginning is we need to create a plan, right? We need to create how the federation will work and how it will be doing, right? So for that, we need to go to OpenFL, provide an API that you can use, you can use it in an API if you're working with Python or, yes, with Python. You can develop your own application or you can use the API that the algorithm gives. So if we do, for instance, federate effects minus, minus help, these are all the things, I mean, it's a bit complicated, but you can see that we have the workspace commands, the plan commands, the tutorials and so on. What we have is we have some tutorials that you can download and you have all the workspace downloaded for you to use it. So in that case, we'll have, put it here, we'll be training a CNN MNIST model. It's pretty easy, I mean, it's pretty simple, but it's not the idea to go in the details of the model, but it's running on PyTorch, so it's framework agnostic. You can train your models in PyTorch or TensorFlow. And if you go, we have some pretty cool files to see here. So if you go to see the plan, you can check the plan here. We can see, for instance, that we have all the configuration that each aggregator will take. Like, for instance, what will be the batch size of the model, what will be the model resides, what will be the address of each aggregator or each collaborator. So you are centralizing, but you also need to communicate to the other aggregator. So you need the FQN, FQDN, so the model can communicate to the other aggregators. And basically, what you define here is when we are starting that, we are saying, this is the model, this is how we are training the model. These are the parameters that all the models, all the collaborators will share, and we will agree on that. And it's also what you define here is how you would like to make the, how you would like to update your weights. Because in the first round, let's suppose that you train a model in the collaborator one or collaborator two, and they will send the models to the aggregator. And the aggregator, they should decide to see, okay, I would like to update the weights in a weighted average. I would like to put more importance in this node or this other node, and so on. These are all the things that you can define when you are working on, when you are defining your federator plan. The second good option to show is, if we go to the workplace, we can see the configuration of the algorithm, right? It's, of course, not to go in the details of all this stuff, but it's as usual when you train a model. It's the same thing. The only thing is, if you are probably aware about Biotorch, when you download your model, you need to use the model class, for instance. What OpenFL does is, instead of using this class, you can use a class that is defined by OpenFL, that is probably, it's the same, but underneath, it configures, like, for instance, how you can send, how you can share your weight or when you will update your model, and so on. So all these details, you have in that thing. And once you have it there, when you are defining the plan, all these files, we need to encrypt those files and you need to send the workplace to each collaborator, right? So here we go. Now what I will do is, I will start the plan. And what it does here is, it prepares this workspace module, right? If you put in one file, the model, the plan, and all the parameters that you can send to all the other collaborators, right? So I will not move to the other collaborators, but the files are there, right? I suppose that you do it offline, and it's in the aggregator, and it's also there for the other aggregator. But it also has a very important part, as I said at the beginning, security is the main goal of this framework. So what you can do is, it comes internally with a certificate authority, so you can use the certificate authority to sign all the certificates between the collaborator and the other aggregators. So it's pretty easy. You can use workspace, certificate, and you can validate that, let me clear. Workspace, certify. And it is that, the, FX aggregator, because I would like to certify the aggregator, certify, right? So it asked me if I would like to sign the certificate and it's now done. Now let's suppose that we are in the aggregator, and what we will do it will be generating a certification, a certificate request, a CSRA. So let's suppose that we have the collaborator, we will like generate a cert request for the collaborator once, right? So it will be generating a certificate to, and we will do the same for the second one, right? Now that we have both certificate requested, we will need to go to the CA so they can sign our certificates. Now we do collaborator, or yes, collaborator, collaborator, certify minus I, right? And now you are validating your certificate. What it will do right here is if you are working in another environment, in a real environment, you will probably send certificate out of bounds to the collaborators. And this is what I have already downloaded to the other parts of the certifications. So we have everything ready, we have all the plans, the plan is downloaded in each collaborator, the plan is ready in the aggregator, the certificates are ready to all the points of the certification, of the federation. What we will do now is we could start with our federated process, right? So what we can do is I will start with the collaborator, I will be starting the process, or the server, start, this is the one, and you can see here, right over here, it says that it is waiting for tasks. So the model will not start to do anything until the aggregator says, okay, you should start training, you should, this is your first round, this is your second round. So until they don't receive this information, they just can stand by waiting for instructions, or what is to do something. I will start, I started the first collaborator, I will do the same with the second one, and it's also, do the same, it's waiting for tasks. And what I will do now is I will start the aggregator, and now the aggregator that has the plan, he will say, okay, he will talk to the collaborator one, I will say start training in the round one model, and they will do the same with the second collaborator, right, so it's starting the process, it probably will take a time. It starts a GRPC server, because of communication between all the others, all the others, between the collaborators and the aggregators, each using a GRPC server. So if you see in that part, he said, okay, he received how to train the model, how they would do with the weights, and this is another configuration that is in the details of this class that each model uses, is that they need to know how they will update the weights, so you can define that internally in each particular process. So if you see here, it's already training over there, and in the left side, and, oh, sorry, in the right side, it's sending the task to the other one to start working on that. So it probably will take time because I'm running that on my PC, but if you work that in another, I don't know, probably in a cloud-provided services or in another provided services, it's probably much faster compared with my PC. And it runs, it works round after round, and it will be updating the weights, and you will see how the accuracy is working between how it's improving between one and the other one. And this is the demo, I just wanted to finish explaining that since OpenFL is an open source project and in multiple companies, they are using the project, so we did, just to mention some of you, we did things with VMware because they contributed and optimized an compression for the pipeline when you are sending the model from one point to another point, they added the compression, they added a compression weight to send the weights between one model and the other model. And we did a great, the University of Pennsylvania, they did a great job trying to do the largest validation healthcare process for tumor detection. They had a lot of data distributed in multiple countries, and they used OpenFL to train a model to detect tumor cancer. And the other that's pretty interesting is the NASA one, it's not the problem to use the data because they have the access to all the data, but the problem is that some data, it's not in the planet, right? So it's outside, so the problem that we have here is with this data is in silos, so downloaded data from a satellite or another planet, it could be a bit difficult and it could be harder and it could be expensive if we like to download this data. So OpenFL helped in that way because it helped it to train a model to detect something within the NASA and that is private, but we help on that because they can train a model, things that they have a federated learning process and because they would like to use in the traditional way, it could be pretty expensive if they would like to use it or to download the data. So as I said, the goal to action is if you are savvy or if you like to solve problems, we are OpenFL, it's an open source project, so go to the GitHub, try to pick some issues, try to solve the issues, if you want to be involved, we have a lot of tutorials, like this thing that I showed about Open, about CNN and M&S, we have a lot of different tutorials in bytes or in terms of low NLP computer vision, a lot of them that can give you an idea on how you can build your own federated learning process and we have read our blog post, explaining how the technology works and we are launching release after release, we are adding more security features that are provided by universities that are doing research and they donate all the things to the project. Check our documentation, if you'd like to learn about OpenFL, about how you do the federation, you can go online and you can see the sites and we have virtual community meetings every month, one for Europe time and the other one for Latin America, for North American time, so we are pretty open, we are thinking on adding some hackathons, we did some internal with some communities, some kind of hackathons for federated learning, which is pretty interesting, pretty nice, so if you are interested in that, we can try to think on that, so that's it, thank you so much, I'm open to questions, if you have any questions in it out, so thank you so much for your time, really appreciate it. For each collaborator, do they all have the same copy, the same model, but they all have different data and they're training it and it's aggregated, or can you segment the model and say collaborator, A and B, you train this section of it, and C and D, you train these ways and then the aggregator things them together. Thank you, yeah, that's a very good question. We can divide, the answer could be in two parts, the first one is you have horizontal federated learning and vertical federated learning, right, so when you're working with horizontal federated learning, you have the same data, it's not the same data, because it's distributed, but really I suppose that you have to explain in a very easy way, I suppose that you have a spreadsheet and you have the features as a columns and you have the rows as a timestamps or whatever, right, so in an horizontal, you have the same features distributed in all the collaborators, so how you distribute the data, of course we depend on which data is available for each particular collaborator, but the horizontal is you have the same shape of the data for the same things distributed between all the collaborators. The other option that is something that we are working on that is the vertical federation, that is instead of having all the features distributed in all the other collaborators, you have, as you said, you have a set of features in one collaborator, a set of other features in other collaborators and you put it together in a way so they can learn about it, yes, but you can use with both of them, could be horizontal, could be vertical, and they, yes, they are training in the same environment, yes, thank you so much for the question. Thank you for the talk, I have a question, how does OpenFL compare to other federated learning frameworks like Flour, for example, and why should I start using OpenFL and contribute to it? Awesome, great, good question. We work with Flour, the main difference between OpenFL, it's not a difference, I think that they are complementary, that we add this security layer that you probably don't get it on Flour, so we work with them, I think that they are pretty complementary because we add these mechanisms, as I said, the Confidation Computing mechanisms and all these security part, this is the main difference of OpenFL compared with the other ones, and also I could say that it was initially developed for healthcare, so if you have a new case that it's working with something similar with healthcare, you can use OpenFL for that because it was initially developed for that, of course it's not the main use case, now it's working with all the others use case, and this is why we need the community and we invite the community to provide new features and so on, but yes, this is a really different, and if you see the, once we donated the project to the Linux Foundation, initially our project was github.int-slash-intel-slash-OpenFL, and they changed the name of the folder to say secured federated AI-slash-OpenFL, so this is the main difference between the other ones. Thank you. You're welcome. All right, thank you. Thank you so much for your time, and I hope to see you. Thank you.


Okay, if the arm is getting tired, keep going. Now palm lower, imagine the person is ducking and you're palming downwards. Make sure you're breathing. Now go back to center and triple speed. One, two, three, four, five, six, seven, eight, nine, 10. Like that.


And in a nutshell, brain integrating is about creating balance between your left and right brain hemispheres and balance between the three layers of your brain, the neocortex which is the thinking brain, the limbic system which is the emotional brain, and then the brain stem which regulates your life. If you want to know more information about step four of brain education which is brain integrating, I made another video before about it so I'll link that video down in the description below. So many people as we live our lives, depending on some of the genetics that we have or some of the things that we're drawn to, we can become either really left brain or really right brain or on the other hand some people can get really heady, think a lot, so really active in the neocortex layer or maybe some people have a lot of emotions that control them which means that they're mostly focused in the limbic system or people might have really damaged brain stems which compromise life functions in the body to reduce their health. So whatever state you feel you are in, it doesn't matter because there is a solution to create balance between your whole brain. So all of your brain works harmoniously together so that you're not leaning either way towards the left or way towards the right or way back or way forward. So the exercise that I'm gonna show you today is called circuit drawing exercise with affirmations. So maybe you are already familiar with affirmations but basically affirmations are really simple sentences that you say to yourself that is positive that you keep repeating until your brain really gets ingrained with that information and really believes that information. So for example, let's say that you're someone who has a lot of fear. And an affirmation to combat that is I am courageous. So for someone with a lot of fear you would say I am courageous. I am courageous many times over and over until you embody the energy of courage. Now a lot of people practice affirmations during their meditations but let's be real. Is it easy or difficult to sit still and meditate for a long time? It's very difficult, right? So today I'm gonna show you a very practical, easy, realistic way that you can practice affirmations by simply drawing these energy circuits. There are five energy circuits that we'll practice together. So as you draw these energy circuits imagine drawing them inside of your brain. And by that visualization on paper physical visualization and mental visualization it'll help integrate the energy of your left and right hemispheres and also integrate the three vertical layers of your brain. So if you're somewhere where you can take out a piece of paper and draw them with me please do so but if you're not in a place where you can take out a piece of paper you can just use your finger and draw it in the air. You can do it with your eyes open or you can draw them with your eyes closed once you've seen the image. But the important thing is whether you're drawing it on paper or drawing it in the air that you fully embody and say the affirmation that goes along with it so that information can get integrated and ingrained in your mind. I love myself. I love myself. I love myself. I love myself. I love myself. I love myself. I love myself. I respect myself. I respect myself. I respect myself. I respect myself. I respect myself. I respect myself. I respect myself. I am beautiful. I am beautiful. I am beautiful. I am beautiful. I am beautiful. I am beautiful. I am beautiful. I'm a precious being. I'm a precious being. I'm a precious being. I'm a precious being. I'm a precious being. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I am courageous. I forgive myself. I forgive myself. I forgive myself. I forgive myself. I am creative. I am creative. I am smart. I am smart. I am loved. I am loved. I am loved. I am loved. I am loved. So all the information about Stuff 4 of Brain Education that I shared with you in this video and also, the circuit drawing exercise you can find them in this book The Power Brain by Ilchi Lee. Thanks for tuning in, guys. If you really like this video, make sure you hit that like button and also subscribe to our channel to get more updates and content of how to upgrade your brain to improve your life.


What's going on guys, it's your boy DPJ here today with another destiny video and in today's video We have top five three count reactions now some of these clips may be pretty loud for you guys So you may want to turn down that volume just a little bit, but guys I hope you do enjoy the video thanks to everybody who has submitted and I'll catch you guys on that next one Peace out until next time Triple oh Oh My god video clip, baby, please Bungie Give me one of the chests I've been wanting that guy for so long. Oh my god Subscribe


I'm John Furrier with theCUBE. We are here in Palo Alto at our studio here with a special guest, Larry Augustin, who's the CEO, Chief Executive Officer of Sugar CRM, luminary in the business. He's a technical geek, formerly the owner of Slash. And a lot of early web properties that we all know us old guys know. Welcome to theCUBE studios here in Palo Alto. Great to see you. Great to see you, John. Thrilled to be here. I did not know you were just talking before you, we got on camera here about your history and media, besides being one of the best CRM companies out there, Sugar CRM. Great, great history. Yeah, you know, I was the founder and CEO of a company VA Linux, which I took public in 1999, sort of the peak of the bubble. Still have the record for the largest first day gain ever in an IPO, somewhat dubious record, but great record nonetheless. And we had acquired a set of properties, Slash.linux.com, IT manager's journal that we put together. And our goal was to build a whole media segment around open source and Linux. And it was fun to be in that business. Throughout my career, I sort of steadily moved my way up the software stack, if you will, starting out in systems there and now in applications with customer relationship management. And you have multiple computer science degrees. So we know we can talk shop and get down and dirty. But it was interesting though is that looking back and I didn't know that history kind of connects the dots for me, is that those was, that was early day community. I mean, back then that was right at the beat, right at the thrust of the beach head being developed for open source. Yes. You saw a great Earl, I called Gen one. I'm calling it Gen one because that's what I'm saying. But it was probably before that, but that was really when the notion of using free software became really happening. Yes, yes. And that was the early formation of communities. We were probably one of the first companies to have a, what you would call a community marketing function, which has become far more common than in fact, I look at my original community marketing team. Most of them are now running some function of marketing related to community at a lot of existing companies today, right? And sort of building that concept out. And kind of at the early days of open source, and now you look at any company today in the space and they all build on open source. I mean, sugar, a big part of what we do is built on open source. An important part of what we do is community, reaching out to all those developers that build around us. And the company really got its start as a CRM that we reached out to the community and built on open source principles. And let's go back to the, let's connect the dots there. I want to get into the sugar dynamic because at that time, the community wanted an alternative. Yes. Talk about what happened there because you're seeing the notion of communities we just talked about from the early days to being state of the art part of now our marketing functions, our customer service functions, data acquisition functions for product development. Yes. Data and networks driving everything. I think one of the key elements here is if you look at the way people buy, it's changed. We've all bought things. If you buy things, I buy things, everyone out there listening, we're all consumers. We all buy things. But the way we buy has changed over the past two decades. If you go back 10 years, 20 years, the information we got as consumers was all what was given to us by companies. Or it was what companies controlled through reviews or product placement. And our sources of information were limited. And part of that was because of the ability to communicate. The ability of a buyer, a consumer, to find another person like themselves and understand that buying dynamic was limited. So along comes the internet. And one of the great things about the internet is where you can always find another person like yourself. It's easy to complain too about things too. Yes, it's easy to complain. But one of the great things is you can always find other people like yourselves. You can come together and whatever your interest is, now on the internet, the odds are there's somebody in the world who's making their mission to tell everyone else in the world about that space and they're not beholden to a company. They're not beholden to any kind of special interest there. And they do it just because they value it and it's their passion. And what this means is the way people buy has changed. So it's become the now the number one influencer of a buying decision is other people like yourself in particular through the internet. So customer experience has become more important. Honesty and integrity and transparency. In that companies can no longer project a brand image and do that through marketing that is inconsistent with the real behavior with customers because it becomes apparent. And the internet has facilitated that. So it's more important than ever that companies are looking at creating that authentic image. And that is driving a lot of the interest in the market and space today around solutions like ours that help companies create and manage that experience with customers. I want to get into the sugar product in a second but I want to get your thoughts because this is a great thread and thanks for sharing. It's great to have you here. There's all this expertise and historical view. So you look at the old expression what is old is new again? Yes. You know, we talk about communities. You know, we just talking on my morning show this morning on the Silicon Valley Friday show about AI and you know, my guest, Jim Long, friend, Cal guy, systems guy. We're talking about neural networks are now hot but neural networks have been around for a while. So you're seeing things like neural networks. We're talking about communities now morphing at a whole new level have been around but now the notion of scale. You talk about the internet. You bring in a notion of scale. I mean, we can always say what was on IRC 15, 20 years ago IRC chat is basically slack now at scale. Yes. So you now have older concepts at a scale point. Yes. What's your thoughts on that? Certainly neural networks points to AI. It's fascinating.  I've been through this for, you know, enough decades now. We will look back and we say, yeah, you know, 20 years ago I heard that when we were talking about just the other day was predictive analytics.  You know, well, those things have been around and you look at the many, many of the ways we build technologies. Technology goes through waves. These things go through cycles. What was old comes back around, you know, what was new things created and I think it's important to be in the right place and right time around those waves. You know, you take cloud computing today or you take the way we build technologies. If you go back to the days of client server, I mean, if you're an old Unix person, you remember those days when the exciting thing was removing the client server. So I had a desktop client and a server out in the cloud, right, and of course the internet has let's just takes that server and move it out to a vendor cloud or onto Amazon or IBM or any one of multiple clouds so the company doesn't have to manage it. A great help for business in terms of spinning something up. But what's interesting in the early days of the web, when we built web applications, it was this HTML webpage sort of experience and application. All of those today have moved to what is effectively a client that happens to be written in JavaScript instead of C or whatever the client language was, right? Happens to run in a web browser which is internet explorer or Chrome or Netscape is your operating system, right? And they actually talk to that server side in the same way those old client server ask it. They're looking mobile out there too, a whole nother bulking. Yeah, so getting a little, maybe a little bit technical from our backgrounds here, but the world of client server is effectively what is happening with modern web applications. And it's interesting to see those waves and how they change and sometimes having had that experience, you can look back and say, okay, I get what's happening with this. It's new technologies, it's rebranded a bit, but there's a lot of the similar concepts that come and go. Talk about the sugar CRM business for a minute because that's an interesting position now. You guys have come out from an open source kind of philosophy as an alternative and also that just goes through also the big giant as these Oracle and others. But now there's a lot of shifts happening in what CRM means. Yes. So because you have a change in the landscape. Yes. And certainly cloud is going to impact that on prem data centers moving to the cloud and you get mobile, multiple channels. How is the business changing? I mean, give us the update, spend a minute to update. Yeah, yeah, well I think the real opportunity around CRM is historically CRM, and again, those of us who've been around may remember when CRM was hot and then it went cold. And it's hot again, right? And again, going in waves. It was hot originally as, look, there needs to be information around the customer. You need something we put at the center around the customer. And it originally emerged as what I'll call a system of record. And it's simplest level of customer database and it's more complicated, a whole set of information that brought a view of the customer together. And that was very useful. And many companies, the prime use of that was something we call Salesforce Automation which is help a company manage the sales team. What is my sales person doing? How many meetings did they go to? Who did they talk to today? How many calls? Activity-based management of the sales team. Useful for CEO. I certainly value the information. What's the pipeline look like? What's the pipeline look like? Forecasting, exactly, right? But if you think about it, that doesn't help the end user that individual do their job. Sales person. How does forecasting help them go into a conversation and have a meeting with a customer? It doesn't. And what happened was those systems turned into systems where the sales person would show up once every two weeks. And put their information in. Put their information in and it was reporting up to the boss, right? And a role for that, but all faced with challenges of adoption, usefulness for the sales team. It's like getting pulled in teeth. Yes, and everyone knows the story, right? This is my boss's report, so I'm sandbagging it. Yeah, I had a call this month. I had a call this month, you know, and all I got to go in at the end of the week. So I'll do it later on a Friday afternoon. I'll put enough in to keep my boss happy but the system didn't help them do their job. And I'll call that legacy CRM. Where we are now is the next generation and that's our vision. And we think of CRM as the tool that helps the sales person do their job. So you're about to walk into a meeting as a sales person. How can we help you prepare for that? We want to be the most useful application. Is that the focus now? Yes. So it's more engagement driven. It's much more engagement. And I'll call it moving from a system of record to a system of engagement, right? It's much more engagement driven. It's much more about how you enable that individual. And if you think about selling, whether it's business to business, which is the majority of our customers, business to business, we have a lot of retail too, but business to business and majority, even in the business to business world, you're talking to a person. So it's person to person engagement. It's all SaaS though, right? SaaS products? SaaS, but we'll go on premise as well. So something interesting here, we don't, we determine our business by customer relationship management. That's what we do. Those are the problems we solve. We help a company with relationship management. We help them deliver a better experience to their customers. We help their sales team understand the customer better. We're deployment agnostic. So you can go to our website today, turn it on, instantly start running out of the cloud. You can bring up and we can manage for you a private instance out of the cloud. So if you don't want to be caught up in the multi-tenant, you want a little bit more flexibility around timing of upgrades. You want a little more flexibility around implementation. We can go to multi-tenant or we can put it into your own data center. So we're not defined by deployment. For us though, it's all subscription. So we look completely like a SaaS business when you look at the coverage. It's really the customer choice, what they want, right? It's customer choice. And we have some customers for whom they have to do a lot of integration where they have big, big data sets and they do analytics on those and it's difficult to do that when it's remote in the cloud or they have regulatory or compliance concerns or they just want more control over timing and updates and flexibility. What do you guys do well when you're winning?  What's your winning formula? What do you guys do best? What do you win the most? What's the use case scenarios? Great, great, great question. So where do we win the most? It's in cases where the customer is looking for, I'll say a real platform to drive the front office. They're a bit of a maverick. They want to look forward in terms of the next generation of CRM, not the past, not the legacy. They see CRM as a differentiator in their business. They see the customer experience as a differentiator. They want to give their sales team real tools to use. They understand it's about person to person connections with the individual. So they want to enable that. There were some other more technical areas. We have a great platform for workflow and managing the customer lifecycle across the business. As the world moves to SaaS and subscription, we really see sales not just being about transactional business, but about being customer legacy and customer lifetime. So for example, we do service support, case management in there, because a lot of our customers- See all the features people need, but you're really looking at the people saying, hey, I want a forward-looking, modern view. Forward-looking, modern system that's all about engagement with the customer and is not just a customer record. And automate some of the administrative, mundane boss reporting stuff. We'll make it easy for that, right? So we still provide that, but it's a side effect of the fact that the sales team uses us. And going forward, things you're looking at investing in, chatbots and AI, and you got to kind of lick your chops and say, hmm, there's some good stuff coming around the corner. There's some great stuff going there. So we have a service in beta right now, which is very exciting. I said, sales is now about all person to person. So this service takes, effectively starts with an email address and returns what is a person profile based on the email address. So you're about to talk to somebody. Okay, well, tell me a little bit about them. Now, a good sales person, go out to the web, do some searches. Right now they're using LinkedIn and who they connected with. Go to LinkedIn, right? Are they on Twitter? Are they on Facebook? Do they have Instagram? Learn about them, right? You can learn a lot of information. So your trip to Hawaii, how was it? That's a good alignment. That's a good alignment, you know? Or your favorite sports team. You know, did you see that Warriors game, right? Yeah, he's in red socks fans getting together. Do you avoid the topic if that's the case? Yeah, did you suffer that 49ers game last weekend? Right? Yeah, exactly. You know, you learn that about a person. We have a service that goes out. It's faster closure tools. You move the needle on that. I mean, it's just basic common sense that you have that data. You avoid stepping on yourself. If someone's, you know, who knows? It could be a Trump fan or Obama fan. If you're one side or the other, you don't, you want to know that. You want to know that and not to talk about. Well, it used to be that, you know, in selling, you'd go visit someone in the office and you could look around their office and you'd see, you know, a diploma on the wall. Some people would be like, hey, nice thing, you know. You're cubicle. Exactly right. You know, today, the internet is that virtual office, right? What the person says on Facebook, what they say on Twitter, their profile on LinkedIn, any other social media, news articles even, pull all that together. So that we see is kind of the initial next stage. You guys have a customer event that you guys put on anything going on in the market in terms of events that you guys were just being in where can people find more about sugar in the market? Well, yeah, of course always our website, shrewdcrm.com. We put on a great customer event every year, SugarCon. That'll be coming up at the end of next year, actually. Great event for us. Lots of companies come together. There's a lot of information. Practitioner, not an industry, but more of a branded show for you guys. Yes, yes. Practitioners. Branded show for us, practitioners, people that come together around the industry. Great customer reference stories you can put together there. Great things. I mean, we have, we're the system for IBM, largest in the world. In media, New York Times uses us.  Even with the post-election that I saw that John Markov who's retiring, good friend, but he was mentioning that their digital subscriptions are up through the roof since the election. So good software. Everyone wants that information, right? So yeah, lots of places for us. Larry, thanks so much for spending the time here on theCUBE and we have another segment talking about the bigger picture, but congratulations and thanks for coming and sharing your content. Great, thank you very much. This is theCUBE in Palo Alto. I'm John Fourier. Thanks for watching.


The whole goal should be work half as much with twice the results. I had a neighbor, this guy, I would play basketball outside, he would come jogging by me. Every day, it says 2009, that I was there, he would come jogging around. The dude got fatter, and fatter, and fatter, and I was going, you got a job, I never said anything but I wanted to say, first of all, whatever you're doing, stop. Because it's actually, unless your goal is to gain weight by jogging. Number two, he was doing too much. Like he could have done sprints. If he could have done 20 minutes of sprints, it was better than his two hour run. And so I feel like that's how most entrepreneurs are. They're like, Ty, I'm grinding away, I'm working, I'm working. I'm like, yeah, but number one, you're working on the wrong thing.


What you got, dude? Let's go, gang! Ain't too much talking today, Stray Axe. I might dump, too, now. Yeah. Just kidding. Oh, let's go, Oat. Let's go, man. Let's go, man. Let's go, man. Let's go. What'd that do on your nose? Need a tip. Damn, one target is done. One target, I had one little PBU over there. I'm saying one target, though. Yeah, one target, yeah. I don't know what I have, I know how to drop me, though. I know that. I'm going to own up to that. First in 15. Send me a wants to throw. My boy Kuat does. Let's get him. And feel good. They'll feel too good, boy.


How to use the one click address copier. This feature is going to save you a lot of time when fulfilling your orders because you won't need to fill in all of the customer's information manually on your supplier's page when fulfilling their orders, which let's face it, we are human and we make errors every now and then. So, on top of also saving time, copying our addresses, we're also going to avoid mistakes like shipping out our products to the wrong customer's address, which is a mistake that happens every now and then when we're doing everything manually on top of other things. So, let's see exactly how this one click address copier works. So, here's the Autodesk platform on the left side, I'm going to click on orders and here we have an order on pending status, which wasn't fulfilled yet. So, let's go ahead and fulfill this order right now using the one click address copier. So, here is the order's item ID, I'm simply going to click on it and here it is right over here. So, this is the product, I'm going to add it to cart, I'm going to assign it as a gift so that my customer will not get a receipt and will not see the price that we paid. And the next section should be the address section, which is where we're going to use that one click address feature and here it is right here in front of us. So, first I'm going to see all of the addresses that I shipped to in the past, which is a whole bunch of different addresses and to get to the address section to add a new address I'll need to scroll all the way to the bottom of the page, which is less practical the more addresses that we have. And once I reach the bottom, here we have the add a new address section where we can add that address using the one click address copier, which you can see right here we have a paste button. But right before we get to that, I want to tell you guys that all of the addresses that we see over here, I'm going to show you a shortcut really soon using the Autodesk extension to delete all of these addresses instead of us having to click that remove button one by one and simply wasting way too much time and energy doing so. And on top of that, if you don't want to scroll all the way down each time you want to add a new address, if you haven't removed these yet using the shortcut that I will show you in just a minute, you can simply open up the search function on your browser and search for add a new address. And now as you see, it's simply scrolled all the way down to the bottom of the page where we have the add a new address section and we skip the whole scrolling to the bottom of the page. So now instead of using our time and energies writing the customer's address, let's see how we can automate that using that one click address copier. So I headed back to the order section on auto DS. Now I'm going to open up this order and in the orders details, you have a copy address link left click on that and then you'll have an option to copy only the address or to copy the address and also the customer's phone number. Since we're shipping from the US to the US in this example and it's from Amazon, we don't need to copy the customer's phone number and address is copied as we can see here on the bottom right. I'm going to head back to Amazon. Once the address is copied, all that's left to do is click on pace. Now I'm just going to wait less than two seconds, one, two, and it's already here. So we have the customer's name, address, city, state, zip code, and the phone number is all nines because I asked the extension to not copy the customer's phone number. So everything here looks good. We're going to click on add address and continue with the checkout process. So that is how simple it is to use the one click address copier and save a whole bunch of time when fulfilling our orders. Now let me just show you really quick how you can delete all of those addresses that we just talked about a minute ago. So I'm going to head to Amazon. I'm going to click on the account name up here. Then in the account settings page, I'm going to click on your addresses. And once again, we'll have that list of all of those addresses that we sent our products to in the past. Now, once we're on this addresses page on our account settings on Amazon, if you scroll to the top of the page, you'll see delete all except default coming from the Autodesk Chrome dropshipping extension. It's going to delete all of the addresses that we have on this page, clean up this whole big mess that we're seeing here in front of me. And it's going to only keep the default address that you have set on this page. So if there's some address that you would like to save, if it's your home address or anything else, simply click on set as default. Then it will become your default address. And once I delete all except default, it's going to delete all of the addresses except that default address. And as you see, it's starting the deletion process right now. As long as you leave this tab open, it's going to delete them one by one. So the more addresses that you have, the longer it's going to take. So simply leave the tab open and continue working on different tabs. That's how simple it is to delete all of those addresses that you have clocked up in your Amazon addresses page. But more importantly, that is how simple it is to use that one click address importer and save a whole lot of time while fulfilling your orders on AutoDS.


Mr. District Attorney, starring David Bryan. Mr. District Attorney, champion of the people, defender of truth, guardian of our fundamental right to life, liberty and the pursuit of happiness. And it shall be my duty as District Attorney, not only to prosecute to the limit of the law, all persons accused of crimes perpetrated within this county. But to defend with equal vigor the rights and privileges of all its citizens. This is David Bryan. In a moment we'll bring you another case from the files of Mr. District Attorney. But first the word from our sponsor. Our David Bryan as Paul Garrett, Mr. District Attorney. A District Attorney knows that crime does not always end when the criminal is put behind bars. Some men reform, but others begin immediately to plot their next crime. This case started in the state penitentiary just after the weekly visiting hour. Your wife bring what I told you to get for me? Yeah. She brought it, Johnny. Here. Vitamin tablets and the razor blades. You know, we're not supposed to have razor blades. Yeah. If they find them on me they might put me in jail. What are you so jumpy about with your lousy year? Another five months and you'll be out. I'm doing life and my nerves are still better than yours. Look, Johnny, with good behavior credits I can get out in three months. I don't want getting no trouble. Lay off, will you?   A big favor. Look, I got to be careful what I ask her. I can't upset her now. You know that. Oh, that's right. A baby is too soon, ain't it, Papa? Wouldn't want the kid to start out without an old man, would you? What are you talking like that for, Johnny? I wanted to see if your wife could get those razor blades in. She did. Next time she can bring in what I really want. What? A gun. No, Johnny, she can't. You don't think I'm going to end my life in here then think again.  I can take one of these razor blades to your throat like that. No, no, Johnny, I... All right, Johnny, all right. I'll do it. I'll tell her to get it for you. Don't kid me. I can hear the wheels turning in that square here to yours.  Oh, Johnny, I swear. I know you won't, and I'll tell you why.  Remember that. Remember it if you ever want to see that kid. You don't realize what you're asking me to do. I'm asking. I'm telling.  You wouldn't do that. Wouldn't I? Try me and see. As the squirrel making his count now, stop him when he comes past. Tell him he'll get you out of here and take you to the warden. You can spill your guts and they'll put you in a nice safe cell away from me.  You'll never know when or where from. All right, here he comes for your big chance. That's a bright boy, Abbott.  The tongue of the lock has been cut by a hex saw blade. They must have waited in the passage until the jailer turned the corner here and shot him through the stomach and took the keys. Any idea where they got the gun? I guess Abbott's wife must have brought it in during her visit. Why would she get a gun through the visiting screen? They didn't use the regular visiting room. Warden let them meet in the privilege room. Why? Well, because Abbott was a first offender with only a few months to go and his wife was expecting a fate. I see. You put out a pick up for him? We've already got him. Where? God's office at the end of the tear. You want to see it? Yes.  I don't know, Hankan. A life like Johnny Curtin had a reason for crashing out. The first time I like Abbott was only a few months to go. He doesn't figure to make a break. Just the same. Abbott's gone too. Well, we may find out why when we see his wife. Sometimes a man goes places he doesn't want to go. Well, the gun on his back. She's in here. Mrs. Abbott? Yes. Do you want to help your husband? And the best way is to help us. You can't get away and the quicker we get to him the better will be for all concerned. Did you supply him with a gun? It wasn't for him. It was for that other man they put him in the cell with. Johnny Curtin. What? I'm afraid this isn't going to be any comfort to you, Mrs. Abbott. But I don't think your husband went willingly. I'm afraid he went at the point of that gun you brought in. I'm beginning to agree with that idea, Chief. You brought other things for Johnny Curtin. What sort of things? Vitamin pills mostly. Every week. Vitamin pills? Curtin was some kind of a health bug, Chief. He was always after the prison doctor for vitamin shots. Even though letter to the governor demanding the state keep him supplied. I see. Excuse us for a moment, Mrs. Abbott. I'd like to have a word with you outside. Can you sign anybody to watch your home? In case Abbott and Curtin show up there? Yeah. Moran and Phelps have it covered. When we get to our car, we can put out a radio call to all units. I want to careful check on every robbery report involving a food store and an itemized account of everything taken. Why an itemized account? They'll probably take anything they can lay their hands on. Maybe, but Johnny Curtin may make a special effort to get his hands on some vitamin pills. Hey, that's right. Uh, what about Mrs. Abbott? Just leave her here? Oh, for now. There's nothing else we can do. Now, let's get to the car. This guy's beginning to turn gray. Yeah, son will be coming up in half hour. I can't figure why you want to concentrate on these back roads, chief. We haven't spotted a living soul in an hour. No. Not even a state police car. Well, they're concentrating on main highways leading toward the border. Yes, and these farm roads occasionally intersect the main highways, Hagen.  He's not going to strike from main highway while he's on foot and wearing prison clothes. And another farm gate up ahead? Want to stop? Yes. I'm surprised we haven't got the farmers after us the way we've been robbing them out of bed. Gate's locked. And we're parked here. We can slip through the fence and walk up to the house. Seems to be some sort of a light in the barn. Yeah. Probably up already for early morning chores. Ah, here. Here's a loose string. Go ahead. Slide through. I got it. Dogs. They sound like they're tired of that tree in front of the house. No, they won't bother us. Good. I don't like being stout.  It was. I heard the pellets whizz right over our heads. Come to the loft of the barn.   You'll be the one to get hurt if you fire once more.  The next one won't be over your head. Please can take care of you as soon as I can get you to him. What kind of a line are you? Just a minute, Hagen. He sounds like a farmer. Cut the loose with a shotgun? Freddon doesn't have a shotgun. He has a revolver. Are you the owner of this place? You'll find out who I am as soon as I can see who you are. I'm the district attorney of this county. My car's down by your gate. I have an assistant with me. Or after two men who escaped from the state penitentiary a few hours ago. Can you see us now? Yeah, I see it. Go up toward the barn and I'll come down from the loft. Come on, Hagen.  Let's find out why he did it in the first place. There. Ellie is now coming out of the barn. I wouldn't have fired if I'd known who you was. You wouldn't waste any time trying to find out. Now look, mister, I don't like being shot at any better than you do. And I was shot at, not 20 minutes ago, by a couple of flowers. That's what I was expecting, Hagen. Did you see what the men looked like? Just a shadow as the dogs woke me up, knew something was wrong as soon as they came out of the house. Jeans and shirts missing from the back clothes line. And I spotted them over toward the hen house and heard a couple of my hands of fluttering. I called Zoom and one of them fired a shot at me, so I ducked into the barn. They got the clothes to take a chance on the highway now. Oh. What's the nearest main road? Road your car's on, cuts into state 12, about half a mile ahead. We'd better get to that highway fast, Hagen. They've got clothes now. They'll try for a car. Hitchhike? Yes. A hitchhike with a gun. Haven't helped any motorists foolish enough to stop for them. Come on. Here's the highway intersection. Well, nothing in sight. Which way do we try? Left of the general direction of the city. Maybe they... What's the matter? What are you looking at? The rush on the far side of the state road there. I thought I saw a little smoke. Yeah, yeah. I see it, too. Oh, I'd better have a look. Right in between those two trees. Mm-hmm. A little campfire dying out. Oh, there. Veggie. Tire cracks. A few sets of footprints, too. Hey, look. The prints go up into the brush and come back again. And what are those spots there? Blood stains. The driver who stopped for them? We'd better go in there and look around. It must have been them all right. No doubt about that, Hagen. Look at the way he was killed. Johnny Curtin's trademark. He was shot through the stomach. This is David Bryan. Before we continue with Mr. District Attorney in the case of the hungry killer, here is an important message from our sponsor. And now back to David Bryan, starring as Paul Garrett, Mr. District Attorney. A jail guard in an unsuspecting motorist had been viciously murdered by an escaped convict, holding an unwilling cellmate as hostage. I ordered roadblocks thrown up over every possible escape route, and Harrington and I drove back to my office to supervise all phases of the manhunt. By the time we got there, Miss Miller and my staff had assembled every bit of available information on the previous life habits and association of Johnny Curtin. Here are the mates on Curtin's together. Oh, thank you, Miss Miller. What do we show on known associates? Blank on our records, I'm afraid. He was a sort of lone wolf type kid. There's something in his record from the state of Illinois, though. He did time in Joliet for armed robbery before he moved here. During the time he lived in Illinois, there was a woman named Marcella Roberts. She ran a beauty parlor in Springfield. Hmm. Any line on her present whereabouts? No. Telecipe from the Springfield police says she sold her shop there three months ago. Moved, no forwarding, I guess. Now, I want to find out where she moved. That isn't going to be easy. It will be if she went into business again. Well, here's what you do, Miss Miller. Check all cosmetic distributors and supply houses where Marcella Roberts had established credit. If they... I'll take it, Chief. If she's back in business, her new suppliers will be checking the old ones for credit references. Find out who the new suppliers are and they'll be able to tell us where to locate Marcella Roberts. I'll get right on her. Oh, that was Charlie Benton, Chief. Dispatch with the Sheriff's Office. Robbery report on a food store. Where? Just outside of Eaton. We going out there? As fast as we can get there. I told the fella from the Sheriff's Office I was asleep in this room here. Right back to the store. When I heard this noise I told you about. It was still dark just before daybreak. Do you see anybody? Oh, as a matter of fact, it didn't. I didn't even put on the store lights. Why not? Well, of course, when I opened the door to the store here the dang cat popped into my room and started purring and rubbing against my leg. So I just figured she'd knocked something over so I went back to bed. I didn't know the place had been robbed till I got up at eight o'clock and found the front door had been bright open. I must have slept through that, though. I sleep sound. I guess I woke up when they knocked that stack of canned goods over. What's that? Fruit you, sir. I've got it all stacked again. Third time I've been robbed in two years. Why do people want to pick on a small store like this? Think they'd drive into Easton over a supermarket or something. You've been robbed before, huh? Yeah, like I said, three times. Yeah, it might not have been the boys who were after you. No. Better get a fingerprint through out, though. Make sure. I'll get them on the car radio. You got any idea what they took? Yeah, I don't know. I don't have much of an inventory system. No ways I could tell for sure. I wouldn't even have known they took anything if they hadn't been through the door in the cash register. I can understand them lifting the six bucks from the register, but why do they have to steal my pills? What pills? Oh, some pills the doctor gave me to take. Kept them right on the shelf under your register. Vitamin pills. Vitamin pills. Why didn't you mention that to the sheriff's deputy? Because only found out they were missing when I went to take one just before you drove up. Why? What's so important about the pills? Just a very slight thing. Something that spells the difference between an ordinary burglar and a vicious murderer. You'll hear from us. Oh, chief, I was just coming in after you. We're not going to need that fingerprint through after all, Harrington. The grocer just told me the burglar stole a bottle of vitamin pills. Oh, then we're getting hot. Why? When I came out to the radio, headquarters was trying to reach us. They find the car Kirtan and Abbott were using? No, but they got a line on Kirtan's girlfriend, Marcella Roberts. She opened the new beauty shop. Just 40 miles east on this highway, Lindbrook. That's what Kirtan was headed for then. Come on. You figure the woman is helping him hide out? Kirtan didn't have this way without a reason. If she isn't hiding him, she'll know where he's running. Chief, I don't like it. Don't be patient, Harrington. How long? Based on the beauty parlor is closed. Now we wait all day and she doesn't come home. The sign said the beauty parlor is closed every Monday. That's not uncommon. Why isn't she here then? For all we know, she's taken case in some place where we'll never be able to find her. In which case we have no choice but to wait and hope we can find a way to make her tell us where that place is. Yeah, I guess you're right. But getting dark and all we have... Hey. Here comes a car. Staying the shadows on the side of the porch here. This is my assistant, Mr. Harrington. We thought you might be able to help us. You know a man named Johnny Kirtan? I... Well, I used to know him a long time ago. Then you haven't seen him lately. Well, how could I? I heard he was in jail. Your news boy must have neglected you this morning. He's out. We're looking for him. Well, I haven't seen him. Good. Then you shouldn't mind if we take a look through your apartment. If you've got any objections, Miss, the chief can wait here with you while I go for a walk. Well, I only hesitated because the place is a mess inside. Don't worry. We won't tell the neighbors. Well, here you are. Couldn't hide a mouse in here. Check the closets in the bathroom, Harrington. Now have a look at the kitchen. Okay, Chief. Chief, that's for sure. No, not now. But there was somebody here. What do you mean by that?  Take a look in the kitchen, Harrington. I don't see nothing. I'm looking at the shelves. They're rather dusty. Except for the clean rings left by a bunch of canned goods. And the cans were removed. Mr. Garrett, I... You're concealing and aiding a murderer if you know where Johnny Curtin is. Miss Roberts, you can serve a lot of time for that. Now where is he? What? Well, I drove him and another fellow upstate. You know where the old state fish hatcheries used to be. Was he going to stay there? Yes. He said he'd stay there for a week. That I should raise some money to get him out of the country and bring it to him next Monday. Drive us to the spot where you left him. And don't bother about raising the money. He isn't going to be needing it. I thought I told you to sit down, Abbott. I can't. I'm cold. Why can't we build a fire?  I wanted anybody to know I was up here and send out invitations, not sit down. Sit down before you get knocked down. It's better, Abbott. Live a little while you can. You shouldn't mind the cold when you've only got a week. Stop slinging that. What do you want me to say?  Oh, no, Abbott. When I get on that ship and leave the country, you're going to be lying nice and quiet someplace. Say nothing. Why? I never crossed you up. When you wanted things, I got them for you. Because I was right there making sure you did. But once I get my chance to run up for good, what was that? What? Saw a flash of light against the trees, down that way toward the road. Maybe it's your girl coming back for something. Maybe it's the police, whatever it is. It's stopped down there because the lights went off. Come on. Up on your feet, move. Not that way down toward the road. But suppose it is the police? Suppose they shoot? That's what I got you for, Abbott. So stay right in front of me all the way. I'll move or I'll give it to you right here and now. It must be your girl. She's blowing a horn. Cops wouldn't do that.  I'm glad it's not the cops, Johnny. Honest I am. Oh, yeah, but you're dumber than I thought. Maybe she got her hands on the door I need already. Have a think of that. Because if she did, you just lost a week. You've got to give me a break, Johnny. You've got to give me a chance. All right. If she's got the money, I'll give you a chance. I'll count up to five on your run before I... All right, Curtin. You can stop right there, both of you. It is the cops. Now you're slugging around, Curtin. You'd never make it back into the trees. Don't shoot, please. I didn't want to be with him. You hear that? He's telling the truth. Little Abbott doesn't want to die. But he's going to die if you make one move to get me. Take that right, Abbott. Tuck up. No, stop. Johnny, my arm.  Why don't you shoot? Come on. You'll hit Abbott first, but I don't mind. Would you rather make a deal? We don't make deals. You'll make this one of Abbott's a dead pigeon by the time I count ten. You mean this?  What's your deal? Just turn around and walk away from your car. And keep on walking until I get it started and get out of here with my friend. It's all right, Angon. Fair enough choice. That's nice. Just keep moving. All right, Abbott. Now we can go. No. Move, you crazy punk. Why?  No. You're going to kill me any house or do it now.     Let go of me. You're crazy. I'll put a bullet through your crack.  Let him go. Let him go. I don't just... It's my hand. He bit my tooth in the bone.  Now, March, both of you, down to the car. I never expected this one to turn out this way, Chief. And none of that I, Hankon. But a man can only be driven so far. Curtin drove Abbott to the breaking point.  Abbott stopped Justin from... This is David Bryan again. I hope you've enjoyed this case from the file of Mr. District Attorney. I'll be back in just a moment after this message from our sponsor. Here's the star of Mr. District Attorney, David Bryan, with a word about the program you have just heard. Johnny Curtin, already sentenced to life imprisonment, was tried and convicted on two counts of murder on the first degree. He was sentenced to be executed in the manner prescribed by law. Ralph Abbott and his wife, Francis Abbott, were each sentenced to two years for aiding Curtin. But since they had acted under duress, sentences were suspended. Now this is David Bryan and based on the facts of crime from the files of Mr. District Attorney. Mr. District Attorney was originated by Philip S. Floyd.