1 00:00:00,480 --> 00:00:04,640 Speaker 1: The Bread Show is on Fred's Biggest Stories of the Day. 2 00:00:05,240 --> 00:00:13,320 Speaker 1: Florida the Gators, Jason, they beat the Houston Horses. Yep, 3 00:00:14,400 --> 00:00:18,360 Speaker 1: that's exactly right, the Houston Horses. The Florida Gators beat 4 00:00:18,400 --> 00:00:24,560 Speaker 1: the Houston Cougars in an NCAA title game thriller, which 5 00:00:24,600 --> 00:00:26,119 Speaker 1: was stopped by some defense at the very end. So 6 00:00:26,160 --> 00:00:28,320 Speaker 1: it was very exciting. Sixty five to sixty three. Florida 7 00:00:28,400 --> 00:00:32,360 Speaker 1: is the NCAA men's basketball national champion, So congratulations to them. 8 00:00:32,560 --> 00:00:35,560 Speaker 1: Have you been paying attention to this Karen Reid trial. No, 9 00:00:35,640 --> 00:00:39,280 Speaker 1: there's a whole documentary about him. I can't remember where 10 00:00:39,320 --> 00:00:43,280 Speaker 1: the documentary is, Hulu or I think it's on Hulu. Essentially, 11 00:00:43,320 --> 00:00:46,360 Speaker 1: this woman is accused of killing her boyfriend who was 12 00:00:46,400 --> 00:00:49,800 Speaker 1: a cop in the Massachusetts I think, I said, of 13 00:00:49,800 --> 00:00:56,200 Speaker 1: Boston maybe, and she says she's being framed, and of 14 00:00:56,240 --> 00:00:58,160 Speaker 1: course the prosecution is saying that she ran this guy 15 00:00:58,200 --> 00:01:00,200 Speaker 1: over while drinking in the middle of the night, in 16 00:01:00,200 --> 00:01:03,040 Speaker 1: the middle of the winter, and there's a lot of 17 00:01:03,120 --> 00:01:05,520 Speaker 1: talk about this thing. A lot of people think that 18 00:01:05,600 --> 00:01:09,440 Speaker 1: she's innocent. And if you watch the documentary, I mean, 19 00:01:09,959 --> 00:01:11,280 Speaker 1: my mom and I said and watched the whole thing 20 00:01:11,280 --> 00:01:12,560 Speaker 1: a couple of weeks ago, and I was like, I 21 00:01:12,600 --> 00:01:15,399 Speaker 1: don't know, maybe she did, maybe she didn't. It's not 22 00:01:15,440 --> 00:01:17,920 Speaker 1: cut and dry, but there's some definitely some shady stuff 23 00:01:17,959 --> 00:01:21,160 Speaker 1: going on with this, But it was a hung jury 24 00:01:21,160 --> 00:01:24,720 Speaker 1: the first time around. And so now is the sixth 25 00:01:24,840 --> 00:01:27,840 Speaker 1: day of jury selection in the second Massachusetts trial of 26 00:01:27,920 --> 00:01:30,640 Speaker 1: Karen Reid. Ten jurors have been seated for the retrial 27 00:01:30,720 --> 00:01:33,360 Speaker 1: of Reid, accused of killing her Boston police officer boyfriend 28 00:01:33,440 --> 00:01:36,080 Speaker 1: John O'Keeffe by hitting him with her SUV in twenty 29 00:01:36,120 --> 00:01:38,520 Speaker 1: twenty two. At least sixteen jurors who needed before the 30 00:01:38,560 --> 00:01:41,720 Speaker 1: trial can begin, but things tolled yesterday with no jurors 31 00:01:41,720 --> 00:01:43,720 Speaker 1: were selected. It's going to be hard, I think for 32 00:01:43,760 --> 00:01:46,000 Speaker 1: people around them to find jurors around there who don't 33 00:01:46,000 --> 00:01:48,559 Speaker 1: know anything about this case because it's been so widely 34 00:01:48,600 --> 00:01:51,800 Speaker 1: talked about. I mean, it's all over TikTok. Of course, 35 00:01:51,840 --> 00:01:54,680 Speaker 1: the documentary. I'm sure there's been a dateline about it 36 00:01:54,800 --> 00:01:59,120 Speaker 1: or forty eight hours or whatever else. But Reid claims 37 00:01:59,160 --> 00:02:01,320 Speaker 1: that she left o'kee at the house where he was 38 00:02:01,360 --> 00:02:04,560 Speaker 1: found dead, and she is being framed for the actual 39 00:02:05,200 --> 00:02:08,160 Speaker 1: murdered by the actual killers. The judge declared a mistrout 40 00:02:08,200 --> 00:02:11,440 Speaker 1: last year when the jury found that they couldn't reach 41 00:02:11,440 --> 00:02:13,960 Speaker 1: a unanimous verdict. So we'll see what happens with that. 42 00:02:14,040 --> 00:02:16,880 Speaker 1: But I watched the documentary. I think it's Hulu. See 43 00:02:16,880 --> 00:02:19,120 Speaker 1: what you think, fred Olay, This is for you, paulin him. 44 00:02:19,160 --> 00:02:21,200 Speaker 1: You know, I like to try and cater the stories 45 00:02:21,200 --> 00:02:23,200 Speaker 1: to the people in a room who need the information. 46 00:02:23,400 --> 00:02:25,320 Speaker 1: I might realize there are tents of people listening at home, 47 00:02:25,360 --> 00:02:28,240 Speaker 1: but but no, I do it for you. Fredo Lay 48 00:02:28,280 --> 00:02:33,040 Speaker 1: recalls the Cantina tostitos because of milk contamination. These are 49 00:02:33,040 --> 00:02:37,720 Speaker 1: the corn tortilla chips. The Tostitos Cantina traditional yellow corn 50 00:02:37,800 --> 00:02:40,919 Speaker 1: tortilla chips rolls off the tongue. They might contain nacho 51 00:02:41,000 --> 00:02:43,320 Speaker 1: cheese made with real milk and can cause issues with 52 00:02:43,360 --> 00:02:46,000 Speaker 1: people that are allergic or have sensitivities to milk. The 53 00:02:46,080 --> 00:02:49,400 Speaker 1: recall only affects thirteen ounce bags and were available for 54 00:02:49,480 --> 00:02:52,040 Speaker 1: purchase as of March seventh. The chips were sold in grocery, 55 00:02:52,080 --> 00:02:56,359 Speaker 1: drug and convenience stories in thirteen states. So there, I need. 56 00:02:56,200 --> 00:02:58,560 Speaker 2: To go to my best friend's house right now because 57 00:02:58,600 --> 00:03:00,520 Speaker 2: he can't have that and have milk. 58 00:03:00,639 --> 00:03:03,040 Speaker 1: You better see if you've got the tostitos cantina traditional 59 00:03:03,080 --> 00:03:05,359 Speaker 1: yellow corn tortilla chips. The only one he eats. What 60 00:03:05,400 --> 00:03:07,639 Speaker 1: are you talking about? Those? The one? He's a cantina guy. 61 00:03:07,720 --> 00:03:08,080 Speaker 3: He is. 62 00:03:08,320 --> 00:03:10,520 Speaker 2: He eates pretzels and tortilla chips all he can have. 63 00:03:11,040 --> 00:03:13,560 Speaker 1: Okay, well you better call him up. You better call 64 00:03:13,639 --> 00:03:17,359 Speaker 1: him up and see. Gen Z is this, according to 65 00:03:17,440 --> 00:03:20,239 Speaker 1: The New York Post, is being labeled as the Ghosted Generation. 66 00:03:20,440 --> 00:03:23,079 Speaker 1: So gen Z is defined as what I always get 67 00:03:23,080 --> 00:03:26,560 Speaker 1: these messed up. I'm technically somewhere between millennial and I'm 68 00:03:26,600 --> 00:03:29,160 Speaker 1: right on the cusp of millennial and gen X is it? No, 69 00:03:29,320 --> 00:03:32,600 Speaker 1: ninety seven to twenty twelve is gen Z? But what 70 00:03:32,720 --> 00:03:36,240 Speaker 1: am I? What am I again? Millennial? You're a fairly millennial? 71 00:03:36,560 --> 00:03:41,080 Speaker 1: Or but what's before that? What's older than that? Why? X? 72 00:03:41,200 --> 00:03:42,360 Speaker 4: Right? No? 73 00:03:42,480 --> 00:03:45,520 Speaker 1: So yeah, so gen Z starts at ninety seven, Millennials 74 00:03:45,520 --> 00:03:48,000 Speaker 1: are eighty one and ninety six, and it's right before 75 00:03:48,040 --> 00:03:50,240 Speaker 1: that because that was born at the end of eighties 76 00:03:50,240 --> 00:03:54,400 Speaker 1: gen x X Yeah, right, So I'm somewhere between millennial. Okay, 77 00:03:54,680 --> 00:03:59,240 Speaker 1: So gen Z is becoming the ghosted generation? Or is 78 00:03:59,240 --> 00:04:01,800 Speaker 1: according to a new article from Business Insider, young adults 79 00:04:01,800 --> 00:04:05,960 Speaker 1: today are facing more knows than any generation before them, 80 00:04:06,080 --> 00:04:09,800 Speaker 1: from dating apps to college applications to the brutal job market. 81 00:04:10,520 --> 00:04:13,240 Speaker 1: Is that true though? I mean maybe dating apps, because 82 00:04:13,280 --> 00:04:16,960 Speaker 1: you know you're there's a much a much higher percentage 83 00:04:16,960 --> 00:04:19,640 Speaker 1: of folks that you're looking at and that could potentially 84 00:04:19,680 --> 00:04:21,920 Speaker 1: not swipe right on you, which I don't necessarily see 85 00:04:21,920 --> 00:04:24,120 Speaker 1: as a no. That doesn't seem like I mean, it's 86 00:04:24,120 --> 00:04:27,200 Speaker 1: not if someone doesn't match with me, it's not necessarily rejection. 87 00:04:27,440 --> 00:04:29,640 Speaker 1: I don't if I don't know them. Maybe if I 88 00:04:29,720 --> 00:04:32,600 Speaker 1: know them, i'd feel rejected. But I don't know. How 89 00:04:32,640 --> 00:04:34,479 Speaker 1: is that any different than when I used to have 90 00:04:34,520 --> 00:04:36,119 Speaker 1: to go out back in the day, like in high school, 91 00:04:36,120 --> 00:04:37,440 Speaker 1: walk up to the girl in high school and talk 92 00:04:37,480 --> 00:04:39,479 Speaker 1: to her because I couldn't text her because we didn't 93 00:04:39,520 --> 00:04:43,560 Speaker 1: have that. I don't know. But and why are there 94 00:04:43,600 --> 00:04:45,360 Speaker 1: more nos in the job market now than there were 95 00:04:45,360 --> 00:04:47,880 Speaker 1: when we were younger? I mean, I mean, how many 96 00:04:47,920 --> 00:04:49,720 Speaker 1: nos have I gotten in this business? I get them 97 00:04:49,720 --> 00:04:53,279 Speaker 1: every day still to this day. But there's an author 98 00:04:53,320 --> 00:04:55,640 Speaker 1: who said, it's not about entitlement, it's about gen z 99 00:04:55,800 --> 00:04:58,040 Speaker 1: growing up in a world where yes, seems more out 100 00:04:58,120 --> 00:05:00,880 Speaker 1: of reach than ever, despite how having more access to 101 00:05:00,960 --> 00:05:04,720 Speaker 1: opportunities think endless dating options at your fingertips get higher 102 00:05:04,800 --> 00:05:07,520 Speaker 1: rates of loneliness. Or sending out hundreds of job applications 103 00:05:07,560 --> 00:05:10,520 Speaker 1: with nothing but radio silence in return? Is that a 104 00:05:10,560 --> 00:05:13,400 Speaker 1: new thing? Though? I don't know. I'm am asking an 105 00:05:13,400 --> 00:05:16,120 Speaker 1: honest question. I'm not picking on anybody, but are there 106 00:05:16,160 --> 00:05:18,680 Speaker 1: really more nos now in the job market than there 107 00:05:18,680 --> 00:05:20,600 Speaker 1: ever have been? I mean, I. 108 00:05:20,520 --> 00:05:23,480 Speaker 4: Feel like because the way we get jobs now is different. 109 00:05:23,520 --> 00:05:26,640 Speaker 4: So now you can mass you know, fine on indeed 110 00:05:26,640 --> 00:05:29,360 Speaker 4: a thousand job opportunities and apply for all of them. 111 00:05:29,560 --> 00:05:31,560 Speaker 4: Back in the day, you had to know somebody or 112 00:05:31,600 --> 00:05:34,359 Speaker 4: have an internship, or you shot your shot at like 113 00:05:34,440 --> 00:05:36,279 Speaker 4: one job and works your way to get it. Now 114 00:05:36,320 --> 00:05:38,400 Speaker 4: they could shoot their shot at a million jobs. Yeah, 115 00:05:38,400 --> 00:05:38,880 Speaker 4: but it's old. 116 00:05:38,920 --> 00:05:41,640 Speaker 1: No, Kiki, If I send a thousand mass job you 117 00:05:41,640 --> 00:05:45,520 Speaker 1: know resumes out, one's you know, generic application to a 118 00:05:45,560 --> 00:05:47,880 Speaker 1: thousand places, and I know that's probably an exaggeration, but 119 00:05:47,920 --> 00:05:50,880 Speaker 1: let's say I do and and nine and ninety nine. 120 00:05:50,920 --> 00:05:52,960 Speaker 1: Tell me no, I don't see that as a rejection 121 00:05:53,000 --> 00:05:55,200 Speaker 1: because I didn't really invest myself in any of that. 122 00:05:55,360 --> 00:05:59,840 Speaker 4: Right, because you're you're fishing, You're normal, right, So they 123 00:06:00,080 --> 00:06:03,000 Speaker 4: illusional and aything that they deserve all one thousand jobs 124 00:06:03,040 --> 00:06:05,200 Speaker 4: that they applied for. Like I applied to be a 125 00:06:05,240 --> 00:06:07,960 Speaker 4: doctor yesterday. You know what I'm saying that I think. 126 00:06:07,880 --> 00:06:09,839 Speaker 1: You could do it. I mean, you're a judge, right, 127 00:06:09,920 --> 00:06:10,120 Speaker 1: you know. 128 00:06:10,240 --> 00:06:12,360 Speaker 4: It's that type of delusion that they had that our 129 00:06:12,400 --> 00:06:14,599 Speaker 4: generation and the ones before us we didn't have. We 130 00:06:14,640 --> 00:06:16,719 Speaker 4: lived in like a different reality because we were humbled 131 00:06:16,720 --> 00:06:17,120 Speaker 4: every day. 132 00:06:17,760 --> 00:06:19,560 Speaker 1: I mean, that might make it. I can see why 133 00:06:19,560 --> 00:06:22,320 Speaker 1: it might be harder to get a job because everyone's 134 00:06:22,400 --> 00:06:25,159 Speaker 1: doing that. So it may be harder for people to 135 00:06:25,839 --> 00:06:28,080 Speaker 1: if I'm a hiring manager and people are applying for 136 00:06:28,160 --> 00:06:30,200 Speaker 1: the job and they don't even know what they applied 137 00:06:30,240 --> 00:06:33,480 Speaker 1: for because it's because they just applied, Because then then 138 00:06:33,520 --> 00:06:36,200 Speaker 1: it might be harder for me to stand out than 139 00:06:36,240 --> 00:06:38,719 Speaker 1: it was before. Because like when I was applying for 140 00:06:38,800 --> 00:06:40,960 Speaker 1: radio jobs, I'm not even that old, but I mean 141 00:06:41,000 --> 00:06:44,120 Speaker 1: this was you know, early two thousands when I'm first 142 00:06:44,120 --> 00:06:45,640 Speaker 1: applying for radio jobs. The way you had to do 143 00:06:45,720 --> 00:06:48,080 Speaker 1: it was you had to make a CD, right, and 144 00:06:48,120 --> 00:06:50,320 Speaker 1: you had to type out a resume and a CD, 145 00:06:50,800 --> 00:06:52,159 Speaker 1: and then you had to figure out a way to 146 00:06:52,160 --> 00:06:54,200 Speaker 1: make that stand out, but you still had to put 147 00:06:54,200 --> 00:06:56,400 Speaker 1: it in a fed X envelope and send it to 148 00:06:56,520 --> 00:06:59,919 Speaker 1: a radio station. And I and then when I finally 149 00:07:00,080 --> 00:07:02,920 Speaker 1: got said jobs, and I was the guy receiving those things, 150 00:07:02,960 --> 00:07:05,760 Speaker 1: and I can remember there would be bins of these applications, 151 00:07:05,760 --> 00:07:08,120 Speaker 1: but there would be maybe thirty, and I thought that 152 00:07:08,240 --> 00:07:10,360 Speaker 1: was a lot. You know, We'd have like these bins 153 00:07:10,400 --> 00:07:12,600 Speaker 1: of envelopes of people who wanted jobs we didn't have, 154 00:07:13,000 --> 00:07:15,880 Speaker 1: and I would try, because I remember applying for them 155 00:07:15,920 --> 00:07:18,320 Speaker 1: and no one writing me back. I can remember, but 156 00:07:18,360 --> 00:07:20,080 Speaker 1: I knew they got it because it was FedEx so 157 00:07:20,080 --> 00:07:21,800 Speaker 1: you could put a little receipt on it. But I 158 00:07:22,840 --> 00:07:25,120 Speaker 1: remember trying to go through them all and at least 159 00:07:25,120 --> 00:07:27,840 Speaker 1: call them back. I had no ability to hire them, 160 00:07:27,920 --> 00:07:29,640 Speaker 1: I had no juice, but I just remember what it 161 00:07:29,680 --> 00:07:31,920 Speaker 1: was like to send the envelope and get nothing back. 162 00:07:31,920 --> 00:07:34,800 Speaker 1: I can remember. I remember this guy. There was a 163 00:07:34,840 --> 00:07:38,280 Speaker 1: guy in Louisville, Kentucky. I said, I made a I 164 00:07:38,320 --> 00:07:41,560 Speaker 1: took a bottle of Jack Daniels because it's Kentucky whiskey, 165 00:07:41,920 --> 00:07:42,960 Speaker 1: and I bless you. 166 00:07:43,360 --> 00:07:45,160 Speaker 3: I'm sorry I make it away from the mine. 167 00:07:45,240 --> 00:07:46,760 Speaker 1: I know you're not allergic to them because that's one 168 00:07:46,800 --> 00:07:50,280 Speaker 1: of your favorites show. And I made a custom label 169 00:07:50,680 --> 00:07:52,600 Speaker 1: for the front of the Jack Daniels bottle with my 170 00:07:52,760 --> 00:07:55,040 Speaker 1: face on it, my name and the whole thing, and 171 00:07:55,080 --> 00:07:56,360 Speaker 1: I put it on there and I sent it to 172 00:07:56,440 --> 00:07:58,640 Speaker 1: him and he never hooked me back. And I saw 173 00:07:58,720 --> 00:08:01,560 Speaker 1: him at a conference three years ago because he's still 174 00:08:01,560 --> 00:08:03,400 Speaker 1: in the business, and I go, do you remember when 175 00:08:03,440 --> 00:08:05,400 Speaker 1: I did that? He goes, yeah, thanks for the whiskey. 176 00:08:05,720 --> 00:08:07,600 Speaker 1: And I was like, you couldn't have answered. I go, 177 00:08:07,640 --> 00:08:09,120 Speaker 1: I go to anyone else do anything like that. He 178 00:08:09,200 --> 00:08:11,280 Speaker 1: was like no. I'm like, couldn't you have at least 179 00:08:11,560 --> 00:08:13,280 Speaker 1: called me and said I don't have a job for you. 180 00:08:13,320 --> 00:08:16,240 Speaker 1: But that was really creative than you. You know, it's 181 00:08:16,240 --> 00:08:18,680 Speaker 1: funny that you don't forget these things. But I guess 182 00:08:18,680 --> 00:08:21,760 Speaker 1: what I'm saying is if you're if you're swiping on 183 00:08:21,760 --> 00:08:24,440 Speaker 1: one hundred people on a dating app and nobody matches 184 00:08:24,480 --> 00:08:28,240 Speaker 1: with you, I don't necessarily think that's rejection because I 185 00:08:28,280 --> 00:08:31,720 Speaker 1: don't there's no investment. Yeah, you know, if I make it, 186 00:08:31,760 --> 00:08:33,840 Speaker 1: If I go ten rounds in an interview and don't 187 00:08:33,840 --> 00:08:37,720 Speaker 1: get the job, that's rejection. They decided they didn't want you. Now, 188 00:08:37,760 --> 00:08:41,720 Speaker 1: that sucks, but that's nothing new, right, That's what happened forever. 189 00:08:41,880 --> 00:08:43,880 Speaker 2: Well, I think now too. I listen to a whole 190 00:08:43,880 --> 00:08:46,040 Speaker 2: podcast episode yesterday about it was really interesting, and I 191 00:08:46,120 --> 00:08:48,240 Speaker 2: think what's going on to his AI, I think is 192 00:08:48,840 --> 00:08:52,439 Speaker 2: going through those applications and automatically disqualifying a lot of people. 193 00:08:52,480 --> 00:08:53,679 Speaker 2: So I think, oh, that's the. 194 00:08:53,640 --> 00:08:56,320 Speaker 1: Only way, right, because how can they possibly If everybody 195 00:08:56,400 --> 00:08:58,280 Speaker 1: on Earth who's looking for a job is just mass 196 00:08:58,320 --> 00:09:00,960 Speaker 1: applying for jobs correct, then how do they know which 197 00:09:00,960 --> 00:09:01,520 Speaker 1: you recommended? 198 00:09:01,559 --> 00:09:04,440 Speaker 2: They're like, don't mass apply, like make this personal, like 199 00:09:04,520 --> 00:09:06,920 Speaker 2: actually like do it the correct way. But people are 200 00:09:06,960 --> 00:09:09,120 Speaker 2: not gen Z, I'm talking to you, so then you know, 201 00:09:09,160 --> 00:09:11,960 Speaker 2: AI is just kind of like throwing them out basically 202 00:09:11,960 --> 00:09:14,360 Speaker 2: in the trash and it sucks. But also too, I 203 00:09:14,840 --> 00:09:16,360 Speaker 2: see on TikTok a lot of gen Z say that 204 00:09:16,400 --> 00:09:17,960 Speaker 2: it's hard to get a job, and I don't know 205 00:09:17,960 --> 00:09:19,920 Speaker 2: how true this is, but somebody said that even Trader 206 00:09:20,080 --> 00:09:23,040 Speaker 2: Joe's has like a list of people applying every day 207 00:09:23,120 --> 00:09:25,040 Speaker 2: and that they can't even hire. So I don't know, 208 00:09:25,080 --> 00:09:27,640 Speaker 2: I'm a job market expert, but it doesn't seem great, right, now. 209 00:09:28,000 --> 00:09:30,320 Speaker 4: No, I don't really. The market is crazy. I've heard 210 00:09:30,400 --> 00:09:32,920 Speaker 4: and think about it. Now they have fool companies that 211 00:09:33,320 --> 00:09:36,800 Speaker 4: all they do is scan through applications for other job 212 00:09:36,920 --> 00:09:37,600 Speaker 4: like for companies. 213 00:09:37,600 --> 00:09:39,120 Speaker 1: Oh yeah, you'll see it on TikTok all the time. 214 00:09:39,160 --> 00:09:42,000 Speaker 1: Ways to optimize your resume, so AI will pick up that, right, 215 00:09:42,240 --> 00:09:44,320 Speaker 1: you know and stuff. So I mean I would agree, 216 00:09:44,320 --> 00:09:48,880 Speaker 1: now you're competing with a new level of sophistication. But 217 00:09:49,000 --> 00:09:52,280 Speaker 1: I don't know that that means that you should feel 218 00:09:52,360 --> 00:09:55,080 Speaker 1: more rejected than any other generation who didn't get a 219 00:09:55,160 --> 00:09:58,199 Speaker 1: job either. I mean, because I guess every generation has 220 00:09:58,200 --> 00:10:00,960 Speaker 1: had challenges. Right. It used to be you couldn't even 221 00:10:00,960 --> 00:10:03,160 Speaker 1: apply online. You had to physically go to all these 222 00:10:03,160 --> 00:10:06,440 Speaker 1: places and fill out individual applications and whatever. You know, 223 00:10:06,480 --> 00:10:08,439 Speaker 1: So that was a challenge. But I guess that meant 224 00:10:08,480 --> 00:10:12,720 Speaker 1: there was less competition because everybody couldn't just push one button. 225 00:10:13,160 --> 00:10:14,959 Speaker 1: But I guess college is probably the same way. I 226 00:10:14,960 --> 00:10:17,880 Speaker 1: remember I had to fill out individual college applications for 227 00:10:18,000 --> 00:10:22,360 Speaker 1: every college. Yeah, now that felt like rejection because every 228 00:10:22,400 --> 00:10:25,040 Speaker 1: process was different everyone. I mean, there's some of the 229 00:10:25,559 --> 00:10:28,120 Speaker 1: essays you could reuse, but a lot of colleges wanted 230 00:10:28,200 --> 00:10:31,760 Speaker 1: different subject matters, so you had to write different essays. Then, 231 00:10:31,800 --> 00:10:33,760 Speaker 1: of course you had different levels of investment. I can 232 00:10:33,840 --> 00:10:37,040 Speaker 1: remember not getting into colleges I really thought I wanted 233 00:10:37,040 --> 00:10:39,760 Speaker 1: to go to and that felt terrible because you're rejecting me. 234 00:10:40,520 --> 00:10:43,520 Speaker 1: Somebody read that and looked through my grades and looked 235 00:10:43,520 --> 00:10:45,760 Speaker 1: through my resume and looked through my essays and decided 236 00:10:45,840 --> 00:10:48,920 Speaker 1: I wasn't good enough. But I'm not even that personal. 237 00:10:49,080 --> 00:10:49,480 Speaker 1: I don't know. 238 00:10:49,600 --> 00:10:51,160 Speaker 3: I mean, you never had the thought like, oh, I'm 239 00:10:51,160 --> 00:10:54,120 Speaker 3: getting rejected more than like Susie down the hall, did 240 00:10:54,160 --> 00:10:56,280 Speaker 3: you like? I would never think like that. I mean, 241 00:10:56,480 --> 00:10:58,960 Speaker 3: I know they have people like designated when you're applying 242 00:10:59,000 --> 00:11:01,120 Speaker 3: to like combing through your social and that's got to 243 00:11:01,160 --> 00:11:04,040 Speaker 3: be an issue these days. But I just I don't 244 00:11:04,040 --> 00:11:06,600 Speaker 3: know how we can quantify the amount of rejection each 245 00:11:06,679 --> 00:11:09,319 Speaker 3: generation gets. I just think every other generation never had 246 00:11:09,320 --> 00:11:11,560 Speaker 3: the thought like I'm getting it worse. 247 00:11:12,160 --> 00:11:13,240 Speaker 2: Good point, you know what I mean? 248 00:11:13,440 --> 00:11:15,640 Speaker 1: Somebody said he didn't respond because Jack's made in Tennessee 249 00:11:15,760 --> 00:11:18,240 Speaker 1: at Kentucky. I think I don't. I don't. Maybe it 250 00:11:18,320 --> 00:11:20,360 Speaker 1: was a Tennessee job. I don't know, I don't know. 251 00:11:20,400 --> 00:11:22,760 Speaker 1: That's that's the point he put. 252 00:11:22,600 --> 00:11:23,640 Speaker 3: His last twenty dollars. 253 00:11:23,640 --> 00:11:26,680 Speaker 1: On the point is, I couldn't afford to do any 254 00:11:26,720 --> 00:11:29,360 Speaker 1: of this, and I don't know when I became a 255 00:11:29,400 --> 00:11:33,120 Speaker 1: photoshop expert to make the label. That's the point. The 256 00:11:33,160 --> 00:11:35,680 Speaker 1: point is, I guess I know that nobody else did that, 257 00:11:36,160 --> 00:11:38,480 Speaker 1: so at least take one second to call me and go, 258 00:11:38,520 --> 00:11:42,000 Speaker 1: your tape sucked. But that was really that was her creative. 259 00:11:42,160 --> 00:11:44,439 Speaker 1: But maybe maybe that's what happened. Maybe that's what happened. 260 00:11:45,080 --> 00:11:47,240 Speaker 1: Critics say that gen Z was never taught how to lose, 261 00:11:47,960 --> 00:11:49,960 Speaker 1: was raised in a culture where everybody is a winner, 262 00:11:50,240 --> 00:11:52,839 Speaker 1: and now in the real world, the crash is hard. Okay, 263 00:11:53,160 --> 00:11:53,520 Speaker 1: I don't know. 264 00:11:53,679 --> 00:11:56,440 Speaker 3: Maybe I mean my sister's getting rejected right now for internship. 265 00:11:56,480 --> 00:11:58,319 Speaker 3: She's applying and I've never heard her saying, I mean, 266 00:11:58,320 --> 00:12:00,960 Speaker 3: she's bombed, but she moves on. She's like, you know, 267 00:12:01,320 --> 00:12:02,800 Speaker 3: I learned something in every interview. 268 00:12:03,040 --> 00:12:04,640 Speaker 1: See But you were saying she's getting to like three 269 00:12:04,760 --> 00:12:07,400 Speaker 1: rounds of interviews, and I would argue that is a rejection. 270 00:12:07,480 --> 00:12:09,440 Speaker 1: Now I'm not saying she's not good enough, but what. 271 00:12:09,360 --> 00:12:11,640 Speaker 3: I mean is it hurts to make the final round. 272 00:12:11,679 --> 00:12:14,240 Speaker 1: Yes, Like if I send an application and you don't 273 00:12:14,240 --> 00:12:17,240 Speaker 1: write me back or I or I swipe right on 274 00:12:17,280 --> 00:12:19,880 Speaker 1: you simply and you don't swipe right on me. I 275 00:12:19,880 --> 00:12:21,880 Speaker 1: don't see that as a rejection. You don't know me 276 00:12:22,480 --> 00:12:26,040 Speaker 1: from anything. Now, if I interviewed three times for a 277 00:12:26,160 --> 00:12:29,480 Speaker 1: job and then you say I want somebody else, now 278 00:12:29,559 --> 00:12:32,280 Speaker 1: that I can understand that that's rejection. That's them saying 279 00:12:32,400 --> 00:12:34,480 Speaker 1: someone else is better than you. Yeah, And I don't 280 00:12:34,480 --> 00:12:35,560 Speaker 1: think that's a terrible thing. 281 00:12:35,720 --> 00:12:37,840 Speaker 3: And she, I will say, like she takes it better 282 00:12:37,840 --> 00:12:40,600 Speaker 3: based on she works with recruiters, so like some recruiters 283 00:12:40,640 --> 00:12:42,760 Speaker 3: are really great at telling her like why she may 284 00:12:42,760 --> 00:12:45,000 Speaker 3: not have gotten it and talking her through like this 285 00:12:45,080 --> 00:12:47,000 Speaker 3: is not about you personally, there was someone a little 286 00:12:47,000 --> 00:12:49,560 Speaker 3: more qualified, Like she like takes it better than if 287 00:12:49,600 --> 00:12:51,640 Speaker 3: someone just like goes her and then is like, sorry, 288 00:12:51,640 --> 00:12:53,600 Speaker 3: someone else got the job. You know, because she's putting 289 00:12:53,600 --> 00:12:56,040 Speaker 3: time in these interviews. But she's never once said like 290 00:12:56,320 --> 00:12:57,960 Speaker 3: this is worse than when you were going through it. 291 00:12:58,040 --> 00:13:03,840 Speaker 1: You know, maybe the JEB was a Knox whatever twenty 292 00:13:03,880 --> 00:13:06,360 Speaker 1: two years ago, And I promise you I was considerate 293 00:13:06,360 --> 00:13:09,520 Speaker 1: about what I was doing. I don't know, it doesn't 294 00:13:09,720 --> 00:13:12,480 Speaker 1: I didn't. I thought it was clever men who I'll 295 00:13:12,480 --> 00:13:15,040 Speaker 1: finish these headlines quickly. Men who regularly use cannabis or 296 00:13:15,120 --> 00:13:23,040 Speaker 1: synthetic cannabinoids cannabinoids okay reports significantly lower sexual satisfaction, desire, 297 00:13:23,080 --> 00:13:28,080 Speaker 1: and erectile function compared to non users. Hmmm, I don't know. 298 00:13:28,800 --> 00:13:31,480 Speaker 1: I'm doing all right, Thank you, Thanks for going fine 299 00:13:31,600 --> 00:13:34,240 Speaker 1: in that area. I don't know if I agree with that. 300 00:13:34,960 --> 00:13:37,200 Speaker 1: I feel like if i'm you know, hypothetically, if I 301 00:13:37,200 --> 00:13:41,400 Speaker 1: had a little bit of a right the sensation is 302 00:13:41,440 --> 00:13:44,760 Speaker 1: actually a little I don't know about that from what 303 00:13:44,800 --> 00:13:48,520 Speaker 1: I've heard. Allegedly, there's a phone case that flips over 304 00:13:48,600 --> 00:13:52,040 Speaker 1: when it hear's the word cheers. Heineken has created what 305 00:13:52,080 --> 00:13:54,720 Speaker 1: they're calling the Flipper. It's a phone case which flips 306 00:13:54,760 --> 00:13:57,719 Speaker 1: your phone face down so you don't get distracted by 307 00:13:57,760 --> 00:14:01,480 Speaker 1: socials when you're out socializing. It uses AI trained listening 308 00:14:01,520 --> 00:14:05,520 Speaker 1: tools connected to a robotic arm to flip the phone 309 00:14:05,559 --> 00:14:08,640 Speaker 1: nestled inside it when it senses the word cheers, a 310 00:14:08,720 --> 00:14:12,199 Speaker 1: universal sign that you're out having in person conversation. It's 311 00:14:12,200 --> 00:14:14,080 Speaker 1: a prototype for now, but the idea, of course is 312 00:14:14,080 --> 00:14:16,920 Speaker 1: that you wouldn't be distracted by your phone, which the 313 00:14:17,000 --> 00:14:19,800 Speaker 1: kiki would just flip it back over so it wouldn't work. 314 00:14:19,800 --> 00:14:22,760 Speaker 1: And a guy who is four feet three inches tall 315 00:14:22,920 --> 00:14:25,560 Speaker 1: is believed to be the world's oldest person after he 316 00:14:25,600 --> 00:14:28,600 Speaker 1: turned one hundred and twenty five on Saturday, April fifth. 317 00:14:29,400 --> 00:14:34,160 Speaker 1: This guy lives in Peru. His name is Mashiko and 318 00:14:34,680 --> 00:14:37,360 Speaker 1: that's what his government issued photo says, and it lists 319 00:14:37,400 --> 00:14:40,920 Speaker 1: his birth year is nineteen hundred. The old and tiny 320 00:14:40,960 --> 00:14:43,200 Speaker 1: man was orphan at the age of seven after his 321 00:14:43,240 --> 00:14:45,880 Speaker 1: parents tragically died while trying to cross the river in 322 00:14:45,960 --> 00:14:48,680 Speaker 1: nineteen oh seven. The guy worked in the fields from 323 00:14:48,720 --> 00:14:50,920 Speaker 1: a young age, unable to attend school because the closest 324 00:14:50,960 --> 00:14:53,120 Speaker 1: one was too far away. During his time working in 325 00:14:53,160 --> 00:14:57,800 Speaker 1: the fields, he reared animals and bartered farm goods. He 326 00:14:57,960 --> 00:15:01,080 Speaker 1: never had a partner or children, lived a simple, solitary 327 00:15:01,240 --> 00:15:04,080 Speaker 1: and self sufficient life. But apparently he's one hundred and 328 00:15:04,120 --> 00:15:07,480 Speaker 1: twenty five years old. I'm all sad. My goodness, I 329 00:15:07,520 --> 00:15:10,080 Speaker 1: think a nice eighty five ninety would be And at 330 00:15:10,080 --> 00:15:12,920 Speaker 1: this rate, I'm not even sure about maybe a nice 331 00:15:13,120 --> 00:15:15,440 Speaker 1: if I could live, If I could live healthfully to 332 00:15:15,520 --> 00:15:17,720 Speaker 1: about eighty and then I just dropped dead. 333 00:15:17,880 --> 00:15:20,760 Speaker 4: Oh don't say that. Eighties, young, Yeah, I still need 334 00:15:20,760 --> 00:15:24,040 Speaker 4: to get it in at eighty get it in? Yeah, 335 00:15:24,360 --> 00:15:25,640 Speaker 4: oh lord, he is young. 336 00:15:27,080 --> 00:15:27,600 Speaker 3: I agree. 337 00:15:28,200 --> 00:15:30,040 Speaker 1: Okay, well you know what I mean. At one hundred 338 00:15:30,040 --> 00:15:32,520 Speaker 1: and twenty five, I think I'm probably good. I'll set 339 00:15:32,520 --> 00:15:35,960 Speaker 1: with them. It's National Library Workers Day, National Mpanada Day, 340 00:15:36,080 --> 00:15:39,080 Speaker 1: and National Zoo Lover's Day. The Entertainer Report, blogs and 341 00:15:39,320 --> 00:15:41,680 Speaker 1: Stay or Go will debate some relationship drama all next 342 00:15:41,720 --> 00:15:42,240 Speaker 1: Friend Show