Daily Tech News show is made possible by you, the listener, thanks to all of you, including John Atwood, Pat, Mike Cortez, and everybody welcome our new patron, Sam! Welcome, Sam! On this episode of DTNS with so many tech layoffs happening, what are tech workers planning to do? We talked to two folks who recently lost their jobs about just that. Plus, a change that could make LLMs much more reliable, and whether open table is being fair to its reviewers. This is the Daily Tech News for Friday, April 12th, 2024. In Los Angeles, and anywhere I am, I'm Tom Merritt. From Studio Animal House, I'm Sarah Lane. From San Francisco, I'm Nicole Lee. From the Bloc Montchanteau in British Columbia, I'm Veronica Belmont. Oh, drawing the top tech stories in Cleveland, I'm Len Peralta. And it's me, Roger, the show's producer. Oh my gosh, Roger, good job bringing all these folks together today. Well done. Wow, good stuff. We have a lovely panel today. Thank you, Nicole. Thank you, Veronica, for being with us. This is lovely. Happy to be here. Me too. We begin with a serving of the Quick Hits. You might ask yourself, is Google shutting down a service, even really news anymore? Well, in case it is, Google says it will remove its VPN service from the Google One paid subscription plans, because, quote, people simply weren't using it, end quote. The idea is to let the support team focus more of their time on in-demand features. Google didn't give an exact date, just said it would go away in the next few months. The VPN introduced for Pixel users on the Pixel 7 will continue, though, at least for now. China's Ministry of Industry and Information Technology is directing Chinese telecoms to remove foreign processors from their network equipment by 2027. So, you know, Intel, AMD, that kind of stuff. Locally made chips from Huawei, high-silicon, high-gon IT, and the National University of Defense Technology have improved enough that telecoms have begun to switch over for other reasons in many cases, and that has given China the confidence to require them to switch over. China accounted for 27% of Intel's revenue last year and 15% of AMD's, while it will still be able to sell chips to Chinese companies for other uses. This is just for telecom use. It will certainly have an impact. And China is attempting to restrict the use of foreign-made chips in other cases as well. The U.S. Cybersecurity and Infrastructure Security Agency, or CISA, is investigating a breach at SISENS, which, among other things, makes a dashboard to monitor availability of third-party online services. CISA and SISENS recommend customers reset their credentials shared between monitored services and SISENS products. CREBS on security sources say that the attacker gained access to an Amazon S3 token through a GitLab code repository. It used the S3 server reportedly to access millions of tokens, email account passwords, and SSL certificates. That would let the attackers appear to be validly logged in users of any third-party service attached to SISENS dashboards. SISENS has more than 1,000 customers across financial, education, healthcare, and telecommunications services. Kind of an nightmare, to be honest, for the folks who have to deal with resetting all those credentials. The conversation has an article out showing that weather predictions have been getting better, not worse, despite the fact that we humans generally focus on the failures rather than the successes. Improved accuracy is not 100% accuracy, but it is improved. According to the Met Office in the UK, a four-day forecast today is as accurate as a one-day forecast was 30 years ago. And even more important than whether you should wear a raincoat, meteorologists can now accurately forecast where a hurricane will hit up to three to four days in advance within 50 miles or less. And yes, you all can remember that one time that that was wrong, but now try to remember all the times it was right. You probably won't, since that's not how our brains work. But there are a lot more right predictions in weather than mistakes these days. Good to remember. Well, my weather app says it's going to rain in LA tomorrow, so... We'll find out. We'll find out, won't we? Yeah. That's fine. It's still April. It counts. Paramount will shut down its standalone Showtime app on April 30. Showtime is now included in the Paramount Plus tiers of subscriptions and can be accessed through the Paramount Plus app as well. This is similar in approach to what Warner Brothers did when it merged HBO into its other services to create what is now called Max. Max. Alright, let's talk chatbots. Let's do it. META is testing its large language model powered at chatbot META AI on WhatsApp, on Instagram, and also Messenger in India, Nigeria, and some other countries in Africa. India is META's single largest market. A lot of you might not have known that before, with more than 500 million users across Facebook and WhatsApp. And is the latest in the march of AI tools being released to the public around the world. So as we all get more access to more of these tools, it's worth noting that how they work is changing. I did an episode recently on Know a Little More about chat GPT. And if you heard that, you know that I described that large language models work by basically predicting what the next word or next pixel in image generators is going to be based on what it has been trained on and what has come before in the sequence. So the prompts or anything else that's said so far. The professor of AI at University of Bath, Nello Christianini has an article on the conversation about how that may be about to change and make chatbots more capable. Open AI's GPT 5 and Meta's Llama 3 models are expected to have the ability to plan ahead. So not just predict the next thing, be able to have a goal in mind. Say, oh, we're headed towards this. Let's figure out how to get there. Google DeepMind famously developed an algorithm that was good at planning ahead called AlphaGo. That's the one that beat world champions at the game of Go or Botic. The idea is to incorporate the planning element of an AlphaGo into LLMs and replace the predictive or autoregressive element with planning. This would mean a chatbot might understand that you have an end in mind and can help you reach that end. Current LLMs have no conception of what your goals are. They are just making predictions. And if that plays out in Meta and Open AI's next models, which is what it sounds like it might, you will see a big improvement in what they can do.  I am curious, Veronica, as someone who has followed chatbots and even worked with chatbots in the past, you know, this seems pretty optimistic. What do you think of this? No, I think this is a fantastic sub-forward, I would say. I think some of the main problems that we have currently with these tools are particularly AI not only just using predictive text and kind of generating sentences. And we've called them around the house just sentence generators. It's unfair even to call them AI at this point in the game, but the term has become broadly accepted as such. But also the fact that it has a hard time remembering things. So if you try to start a conversation, it starts hallucinating, as you mentioned. It doesn't really remember much about who or what you are. I know that Open AI is trying to add some more tools and features to help prevent that moving forward so that it does actually remember your goals, what you're trying to achieve, who you are, your preferences. And I think in order for us to kind of get to that next step, it needs to be able to do that without having to send the conversation to itself repeatedly over and over again, which is just a huge technological issue I think that all of these companies are dealing with right now. Yeah, Nicole, I feel like a lot of people don't even realize how LLMs work now. And so they may just look at this as, you know, oh, it's going to get better, but it would be a fundamental change underneath, right? Yeah, I think so. Like you mentioned, do moving away from just purely predictive to, you know, actively planning things out, that would probably veer more towards the artificial intelligence end of things. But, you know, I don't think we're quite there yet, but I think this is obviously their attempt to do so. Yeah, I think about one of the obvious examples, you know, when people are trying some of these tools out is like, you know, let's try to apply for a job, right? You know, like help me with my resume type thing. It's like, well, if an LLM knows that you want that job, you know, what does the output look differently like with, you know, some of this new technology that we're talking about now rather than just pure predictive you know, finishing your sentence type style. That's a great question. Yeah, and I've actually, I can say from experience that I've been doing just that because I actually taught a I created a personal GPT to help with resume and cover letter creation. And so it does actually input, you know, I can input my resume, but it doesn't remember that from session to session. And I think that's one of the difficult things is that it should know like, okay, this this resume was successful, like it should ask me for updates or it should just know automatically like, okay, you you submitted your resume and cover letter to to this role. How did that work out what worked about our edits and what didn't being able to learn from these experiences I think are really going to be game changers and how these actually work to help people in the different tasks. I think we also know that these large language models when they're very when they have a broad set of things they need to do they don't perform very well when they're much narrower much more vertical than they perform much better. And so having these specialized tasks that they can train very specifically on I think is also a really good use case for these these personal LLMs that open AI and other services are starting to create. We hear about Sam Altman and others Johnny I've creating a hardware device that's supposed to be like a personal AI that will learn all about you and be able to come with you through different experiences and times in your life. And I really think that's the next step is having something that's trained very specifically on very specific goals and requiring specific outcomes, while also still being very smart having all of the information of the Internet available to it, while also retaining your personal information and staying secure. That's all we asked. Just those little things. Yeah. Yeah, it's easy. Small matters. What's the problem. Well, let's talk about restaurant reservations and why OpenTable has ruffled some feathers today. OpenTable said in an email to members Friday that starting on May 22nd all reviews on the platform will now show and members profile picture if there is one and first name, even if the past review was sent anonymously and posted anonymously, OpenTable says that the change was made to provide more transparency in its review system, and also says that diners have contributed over 136 million reviews on its platform sharing dining experiences as good and bad with other members. So it's a pretty big shift to go from you can be anonymous if you choose to you could be pinpointed at a location based on the date of review or your name or both. Now, we all have lived in San Francisco at one point. Nicole, I know you're still there. So I'm going to go ahead and guess we've all used OpenTable at least once or twice. I actually logged into my account earlier and I was like, Oh, yeah, I haven't reviewed anything. But I mean, I, I, I last used it in 2019 got a reservation at a table. Some folks very unhappy though about the retroactive part of this saying going forward. Okay, terms have changed. But if I left a scathing review or even a really positive one and I chose to be anonymous, I have a problem with that being linked back to me. Nicole, what are your thoughts? As you mentioned, the retroactive part is problematic. And I mean, well, I'm not sure if we've heard from OpenTable or not, whether they've going to they're going to notify its users on this big change. And even if they do, you know, how many users would like to pay attention to those notification emails, that kind of a thing. So I think the important thing here is like them letting users know that they're going to make this change. And hopefully there is a way to like opt out or opt in or that kind of thing, you know, to hopefully detach yourself from that process. But I do agree that the retroactive part of this is problematic. I would personally, I would hopefully advise OpenTable to just like, you know, from this point on where it will attach your name to your reviews. But anything before this point will disregard that. I think that was the ideal move for going forward. I'd be curious to do it from a from a legality perspective. Like I'm sure in the actual terms and like the Yula or whatever we signed when we initially signed up for OpenTable. Like maybe it said things would be anonymous, but maybe they didn't. I don't know. I didn't read it. Did you? Maybe Tom did. No, I even I don't read in terms of service.  I would like to note that they did notify members of the change in policy in an email. So if you had left a review, which I have left 10 of apparently I had no idea that they told you. But I mean, I was going to agree with Nicole and so far that there's a difference between being like legal and also just being like decent. And I think like just doing that and it's a good thing that they told people. Yeah, I have left some reviews on Yelp that I've forgotten about because I don't know I moved out of the city or I don't care anymore. They're usually bad reviews because that's what drives and fuels me when I'm upset about something I'm like the world needs to know. And it just didn't happen on OpenTable, but same idea. I've considered deleting them just kind of like, I don't know, it just makes me sound like an angry person, you know, some years down the road. But at the same time, I knew that that was something that could be attributed to me.  I mean, there are all sorts of reasons that an anonymous review is not really helpful to anybody. But if you if you truly think you're anonymous and and the company says yes, you have that option and then later on says, well, now we want to be more transparent. I can see where that that can be problematic. It's probably not very often that somebody who wrote a really bad review of the restaurant on the corner five years ago is, you know, someone's going to knock on the door and be like, we know it was you now kind of thing. But, you know, privacy is important. Yeah, this is not the biggest problem in the world. I'm with you on that. Restaurants could probably figure out who was leaving their scathing reviews just because that person was probably not happy when they were in the restaurant. They already knew the date that was already associated with the review, even when it was anonymous. But it's the principle of the thing, right? It's one thing to say from now on, they won't be anonymous. Just so you know, that's fine. That's a change in policy. And I'll deal with it. But to say retroactively, oh, those things you thought didn't have your name on them. Well, guess what they have your first name on them? Not not cool. And yes, I know you can go read, remove your reviews if you're worried about it. So at least you have some action you can take. But control. Yeah. Yeah. Not the best. It's like family restaurants everywhere are like, wait, you didn't like our restaurant this entire time. You're my son. That's what I mean. Like restaurants seats 30 people. One person is angry that day. And then they leave a review about their stay that day. You kind of know who was already. I never show my anger on my sleeve, man. I know. That's that's not the Belmont way. And just smile all the way to the end and then grumble, grumble, grumble on the way. Well, on a different note, you might be trying to save money these days, right? With inflation. Have you seen the price of grapes? Well, PC upgrades are something you need to be careful about because not only could they save you money that could keep you from buying a new computer, but you don't want to be wasting money on upgrading the wrong things. So Roger and I put together the top five PC upgrades you should consider. It'll take you all 60 seconds to catch up on this. Go watch our new top five PC upgrades at Daily Tech News Show on Tiktok, DTNSPIX on Instagram or youtube.com slash Daily Tech News Show. Well, the U.S. economy has been growing and job growth remains strong. The tech and media sectors have been suffering round after round of layoffs. We talk about a lot of these on the show when we feel like, you know, it pertains to tech in our audience. Just in April, checker, that's a technology that offers employee background checks laid off 800, I'm sorry, 382 people, 832 would be a lot more. Still quite a few people. Ghost autonomy, a startup focused on developing software for self-driving cars closed its doors, April 3rd, leading to more than 100 layoffs in Mountain View, Dallas, Detroit, and Sydney. There are other examples of this, obviously. On the bigger company side, Intel is planning layoffs beginning around May 25th. Last Friday, Apple laid off more than 600 employees. Got a lot of news because, you know, it's Apple, but companies, especially in the tech and media sector are downsizing. With so many people being laid off in these sectors, we wanted to talk to a couple folks about what they plan to do next. Veronica and Nicole, thank you for being willing to share your stories with us. Veronica, let's start with you. How do you feel about the tech sector right now? Because as you mentioned earlier in the show, you're actively looking for work and working on resumes and stuff. Yeah, I mean, it's a very, it's a tough time. And it feels very, even very privileged now to say that because the tech industry has seen so many years of growth. And I think, especially during the pandemic, there was a huge bubble of hiring. So many companies got inflated so very quickly. And now there's a big correction in the industry. And it's, it makes a lot of sense in a lot of ways, but that doesn't mean it stings any less when you and a thousand or 2,000 of your coworkers get let go all around the same time. My company that I previously was at did 3 or 4 rounds of layoffs just in the 2 years that I was there alone. And all of those were public, so I don't mind saying so. But it's a difficult climate to work under. And for these companies now that are still awaiting their next round of layoffs or are hearing about it in the news or probably being spoken to about it in all hands and town halls all across the world. It's, it's that fear is very difficult climate to work under. And so, yeah, it's a tough time. And the industry itself, the job market is really difficult. And especially with sites like LinkedIn or indeed where you're just kind of throwing your resume and to avoid a black hole, not really understanding who's looking at it and when and how and how best to optimize your resume and your cover letters. It's difficult and we can talk more about some of the ways that I've been looking at it personally. But a lot of folks are going through the same thing right now. So, Nicole, I know your experience is a little bit different. It was more of a, like a media shutdown, I guess, than a layoff. But does what Veronica says resonate with you? Yeah, you know, I think there's a decent amount of crossover because the media industry is affected a lot by the less reliability on programmatic ads and advertising revenue has gone down. And there's definitely some crossover with the tech industry as well. You know, it's just the environment is rough, I think, for a lot of media companies because they're owned more frequently than ever. A lot of media companies are bought by, you know, private equity and private equity, there's a strong incentive to make money like not like yesterday because they bought these companies for billions of dollars, so they want the return on their investment. And in order to make money quickly, you have to, you know, more often than not, let people go. You have to cut departments, cut jobs and things like that. And the people who are still left in the company, they're driven, you know, to work harder to like meet those goals, you know, to get those SEO numbers. So it's a tough industry for sure. And we can talk about like what we're doing right now to get through it. But yeah, it's, I can definitely feel the simpatico between the two different sectors just because, you know, we are both getting laid off in the huge numbers and we have to deal with pivoting our careers maybe or like looking for different ways to do our job. Using those chat GPT tools to like, you know, customize our resumes and cover letters, but it is, it's very interesting. If you mentioned, you mentioned LinkedIn Veronica. LinkedIn is like the hottest social network right now. Everybody's posting. I don't know how this happened, by the way. It's like LinkedIn was sort of, yeah, like it was like, it was a good tool and then it was sort of, I don't want to say a joke, but something that a lot of people were like, eh, LinkedIn, you know, so corporate me. And now it's like, wow, it's, you know, like a great place to network. It is, it is the hotspot for sure. And I think a lot of people, myself included are still figuring out how to, how to utilize it and maximize it. Because, you know, my voice, my internet voice is very catered to the, the, the threads and the X's of the world, though I no longer am on X or Twitter, um, functionally speaking. Uh, and so like figuring out how to do like corporate LinkedIn speak is like a whole new skill and it's, it's very uncomfortable for me. And yet I know that recruiters are looking there. I know that potential hiring managers are looking there. And so you feel this very strong urge to, to be a voice, to be an influencer, to, to be a thought leader in your space. And that doesn't come naturally to everybody. Yeah. Well, so. Brand. Yeah. Totally. Okay.  Some people decide, you know what, you know, maybe my industry, uh, is just not popping right now.  Other people don't have the luxury of doing that. Everybody's different. Um, but at the same time, taking a job that you don't really want because you need a job is never really the solution. Um, it can be a stopgap, but it, you know, it, it doesn't necessarily lend itself to happiness for the company or yourself. So, so how do you, how do you handle looking at jobs that could work but aren't right? Nicole, do you want to go first? Yeah. Uh, you know, uh, at a certain point when you're unemployed, uh, there's, there's, there's definitely stages, right? The first stage is like, okay, you have enough savings to last you a little while. Maybe at the beginning of your job search, you kind of be more selective. Maybe you're like, you're looking for the jobs that really fit your desires and your wishes. And then as maybe the weeks go by, maybe like, oh, maybe I shouldn't be so like selective.  You know, you have to be like, you have your wish list and then like, if the compromises start, give the, give compromise as, as the search goes on. And, but at the same time, I think honestly, I think the important thing is to know who you are, know what you want. Uh, know the compromises that you're willing to make and know the compromise that you're not, that you're not willing to make and sort of use that as your like moral guidance. If that's the right word to use. Um, and hopefully that's like your, your guiding light, you know, as to which jobs you're willing to do. So I'm going to say, okay, this is not a hundred percent of what I want, but it's close enough. Or this other job that, um, I really want, but the qualifications, I miss out on a couple of those qualifications, but I can make a case for myself. So I'm going to, I'm going to apply for it anyway. Kind of a thing.  I think is really important. Yeah. So I'm going to give yourself open to, to career pivots as well. Hmm. Yeah. I know that looking for a job is a full-time job. Um, so I took a, I took a couple of months to really get my head on straight. And I did have the, the privilege of being able to do that because of my severance. Um, that doesn't last forever though. Uh, so I have started that process now. Um, but yeah, when Nicole says is absolutely true, like if you're, if you're looking for something and you don't, and women especially are, are tend to do this, which is about a hundred percent of the quality qualifications for. Um, but also don't forget to network. I think all of my previous roles have pretty much come from networking and not from just cold applying online. Um, so do that. If you see things that look really good, but also make sure to talk to the people within your industry, within your network, because that's going to make a big difference. Yeah. I've seen that with my wife with Eileen Rivera. She's, she's looking for, for jobs as well. And it's the same thing where, uh, she comes across jobs that are like, well, I fit it, but would I be happy or that one looks interesting, but I'm not sure I fit it. Uh, and then a lot of times they're cold applications and they go nowhere. Whereas the ones that she ends up getting interviews for are things out of her network. Yeah. At the very least it's good experience to keep interviewing. Also do not underestimate what constitutes a network. It can be a friend, it can be a family member, but literally it can be anyone you've met throughout your entire career. Like that one person, that one, that one contact you've talked through through a networking event, it counts. That one person you talk through to get to get an assignment somewhere, it counts. Like literally anyone in your network counts to reach out to them to like get information out of or to get a job opportunity out of. Yeah. Well, thank you both for, uh, for, you know, sharing your, your thoughts and your experiences and your tips with folks really appreciate it. Happy to. Yeah. Let's check out the mail bag. Let's do it. We have the week with, uh, people sharing their EV experiences because boy, when we talk about EVs, y'all write in and we love it. Thoughts from both Andy and Alison shared and pointing out that while it does take longer to charge up an EV than to fill up gas in your car, you fill up less often if you charge overnight at home. In those cases, you almost never go to a charging station unless you're going on a longer trip. Andy put it, uh, well, saying, I've had a Ford, not really a Mustang, Mach E for about two years. It's amazing for my commute. I save a decent amount of money and time not having to stop at gas stations anymore. I set my max charging at 80% and start with a full tank every morning. Alison did the math, posted the results, uh, over on pod feet.com. We will have that link in our show notes as well. And Andy does agree that longer trips feel harder for him with the EV. He pointed, he pointed out the downside is a 1000 mile trip to Wisconsin. I think he lives in New Hampshire is not pleasant. If I was driving over multiple days, it would be great. No different than our regional trips here. However, my practice is driving straight through and what was a 14 to 17 hour trip in a nice car is 20 to 23 hour trip in the EV with that extended battery. So thank you to everybody for sharing their EV experiences with us. We always love when a story gets just a lot of attention and people really want to add to the conversation. So keep it coming. Feedback at daily tech news show.com. Indeed. All right. Throughout this show, Len Peralta has been using his imagination to make art happen. Len, what came out of your head? You know, 23 years ago, I was a casualty of 9 11 where I was let I was let go from my job. Gosh, Len. Geez. He'll put it that way. That was a good word. Maybe Christine might have shot that. No, my point is, is that I know what it feels like to let go and having to start all over again. That was 23 years ago. And I can't emphasize enough networking, networking and networking. And I agree 100%. Today's art is sort of kind of feeling a little bit like, I don't know if it's sad or anything, but if you're recently downsized in tech, you might feel like this. And it doesn't have to feel this way. You can make, I think you can make a very positive thing out of being let go and move into a totally different direction if you need to. So don't be afraid to do that as well. I speak from firsthand experience and, you know, it's tough, but you will find what you want to do. And for anybody listening, most I know most people are listening, not looking. You've got to go take a look at this art that Len did. The most pointer picking up a person that is about to be dropped into the recycle bin of a computer. That's exactly. Well done. Yes. And if you want to see it, you can go to my Patreon page, patreon.com forward slash Len, where you actually, if you join at the DTNS Lover level, you get this image or networking, of course, go to my online store, get it there, or hire me to do non-IAR at lenproldestore.com. Nicole Lee, always a pleasure. Let folks know what they can keep up with your latest. Yes. So I just created this like 10 minutes ago. So this is my like online portfolio. I'm still under construction somewhat, but this is like a very basic information about me and what I hope to bring this. Nicole Lee dot pro. Nicole Lee dot pro. That is a good URL. Veronica Belmont, always a pleasure as well. I wish I could hug you in person. It's been a long time, but let folks know where they can hug you virtually. I'm primarily on threads these days. So at Veronica, same as Instagram. You can find me on LinkedIn, Veronica Belmont is the handle over there and all my other stuff is linked from Veronica Belmont dot com. Excellent patrons stick around for the extended show, Good Day Internet. It's Friday and we have a special who am I quiz from Roger Chang, focused on famous folks who got fired, but then went on to become huge successes. Can you figure out who they are before the final clues stick around and play along with us? Just a reminder, you can catch our show live because we do it live Monday through Friday 4 p.m. Eastern 20 hundred UTC. Find out more at daily tech news show dot com slash live. We're back on Monday with me come on for joining us. Have a great weekend everyone. This week's episodes of Daily Tech news show were created by the following people, host producer and writer Tom Merritt, host producer and writer Sarah Lane, executive producer and Booker Roger Chang, producer, writer and co-host Rob Dunwood, video producer and Twitch producer Joe Kuntz, technical producer Anthony Lemos, Spanish language host, writer and producer Dan Campos, science correspondent Dr. Nicky Ackermanns, social media producer and moderator Zoe Deterding. Our mods beatmaster W. Scottis one, Biocow, Captain Kipper, Steve Guadirama, Paul Reese, Matthew J. Stevens, a.k.a. Gadget Virtuoso and J.D. Galloway, modern video hosting by Dan Christensen, music and art provided by Martin Bell, Dan Looters, Mustafa A, A-Cast and Len Peralta, live art performed by Len Peralta, A-Cast ad support from Tatiana Matias, Patreon support from Tom McNeil and contributors for this week's shows included Chris Ashley, Ron Richards, Scott Johnson, Justin Robert Young, Veronica Belmont and Nicole Lee and thanks to all the patrons who make the show possible. This show is part of the Frog Pants Network. Get more at frogpants.com.


Yo, what's going on you too? So today I'm gonna be telling you guys a little personal story of mine that I hope that it's food for thought And it'll help you out in the long run. I'm gonna tell you a little personal story about mine about like About like two years ago. I actually wanted to stop barbaraing. I didn't want to do it no more I wasn't getting enough clientele that I wanted it. I wanted to and I was in a dark spot in my life And it was actually one person that kind of convinced me. It wasn't one person, but he actually kind of Helped me a lot. It was Jorge. He I Told him that I didn't want to barbara no more and he told me that dude. We have so much talent do not quit and At that time I I didn't listen to him You know, I was in my own, you know feelings like man, I don't want to do this no more It's just not for me no more So I thought about it and I gave it a try. I was like, you know what let me just stick to this and see how this turns out So then look at me now All because I listened to one person and their advice to give me it changed my world completely everybody at velocity Memo to rail Ramon Stan Oda Uncle Kev and also 360 cheesy. They all helped me out so much words that I can't even describe man They are true brothers to me These years have been great, you know, we built a bond over these years Especially me Jorge Jerelle Ramon and memo. We are worked at the same shop before so we kind of had like a little bond but even now it's way better y'all and they're like brothers to me and I want to trade them for the world and They stuck with me through these years so I'm gonna stick with them through these years, you know So the moral of the story is y'all is do not give up on your passion Do not give up on something that you love to do it might not it might not be I Paying the bills yet. It might not be Succeeding yet, but in the long run do y'all It is going to help. I can guarantee y'all that if you work hard at something you're going to succeed I can guarantee you all that I've seen 360 cheesy do that, you know He's he worked hard. He worked his his butt off He worked hard and look where he's at now and I actually got a witness all that You know and look at him now. He's like one of the most viewed YouTube barbers on on YouTube So and he's an icon I actually spoke to him about this and you know the other day I was like, you know the reason why all the little kids want to cut hair. He's like nah I was like because you It's because of you that all these kids want to cut hair now And it's growing the industry even much higher and higher and higher and this is where we're taking over You know like I said the moral of the story y'all is don't give up on something that you love to do I didn't look at me now Just keep working hard and it'll succeed and it'll pay off in the long run So to begin with I'm gonna be combing my client's hair It's always good to comb the hair before you actually cut the hair.  I'm not gonna be doing any Side hooks or anything. So I'm back. I'm actually dropping it lower kind of towards an observable I'm kind of making that mid drop fade look. So basically what I'm doing is I'm making my my first ball line I'm gonna be making it as straight as I can do it So that way my guidelines will be set in straight also So for the first step of this mid drop fade at my wall seniors and I have the lever all the way open So what I'm doing is I'm gonna make the first guideline about Half an inch long to a quarter of an inch Make sure that that guideline is straight and when you get to the whatever that you wanted to stop at where your guideline You wanted to stop at you just flick out. You don't really want to make a hard guideline You don't want to just set it in and just make that Hard to take out. So basically what I do it at the top is I flick out from it So that way when I do my next guideline is not gonna be set in stone up in there You know I'm saying my next step. I have my number one guard and we make another guideline about let me guess half an inch long So basically when like I said Just flick out really and as you can see it's not really believing in the hard way because you know Obviously I did that one with the grain in the beginning of the video So usually a one with the grain and if you do a one against your grain It's really not gonna make any hard line So basically what I'm doing is I have my one guard and I'm just flicking out half an inch So for this next step, I have my zero guard. I'm gonna make the lever all the way open So I'm blending down the way I do this is that I Obviously, I have the lever all the way open. I'm just taking as much dark spots as possible It really is it gets easier in time some people might not know how to blend down But honestly it just takes a lot of time and practice to do it So what I'm doing is I just have my lever all the open and taking out all the dark spots So then when I take enough dark spots out, I close the lever just a little bit more And then when I want to get even closer I close it even more.  You've got to play with it Everybody has their own technique and have everybody has their own way of blending I hope that you guys find yours and I hope that you guys have like learned from my you know my methods So like again Close halfway open this play with the levers a lot I'm gonna be taking the hairs that are we want to have long hairs on the hairline So that way when I line up the hair it's gonna be hard to make that line So I'm going to one with the grain I'm just taking all the hairs and basically what it's doing is it just cuts it all at an even length and it lays it Down so when I hit that line, it would just be so time for this lineup part. So I have my my and this tea outliners. So what I'm doing is it's a little blurry right here, but This bear with me I'm starting from the middle and I'm making my way to the right side and what I'm doing is I'm setting my base in the middle So that way when I line up from the right side and I want to line up to the left side It's all gonna meet up in that middle So that way one side won't be higher than the other So I always tell you this in my videos to start from the middle and then work your way to the right Back to the middle then to the left back to the middle. So that way it all meets up So I'm gonna be spraying enhancements to my client's hair He obviously really doesn't need it, but I want to show you guys every little detail I do into my hair cut so that way when you guys try it on your own you guys would be professionals at it I'm gonna be putting the airbrush in the description below. I'm gonna put in the airbrush in the airbrush Gun so I hope you guys can order yours So that way when you guys by the time y'all have it y'all be Clean at it, you know so YouTube Hope you guys enjoyed this video and make sure you put the thumbs up and also I think you guys so much for watching this video means a lot to me y'all and Shout out to the man that makes my beats and prices Instagram will be in the description and also his YouTube link will be in the description also Feel free to follow me on Instagram y'all and Take care and also don't forget to subscribe either y'all. Okay. Okay?


Hey everyone welcome to figure fantasy and no i'm not leaving this game no ifs no buts i'm not leaving anytime soon so please make sure that you stay tuned for more figure fantasy content as resumed with yulanda in this update after tia so this update is all dedicated to yulanda so the limited rate up even okay so do not consider this the personal designer brand do not pull for that there's also a new skin for yulanda so this is going to be limited time in stock if you've seen my thumbnail then that is the skin that we are talking about we have a couple of events related to yulanda here all the events are going to be december 2 until 22 some of them are only up to 16 so there are a lot of events for this girl an event uh limited challenge dungeon as well coming soon so tomorrow definitely i'll be creating lots of videos especially for the usual guides that i do event limited idle drop fortune puzzle fairytale magic limited event again new packs combining magic and science card packs and a lot of packs here then solo dungeon event brave the mill fort is coming back and that is it so other updates figure in covenant there they have added yulanda chow chow sakura crossel and izumi then yulanda adornment also added exclusive special edition zhaoyun vow of pure white version also added in permanent in stock so i'm just going to give you guys a reminder before we go to the review of yulanda's kit the update might be delayed in north american eu so please be sure to check the time the time deployment in your areas so that you won't ask again if there's no update for today or tomorrow so anyway that is it we all have a lot of things to do tomorrow for the event for yulanda's event um uh i will be pulling for her tomorrow with what i have currently and let's move on to yulanda's kit let's do a small review whether she is worth pulling for or not so yulanda is going to be she's inclined with with uh with fire so let us check out her kit so she's rated an 8.8 out of 10 so let's see if that is correct okay so attack skill is ranked 6 so she is a militarist guys her attack speed is fast prioritizing attacking the front most enemy in the same horizontal row as herself deals damage uh additional when the target is set on fire or ignited so she's gonna work well with your ignite teams um you just have to make sure that she has you know space there but i think you have i'll feature a new ignite team once uh she is going to be out increases norm attack damage by 25 for her ultimate initial energy 70 which makes her um you know uh put out her energy uh energy or ultimate as early as possible so damages the front enemies in front sets them on fire for five seconds then buffs herself for a reagent for five seconds increase attack speed by 80 when buffs so sets them on fire then buffs herself and increases attack speed so while she already has a fast attack this makes her even faster during the enhancement damage is increased by 30 when hp is 70 or more hp absorption is increased by 50 when hp is less than seven so take note of that as well enemy burn time and buff duration is extended to seven seconds so that's five plus seven with a total of 12 passive skill rilanda performs a flask attack after a friendly figurine old uh friendly figures ultimate is activated so every ultimate that your team does her passive triggers and the deals damage to the currently attacking enemy so more or less the one that she's attacking and right in front of her flask damage is increased for level up and damage is increased by an additional 40 percent when the target is on fire that's a big damage she's going to be good for bosses i have a feeling this is this is the this is the the figure that we're waiting for for bosses because this enhances her damage enhances her attack and takes advantage of ignite okay so let's go back to level up effect flask damage increases and damage increased by 40 when targets on fire increased flask damage and ignites all immobilized effects flask flask attacks and restores 30 energy when immobilized this is nice um specialized skills so increased damage dealt by 50 where there are no enemies around this is the usual for your militarist basically for your passive skill increases flask damage and negates all immobilization effects immobilization so uh freeze what else immobilization effects so other all effects she negates that that can immobilize her but she also increased flask damage flask flask that attacks and restores 30 energy when immobilized that's nice this is nice this is going to hasten her ultimate eventually so what do i think of her um i don't think she's going to be s tier at this point um she can be depending on how you're gonna build her i still don't have to more or less see how we're going to build her probably have because right now she's ranked at s tier she's ranked at s tier but i think she drops one notch below it really is a toss up depending on how you build her i'll have to test her out uh first but for now she's with s tier might be different after a few trials so strongest rank is s as you can see there um also if you can see here going through her skins this is a skin that i am actually looking for the witch skin so magic recipe magic medicine recipe version so this is one that i'm waiting for the mark the margarita version is this one okay so this is the skin that is available now on limited time only but this is the one that i'm waiting for the witch skin that i'm interested in so she's actually i'm actually um curious to use her um looking forward to using her um she gives ignite uh pretty much pretty much a good damage dealer you know and more or less she's going to work with a team with ignite so zauyu mit suhide zuki liang sanada and re they're going to be crucial and making her better so again i will leave my um what do you call this my final review and the build guide that i'm going to be putting out probably tomorrow or the day after so for now i think she's a good um investment to pull unless if you don't want to add to your militarist for uh let's read she's a good one if you're building a fire team she's a she's definitely one of your core contributors for your fight fire team now um aside from having a couple of dps there already you will definitely need her um as she what they call this as she is uh incorporated in your fire team so increase on attack speed by setting enemies on fire absorption and damage increase according to remaining hp follow up attacks occur when allies activate secret techniques additional damage to burning enemies so um when they're burned they definitely take more you know she she's she's technically suited for boss uh boss stages and boss content so if you want to invest on a specialist like her to take down bosses and to deal more damage definitely you'll have to summon for her but again i'm sh at this point it i would say that it really depends on what you have for let's read and if you're building a fire team but for free to play i don't think she's a must summon if you're not free to play then she's a must summon so at this point it's really up to you guys if you're going to be summoning for her so that is it hopefully this will end my short review if she's worth it or not a more in-depth review is coming soon so take your guys stay safe this is the warden and i'm out of here


This course aims to be a generic introduction to the concept of big data and how we can manage these large volumes of data using artificial intelligence. We will see several applications coming from different fields such as politics, health, finance, education, and we will also see how to manage data coming from social networks such as, for example, Twitter. One of the main important points of this course is that we will see the challenge faced while working with big data, such as data bias, transparency, the loss of privacy, and I would say that one of the objectives of this course is that students with no technical background about big data and artificial intelligence can understand and play with these tools.


It can be difficult to practice defending on your own, but in this video, I want to show you soccer drills for defenders. That pass is coming as that ball gets there, boom, you want to be here. Okay, so focus on closing quickly is number one, but this drill, what you're going to do is I'm going to close him down, close him down and then practice kind of jockeying back into space. Go again, close him down, jockeying, staying low, jockeying back into space, kind of trap him one way. So one, speed of the drill, speed of the close. At this point, now I'm getting cautious. Now I'm not running in crazy. He's in my defensive third, I'm getting cautious. If I run directly at him, set up like this, two ways for him to go, three ways for him to go. What I want to do is think about trapping him, pushing him one way. Let's say I want to take him to the sideline. So I'm going to close quickly, but I'm going to curve my run. So I know where he's going, I'm pushing him this way. So practice curving your run, then practice keeping him into that space. Good, if I want to bring him this way, curve my run. Opening up the body, play it to the other side, go again. Practice opening up the body, facing the field. The field's this way now, facing the field. Switch of play, okay? And you can let that ball roll across your body or hit it with a bit more pace. Now we're playing two touch and play, okay? Switching feet, first step of this drill is opening up the body, seeing the field, not closing yourself off when I know I want to go that way. Receiving in half turn, so I can switch the ball quickly. The other thing is the quality of your pass. As a defender, you need to be an expert passer. You can't give the ball away. Best defenders have very high passing percentage completion, okay? So when you're playing that pass, focus on the quality of the pass. Get over the ball, open your foot, strong contact, aim for a spot on the wall, hit that spot, go again. Yes, good, play. In this drill, we're going to do some long passing. And if you only have one ball, find a wall, ping it against that wall, let it bounce back to you. Go again.  So, good technique. So as I said, it's better for you to practice off a dribble. It's more realistic. Get that ball down, good technique. Playing with both feet, there we go, beautiful. First, just practice good contact off the forehead. As a defender, a lot of times, maybe you're doing a defensive clearance. Okay, so you can practice going up, going high, okay? But this is a good way to get that technique. Can't be scared of the ball as a defender. Practice good contact off the forehead, snapping with the body, okay? The more power you want, the more you have to generate from the hips, from the upper body, from the neck, but developing confidence with your heading skills.


Welcome traders to another Tickmail Earnings Report preview with me, Patrick Mullerley. For Jumping Today's report, it's important that we understand the risk disclaimer. The material provided is for information purposes only and should not be considered as investment advice. The views, information and opinions expressed by me in this recording are solely mine and they're not indicative or representative of those held by Tickmail UK or Tickmail Europe Limited. So, let's jump in today's report. We are looking at Berkshire Hathaway, who announced earnings over the weekend and will file before the market opens today. Berkshire Hathaway reported Q1 financial year 2022 earnings that exceeded analyst expectations. Earnings per share, though, were down by 51% year over year, but 23.4% better than analyst forecasts. Revenues for the first quarter of 2022 were 68.832 billion down 2.1% year over year and missing the estimates by 5.6%. Note that this revenue figure is the sum of operating revenues from Berkshire's operating subsidiaries, which account for 70.810 billion. The pre-tax loss on Berkshire's investments and derivative contracts was 1.978 billion. In the first quarter of 2021, these figures were 64.59 billion and again are 5.7 billion respectively. In the first quarter of 2022, Berkshire Hathaway recorded an after-tax net loss of 1.58 billion on investments and derivative contracts. The company reported a gain of 4.693 billion in the same period 2021, operating earnings, which includes these gains were 7.04 billion compared to 7.18 billion in the same course for 2021. This was a slight improvement of 0.3% year over year, but 7.7% above the estimate. The operating earnings figures that Berkshire reports are calculated after income taxes and excluding attributable to non-controlling interest. Berkshire spent approximately 3.2 billion on share repurchases, stock buybacks in the first quarter of 2022, buybacks included both its Class A and its Class B common stock over the past year. Berkshire Hathaway's shares have provided a total return of 20.8% outperforming the S&P 500 return of negative 0.03%. So let's look at some of these statistical patterns of how the stock might trade today. Stock has moved higher in the immediate aftermath earnings, 8 out of 12 previous reports. On average, the stock moved up 0.4% in the first day after trading. Based on the previous 12 earnings releases, Berkshire stock is more likely to trade higher one day after earnings for an average gain of 0%. Stock has moved higher one week after earnings, 50% of the time out of the previous 12 reports, and an average has moved up 0.3%. Let's take a look at the options market and what it's telling us. Options traders are pricing a 2.7% move on earnings, and the stock has averaged 2.2% in recent quarters. From a flow and sentiment perspective, on Friday there was some notable buying, 1224 contracts of a $320 put expiring May 20th. Options order flow is in the main bearish. Investor sentiment going into the earnings release has 60% expecting an earnings beat. Stock is currently 7.4% above its 200-day moving average, which comes in at $362. So let's take a quick look at where there might be an opportunity to trade today in Berkshire stock. We're sitting on this daily trend line just above it at the 319 handle. If we get a close through there, I will be looking for further downside to complete a potential five-wave sequence from the highs here, and that should have us testing back into support at the 293 area. From there, I'd watch for the potential for bullish reversal patterns to play the long side, at least looking for a three-wave counter trend move back up to test the underside of this broken trend line, which will be coming in around $333. If, however, we don't find buyers into this first support zone, then we look for a deeper pullback into the high-volume node at $279.27. At this stage, difficult to get meaningfully bearish on Berkshire unless we take out this weekly trend line, and that comes in at $298. As always, traders, plan the trade, trade the plan, and most importantly, manage your risk. Until next time, thanks very much.


Well, thanks, everyone. It's my pleasure to introduce Samuel Gamboa, who is, in fact, to welcome you to the Metagenomics short talk series, Metagenomics and Cancer, short talk series of the Myoconductor 2022 conference. Samuel Gamboa is working with Levi Waldron's lab at Cooney, and he'll be speaking about a resource of microbiome benchmark data sets with biological ground truth. Thank you, Samuel. Hi, thank you, Vincent. Right. Well, I would like to start by speaking a little bit about differential abundance analysis, which is the major focus of this work, what's kind of a statistical approach aimed mainly to identify microbes that are associated with a given condition or given body site, sometimes for the purpose of identifying biomarkers or signatures. So this method has some challenges, and these challenges usually come from the type of data itself, such as the high compositionality of sparsity, these type of data composition. And so a array of methods having used to tackle this and having implemented to identify differential abundance features of TACSA, which go from classical statistical tests like coaxon, T-test, some of them are compositional, which are based in a central low-grade transformation. Other methods implement their own normalization transformation methods, just as metagenomic, and there are some other methods borrowed from the field of anesthetic and secret anesthetic. Well, bottom line here is that there is no consensus method or a pro ratch, so pretty much this has to be some kind of benchmarking before using any of these methods. So another limitation that exists right now for the development of these differential abundance methods is that the limited options for benchmark data sets. So commonly, these data sets that are used come from simulation data sets, which often do not reflect the complexity of biological data sets. Some biological data sets are used, but some of them lack a biological ground truth, so the researchers cannot really know if their results are correct or not, because it just comes from statistical analysis. And on the other hand, some other data sets are not real, we are viable or reusable. So to tackle this, we are creating a collection of data sets, which have been described in literature, and they are viable somehow. So we are standardizing these with all of these in a single resource, and well, there are actually three data sets, and one of them, the first that you see there is presented in several versions. So as you can see, they come from different boy parts, the Gigi ball, stool samples and vagina, and they have different contrasts. This is important because it's assumed to be some differential evidence in these data sets, and they all have a biological ground truth that has been very well characterized in the literature, not only through sequencing methods, but all their approaches. For example, in the Gigi ball aerobic dioxide, it's well known that's enriched in the super Gigi ball plague, as opposed to the aerobic, as opposed to the sub-Gigi ball plague, which is enriched in anaerobic taxes. So it's two samples, and we have this data set that they're really, the real ground truth here is that has some spiking bacteria, these are exogenous, and they have been added in a fixed amount, which is known. So this can be used to recalibrate the whole data set. So we have accurate counts, and the last one comes from bacterial vaginosis, which is well known that they've probably decreased in lactobacillus during bacterial vaginosis, and an increase of older taxa, which has gotten realized. So, well, this collection of data sets is viable in Saint-Noel right now, at least the first three data sets that you see there. We're also developing a package that's to be submitted to Biocontactor 3.16, in which the data sets are delivered as trisumorized experiments, while all the components of the data sets are viable, use just the sample metadata, the ambulance matrix, taxonomy annotation, and the phlegic tree for some cases. And these increase the fare, the final accessible, interpretable, and reusable approach for the data sets. So I would like to speak a couple of cases of how we are using these data sets, just an example, and the first that we have to mention is the bacterial vaginosis data set. Well, the data set has some experimental evidence, which has based on an annotation of taxa, which have been isolated from bacterial vaginosis samples. So we know that there should be differential amulet. We have a sample metadata that is also backed up by an experimental approach, in this case, based on the engine scores, which divide as in bacterial vaginosis and healthy tissues. And all the taxa are annotated, so we have a reference. So we're using these for creating an arrangement analysis. So in this plot, we are comparing several differential amulet methods and normalization methods here. We're comparing, we classify them into classical composition, now the anomie is RNA-seq and single-cell RNA-seq, which is what you're presenting in the first slide. And well, on the left side, you can see that we have the expected biological ground truth, right? So we would expect that the methods would detect bacteria as a site with bacterial vaginosis up and with healthy vagina down. So we can see in the plot that just by looking at the number of features that most of them did find the taxa that we expected. But as you can see, some of the compositional methods also detected the bacteria that should be up in the other direction. So this is preliminary data, so I still have to do some digging there. But this is an example of how we think that this dataset could be useful to compare the outputs of the different differential amulet methods. And the other dataset that I would like to talk about a little bit is about the standard 2016. This is called, as I mentioned, for nestle samples before and after allogeneic cell transplantation. There are three bacteria that were added exogenously, saline bacteria, AST fluids, and resorbonate bacteria, which are totally exogenous to the stool samples. So we can pretty much show that they're not there. And will the authors or in the count data, well, we know how much of those bacteria are. So it can be used to be recalibrated. So we use this to compare the coefficient of variation of compositional and non-compositional data transformation with space in the low-radio transformation. And as you can see in the plot in the first panel, all right, the recalibrated counts are, in this case, with saline bacteria, the variation is zero, which is expected because it's the same amount in all samples. So this would be the biological ground truth. And we compare the performance of different normalization methods, and we see that, for example, even a method that is in the low-radio, which is considered appropriate for compositional data, didn't perform much better than the simpler approach, which is relative abundance. So we can see there's still a lot of variation here. And we see this also in the abundance of the older taxa. So this is another example of how to use one of these data sets for benchmarking and compare the results. So while summary and perspectives, well, we are expecting that this resource and this package will provide these data sets, which will be suitable for benchmarking and differential evidence methods to evaluate the correctness of discoveries because we already know what to expect from them. And we expect to add more of these data sets from different organisms and habitats so we can have an array of methods there. And we'll increase the finability with these arenas in all already, and what they will be submitted to by a conductor. Well, thank you all for listening. Thanks to my co-authors and all the Waddon lab and the research foundation at CUNY for funding this. Thank you. Great. Thanks, Samuel. We have a minute for one or two questions, if there are any. Yes. I think you would go to the microphone, and then others will be able to hear you, and you can come to take the response. Thank you for your talk. I just had a question. Looks like your samples were just 16S subunit, using metagenomic shotgun sequencing as well. Yes. Well, right now, thank you for asking. Yeah, right now, all there are 16, except for one. The first is Gingival. We have some metagenomic data there. Yes, we do look for expanding this. So we're open to proposals of data that's to include. Yes, and definitely including also metagenomic data is in sight, and we would like to add those. Yeah. And just like a follow-up question. I'm doing some similar type of there's room for lack of function because of the way that bacteria share genes like that, looking at disease to try to make a whole disease target. Sorry. Yeah, sorry. Repeat the question. Is this OK? You never hear me find this close? My question was, are you interested in taking this further into some type of functional gene annotation, not just like a taxonomical basis for interrelatedness between species? Well, yes. Thank you. Yes, we do. I intend to. Well, the laboratory is working with a lot of annotations. I think the next talk is going to be related to that. We also have other packages. And we look into ontologies as well. Yes, that would be nice to annotate the taxa based on functional features, not just the taxonomy. Yeah, that's definitely something that we would like to include just in future datasets. And we look forward for that. Yeah. Awesome. Thank you very much. No, thank you. All right. Thanks again, Samuel.