Thank you all for having me here. It's a long time. I consider this to be somewhat of an academic conference, if I may. And so this is a long time ago since I talked to academics. And I hope that I have a story for you that can take you where you find some utility in and maybe gives you some ideas about the IT side of things. As I, as Marco really said, I'm the Chief Technology Officer for Amazon.com for the past 14 years. And you may ask yourself why, what's a bookseller doing here at the Rights Congress? Well, about 10 years ago, 12 years ago, we pioneered a concept called cloud computing. Basically, removing the need for anyone to own their own IT infrastructure, where you can get databases storage, compute, networking, security on demand. And so that's become a very big part of the Amazon business. And literally, millions of businesses around the world are running on the what's called Amazon Web Services, AWS. It's something that you'll see coming back in the presentation a number of times. And I'm very fortunate that on this platform, it's not only millions of businesses are running, but a lot of non-profit organizations and research organizations are making use of this. Because one of the concepts around cloud computing is that it reduces costs significantly while giving you access to almost infinite capacity for doing computer research. And of course, I think as a research organization, anything that you can do to save some dollars off can be contributed to doing research instead of sort of having to fund hardware companies and buying hardware. And so as such, there's a great match between sort of the on-demand infinite scale capacity that a cloud computing environment gives you and heavy computational research. Because I think most research these days is heavy computational because it circles around data today. Now, if you think Jim Gray famously called this sort of the fourth generation of research, where the first one was thousands of years ago where research was all about observations. Now, Newton said that I saw an apple coming down. Hundreds of years ago in the second generation of research, it was all about theory, thinking about theories. And then tens of years ago, the third generation is really focused on trying to find computational proofs for the theories that we've done. But I think everything is shifting today to fact-based research. Basically, everything is becoming data-driven. Everything with that is also becoming computational-driven. So there's a big synergy between organizations like ours, like AWS, who provide infinite capacity around the world and sort of these new computational research, and whether that is done at academic institutions or at commercial institutions. I mean, it's very fortunate that there's all these amazing organizations running on AWS and making use of AWS. And there might be, on one hand, maybe even for their EAP systems that they're using to connect different organizations together or really actually doing hardcore genomics research. And so one of these organizations that we're really proud of that's been a great partner with us for a long time is Erie. And so you probably all know Erie much better maybe than I do, but really the support for the poorest farmers in the world and building research programs around that is very close to Amazon's heart as well. And we'll do whatever we do can actually support this kind of research. One of the areas that we're working with researchers around the world is making sure that the data that they do produce can be made available to everyone. And literally many of these data sets are becoming so large that it's very hard for anyone to sort of send these data sets around. And there's a great anecdote about the 1,000 genome set that I'll come to in a bit. But more importantly, Erie, together with two other research universities, has made the 3K RGP data set available on AWS. This is well over 3,000 sequence rise genomes from 89 different countries. In essence, it's about 30 million different variations that you have access to. And this is a data set that is available for everyone to access on AWS. And I think these things are crucial to actually really accelerating research. And we see this across the board, not only with the great data set that Erie makes available on AWS, but we see it across many other disciplines as well. As soon as you make this available on a platform like AWS, research truly explodes, because now everyone has access to this data. An interesting thing is also that you have to think about sort of what format you put your data into, such that you can make computational processing of this very, very simple. For example, Erie has built a web-based interface to the data sets that lives in S3 that you can use to immediately sort of search for all the different variations that you're looking for. So it's not just that you have access to the data set, you actually already get web-based portals that actually give you access to this data set as well. It's great work being done by Erie, and we're really proud at Amazon that we're able to support this through the OpenData program. If I think about sort of how these data sets are growing over time, it's interesting to look back at the sort of the human genome program. If you remember, the human genome project started off with a sequencing of one human genome which literally took 13 years to shoot. And the resulting data set of that was actually put on an iPod, which was then sent around the world to different researchers, which could take the data off. And of course, that data set wasn't that terribly big. I mean, gigabytes in those days definitely were. But if we then look at how the human genome project evolved was that doing that one human genome was way too much work. Yeah, it was really, you couldn't do all the genomes in doing all the 13 years. So everybody went on to doing easier animals, yeah, mouses, rats, things like that. And basically that set got to the hundreds of gigabytes. And then the sort of next generation happened where you get these new sequencing instruments becoming available, where actually sequencing genomes is becoming extremely cheap, yeah? And so the result of that is already getting into terabytes. Yeah, and terabytes are becoming more, it's harder and harder to download just a terabyte of data, especially if you start talking about hundreds of terabytes of data. Because if you look at the 1,000 genome project, the resulting data set is that of 1,000 genomes and actually has 200 terabytes. Yeah, and again, this is one of those data sets that is available on AWS for everyone to access and to operate on a drive enormous amount of research. Also on one hand, because everybody now is operating on the same data set. I think research in the past often happened on your private data set. And maybe your results will be published in the paper, but there were very few people that were actually publishing their data sets also, such that research could be repeatable. And I think some side of the whole open data process that we run on AWS and other organizations do as well is to drive repeatable research. And so if you look at sort of the different types of organizations that are all putting their data on a cloud provider such as AWS as open data, it can be on one hand, for example, research organizations like the Met Office in the UK or companies like Digital Globe who do all the digital with all the satellite imagery who actually also rely for a very large part on open data. And so we do this and make it available for anyone to use. If you go to this website, opendata.aws, you'll find a whole collection of data sets with detailed description about exactly how to access if you're kind of licensing around the data sets and also what kind of formats there are. And so we have quite a number of right variety of different data sets available here from the US government, to NASA, to Erie, to the tax office in the US or different countries. And this is just a very small number of these data sets that are available. And if you're a researcher who is thinking about publishing and actually thinking about sort of also making your data available, I urge you to contact us and work with us to actually make your data available for every other researcher to access as well. The thing is that I think most research these days is really co-collaborative. This is jokingly called Joy's Law. He, Bill Joy, used to be the co-founder of Sun Microsystems, a company that no longer exists. I agree. But he was smart enough. He always said that no matter who you are, most of the smartest people will work for someone else. And it always means that sort of you can augment your research basically by sort of working together with other people. However, traditional data acquisition was sort of hard. It was really from tape to boxes to so much research funding being wasted in being a sort of indirect funding for the computer hardware industry that we really need to move away from this. One thing is, of course, that already much of this data is actually being generated in the cloud itself. DNA Nexus, which worked with Erie on the 3K-RGP dataset, actually did all the processing of that data in the cloud. And they used 37,000 cores for two days to actually create, to do all the sequencing necessary to actually make this dataset available for everyone else. And of course, all the stuff is really happening in the cloud itself. And as such, it's a great sort of centralized place for much of this research to be taking place. A lot of this stuff that I think is, and I've been a researcher for a long time, myself, and I know how much time I wasted on what I would now call undifferentiated heavy lifting. I was a computer science researcher at the time, the amount of time that I actually spent putting cables together, putting servers together, building clusters, all these kind of things was terribly interesting, but so terribly wasteful from a research perspective. I learned a lot about sort of keeping hardware up and running, but that had nothing to do with the research that I was doing. So there's a lot of undifferentiating lifting in and around all this data research that I think we need to really move away from. And so the cool thing is, of course, sharing this data in this one particular location will, first of all, give you a whole set of new services and tools that you did not have available before you, and whether that is, let's say, the more traditional sort of analytics tools that Amazon provides you with. But it can also be all sorts of partner tools and sort of open source tools. If you're a user of, for example, HTC Condor with one click of a button, actually, you can launch a whole Condor cluster on AWS without ever having to sort of instantiate different machines again ever. And so it significantly lowers the cost of research, but it also really drives sort of acceleration of research as well, because everybody now has access to the same data sets. And I'm going to point out one particular data set that I really like. So this Landsat, the Landsat satellite, if you know, number eight is, I think, circling the world at the moment. So what NASA did was actually put all the data from Landsat as an open data set on AWS. I think this is the 2015 data set. And after that, every new image that the Landsat satellites produce actually immediately gets added to this particular data set. So Landsat is the largest collection of data sets in the view of the land of Earth seen from space. It's an amazing data set. Interesting is that we worked with NASA to actually find a particular format for the data that contained enough, let's say metadata and other components in each imagery, such that actually it was very simple to build web-based systems immediately on top of this, where you did not need to run any servers or anything like that. You could just create a web page and point it to this data and then create, for example, a Tyler like this one. There is no servers involved here at all. Basically, the data lives in what we call Amazon S3, the simple storage service that is directly internet accessible.  Well, that immediately brings data in front of every researcher or in every anyone that's interested in this particular data. So this is a Tyler that the guys from Mapbox built, who by the way is a great group of individuals. To really figure out what kind of formats to use is really important. So this is actually, this is the data from someone that actually normally had to access the data set from a traditional environment, moved it over to AWS and in a much more efficient way able to process all the imagery because the metadata sits now with the image itself. And actually he shaved off about 250 days of his research by purely using more, let's say, IT optimized imagery instead of the traditional imagery that comes from the satellite itself. There's one particular whole group of data sets, open data sets that I would like to point you to, this may be of your interest. It's what we call the Earth data set. And it has a whole set of public different data sets about geographical imagery and whether that's around climate models or elevation models or satellite imagery that's available for everyone to use. If you actually are interested in doing research with this particular data, go to this URL and we may have research credits available for you to actually process, to actually work on this data. Now I said earlier on, it's a large part about this is tools that actually are available in AWS. I think we help you get most of your data. We have all sorts of different storage options and talked about S3 already. And so it is mechanisms where we can hook up a whole set of different analytics tools with the different storage options that are available and whether those are actually in the cloud or on-premise, we make all of these things available for you. Machine learning is becoming increasingly important part of research and I'll talk a bit more about that in a minute. Many of you have been running your own hardware and things like that and there are quite a few researchers who are always interested in what kind of machinery they need to use to do their optimizations. Well, we have a whole family available for you. Really you want to do multi-massive in-memory processing, whether you want to use GPUs or general-purpose GPUs or whether you want to put it onto FPGA arrays. All of this stuff is available for you. Hit us up if you want to get research credits to make use of any of these machinery. One thing I want to talk a bit about because it's so much so hot at this moment everywhere is machine learning. And so I'm not really sure how many of you in the room are aware of what machine learning is. I think it's part of what we call artificial intelligence and that scares everybody immediately. Of course you start thinking about robots and Skynet and things like that. It's not. Machine learning, if I think about analytics, there's sort of three different types of analytics. I think there's analytics that looks towards the past and sort of the traditional data warehousing and some of that kind of analytics. Then there is analytics that looks at the current state of affairs. What is happening right now in real time? You're not interested in your inventory level. Yesterday you're interested in what's your inventory level right now. And then there's the third part of analytics and that is making predictions. But it turns out we're really bad in making predictions. But what we can do is actually take data from the past and then try to make use of that data to make an educated guess about the future. And that's what machine learning is all about. At one moment, data sets are becoming so large that it's so complex that it's no longer possible for humans to just write an algorithm. You actually want a computer to start sort of figuring out what are the most important aspects of this particular data? What are the things that we should be looking for if we are looking for, let's say, objects in this imagery? Or if we are looking for, let's say, maybe doing inventory level planning or things like that. At Amazon, we have a very long history at machine learning.  And that's all the things that we've pioneered, for example, around recommendations or all the robots that we're running in our fulfillment centers.  All of those applications are machine learning in one way or another. Basically operating on very large data sets and then discovering, let's say, what the content is in there for you to use. Well, those were all big innovations but we've been using machine learning all over the place for such a long time. And whether that is things like from the lead time detection or visual search or product matching, all these kinds of things are machine learning driven. However, they may have been many of our innovations in that world, but turn out there was pretty heavy weight processes to get these done because you needed data scientists for them. These were data scientists that were writing new algorithms that were processing your data, using your TensorFlow or MaxNet or Cafe, any of the popular frameworks there. But they were very, very heavy weight. And so what we were looking for was a mechanism such that every developer could make use of machine learning because it's such an important part of an organization like Amazon where we have very large corpuses of data and then actually would like to make use of the data to actually serve our customers better. And so for example, we literally sit on billions of orders. And so you know which one of those orders in the past were fraudulent and which ones were not. And then you can make use of machine learning to make a model out of that. That if a new order comes in, that you can give it a score what the likelihood that this is also a fraudulent order. Yeah, and so this is all about sort of discovering patterns in that last data set that you then can use to give this new score. That's not that you don't automatically reject that order, it then still goes to a human investigator, but it sort of is augmenting humans. Important there is that we want every developer to do this. So we started developing services around that. And so with these new services, suddenly you no longer needed to be a data scientist to actually make use of machine learning. Everyone could do that. And we saw literally an explosion of hundreds of new applications happening within Amazon because of the use of machine learning. Yeah, and whether that is for example, counterfeit good detection or sort of display ads and all sorts of other things that are really driven by machine learning. And we have literally tens of thousands of customers also willing on AWS doing all this machine learning. And so with all of that, what have we learned actually from both the Amazon experiences as well from the experiences that we see it, all these customers on AWS that are willing machine learning is that machine learning needs a new stack because it really is getting outdated. No, nobody can operate anymore really at the level of the old data scientist, although we do need to support them, but we need to start looking at putting machine learning in the hands of everyone, including you as scientists and researchers. So in essence, if you know what machine learning is, it basically takes your data, you do a lot of you run it through a number of algorithms repeatedly with a whole set of different parameters until the accuracy that you get out of it is something that you satisfy, then you create a model, you run that model somewhere you can ask questions against it. And so you have new data then coming in, you can use that against the model and then do predictions based on that model. Just like I just said with the order data set, you can sort of start making predictions where the new orders are actually forward or not. Or it might be something else, might be an abusive review detection mechanism, things like that. There's whole things across the board that you can do with machine learning. So yeah, our mission for machine learning at the AWS division is really to put it in the hands of every developer and every scientist. So for that, there's a few new pieces of this tech necessary. At the bottom, there's still the traditional frameworks that sort of the data scientists are using. But on top of that, you build a platform that makes it easy for everyone to use these machine learning algorithms. And then there's a whole set of services on top of that again, for if you don't even want to run these algorithms, but want to have several pre-built models that you can use, we have those available for you as well. So let's take a look a little bit deeper. So the framework level is still all the work that normally the data scientists do. And if you've ever been doing machine learning, you know these ones very well, Café, MXNet, TensorFlow are sort of the well-known frameworks and interfaces out there that most data scientists use. And we run them on an infrastructure with sort of the latest GPU boards that you can have, which basically gives you a petaflight of compute per board with lots of different cores and very fast access to memory so you can build all these graphs and networks very easily. Again, I think this is sort of the level where data scientists want to work. They really want to tinker in creating new types of algorithms. But in reality, if you look what we really do in machine learning, what you do is actually you create your data sets, work hard on data quality, which is very unique and specific for the particular data sets that you have. And that's something that is hard to help people if we look at the data quality, but it depends a bit on the kind of data that you have. You sort of lay out what kind of algorithms you want to use. Then you start to train.  It's basically running the same algorithms over and over and over and over again with a different set of parameters. And then the upcoming model, you pump some historical data in to see whether you can predict the past and then see how well your model actually does with sort of your test set of data. And then once you have that model, you have to deploy it somewhere because you actually have to ask questions against it. So this is what we do. In essence, I think 80% of machine learning has nothing to do with machine learning. It's just heavy lifting. It's just undifferentiated heavy lifting. You have to get your data somewhere. You have to repeatedly execute the same algorithm over and over again. You have to go back to your drawing board and then you have to actually run it somewhere. All of these things are actually pretty hard to do. And so we developed a system for that, for you to use there, a platform called Amazon SageMaker that basically takes all the heavy lifting out of machine learning for you. Basically, what you do is you start off with, in general, a Jupyter notebook where you sort of in a few lines of Python, describe exactly what you want to do. You can use the notebook as your execution environment. You pick the algorithm that you want to have. And so this is where the difference is with the data scientists. They have the data science to create new algorithm. Here, as an engineer, you basically pick the right algorithm that you want to use. And we built very high performance ones that were not available anywhere else. We call them streaming algorithms. Because in essence, data sets are getting larger and larger and larger. And so having to, when, for example, you get a new set of satellite images or where we get a new set of orders in, you do not want to retrain the whole data set. That will be very expensive, both in time as well as in money. And so we've been building these new algorithms for you to use where you can basically stream your data through and then checkpoint it and then basically start adding new data to it. So you pick the algorithm that you want to use, then with one click of a button, you start the training. And you can do this optimization with all the parameters that you have until you get a model that you like. And then again, with one click of a button, you can deploy it. Yeah, and deploying means basically putting it somewhere so that you can ask questions about it. And whether you do that in real time, like with one order coming in, or you had this BAX facilities there as well, if you have messaged amounts of BAX that you want to push for your machine learning model, you can do that as well. And so it might be that, for example, if you want to detect objects or locations or faces and things like that in imagery, you may pick a confluted neural network, K-MIS clustering is where you can use sort of sales prediction. That's what you want to do, or logistic regression. You pick just the algorithm that works best for you. The whole thing there is that all of that, the housing of the algorithms that compete the executing of it and all of these model management or things like that, you no longer have to worry about it in a new machine learning platform such as SageMaker is. So that's what SageMaker basically gives you. It takes away all the heavy lifting for you around machine learning to be able to execute your research. And of course I said, I want to put it in the hands of every developer, but not even every developer needs to train new data sets. Now, there's many occasions where, for example, you just want to do image recognition. And so you may have 1,000 images or 10,000 or maybe a million images that you just want to push through a standard model. And for that, we've created a whole set of application services for you. And whether there's image recognition or video recognition, all sorts of things that you can do on there. We have mechanisms for speech to text and text to speech and automatic speech recognition, text processing, all of these services are available for you without having to become a machine learning expert. Yeah, and so if there's any of these sort of of interest to you, urge you to go to ml.adw.us and you get all the details on actually how to get started there. I want to close this off actually by talking to about another customer that we have on the AWS platform. And this is an organization that I met last month with in Jakarta. And so they basically have, they're tackling one of the hardest problems there is, namely the generation of data. And how can we generate data that how can we generate data from let's say the poorest farmers in the world who may not even have an identity, who may not have a computer who definitely do not have a cell phone. How can we actually start generating data from that such that they get actually included in all sorts of opportunities for them? And so I'm very fortunate that I can talk about these guys because I think it's sort of relevant for your world as well. After all, the targeting rice farmers, not only in Indonesia, but sort of around the world, there's projects like this going on in Colombia, in Uganda and other places as well. So they built most of their systems around the technological blockchain. I'll skip that. Let's just say that that is an indestructible ledger that you may have. So anything you put in this ledger can never be erased anymore, which is important for identity, which is important for sort of tractability of data over time and really finding the lineage of that. So how is mission is to really try to revolutionize the agriculture sector with data and sort of try and find mechanisms and processes such that this data can actually be generated? And so if you look at sort of the challenges are huge in Indonesia. And so there is hardly any information available about the poorest farmers in the world and they're not able to actually really produce and have access to resources as are available in many of the other countries around the world. Of course, this is the things that I have on this slide is absolutely things that you on the room probably all know about. But much of this is actually driven around the lack of information and the lack of data available to any of the other players that might be interested in this. And so they basically created a system that consists of four different stakeholders. One is the data providers that is not necessarily the farmer itself it is most likely an agent that operates in the neighborhood or the village and who actually has the Hara app on its phone and actually collects all the data from the farmers does polygon tracking of the rice fields that they have tracks the yields of the crop and things like that. Then those data qualifiers that basically look at the data and actually validate that this data is correct and actually is in line with other data that you're seeing. And then there's data buyers and the data buyers in that particular case are for example banks and insurance companies. Now there's many of the farmers actually really have no access to financial resources at all and given that there is almost no identity there's hardly any information about the effectiveness of the farmer and so it's very hard for them to actually get access to loans. Most of them will have to go to loan sharks which actually charge something like 2.5% a month for them. And so given that now with all of these mechanisms they actually both their identity is created as well as sort of being tracked in their fields they now have the ability to actually get access to this data through the data sources that they provide. And now actually gives those data buyers the ability to start providing loans and microloans to individuals in ways that they could never do. Yeah, so these are the typical numbers actually the majority of them do not have a bank account mostly because they have no identity whatsoever. Many of them are actually have to borrow money and actually have to borrow money to actually be able to do their job. Now it turns out that working with these financial institutions and this data that comes directly from these farmers, these loans that are actually being produced is actually sort of the repayment on the loans that are getting the microloans that are getting now to these farmers almost have a repayment rate of 100% mostly because I think the interest rates on that are something like 0.003 a month instead of the 2.5 that the loan sharks are actually giving them. Yeah, it's also actually really tracking all of this that we had the high repayment rates make that sort of these data sets are becoming increasingly important for everyone in Indonesia because it really drives access from the farmers to things like insurance and to things like microloans. Yeah, this is another suddenly the whole issues of farm subsidies can be tracked because now suddenly data is available from all these farmers in an immutable way. So you really know that this data is actually data that has been generated by the farmer and not by anybody else. These farmers of course initially cannot be necessarily incentivized by sort of the future promise of a loan. Actually, they get incentivized through a loyalty point system which is actually really simple. Basically, you get a stamp card that every time the data gets collected by your farm you get a stamp on it and once you collect enough stamps you can actually use this to buy fertilizer and to buy farm equipment and things like that. So there is an incentive to actually start contributing this data that is actually immediately impacting farmers to today. So I think this is an amazing system of actually trying to use out of band mechanisms to start creating data sets that can be increasingly important for us understanding really how the poorest farmers in the world are actually farming their rice. And the same goes for the future idea of that. If we have this technology available it makes it much easier for these farmers to actually participate in IoT projects that may be creating actually data on an automatic fashion instead of having these agents running around drawing these polygons or looking at the crop yields. And so with all of that this new data actually combining with all sorts of other research data and satellite imagery now creates a whole large data set that is unparalleled in this world and hopefully can drive a whole lot in future work on the precision agriculture and the likes. And I think we're really proud again that at AWS we're able to support an organization like this that truly has access to that truly gives data access to everyone of the poorest farmers in the world. So with that thank you for your attention I hope you picked up something from this and I truly enjoyed being here. Thank you.


It's time for the Lone Gene Chronoscope, a television journal of the important issues of the hour brought to you every Monday, Wednesday, and Friday. A presentation of the Lone Gene Wittner Watch Company, maker of Lone Gene, the world's most honored watch, and Wittner, distinguished companion to the world-honored Lone Gene. Good evening. This is Frank Knight. May I introduce our co-editors for this edition of the Lone Gene Chronoscope? From the CBS television news staff, Larry Lassur and Winston Bredett. Our distinguished guest for this evening is the Honorable Charles R. Howell, representative from New Jersey. The Democratic Party is often called a party of the liberal North and the conservative South. Well, in times of victory, they've managed to overcome their sectional differences, but, of course, in the last congressional elections, the last election year, they did not. But, within recent days in the Senate, the Democrats managed to put together a front on a labor bill, which rivaled the days of 1932. I don't think it had ever been equaled since then. Now, Congressman Howell, what did that unity on that roll call vote on the killing of the Taft Hartley amendments signify to you? Well, Mr. Lassur, I think we have, for some reason or other, being technically at least in the minority now, got more party unity than we have had for a long time. And, of course, the example of the Senate voting solidly to recommit the Taft Hartley revision was the most forceful example of that. And I think there's a lot of that going on now, but I think part of that unity on that vote came about because different segments of the party for different reasons found it sensible to come to the same conclusion on that bill. The so-called Northern, perhaps pro-labor Democratic senators were afraid that whatever came out of the proceedings this time would be worse than the present bill. And many of the Southern Democrats and conservative Democrats didn't like the possibility of the state's rights business getting defeated and some other things getting added to the bill. So it was a natural situation for them to create a unified front on that particular occasion. In other words, you don't think it actually foretold a unity that would be one which would lead the Democratic Party to victory? Well, I wouldn't get away from that. And I think it was wonderful. But I'm not sure that it was completely that good. We had an ideal set of circumstances to bring it about on that particular vote. Congressman Hollow, the other day you told a rally in New Jersey that you thought the Republican Party was hopelessly split. Do you have any concrete evidence of that? Well, of course you got one very a bit of concrete evidence in the present hearings where you have two different segments or two different individuals in the Republican Party fighting against each other. You're referring to the McCarthy army hearings now. And it's Republicans against Republicans there and one wing of the party so to speak more or less against the other wing and it's not the Republicans investigating or trying to belittle the Democrats. And it is a Republican mess strictly. Of course that's the forceful example of it pointed up by the President McCarthy Stevens hearings. I think there have been plenty of other evidences of it on legislative matters where President Eisenhower, even when he has some fairly good program to send down to Congress, he finds that he has to, in order to get the support of the extreme right wing of the party, he has to either abandon some of his legislative program or water other parts of it down or or get it so that it is acceptable to the extreme right wing of the Republican Party, which is against most of his program or most of his worthwhile program. Well, incidentally, Congressman Howell, before the hearings took place on the army McCarthy dispute, you that that time called for the resignation of Secretary of the Army Stevens. Now, do you still feel the same way about it now the hearings have taken place? I have a lot of sympathy for Mr Stevens, and I think he's an awfully decent guy. But I think he did make some early mistakes there of placating Senator McCarthy by giving in and granting a lot of favors to shine that the ordinary GI would just never hope to expect. And that sort of thing isn't fair. I think he went too far with it. I can sympathize with him. I can understand perhaps why he did it, but I think he ought to have been able to stand up better than that. I think he's got a tough job and I sympathize with him in these hearings, but he actually didn't look very good then. And he hasn't been as forceful and effective witness and shown the real grasp of things that I would have hoped that he would have shown in these hearings. Do you think that this Republican Party split is reflected in our foreign policy, that it's weakened our leadership abroad perhaps? I would say it has. The old isolationist is applied to Europe crowd and perhaps they might be interventionist in Asia or the same crowd that's giving the president administration the same amount of trouble that they gave the Democratic administration previously. They almost seem to forget that they're in power now and then they're fighting their own administration almost as strongly and creating as much trouble as they did under the Truman and Atchison foreign policy situation. Will Congressman Howell in recent days vary as prominent Democratic spokesmen have opened up with rather vigorous attacks on the administration's foreign policy? And what exactly does this signify in terms of bipartisanship? Does it mean an end of it? I honestly hope not and I don't think many responsible Democrats would want it to be interpreted that way or would want it to work out that way. But I think there's been created here such a vacuum and things have been going so bad diplomatically that they feel a responsibility to speak out and I hope they are doing that in a constructive way. But I think most Democrats realize the seriousness of what we're up against in the world today and very much want to have a bipartisan foreign policy. They want to be called in more. They want more participation. They want Congress to have more information and they want to see a little more specific plan of where we're going and in the absence of that lately I think they've felt that they had to speak out on some of these things. Well I'd like to press you further on that now that Senator Lyndon Johnson has spoken out and President Truman against the administration's foreign policy. Do you feel that this it presages a final split with the president on his foreign policy program as we head into the congressional elections? I really hope not and I don't believe at this point it does amount to that. I think the broad foreign policy under Eisenhower is the same policy that we had under Truman and to some extent under Roosevelt. But the diplomacy has been weak. We've done things or haven't done things that have alienated or lost the cooperation of our lives in many parts of the world. We're almost down to St. Henry and Chiang Kai-shek now at this point and it's making it very, very difficult. But I think our broad objectives are the same as those of the Republicans and that with a little more consultation, a little more plan of action on the part of the administration, a little more agreement within the administration on what they're going to do that they'll find the Democrats back of them if we can find what to back. Sir, what do you foresee in this immediate Indochina crisis? Do you foresee that the United States Congress will have to take some action this year at this session with respect to United Allied Action or American intervention? Well, of course, we're moving pretty fast now with the end of Jambian Fu and the imminence of a really tough situation at Hanoi. Something has got to be done fairly quickly. It's just the responsibility of the President and Secretary Dulles to tell us what needs to be done. And certainly it's going to take, I don't think we can get enough out of the negotiations at Geneva to accomplish anything very much. The Secretary went there with very little in the way of cards in his hand and then he gave away one of them very early in the press conference before the Pali started. And I think just at this point we've got to decide how far we need to go. We can't afford to one by one surrender those important vital spots in Asia, or we're just starting a series of events that can only wind up in disaster. I think the Democrats, if they know what the policy is and the people are let in on it, that will be really available for help in the bipartisan foreign policy. Well, Congress, I'd like to get back to the home front for a minute and refer to the economic situation. Now, what would you Democrats have done if you had been in the past two years? Well, I think there are a number of things that could have been done fairly recently, should be done now. I don't think we're in a depression. I'm not one of the so-called prophets of gloom. But I think the Republicans have lost the concept that we need an expanding economy. They seem to be satisfied with a second best prosperity. And they don't realize that our population increases. More people come into our working force every year if we just went along and had the same economic level as we had in 1953. By 1960 we could wind up with 14 millions unemployed. We need increased social security benefits, a tax policy designed to give our economy a lift. We need greater unemployment compensation benefits. We need a better manipulation of interest rates and a possible standby shelf of public works, public facilities that could be put into action quickly if the economy shows more signs of slipping. Those are some of the things that I think they've been slow to deal with and slow to recognize. You don't seem to differ very much from the president in his program. Is there any possibility that you think, sir, of the president getting bipartisan support for his domestic program before the congressional elections? Well, that's much more difficult, of course. You've got a more serious sense of responsibility on foreign affairs. It's too vital to us and to the whole world. Economics, you can play a little more politics with sometimes, but without ruining the country, perhaps. But I think there's general agreement, but that the administration has just been a little slow in moving on some of these things even though they recognize the dangers of them. They've been sitting back and expressing the hope, the old prosperity, just around the corner philosophy and the trickle down theory. Both seem to still be existing today. Thank you very much, Congressman Howells. Nice to have you here tonight. Thank you. The opinions expressed on the Lone Gene Chronoscope were those of the speakers. The editorial board for this edition of the Lone Gene Chronoscope was Larry Lesser and Winston Burdett. Our distinguished guest was the Honorable Charles R. Howell, representative from New Jersey. When next you buy a watch, either for yourself or as an important gift, in all probability your jewelry will show you models of almost every make of watch that you can name at Lone Gene prices and even higher. Now, what's your best buy in this situation? Let's try and find out. 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And when I want to see it What's up my beautiful babes? How are we doing today? Clearly I'm doing fabulous. I'll be reacting to this video You guys have sent me a million times and have been dying for me to react to and I'm dying a wafcha girl I have seen the thumbnail and it looks interesting. Okay. It's called how not to remove purple shampoo bleach fail by Lizzie underscore three three three This wig is literally bringing out the sass in me. So get ready for this Get ready for this. By the way today's video is sponsored by dress lily. Thank you dress lily for being my sponsor You guys are the best So basically they were like do you want some wigs and I was like a yes always Like that even a question and they were like, okay pick up some wigs. I was like, okay Don't have to ask me twice, honey.  What do you wear? Are you at what are you at? They have affordable good quality clothing. They got phone cases. They got accessories or whatever and honey They got some wigs Okay, listen If you don't own a wig, I highly recommend it, okay It just makes you feel so alive all the links for the wigs I'm wearing in today's video will be in the description box Oh You guys know how it works. You know how it is. Okay. All right.  I'm a girl What happened to you as you got yellow roots? You got purple midsections and she's got some burnt hair A little embarrassing last night I wanted to wash my hair because I only wash it just for right now I'm only washing it once a week if I really have to then I'll wash it twice. She's great lips, Lizzie You got fabulous lips, honey I'm gonna tone just like the top of my hair and I'm gonna just tone it and then the rest of it I'll just wash it in the in the restroom like when I'm taking a shower. I'll just tone it with the purple shampoo So here I go. I put like a whole mess of purple shampoo on top of my head and you guys This is how I ended up You guys I love how so many people think purple shampoo is just gonna cure all their problems like no wrong It's not looking up Videos on YouTube like how do I move that strand like the over toned? Uh-huh. Oh, they like bleach it again. They were saying to use like ketchup or something, right?  So I don't know how but some girl use ketchup on your hair and it fixed it So I'm like, okay, I'm just gonna use it You know my wet hair and like hope it removes it She put ketchup on her hair No Like I didn't do anything. I left it on for like five minutes and ketchup. What is the logic behind that? I would love to know if somebody knows please leave a comment telling me what the logic behind putting ketchup on purple hair is I'm gonna wait for it to get a little bit When you pick up her hair and it doesn't go back down like this it just like goes straight out That's when you know girl. That's when you know you should put down the The color bowl and just never touch bleach again. Since I just washed it I don't want to like do anything to it today just because it's so freshly like It's just so freshly washed Good idea. Good idea. I think that it won't be good for my hair if I like do anything to it today She took my own advice So I'm gonna wait until tomorrow She ended up doing it So I'm home now. It's been all day and I'm f***ing ready to get rid of the purple And so basically What I'm gonna be doing is I'm just gonna be um I'm gonna try to remove this basically. That's what I'm gonna do. How's she gonna do with that? Hey guys, I'm so sorry Oh, no, she's putting more bleach in her hair No, no, no Watch it's gonna be like 30 volume to or like 40. It'll be like 30 or 40 volume She's gonna be putting that over damage Record so basically what I'm doing is since this part of my hair is like super wide already. I'm just gonna be like Putting a little bit of bleach on the ends. I know it's not a good idea She even knows Do this at your own risk. I actually don't recommend for you to do this. Hey at least she knows at least you know I mean if you are then I warned you You heard her she warned you don't do this at home So this side is already good But then this side is already so I want it to look even obviously because I'm not bleaching my hair for nothing But I don't want to bleach it again.  Not the worst I'm actually kind of living though. This wig actually sits so well on my head Like I literally did nothing to like customize this yet and it already looks so real It looks like it's going out of my scalp Honey that is how I like my wig. Let's continue the video Oh She could have just gotten away with doing a bleach bath Which is when you mix a batch of bleach that's not very strong like 10 volume or something and you put a shampoo in it And then you just rub around your head and it'll just take that purple edge off And it'll get rid of just the purple and it'll leave your hair nice and blonde again so Lizzie If you want to do this in a way easier way you could have just done a bleach bath For like 10 minutes.  And I'm just gonna apply it however Oh my god, it's literally fried to death Like I thought the last video I watched the girl fried her hair off But this looks even worse I wish he told us what she was using I'm pretty sure this is t8 well a t18 toner Which is a permanent hair color, which is extremely strong and is going to give her hair More damage and also her hair is definitely gonna turn purple again Because her hair is so porous right now.   Oh my god I'm getting chills right now So I'll just check in with you tomorrow. I'm back. These baby hairs they put in here are set mashed up It's Friday Yesterday, I dyed my hair. Yeah, you did. Actually I did it.  Yeah That's right I'm just trying to stay positive. I'm not really how to grow.   I can't even come I Like I don't even want to touch it because it's like breaking off But I'm like, I don't know if I should just wait like maybe like Next week and then just wait for it to like kind of heal a little bit more You can make your hair feel better and look better with products, but you can't actually bring it back to a healthy state Physically So you can make it feel better, but you cannot really bring it back to health Well, let me just check if she has an update video, um Oh, yeah, she does.  It's still even like on her head I'm shook I'm literally like shaking Quaking shaking looks so much better. Lizzie Oh Looks good So basically she's doing this apogee treatment and we're about to see if it made a difference Remember last time I don't know if I mentioned this to you guys, but my hair was not drying I literally have to take the hairdryer and dry it myself the other time right, but this time I'm actually my hair actually dried it dried like Barely like a wow 12 wow, I'm sorry. I'm just like really Really bathroom by this I'm surprised it looks so good And did a little bit of curls like not really that much, but this you look so good girl You have come a long way honey and Lizzie. Hi. How are you? Do you watching? What's up? Your hair looks so much better. I'm so happy for you Also, you should try using olaplex. Um, I never used apogee apogee I don't know if that's you say it but like I never used that treatment before It looks like it did a great job on you but definitely olaplex They a lot of people use it and I use it on many clients and it's brought on their hair Closely back to life not quite back to life, but like very close to it. All right, you guys Thank you dress silly for sponsoring today's video if you guys want to check out all the wigs that I wore in today's video They'll be linked below for you, of course Don't forget to live your extra life like as extra as I am today And I will see you all next time. Peace


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Yeah, we're not I'm not gonna be doing anything I'm talking to y'all I just want to come on and do a quick chit chat since I've been watching a lot of TV and Maybe I'll put on some lipstick while I'm talking y'all Yeah, I wanted my skin to look like Holly Barry Haley Berry when she was doing an interview with Oprah after Eric Benet cheated on her I was like And she was in her I think she was in her 30s when that happened when she was on that end She did that interview with Oprah. I Zoomed in on her skin because her skin looked like butter It was so smooth and often times when you are fairer skin is really hard to get that consistency smooth You she have you can see all the imperfections with lighter skin, right? Her skin Looked so beautiful there. Yeah, I'm trying to work at Lee So I've been trying to be as consistent with my regimen Cutting back on certain foods y'all really honestly truly What you eat and your lifestyle definitely shows up in your skin So been cutting back on eating out because we were eating out a lot when the Coronet thing hit we were eating out a lot And so now when I do eat our order in I try to do something like salad or something like that Anyway, y'all enough of that. Um, that's been going on Y'all look at my nails now that one looks a little right whatever but look at how great my nails look you guys Look look at how great my nails look you guys You know, I gotta do a little bit better on this one But overall and this is just using dip powder now This was a feel but baby it took me a good 30 minutes Just to get that gel off because I had that bright color gel on the The red color reddish pink it took me forever to file that off and typically when you go to the Nelson line They use the drill. I'm gonna have to buy me a drill. It took me 40 minutes just to get that Because I put gel on top of the color powder my sister told me not to but I had to because it was so cute And I did that so I did the same thing here But I went lighter so hopefully won't be as bad But yeah, I added a drill a nail drill to my Amazon cart Because I'm not gonna be doing that every two weeks, you know filing filing filing filing down I think I lost some length or something. I felt like I lost some length Maybe I went down a little bit too low when I was falling across, you know, but yeah, very cute I did get my clear acrylic and so I made I made me a couple of DIY Colors, I'm not sure how it's gonna turn out, but we'll see Um Amazon is getting my on my nerves Amazon change the format of that but they were like we sick of y'all ordering shit So we're gonna confuse you sick of y'all ordering so so we can confuse where to find your inbox Oh, I found it. You at the bottom. I found you. I found you Amazon so yeah, I Have I'll order like I said those supplements a couple of days ago and I rushed that so it came in yesterday then y'all ordered I ordered some Shapewear by made in form and I ordered two types.  Well, I'll speak on it in my vlog. I'm gonna load this up on my vlog. I Spoke to a manager at one of their restaurants We frequent out here and he told me all about what they're doing to encourage social distancing But he also said, you know, we're not doing too good right now. I'm like, what do you mean? He's like, we don't have that many people coming in so that would benefit us He basically basically was like if you get here early on time, you'll probably be the only people here I'm like even better most of their Client teller patrons or 60 and over whenever my husband I go there when we first started going there eight years ago We were laughing because we were always seeing youngest people there I mean always and still today when we go it's a sea of gray heads gray hair everywhere But because of that a lot of the people are not going out because they are considered high risk that population. Okay, so Speaking to the manager speaking to my husband. I said, okay, we'll do it We'll get a table at the far back. We'll take JB with us JB has been here before y'all JB I'll get to JB in a minute my poor baby Um, he's been there before he'll be good. So yeah, we'll do that. Um Girl JB swallow. I know I'm doing this out all of order you guys so people we talk about youtube TV when I'm watching the person life.   I'm like, what what do you mean swallow a Lego? Girl, I'm in the middle of watching claws and you swallowed a Lego. So I'm like, oh my god So I could immediately go on and see okay. What do you do try to call my husband? He was busy So I told him I said, oh, well you're gonna Girl, what's that noise? I said, oh, well, you're gonna have to pass it tear started flowing He started getting scared. He started crying. He cried. He must have cried for a good 10 minutes about that I said baby, you will be okay. Just show me what the Lego look like It's one of those really small Legos. It's like You see this makeup brush here. You see the tip the Lego bit the Lego is that small So it's like the size of an eraser head even smaller than an eraser So I said you'll pass it. You probably won't even feel it or whatever But I think he's kind of he's still scared poor baby.  You'll be okay You'll be fine if I need to give you some medicine if your stomach hurts. Let me know Um, so yeah, he'll be okay. I just have to monitor to make sure it's fine I said you better be glad it wasn't a big one.  He's biting them off Don't do that because they're all together. He if he can't take it apart. He'll bite it to He learned child. Um But y'all, yeah I'm normal of the place getting my skin together I am going to do a formal video video on the what is it the good molecules line But y'all I've been using all different types of stuff. I've been using ordinary I purchased these uh deep pore clencers by vior they were on sale for like 99 cents. Um I've been watching a young lady named golden rx.  Y'all know how long that is So one of the things I do I don't wash my face for 60 seconds, but I do Cleans for quite a bit of time. I mean I'm in here At least 30 seconds 30 seconds and I I cleanse with my hands. Okay. I make sure I wash my hands first I cleanse in my hands in a circular motion I use a bar cleanser. I mean, I'll get it all into detail, but my skin I'm trying to clear up the different spots, but I started I have two lines going across You see them you see that one now watch when I do this it disappears going across here I know y'all like we don't see shit, but I do Okay, so anyway That would be a separate video coming in I'm so itchy All right, y'all.  So I'll put just put some ointment on it. So anyway, y'all Um, so that's what's going on with personal stuff personal life um Like I mentioned it. Well, I will be mentioning in our blog where we are officially done with school and JP's like for now and I know he's just seven years old. He's like, I'm okay to be homeschooling to high school I'm like, okay Well, we'll talk about that when it when the time comes but I officially let my manager know that I will be homeschooling and she's like he was just an older woman. Um Her youngest child is 21 and she said, you know, honestly, if we were going through what you guys are going through We're strong like children. She said I I would homeschool too. Um, she lives in Detroit, but they used to live here in the valley and y'all I She said that with her son that he was just uninterested in school She said they had problems with him some of the same things that we've been experiencing with JB as far as um, the school thinking that there's something wrong with him. He's slow, but we're not sure but and then JB doesn't come off as overly eager to learn And so it makes it seem like there's something wrong with your child. I'm really that's nothing And what they ended up doing was switching their child her her son to a different school that that Taught the same curriculum, but in a different way and I say girl, we don't have time for that We just gonna pull them out and go ahead and proceed. So, um, I'll be talking about a little bit more of this in my vlog But there are going to be some very interesting changes for the schools in general and y'all I am not going to be down for that which is one of Besides the issues we were having at JB school prior to the coronavirus It's going to be very interesting and how things are going to be and from what I understand It's up to the school district or the school to implement those changes. So anyway, enough of that you guys Yeah, let's talk about some of these youtube streets. I've been looking at a lot of different videos Um for what I want my style to look like if we do decide to go out to eat for my birthday y'all We were planning on going to california because I will be turning 40 this year Um, I was I was supposed to be in the middle of planning that Like this week we were going to go to the beach mission bay Had everything planned out going to sea world But hey, it is what it is. That's all been cancelled and we just decided to celebrate at home So I will be having like a completes to help me to feel better. So I'm like, you know, I have health I have wealth quote-unquote meaning like wealthiest for as healthy and sane Sometimes mentally stable um We are blessed to be we're financially blessed and so I am looking at what we have as opposed to what we don't have so when I can't go to california for my birthday Celebrate at home. Okay, so I did reach out to y'all a couple of weeks ago through the community The community tab excuse me to see how those of you who are at home How you're celebrating to and I got a couple of responses. Um, so yeah I'll be at home.  So there will be a birthday giveaway lifestyle with items from welfare I will be trying. Oh child I have stuff coming in right now and I'm gonna show you that's something that came in I will be attempting Too flat out my hair. I am so sick and tired of searching for A video for 4c and I pull it up. You clearly are not 4c Now the young lady or woman, uh, whoever are not mentioning 4c in the title But the results i'm getting back or 3c or 4a I need to see someone who has samuel l jackson's hair type. That's what I need So I probably was able to find four or five young women who Legit had four type hair or I'm looking for 4b 4c. That's what I'm really looking for. Let's just be real I'm just getting some advice and thick hair. Okay, so um Been looking at a lot of those videos So one young lady showed she had long hair and she had four type. Oh, she had a lot of hair One young lady showed herself using a detangling comb with this attachment Because what you want to do is you want to chase it use a chasing method. Okay Um, I'm just okay Got that I went ahead and purchased a new flat iron titanium. Okay titanium is better than ceramic I do have a ceramic in there, but I did see a video of nezzie naps and she Blew out her hair and she flying on her hair. She said it took her like six or eight hours She said she started doing her hair earlier that morning and it was like seven o'clock That's what I'm talking about Anyway, I see all that to say An attempt to flat iron my hair. I will more than likely wash Child I will wash and blow out my hair the day before because there's no way I'm I will be too tired to blow Yeah, this is serious I need a drink. I will more than likely blow out and wash my hair the day before And then the day of I will flat iron my hair.  It's very dry. Um, I will be using the Fantasia's heat serum Um, and I'm going to be buying the can-to heat protectant spray I wasn't sure if I wanted to buy that or the design design extensions Let me know y'all which which if you fly down your hair and blow out your hair What is your favorite heat protectant? Okay Miss or let That's not used actually. That's a lot. She uses a serum But she doesn't do a leave in she doesn't do anything and baby when she she's only fly down my hair once now She blows she's blown up my hair several times when when she blew up my hair that one time My hair was laid and she's one of those types that can fly down it and curl it all in once one pass done It was so bad. Y'all it was so pretty my husband could not keep his hands I had to take like three or four birth control pills that night are already about 20 minutes into this So yes youtube looking at straighten in hair videos. I'm also been looking at it. Y'all I've seen this stuff about doja cat I've never really was a fan of doja cat um, I feel like doja cat is one of those biracial women who Turns on turns turns on and turn off Her blackness when it is convenient for her she has since apologized for some of the stuff Let me do let me say this I did see like two or three of those videos that she made I didn't see anything racist about those particular videos both for when I understand there are several other videos I do think that the young lady has some serious self-esteem issues Because she's looking for validation from complete strangers Um, and when she can't find it and just being her normal self It becomes sexual because man, of course if you do something sexual You have their attention right there. So she was performing several sexual acts You know or emulating sexual acts on cam Before when I understand she's never met her father who was South African Um, she was raised by her mother who was Jewish um But yeah, I understand that she has since put out an apology. I feel like the apology was fake I saw some bits and pieces. I didn't see all of it. It felt forced girl. That was a pure that was all I smelted public relations all over the apology I don't think that she would be counseled this counsel culture girl, please I don't think she would be counseled because she has so many fans That are of different ethnicities races or whatever you want to call it And so people would cancel her for a minute and then they would be out mopping her song But her music later on I do find it very interesting that she all of a sudden went from like I mean, I get it. She's been in the ram for a while. It wasn't she unwounding out for a minute, but I don't know you guys feel about these celebrities and singers who go from Literally basement music to now their number one of the charts are in the top five. I just don't see that Working your way up model that we typically would see with 2,000 artists or or You know people from the 90s. So anyway, enough of that Does you can't that's all I see seeing a lot of that whatever, um Yeah, let's talk about tv because I know my baby's back there. Let's talk about tv girl I'm back to watching claws. I finished watching clause three Now I'm back to watching clause two because I didn't watch all of it now claws two is the one where she hooks up with um um The the the black guys he from siri seary Leon you guys or libya The black guy that played it back back girls the um tall african y'all. I don't think he's good looking He looks weird to me. You know, he's fine From the neck down. He's fine as hell. Yes, but he's not He's not attractive to me. Is that possible for you to be sexy and not attractive I think he's sexy, but I don't find him attractive at all So anyway back to watching season two with the crazy russians and they're not really russians. Is that amazon prime? you need to Amazon prime just flew about here. Anyway, y'all so anyway Back to watching that love net finish good girls. I know I said I wouldn't There was no scenes with rio and bet None, thank you girl for telling me it was on hulu because I got tired of pan pan for it There were no scenes no smothering sexy Thought scenes with beth and rio. Now. There was some chemistry still, but no real scenes. Okay So anyway done with that. I started to watch sweet magnolia on netflix. I like it y'all is good clean rated pg 13 show I'm surrounding three friends. I think they were Childhood friends in this small southern town They want to open up a spot and that's all I'm going to give you in case you want to watch it I'm on episode three and I like it. It's very sweet. Now. It's a little too sweet for me So I have to stop watching it and watch mine honey I had to stop watching it and watch mine hunter y'all my favorite genre besides Postalipsic into the world which I'm not watching right now because I can't handle it I like dark I like dark thriller Give me black spot. Give me dexter. Give me some comedy mixed in that. I could take that which is why I like I like killing eave So I did watch mine mine hunter gotta me Give me kissy You can sit up there go get your toys and come back in here. Okay. Go get you some toys I did watch mine hunter you guys and I know a lot of people like to compare a mine hunter to true detective There's no comparison none True detective text at all And I guess for me mine hunter was a little predictable I have a dark side and I already knew about a lot of these serial killers. I mean even before Like I would have to honestly say the first time they show The btk killer. I already knew who he was I just by the way he was looking when he I already knew because I'm a little crazy And so I I had that moment or I have moments where I would look up serial killers for a while Just research them and look at different documentaries or whatever to the point to when b2k came out the r&b group I was like, why did they choose a name that's very similar to a serial killer? So I couldn't really dig with it. I'm like, why do they have a name? Y'all know with a marion and I'm like, why do I have a name so similar to the man who I can't see it off So y'all I tried to watch hollywood on netflix not doing it too much sex I couldn't do it. I couldn't do it y'all. I just And it looks like it's good. So if you can hang with those type of scenes like every episode Go right ahead girl. How to get away with murder when I tell you I cried and bawled like a baby spoiler alert I watched the last three episodes Y'all why did they do that to frank? The finale that was seriously one of the best finales I have ever seen I still didn't like mckay left the end But I think about the finale that finale was was awesome. Amazing.  What are you? But his eyes his eyes were glazed over done and y'all I'm so sorry I for some reason I kept seeing that frank plays in the walking dead. That's not him That's not the actor that guy's like 52 the actor who plays frank is only 40 something.  Frank is one of them.  He's all itchy scratchy. Um, I did add Blood water is it blood and water? I added blood and water to my list and the five to my list And I'm gonna watch those now y'all one thing I didn't talk about and I really not gonna get that much into because my son is right here by me, but I did hear about Unfortunately, um, what is going on with with me the popular youtuber natural hair youtuber natural 85 I was on facebook a couple of a couple of days ago and I saw some screenshots and and the uh, One of the hair groups that I'm in and I'm like Why y'all playing like why y'all? And so I did a little bit more research Child I cannot believe that I can't but I can't the audacity Now only thing I want to say is this from my understand she has been with or had been with Felipe since or known him Well, she officially with her since she was 15 years old That's a long time. I don't know how old she is now, but that's almost what 20 20 plus years. It's a long time um I don't know how I feel about very young people getting together and getting serious because I feel like you haven't had a time to live Figure out who you are as a woman or a man Um, doesn't mean you got to be fottish that that's not what I'm trying to say Now that he's not out of here We'll go into what allegedly happened and she did share this wasn't on twitter you guys when she shared these I don't know what they she had several posts. It's like 10 of them. So apparently they've been separated since 2019 Then went to therapy did what they're supposed to do as a couple Uh, and let me say this. I am all for marriage. I'm all for love I believe in rekindling even when you broke up even when you have divorced I respect the the covenants of a marriage. Is that a word? I respect that I you know But I will say this if you are unhappy if you are being abused if someone is draining you so sucking so You know you have every means to divorce and biblically sounding or if we want to go there This is one of those reasons why because apparently he cheated on her Girl and he cheated with her on her with one of her subscribers What I read that I was like what in the I wish my husband you know what do you know how hot fish oil can get you Okay, and all seriousness I'd like to add this bit of information you guys because apparently Felipe has came out on instagram live Which he has since removed the state that he'd never cheated on whitney now I'm not sure what his definition of cheating is However, whether it is emotional or physical cheating whitney felt like she was cheated on another thing that i'm kind of Kind of getting that or or a feeling i'm grasping for him Felipe is that he comes off as very toxic and narcissistic because it seems like he's been shifting the blame on whitney Um, but you guys at the end of the day again, this is all my opinion at the end of the day We have no idea what happened behind closed doors. We have no idea what happened in their marriage I just hope that they can get through this for the sake of their children And that whitney can find some peace at the end With a subscriber So he had been in several different subscribers Message box boxes, you know DMing these women her followers her subscribers or whatever because she has a lot of people who follow her Y'all she has a what a million subscribers on youtube So I have a feeling that this is probably Again, this is my opinion. This is not factual. Let's get that out. I'm not trying to be soon Let's get that out there. I have a feeling that this is probably not the first time And what I was trying to say earlier is that I really do think it's important for young people to Not necessarily find themselves But to be out in the world a little bit before you get serious in a relationship Because how many adults do we know grown-ass adults who have Experience still feel that marriages and all this. I think that's a little too young You know to be with someone since you were 15 and this is coming from someone who's moved I've been with my husband off and on since I was 20 20 or 21, but we broke up We didn't even get serious until these last 10 years Um girl and we went through a lot, but we weren't married I had the opportunity opportunity my my uh The person I was with before my husband proposed to me and I was at that time I was barely eight. I was like 17 18 even my young mind at that age. I was like, no I'm not going to get married at a teenager. Basically. No, I love you and I loved him I really did but I wasn't trying to get married. Um I know that Whitney has spoken on this several times, but I I think that she suffers from Self-esteem and I can only imagine what this did to her Uh, I believe she was she bullied in high school to you guys? Um It's just sad. It's a sad situation and like I said, I am all for marriage I'm all for love and rekindling that love but I feel like You know, if it if it's Something like this where it is a loss of trust and you have tried Go through your divorce and Just you know, try to be at peace with it She had wrote in one of these screenshots. I saw that they did try to seek count seek counseling But it's so hard to rebuild that trust you guys, especially if it's something that has happened more than once Again, no one has said it's half. I just have an inkling feeling that it has happened more than once Um, it's just really sad. I feel really bad for her children too. I don't watch her Vlogs even when they were very active. I didn't watch them as much as her hair videos. Um Girl, but a subscriber one of the posts it said is a subscriber who loved a subscriber who loved me Girl, how did you know she looked?  I mean if you if you have a family You know Channel that's different But just to bring my husband on and to just do my husband does my makeup My husband rates my clothes What for I'm still fat. No, we're not doing that. Okay, not on not on this channel. We're not doing that Um, keep your husbands off the channel y'all keep your husbands out of your Keep your family a little bit separated from if you have a business like this This is why I absolutely admire what's the young lady's name prior uh, perla girl The names again for p. She's not she's Nigerian Child she showed up with a whole baby. Her baby was like Her baby was like eight months old She did some Beyonce. She just showed up with a whole baby.  Keep it separate. Don't keep everything.  You stay focused. You don't have to worry about anybody But let's just be real if the man wants to cheat. He doesn't need to be on social media to cheat too I'm just saying, you know something very simple similar happened to Uh, what is her name mommy tang?  I think mommy tang not older But youtube age she is she's 42 43 She did a four part Storytime and she's really good at telling stories on how she met her husband And she admitted that he was a player He was a playboy back in the day, but she met him online in college and he chose her apparently right Well, when soon as she showed him and she she started easing up the almost there were says, how do I say it? Um Mystery to who who he was because she would sometimes she would show a shoulder She would just show a profile. So you never really saw him child as soon as she showed that man. He's fine Oh, yeah, he's fine as soon as she showed him I always had oh These young girls started getting in his DMs and that's what happened to them They are divorced. She finally announced that they've been divorced for a while For when I understand Whitney is not divorced. They are separated, but they are working on on the divorce Right now status really sad.  Um marriage is not easy My husband I make it work. Um Like I said, he gets on my nerves a lot and that's the thing too I think that a lot of younger people who get into a marriage It's a roller coaster. You have your right those you who've been married ten plus years, right? It's a roller coaster. It goes up and down up and down right now.  It's difficult not everybody can do it but keep God first, you know pray over your spouse and I think all things is possible What I find funny though sometimes and because I told you why I mentioned that You know, I think that younger people should date not again. That doesn't mean going out and Uh making it clap for everybody.  I don't think that is that is very irresponsible I do believe in soul ties And y'all it has been science. We ain't gonna even go there, but it has been scientifically proven that Energy especially if you're not using protection There is some transferring of not just bodily fluids, but of energy when you have sex with someone Okay, this is how soul ties are developed. So I think it's Okay, baby. Hold on.  I really am and hoping that they can get through this. So, all right you guys take care


Hey what's up you guys welcome back to my channel if you're new here hi hello and if you are new here make sure you hit the subscribe button and join the growing family Today I thought we could talk about medication So I follow someone on Twitter who has decided they're going to stop taking the anti-epidemic medicine from a vending the vaccine Even if you miss a dose of vending the vaccine this side effect is on I can't believe someone actually is just decreasing the dose on their own and dealing with the side effects Because the side effects of vending the vaccine are horrific if you miss a dose Now I used to get to take my medication when I lived on my own or I just didn't take it Which is what lends me to being so ill so taking meds is good The thing that gets me about with people stopping taking their meds without seeing the consultant Or even speaking to a therapist rather is there was part of the medication for a reason That was an attempt to try and help treat your mental illness The reason this person is stopping them is because vending the vaccine lowers your sex drying And they missed that part of their life But at the same time you've got to realise that you're dealing with depression as well And she's already saying she's depressed coming off it As long as you continue to stop it But when I used to miss doses of vending the vaccine it was brutal It made me feel really shaky, my blood sugar would crash I'd be crying, I couldn't control my temperature I felt like I was going to pass out They're just not nice side effects Now I've never bluntly stopped taking a medication I've always taken most of the time all my medication as a prescriber Because I believe my medication works I believe it's about trial and error I think what this person should have done instead of just stopping taking that as a depressant They should have said to their prescriber They don't want to take it anymore as to something else they can try Because a lot of it deals with the depression and the low sex drive And I'd say this to everyone With all the research I've done All my lived experiences Other people's stories Please never stop taking your medication without speaking to the prescriber You have prescribed it for a reason It's important to understand that maybe you do need the medication to help One medication I needed to come up with quite quickly was to put a tie-up in Because it was horrific But I stopped that when I started on how a parallel There was no crossover that I stopped As soon as I got off the tie-up you know I was part of the helicopter at all In the last 10 years I've never had a break in what I take I've never been off medication I've been on medication for over 10 years And that's okay I needed it to get through a state of life I'd take an anti-psychotic, I'd take a mood stabilizer, I'd take a meds depressant I'd take a sleeping tablet I'd take benders Medication I'd take for a reason And this is what I've explained to my GP about the connoisseur Connoisseur-Pam, antidepressant killer Because my psychiatrist wants me to come up with it But my GP is sat and listening to me explain why I need to be on it The reason I need to be on it is because it's the only thing that controls my anxiety I've tried b-sibling because it's my anxiety, they made me ill I genuinely think that connoisseur-Pam is what keeps my anxiety calm Taking it twice a day I take it midday and I take it at night I wouldn't mind stopping the nighttime one Because I want a sleeping tablet But I don't want to stop taking it completely because it does really help me And people are gonna say you're addicted to it You're now addicted to it Whatever I'm not addicted to it I can go without it and I have gone without it I've got to go without it Friday Just don't do anything to your medication on your own I really wouldn't rise against it So yeah, that's all I've got for this video If you are new, subscribe I hope you enjoyed my little ramble about medication But yeah, let me know what your thoughts are on the subject Leave it in the comments down below And I'll leave it and we'll get back to you Got any questions you want to ask? Like anything if you can be anything about mental health Or just general, I'll make a video answering your question Thanks for watching and I'll see you in my next one Peace