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He couldn't hold it and shot a huge load.🤩🤩👅 #bbcflash #bbcflashing #dickflash #publicflash #publiccum #cockflash #publicnude #public_nudity #nudedick #publicdickflash #mallflash #mallflashtv

Dick Flash TV

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21,595 次观看 • 3 个月前 •via X (Twitter)

NSFW #bbcflash #bbcflashing #dickflash #publicflash #publiccum #cockflash #publicnude #public_nudity #nudedick #publicdickflash #mallflash #mallflashtv

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A 28 shot rally to break and he finished it like that 🤩 Bravo, Nuno 👏 #EstorilOpen

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Tennis TV

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The hospitality of the American South is unmatched 🤩 Back in Atlanta, my friend Andy showed us around Buckhead. As owner of the SpringHill Suites by Marriott Buckhead and proud of the area, he wanted to give us a special introduction to it. Along with our new friend Robert, we watched the first semi-final at Fadó Irish Pub, visited the exclusive Chops Steakhouse Club speakeasy where I smoked my first-ever cigar. Another night, we enjoyed cocktails at Garden Room, dinner at the incredible Umi, and finished the night in Umi’s hidden speakeasy. I’ve rarely felt so welcome in a new place. Huge thanks to Andy Chopra, Robert and everyone we met in Buckhead, Atlanta. What a city! 🇺🇸

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Back in March, Fede Gomez had hit rock bottom. He was on a huge losing streak and in a very dark place mentally, opening up in an emotional letter to his fans (posted below) about how he was not only considering retiring from tennis, but had even reached the point of contemplating suicide. Today, he just made the US Open main draw for the first time in his career. He came into Queens with major fitness and health concerns, having not played in over a month after being forced to retire with an injury vs Pavlovic. Qualifying for the main draw was a long shot, to say the least. In Round 1, he shocked Klein as a +550 underdog. In Round 2, he pulled another upset against rising star Cina as a +240 dog. In Round 3, he was down a set and 0-4 to Grenier The feel-good story of the tournament had almost surely come to a painful end. But Fede fought. With his back against the wall, he stormed back to win five of the next six games, miraculously getting the match back on serve Grenier managed to stop the bleeding at 5-5 and again put Gomez right up against it, needing a hold to keep his US Open dream alive He stared down match point at 5-6 30-40, one false move away from going home But Fede fought. And fought. Until he found himself celebrating in front of the frenzied crowd on Court 10, taking it all in after having completed the unlikeliest of comebacks to cap off one of the most magical qualifying runs you’ll ever see Look how much it means. This was so much more than just a match It was undeniable proof of why you never, EVER give up. Tennis is the greatest sport in the world 🥲

Back in March, Fede Gomez had hit rock bottom. He was on a huge losing streak and in a very dark place mentally, opening up in an emotional letter to his fans (posted below) about how he was not only considering retiring from tennis, but had even reached the point of contemplating suicide. Today, he just made the US Open main draw for the first time in his career. He came into Queens with major fitness and health concerns, having not played in over a month after being forced to retire with an injury vs Pavlovic. Qualifying for the main draw was a long shot, to say the least. In Round 1, he shocked Klein as a +550 underdog. In Round 2, he pulled another upset against rising star Cina as a +240 dog. In Round 3, he was down a set and 0-4 to Grenier The feel-good story of the tournament had almost surely come to a painful end. But Fede fought. With his back against the wall, he stormed back to win five of the next six games, miraculously getting the match back on serve Grenier managed to stop the bleeding at 5-5 and again put Gomez right up against it, needing a hold to keep his US Open dream alive He stared down match point at 5-6 30-40, one false move away from going home But Fede fought. And fought. Until he found himself celebrating in front of the frenzied crowd on Court 10, taking it all in after having completed the unlikeliest of comebacks to cap off one of the most magical qualifying runs you’ll ever see Look how much it means. This was so much more than just a match It was undeniable proof of why you never, EVER give up. Tennis is the greatest sport in the world 🥲

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I revived my 14-year-old dog with peptides. 6 months ago, he was slowing down fast. He was limping, achy, getting up slowly, and couldn't jump on the couch. We honestly didn't know if we had 6 months left with him. Today, our boy is running, jumping on the patio, going on long walks again, and even his hearing is back. I approached his protocol the same way I'd approach mine. - We started with BPC-157 and TB-500. 1-2 mg a day, 5 days on, 2 days off, injected basically the same way you'd inject a human. Within a couple of weeks, we saw less limping, less stiffness, he was moving better, etc. - Then we ran his labs the same way I run mine. Everything looked good except some minor kidney markets, and at his age kidney issues can spiral into problems dogs don't come back from. We addressed this with a bioregulator stack, again the same ones I use. - Then we put him on TRT. We're all aware of what happens to men when testosterone tanks with age. Now consider that we neuter our dogs, cut off their testosterone production entirely, and never think about it again. We put our boy on testosterone and the change was immediate. Within days of the first shot he became a different dog. We started with one shot a week, but just like in humans, by day 5 or 6 the levels drop and you get peaks and troughs. So we split it into two shots a week: Tuesday and Friday. We started conservatively, around 20mg per shot, and titrated up from there based on how he responded and how his labs looked. We landed at about 60mg total per week for a 70 pound dog, keeping a close eye on labs the whole way. That made a huge difference. Shot day is like a revival for him. ... And it's not just us, in fact other families are running the same protocol and seeing similar results. 6 months ago we were counting the time we had left with him. My kids were horrified by the thought that he would no longer be there as they grew up with him as their full-time guardian. Now I genuinely believe we have another 3 years. If you have a dog, understand that he's aging the same way you are. He needs help, but he can't do the research... you can! And after seeing what this protocol did for him, I knew other dog owners deserved access to it too, so check the tweet below.

I revived my 14-year-old dog with peptides. 6 months ago, he was slowing down fast. He was limping, achy, getting up slowly, and couldn't jump on the couch. We honestly didn't know if we had 6 months left with him. Today, our boy is running, jumping on the patio, going on long walks again, and even his hearing is back. I approached his protocol the same way I'd approach mine. - We started with BPC-157 and TB-500. 1-2 mg a day, 5 days on, 2 days off, injected basically the same way you'd inject a human. Within a couple of weeks, we saw less limping, less stiffness, he was moving better, etc. - Then we ran his labs the same way I run mine. Everything looked good except some minor kidney markets, and at his age kidney issues can spiral into problems dogs don't come back from. We addressed this with a bioregulator stack, again the same ones I use. - Then we put him on TRT. We're all aware of what happens to men when testosterone tanks with age. Now consider that we neuter our dogs, cut off their testosterone production entirely, and never think about it again. We put our boy on testosterone and the change was immediate. Within days of the first shot he became a different dog. We started with one shot a week, but just like in humans, by day 5 or 6 the levels drop and you get peaks and troughs. So we split it into two shots a week: Tuesday and Friday. We started conservatively, around 20mg per shot, and titrated up from there based on how he responded and how his labs looked. We landed at about 60mg total per week for a 70 pound dog, keeping a close eye on labs the whole way. That made a huge difference. Shot day is like a revival for him. ... And it's not just us, in fact other families are running the same protocol and seeing similar results. 6 months ago we were counting the time we had left with him. My kids were horrified by the thought that he would no longer be there as they grew up with him as their full-time guardian. Now I genuinely believe we have another 3 years. If you have a dog, understand that he's aging the same way you are. He needs help, but he can't do the research... you can! And after seeing what this protocol did for him, I knew other dog owners deserved access to it too, so check the tweet below.

Michael Morelli

819,927 次观看 • 24 天前

ONCE UPON A TIME IN FRONT OF #msdhoni7 's HOUSE GATE IN RANCHI : This is my little one Naina & her cousin brother Golu on a trip to Ranchi with their grandparents ! And this is the GATE OF Thala- Mahendra Singh Dhoni This is what they did in front of his gate to meet him - spoke to the watchman 🤦🏻🤦🏻 gave him my card - said I am also a minister .. blah blah blah 🤣 obviously it didn't work so then they called me to ask for my help - their name-throwing was hilarious A mentioned every name that they thought I I ew very well to get his number 🤩 when I told them it's impossible - very few has his number & he seldom uses a phone 🤣 Result: I was brutally bullied & trolled with messages & voice notes for being being *A DUMBO* 😢😢😢🤣🤣 but it's heartwarming to see how much love this Man has earned across generations... Take a bow & honestly, I felt sad I couldn't & couldn't have done anything !!! 🤣 #thala #thalaforareason #chennaisuperkings #trendingpost

ONCE UPON A TIME IN FRONT OF #msdhoni7 's HOUSE GATE IN RANCHI : This is my little one Naina & her cousin brother Golu on a trip to Ranchi with their grandparents ! And this is the GATE OF Thala- Mahendra Singh Dhoni This is what they did in front of his gate to meet him - spoke to the watchman 🤦🏻🤦🏻 gave him my card - said I am also a minister .. blah blah blah 🤣 obviously it didn't work so then they called me to ask for my help - their name-throwing was hilarious A mentioned every name that they thought I I ew very well to get his number 🤩 when I told them it's impossible - very few has his number & he seldom uses a phone 🤣 Result: I was brutally bullied & trolled with messages & voice notes for being being A DUMBO 😢😢😢🤣🤣 but it's heartwarming to see how much love this Man has earned across generations... Take a bow & honestly, I felt sad I couldn't & couldn't have done anything !!! 🤣 #thala #thalaforareason #chennaisuperkings #trendingpost

Babul Supriyo

288,647 次观看 • 7 个月前

This Chinese developer linked two $2,999 NVIDIA DGX Sparks into one box and runs the full Qwen3-235B at home, after dropping his $1,999-a-month cloud bill to zero. He wired 2 small boxes into a single computer, split a giant 235-billion-parameter model in half between them, and serves it across his own network at about 10 tokens a second, with no internet, no cloud, right there on the desk. No data center, no thousand-dollar graphics cards, no monthly cloud bill. Just him, 2 gold boxes the size of a sandwich, one cable between them, and 1 power strip. And here is the whole payoff. He used to pay the cloud $1,999 a month for the same model, and the meter ticked on every request. Now he paid $5,998 once for 2 boxes, they covered their cost in 3 months, and after that he sends as many requests as he wants for free, only electricity. The two Sparks talk over one fast cable, each holds 128GB of memory, and together they carry the whole model, about 73GB loaded per box, with the chip inside pinned near the limit at 96%. Both boxes work as one and keep trading data over the cable, with no cloud in the loop and no single word leaking out. The ready model sits on one local address, and any app on his network calls it as easily as ChatGPT. And here is how he described, in plain words, what this pair of boxes does: "this is a pair of boxes that holds the huge Qwen3-235B model and serves it to one network. the model is split in half, and each box owns its half. parts: // Box 1 (holds the first half of the model and starts the answer fast, the first word appears in under a second) // Box 2 (holds the second half and writes out the rest, about 10 tokens a second) // Cable (connects the 2 boxes and moves data between them on every step, with no lag) // Address (one local address where any app sends its request, like to a cloud model) // Test (a script that runs big prompts through and measures speed and delays) // Monitor (checks temperature, power draw, and load on both boxes every 2 seconds). the model never goes to the cloud. he only steps in when a box runs hotter than 80 degrees or the cable between them starts dropping data." So the system knows exactly what it is, what it is for, and where its limits are. It knows it has to hold the whole huge model across 2 boxes on its own. It knows it has to answer every request locally, with no meter, no limits, and no internet. It knows the human is only needed when a box overheats or the link between them stalls. → The setup runs around the clock on 2 boxes, each pulling under 60 watts → However many requests he sends, the monthly bill is $0, only electricity → The first box starts the answer in under a second → The second writes text at about 10 tokens a second → One request at a time: 838 tokens in 85 seconds, first word in 0.8s → Two requests at once: 697 tokens in 108 seconds, first word in 0.7s → Both boxes sit at 96% load and warm up to 76-78 degrees And only when a chip in a box runs hotter than 80 degrees or the cable between the 2 Sparks drops data does the system call the owner. And when he himself is out on a run or in a coffee shop, he still reaches his own model at home from his phone: sends a big prompt to the local Qwen3-235B, gets the full answer back in under a minute and a half, with no token meter ticking and no limit to hit. Here is what the test shows on his screen during one of the night runs: "one request at a time: 838 tokens in 84.9 seconds, first word in 0.8s, then 0.1s per token." "two requests at once: 697 tokens in 107.6 seconds, first word in 0.7s, then 0.15s per token." "Box 1: chip at 96% load, 76 degrees, 56 watts, 73GB used in memory." "Box 2: chip at 96% load, 78 degrees, 56 watts, the Qwen3-235B model fully loaded." And while everyone around is paying for AI by the month and bumping into limits, his top-tier model just sits on the desk and works as much as he wants: his own little power plant instead of a forever meter. He has no server rack of his own and no cloud account behind it. Just 2 DGX Spark boxes on a desk, one model split in half between them, one local address, and a folder of prompts next to it. Out of everything I have seen this year, this is the cleanest way to stop paying for AI: $5,998 of hardware on the desk once, $0 a month to the cloud, unlimited forever, and between them 2 gold boxes, 1 cable, and the full Qwen3-235B answering at home with no internet.

This Chinese developer linked two $2,999 NVIDIA DGX Sparks into one box and runs the full Qwen3-235B at home, after dropping his $1,999-a-month cloud bill to zero. He wired 2 small boxes into a single computer, split a giant 235-billion-parameter model in half between them, and serves it across his own network at about 10 tokens a second, with no internet, no cloud, right there on the desk. No data center, no thousand-dollar graphics cards, no monthly cloud bill. Just him, 2 gold boxes the size of a sandwich, one cable between them, and 1 power strip. And here is the whole payoff. He used to pay the cloud $1,999 a month for the same model, and the meter ticked on every request. Now he paid $5,998 once for 2 boxes, they covered their cost in 3 months, and after that he sends as many requests as he wants for free, only electricity. The two Sparks talk over one fast cable, each holds 128GB of memory, and together they carry the whole model, about 73GB loaded per box, with the chip inside pinned near the limit at 96%. Both boxes work as one and keep trading data over the cable, with no cloud in the loop and no single word leaking out. The ready model sits on one local address, and any app on his network calls it as easily as ChatGPT. And here is how he described, in plain words, what this pair of boxes does: "this is a pair of boxes that holds the huge Qwen3-235B model and serves it to one network. the model is split in half, and each box owns its half. parts: // Box 1 (holds the first half of the model and starts the answer fast, the first word appears in under a second) // Box 2 (holds the second half and writes out the rest, about 10 tokens a second) // Cable (connects the 2 boxes and moves data between them on every step, with no lag) // Address (one local address where any app sends its request, like to a cloud model) // Test (a script that runs big prompts through and measures speed and delays) // Monitor (checks temperature, power draw, and load on both boxes every 2 seconds). the model never goes to the cloud. he only steps in when a box runs hotter than 80 degrees or the cable between them starts dropping data." So the system knows exactly what it is, what it is for, and where its limits are. It knows it has to hold the whole huge model across 2 boxes on its own. It knows it has to answer every request locally, with no meter, no limits, and no internet. It knows the human is only needed when a box overheats or the link between them stalls. → The setup runs around the clock on 2 boxes, each pulling under 60 watts → However many requests he sends, the monthly bill is $0, only electricity → The first box starts the answer in under a second → The second writes text at about 10 tokens a second → One request at a time: 838 tokens in 85 seconds, first word in 0.8s → Two requests at once: 697 tokens in 108 seconds, first word in 0.7s → Both boxes sit at 96% load and warm up to 76-78 degrees And only when a chip in a box runs hotter than 80 degrees or the cable between the 2 Sparks drops data does the system call the owner. And when he himself is out on a run or in a coffee shop, he still reaches his own model at home from his phone: sends a big prompt to the local Qwen3-235B, gets the full answer back in under a minute and a half, with no token meter ticking and no limit to hit. Here is what the test shows on his screen during one of the night runs: "one request at a time: 838 tokens in 84.9 seconds, first word in 0.8s, then 0.1s per token." "two requests at once: 697 tokens in 107.6 seconds, first word in 0.7s, then 0.15s per token." "Box 1: chip at 96% load, 76 degrees, 56 watts, 73GB used in memory." "Box 2: chip at 96% load, 78 degrees, 56 watts, the Qwen3-235B model fully loaded." And while everyone around is paying for AI by the month and bumping into limits, his top-tier model just sits on the desk and works as much as he wants: his own little power plant instead of a forever meter. He has no server rack of his own and no cloud account behind it. Just 2 DGX Spark boxes on a desk, one model split in half between them, one local address, and a folder of prompts next to it. Out of everything I have seen this year, this is the cleanest way to stop paying for AI: $5,998 of hardware on the desk once, $0 a month to the cloud, unlimited forever, and between them 2 gold boxes, 1 cable, and the full Qwen3-235B answering at home with no internet.

Blaze

93,871 次观看 • 2 个月前

EDWARD G. ROBINSON was born Emanuel Goldenberg in Bucharest in 1893, came through Ellis Island at nine, and grew up on the Lower East Side. Nothing about him said movie star. Five foot seven, thick-featured, a face built for character parts. He came up through the stage — trained at the American Academy of Dramatic Arts, put in real years on Broadway — and that grounding shows in everything he did on screen. And yet for two decades he was one of the most magnetic presences in American film, precisely because he never once relied on being handsome. Everybody knows the entry point: Little Caesar (1931). Rico Bandello — the snarling, doomed little Napoleon who basically invented the Warner Bros. gangster template alongside Cagney. "Mother of mercy, is this the end of Rico?" got quoted and parodied for decades. It made him a star and, briefly, a prisoner of the type. The tough guy with the cigar became shorthand for the whole genre. But here's the thing that makes him great rather than just iconic — he was one of the most versatile actors of the studio era, and he spent the rest of his career quietly proving it. Watch him in Double Indemnity (1944) as Barton Keyes, the claims investigator with the "little man" in his gut that tells him when something's wrong. It's a warm, rapid-fire, deeply human performance, and the final scene with MacMurray is one of the tenderest things in all of noir. No gun, no snarl. Just a guy who loved his friend. Then there's his run with Fritz Lang — The Woman in the Window and Scarlet Street, both 1945 — where he plays weak, ordinary men swallowed by desire and circumstance. He was fearless about looking small and pathetic. In Key Largo (1948) he flips back to menace as Johnny Rocco, sweating in a bathtub, and steals the picture out from under Bogart. He'd already gone toe-to-toe with Welles in The Stranger (1946). And he had range far outside crime. He played Paul Ehrlich in Dr. Ehrlich's Magic Bullet (1940) and lent real gravity to Confessions of a Nazi Spy (1939) — one of Hollywood's earliest openly anti-Nazi pictures, made when the studios were still nervous about the German market. Late in life he was still sharp enough to hold the screen against Steve McQueen in The Cincinnati Kid (1965), the old lion teaching the kid a lesson at the poker table. Off screen he was the opposite of every role — cultured, multilingual, one of the great art collectors of Hollywood, with a wall of Impressionists and Post-Impressionists he had to break up in a brutal divorce settlement. A gentle, erudite man playing killers for a living. The ugly chapter: the HUAC years. His liberal politics and donations got him greylisted, and he was dragged in to testify more than once to clear his name. It stalled him, and it clearly wounded him. He never got the respect from the industry he'd earned — astonishingly, he was never nominated for a competitive Oscar. Not once. The Academy finally moved to give him an honorary award in 1973. He died of cancer two months before the ceremony, in January '73. His last film was Soylent Green, and his death scene — Sol Roth choosing to "go home," bathed in music and images of a lost natural world — plays now like a farewell he knew he was giving. Heston reportedly knew he was dying while they shot it. One of the best who never got his statue in his lifetime. Watch the noirs. He's better than his reputation, and his reputation is already huge. Here he is in Fritz Lang's The Woman In The Window (1944):

EDWARD G. ROBINSON was born Emanuel Goldenberg in Bucharest in 1893, came through Ellis Island at nine, and grew up on the Lower East Side. Nothing about him said movie star. Five foot seven, thick-featured, a face built for character parts. He came up through the stage — trained at the American Academy of Dramatic Arts, put in real years on Broadway — and that grounding shows in everything he did on screen. And yet for two decades he was one of the most magnetic presences in American film, precisely because he never once relied on being handsome. Everybody knows the entry point: Little Caesar (1931). Rico Bandello — the snarling, doomed little Napoleon who basically invented the Warner Bros. gangster template alongside Cagney. "Mother of mercy, is this the end of Rico?" got quoted and parodied for decades. It made him a star and, briefly, a prisoner of the type. The tough guy with the cigar became shorthand for the whole genre. But here's the thing that makes him great rather than just iconic — he was one of the most versatile actors of the studio era, and he spent the rest of his career quietly proving it. Watch him in Double Indemnity (1944) as Barton Keyes, the claims investigator with the "little man" in his gut that tells him when something's wrong. It's a warm, rapid-fire, deeply human performance, and the final scene with MacMurray is one of the tenderest things in all of noir. No gun, no snarl. Just a guy who loved his friend. Then there's his run with Fritz Lang — The Woman in the Window and Scarlet Street, both 1945 — where he plays weak, ordinary men swallowed by desire and circumstance. He was fearless about looking small and pathetic. In Key Largo (1948) he flips back to menace as Johnny Rocco, sweating in a bathtub, and steals the picture out from under Bogart. He'd already gone toe-to-toe with Welles in The Stranger (1946). And he had range far outside crime. He played Paul Ehrlich in Dr. Ehrlich's Magic Bullet (1940) and lent real gravity to Confessions of a Nazi Spy (1939) — one of Hollywood's earliest openly anti-Nazi pictures, made when the studios were still nervous about the German market. Late in life he was still sharp enough to hold the screen against Steve McQueen in The Cincinnati Kid (1965), the old lion teaching the kid a lesson at the poker table. Off screen he was the opposite of every role — cultured, multilingual, one of the great art collectors of Hollywood, with a wall of Impressionists and Post-Impressionists he had to break up in a brutal divorce settlement. A gentle, erudite man playing killers for a living. The ugly chapter: the HUAC years. His liberal politics and donations got him greylisted, and he was dragged in to testify more than once to clear his name. It stalled him, and it clearly wounded him. He never got the respect from the industry he'd earned — astonishingly, he was never nominated for a competitive Oscar. Not once. The Academy finally moved to give him an honorary award in 1973. He died of cancer two months before the ceremony, in January '73. His last film was Soylent Green, and his death scene — Sol Roth choosing to "go home," bathed in music and images of a lost natural world — plays now like a farewell he knew he was giving. Heston reportedly knew he was dying while they shot it. One of the best who never got his statue in his lifetime. Watch the noirs. He's better than his reputation, and his reputation is already huge. Here he is in Fritz Lang's The Woman In The Window (1944):

Mike David

18,745 次观看 • 1 个月前