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Drilled by somebody's dad💦🤤 PT.3/final part ft. 🚾Alterverse 📸: PAPs 🇵🇭 (PH Alter Productions) 🎥 full videos on my jff: subscribe on my tg channel:

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238,074 görüntüleme • 5 ay önce •via X (Twitter)

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Confederate monuments stand across the South, but many trace back to the efforts of one influential organization: the United Daughters of the Confederacy. Beyond funding memorials, the group helped shape how the Civil War was taught in schools and remembered by generations of Americans. The AJC's Koralie Barrau explores how the organization's influence became part of the broader Lost Cause movement and why the debate continues today. 👉 : To learn more about the bigger impact of the UDC, watch the full Southern identity episode of "Curiosities of the South" now on the AJC's YouTube channel — and subscribe for more in-depth stories shaping the region. 🎥: AJC | | WSLS-TV News Film Collection, Trimmed from Original | WXIA-TV 📸: Getty Images | Historic Photographs Collection, Daviess County Public Library | Library of Congress | Richmond Times-Dispatch | St. Louis Post-Dispatch | Tennessee State Library and Archives | The Selma Times-Journal | The Times-Picayune | The Virginian-Pilot | United Daughters of the Confederacy

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How to create Farcaster mini app without coding - Step 1: > Go to ChatGPT > Just type: "I would like to create a Farcaster mini app, can you give me some ideas?" > Choose any one of the ideas - Note: - You can also type your own idea to ChatGPT and alter it - Step 2: - Go to ChatGPT > Paste the first prompt (shared in my channel) > Include the project you chose and tell ChatGPT to alter the prompt according to the idea below - Step 3 - Go to: > Sign up using Gmail or GitHub > Projects -> New Project -> Type the name of your project >Just paste the prompt we created earlier > It will start creating your app > If you need to alter anything, just go to GPT and type: [ I need a prompt to alter "your issue (like changing colour, etc.)" in my app already created in v0app by Vercel ] > Copy the prompt and paste it in v0 > No need to worry about errors , it will rectify them for you > If your project is finished, just click "Publish" on your top right > It will automatically host your app in Vercel > Click "Visit site" to see your app on another device and copy the website URL - Step 4 - Go to: v0 app > Just paste Prompt 2 from the file I provided > Click Publish once it’s completed - Step 5 - Go to: v0 app > Just paste the prompt 3 from the file I provided - Step 6 (Important) > Just paste Prompt 4 from the file I provided - Step 7 > Just paste Prompt 4 from the file I provided - Step 8 > Just paste Prompt 6 from the file I provided > It’s an important step to do — you need to create a manifest inside your app so that you can host it on Farcaster - Step 9 - Go to: > Sign up or Login > Settings → Developers → Mini Apps → Create Manifest (New) > Paste your website URL (remove https) > It should be like: > If you find any error while doing this, just copy and paste it in the v0 app > Once everything is finished, you need to create Account Association > Scan the QR on your mobile and tap and hold the Yes button > It will show an error — just copy and paste those errors into the v0 app > Click Publish again, and then click Refresh in Manifest > Click Open your app > for the main prompt file check our tg channel link in our bio

Maran

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DUSK TILL DAWN OFFICIAL MUSIC VIDEO OUT 🔥😘🔥 You guys know how i like to have open endings to my videos. I wrote and rewrote this script for almost 3 months trying to figure out the right amount of confusion 😵‍💫 so i hope ya’ll have fun with it 😊😎 Big thank you to my amazing co-director Addy Chan for being a boss LOVE YA SIS. When Jawn Ha recommended @JoesarAlva to choreograph, YES DUH OF COURSE JOESAR. Thank you Joesar and Eileen for really getting me out of my comfort zone for being the best dance partners ever! Big love to Key to for making sure everything was running smooth and that i was awake 😴 and John for running with us at full speed and capturing everything and for letting JackJack hang out with Gumi! Thank you to everyone on set who helped make this video happen! WE MAKING ART!! 😜 (me every 10 minutes on set) LASTLY THANK YOU 🫵 FOR ALL THE LOVE FOR DUSK TILL DAWN ILL SEE YOU GUYS ON TOUR IN 2 DAYS!!! Directed by: Amber Liu & Addy Chan Produced by: Addy Chan & Zachary Keomysay Director of photography: John Kim Choreography by: Joesar Alva Dancers: Eileen Harman & Joesar Alva AD: Zachary Keomysay AC: Ryan Hasegawa Gaffer/Bartender: Chad Mayate Glam: Yuki Mitsuhashi Editor: John Kim PA: Charles Nguyen & Lara Deluna BTS: Ben Zhao Vibe Setter: Leo Matsuyama Special Thanks: THE KINJAZ & VIBRVNCY 🎥🔗: 🎧🔂
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DUSK TILL DAWN OFFICIAL MUSIC VIDEO OUT 🔥😘🔥 You guys know how i like to have open endings to my videos. I wrote and rewrote this script for almost 3 months trying to figure out the right amount of confusion 😵‍💫 so i hope ya’ll have fun with it 😊😎 Big thank you to my amazing co-director Addy Chan for being a boss LOVE YA SIS. When Jawn Ha recommended @JoesarAlva to choreograph, YES DUH OF COURSE JOESAR. Thank you Joesar and Eileen for really getting me out of my comfort zone for being the best dance partners ever! Big love to Key to for making sure everything was running smooth and that i was awake 😴 and John for running with us at full speed and capturing everything and for letting JackJack hang out with Gumi! Thank you to everyone on set who helped make this video happen! WE MAKING ART!! 😜 (me every 10 minutes on set) LASTLY THANK YOU 🫵 FOR ALL THE LOVE FOR DUSK TILL DAWN ILL SEE YOU GUYS ON TOUR IN 2 DAYS!!! Directed by: Amber Liu & Addy Chan Produced by: Addy Chan & Zachary Keomysay Director of photography: John Kim Choreography by: Joesar Alva Dancers: Eileen Harman & Joesar Alva AD: Zachary Keomysay AC: Ryan Hasegawa Gaffer/Bartender: Chad Mayate Glam: Yuki Mitsuhashi Editor: John Kim PA: Charles Nguyen & Lara Deluna BTS: Ben Zhao Vibe Setter: Leo Matsuyama Special Thanks: THE KINJAZ & VIBRVNCY 🎥🔗: 🎧🔂

Amber Liu 刘逸云

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David Sacks just dismantled the narrative behind Jacob Coxon’s 166M+ view tweet, the ex-Anthropic and OpenAI researcher who resigned. it was a planned “doomer op.” "This is an X account that had almost no activity, almost no followers, and no posts prior to this resignation tweetstorm. If he did have prior posts, they were scrubbed. So, this was a completely blank account, and somehow, within a day, it finds this huge audience. Elon has said it never happened before. And we also know who amplified it in the first 15 minutes. So, there were basically 3 of these well-organized, well-funded doomer groups who amplified it. ... This is a tight-knit community that jumped on this tweet. This was not some spontaneous act by an employee who said, “Oh, I’m just going to post my resignation letter on Twitter.” This was something that was orchestrated. And then, just the final piece of evidence on this point is that someone looked at the Wall Street Journal story that covered the resignation letter, and somehow it was posted minutes before the tweetstorm itself." ---- From "All-In Podcast" YouTube channel, (full video link in comment)
2:45

David Sacks just dismantled the narrative behind Jacob Coxon’s 166M+ view tweet, the ex-Anthropic and OpenAI researcher who resigned. it was a planned “doomer op.” "This is an X account that had almost no activity, almost no followers, and no posts prior to this resignation tweetstorm. If he did have prior posts, they were scrubbed. So, this was a completely blank account, and somehow, within a day, it finds this huge audience. Elon has said it never happened before. And we also know who amplified it in the first 15 minutes. So, there were basically 3 of these well-organized, well-funded doomer groups who amplified it. ... This is a tight-knit community that jumped on this tweet. This was not some spontaneous act by an employee who said, “Oh, I’m just going to post my resignation letter on Twitter.” This was something that was orchestrated. And then, just the final piece of evidence on this point is that someone looked at the Wall Street Journal story that covered the resignation letter, and somehow it was posted minutes before the tweetstorm itself." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

Rohan Paul

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My fox shooting garden defending AI robot is finally done and WORKING! 🤩 (Don’t worry it only shoots 💦 water) After months of slowly moving forward with each part I finished the last step to train a TensorFlow model on the footage of the 🦊 fox I collected hours of footage 📹 with the fox roaming around my garden, from this I labeled around 2000 images with the fox by hand ✋ Honestly, I was quite skeptical training the model was actually gonna work, maybe this was partly the reason I avoided working on this until the very end. If I couldn’t train a model to detect the fox, this whole robot would never be able to function properly. On the flipside though, with no previous experience in hardware or electronics there was a bit of a learning curve and I didn’t want to end up labeling thousands of images, training a TensorFlow model, only to fail on building the hardware. As I started building, I realized that mixing hardware and software adds quite another dimension to debugging things. At times I wasted hours debugging code in my IDE, only to realize the issue was somewhere in the electronics. Furthermore, combining this side project with a full time job and a young family, is not always easy. It can be quite frustrating, to know you only need 4 hours of concentrated effort for a small task, having to spread it out across a week of 20min increments. Then, a few months into the build I noticed the fox had stopped coming to my garden, in fact one day, I recorded her walking with 3 cute little 🐶 pups, and the next day I saw her moving out of my garden completely. Did she know I was building a robot? I had this strange mix of feelings, happy my garden was safe from poop and digging, happy she was safe with her pups, but how was I gonna finish this project if my robot had no fox to detect? For sure they would be back next year, I figured I could postpone the whole thing until next winter, but I also knew it was gonna be much harder to pick up momentum if I did let it sit there for six months. So I decided to keep working, hoping the fox would reappear,.. but she never did. As I finished labeling the footage and started training my model, I could finally see the mAP results, quantifying the precision of my object detection model. It was measuring at 78% across different metrics on detecting my fox. I quickly ran the model on some of the video footage I got from my fox. Inference speed took a hit, but it did a near perfect job detecting the fox, even when she was deep down in the grass or wizzing past in a motion blur. It took me by surprise how well it worked. With the default model I had to drop my confidence threshold way down to 15%, to recognize the fox as 🦜“bird” in one or two frames, with my custom model it followed the fox all the way down to the back of the garden! Still this didn’t solve the issue of there being no actual fox in my garden and how was I gonna wrap this project in a short timeframe. I played with the idea of putting a fox toy 🧸 on an RC 🚗 car, or borrowing a dog to run around the garden to test. Friends suggested I run around the garden in a fox costume.. what a ridiculous idea. I wasn’t really feeling the idea of running around the garden in a floppy cloth fox 🎭 costume, but had a look anyway. I came across these self inflating costumes. This actually could be perfect. Since it’s inflated, it would hold its shape super well, making it much easier to label, train and be recognized by my robot. So I got the costume and shot a time lapse of myself as a fox walking around the garden. I labeled it to around 600 images. Ran the model training again and got a mAP result of 82%. This was even better than my real fox! At this point I knew this was gonna work. So here’s the final 🎥 video, just having some fun with it. I’ll update here whenever the real fox does come back. On a final note, I’m looking for (remote) jobs in these fields of AI now: - object detection - visual generative AI - 3D (nerfs + gaussian splats) So if you know anything let me know! My DMs are open 😊
2:05

My fox shooting garden defending AI robot is finally done and WORKING! 🤩 (Don’t worry it only shoots 💦 water) After months of slowly moving forward with each part I finished the last step to train a TensorFlow model on the footage of the 🦊 fox I collected hours of footage 📹 with the fox roaming around my garden, from this I labeled around 2000 images with the fox by hand ✋ Honestly, I was quite skeptical training the model was actually gonna work, maybe this was partly the reason I avoided working on this until the very end. If I couldn’t train a model to detect the fox, this whole robot would never be able to function properly. On the flipside though, with no previous experience in hardware or electronics there was a bit of a learning curve and I didn’t want to end up labeling thousands of images, training a TensorFlow model, only to fail on building the hardware. As I started building, I realized that mixing hardware and software adds quite another dimension to debugging things. At times I wasted hours debugging code in my IDE, only to realize the issue was somewhere in the electronics. Furthermore, combining this side project with a full time job and a young family, is not always easy. It can be quite frustrating, to know you only need 4 hours of concentrated effort for a small task, having to spread it out across a week of 20min increments. Then, a few months into the build I noticed the fox had stopped coming to my garden, in fact one day, I recorded her walking with 3 cute little 🐶 pups, and the next day I saw her moving out of my garden completely. Did she know I was building a robot? I had this strange mix of feelings, happy my garden was safe from poop and digging, happy she was safe with her pups, but how was I gonna finish this project if my robot had no fox to detect? For sure they would be back next year, I figured I could postpone the whole thing until next winter, but I also knew it was gonna be much harder to pick up momentum if I did let it sit there for six months. So I decided to keep working, hoping the fox would reappear,.. but she never did. As I finished labeling the footage and started training my model, I could finally see the mAP results, quantifying the precision of my object detection model. It was measuring at 78% across different metrics on detecting my fox. I quickly ran the model on some of the video footage I got from my fox. Inference speed took a hit, but it did a near perfect job detecting the fox, even when she was deep down in the grass or wizzing past in a motion blur. It took me by surprise how well it worked. With the default model I had to drop my confidence threshold way down to 15%, to recognize the fox as 🦜“bird” in one or two frames, with my custom model it followed the fox all the way down to the back of the garden! Still this didn’t solve the issue of there being no actual fox in my garden and how was I gonna wrap this project in a short timeframe. I played with the idea of putting a fox toy 🧸 on an RC 🚗 car, or borrowing a dog to run around the garden to test. Friends suggested I run around the garden in a fox costume.. what a ridiculous idea. I wasn’t really feeling the idea of running around the garden in a floppy cloth fox 🎭 costume, but had a look anyway. I came across these self inflating costumes. This actually could be perfect. Since it’s inflated, it would hold its shape super well, making it much easier to label, train and be recognized by my robot. So I got the costume and shot a time lapse of myself as a fox walking around the garden. I labeled it to around 600 images. Ran the model training again and got a mAP result of 82%. This was even better than my real fox! At this point I knew this was gonna work. So here’s the final 🎥 video, just having some fun with it. I’ll update here whenever the real fox does come back. On a final note, I’m looking for (remote) jobs in these fields of AI now: - object detection - visual generative AI - 3D (nerfs + gaussian splats) So if you know anything let me know! My DMs are open 😊

Jeroen Pixel

55,797 görüntüleme • 2 yıl önce

Full-Time Work, Real Pay Raises: How Trump Quietly Rebuilt the Job Market | E.J. Antoni “America’s Job Market Has Entered the Slow Lane”—that was a recent Wall Street Journal headline. Most of the mainstream media echoes this interpretation, but the reality is much better than the headlines suggest. In fact, it’s as if the reporters who wrote those headlines didn’t read beyond the headline of the jobs report. Here’s what the Dec. 2025 jobs report actually showed: ✅People working multiple part-time jobs exchanged them for single full-time jobs in December. ✅During nearly the entire final year of the Biden admin, annual native-born employment was in the red. In 2025, native-born employment beat foreign-born employment by over 1.6 million. ✅The federal workforce is the smallest it’s been since 2014. “So, despite all the naysayers, Trump’s first year back at the helm saw a labor market undergo badly needed structural changes that are making Americans better off… If we keep up with tax reform, regulatory reform, and energy reform, economic growth will turn into a rocket sled on rails," argues Heritage Foundation Chief Economist E.J. Antoni, Ph.D. on his latest video commentary with The Daily Signal. (00:00) Introduction: Trump's Economic Impact (00:50) Media Misinterpretation of Job Market (01:10) Positive Employment Data (03:07) Shift from Part-Time to Full-Time Jobs (05:07) Private Sector Job Growth (06:01) Manufacturing Sector Trends (07:00) Wage Growth and Inflation (07:40) Conclusion: Economic Optimism For more videos like this, subscribe to The Daily Signal’s YouTube channel and enable notifications to be alerted the second a new video drops: ⁠ ⁠
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Full-Time Work, Real Pay Raises: How Trump Quietly Rebuilt the Job Market | E.J. Antoni “America’s Job Market Has Entered the Slow Lane”—that was a recent Wall Street Journal headline. Most of the mainstream media echoes this interpretation, but the reality is much better than the headlines suggest. In fact, it’s as if the reporters who wrote those headlines didn’t read beyond the headline of the jobs report. Here’s what the Dec. 2025 jobs report actually showed: ✅People working multiple part-time jobs exchanged them for single full-time jobs in December. ✅During nearly the entire final year of the Biden admin, annual native-born employment was in the red. In 2025, native-born employment beat foreign-born employment by over 1.6 million. ✅The federal workforce is the smallest it’s been since 2014. “So, despite all the naysayers, Trump’s first year back at the helm saw a labor market undergo badly needed structural changes that are making Americans better off… If we keep up with tax reform, regulatory reform, and energy reform, economic growth will turn into a rocket sled on rails," argues Heritage Foundation Chief Economist E.J. Antoni, Ph.D. on his latest video commentary with The Daily Signal. (00:00) Introduction: Trump's Economic Impact (00:50) Media Misinterpretation of Job Market (01:10) Positive Employment Data (03:07) Shift from Part-Time to Full-Time Jobs (05:07) Private Sector Job Growth (06:01) Manufacturing Sector Trends (07:00) Wage Growth and Inflation (07:40) Conclusion: Economic Optimism For more videos like this, subscribe to The Daily Signal’s YouTube channel and enable notifications to be alerted the second a new video drops: ⁠ ⁠

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