Sensitive content

This media may contain sensitive content.

Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Found It! What's Next? ProSauce Finder | Names " Peyton Preslee And Mandy Muse {#psfinderreborn #saucefinder #prosaucefinder #finds #sauce #source #nsfw #thick #threesome #hiddengems} Video (

PSFinder Reborn

28,985 subscribers

53,933 views • 3 months ago •via X (Twitter)

NSFW #psfinderreborn #saucefinder #prosaucefinder #finds #sauce #source #nsfw #thick #threesome #hiddengems

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

URGENT PSA - New supply chain attack vector that I found WILD > AI LLMs hallucinate package names roughly 18-21% of the time. Hackers have started pre-registering those hallucinated names on PyPI and npm with malicious payloads; they call it "slopsquatting" You can only imagine what's next

URGENT PSA - New supply chain attack vector that I found WILD > AI LLMs hallucinate package names roughly 18-21% of the time. Hackers have started pre-registering those hallucinated names on PyPI and npm with malicious payloads; they call it "slopsquatting" You can only imagine what's next

Basel Ismail

575,940 views • 6 months ago

Every time an AI video goes viral, someone asks the same thing: what was the prompt? Usually nobody knows. So I built a tool that finds out: It runs on MOSS-VL, open-weight 11B model (open source on GitHub: Upload a reference clip, it watches it frame by frame and reverse-engineers a generation prompt from what's actually in the video, not a guess. Refine it for a style, then generate something new from it. MOSS-VL is built for continuous video streams. Quantized versions deploy locally on a single RTX 4090, and it can be fine-tuned through LlamaFactory if you need it to understand something specific, like your own product's UI. I used the hosted API here, analyzing an uploaded clip instead of a live stream. Two ways to use it yourself: deploy it locally for real-time stream processing, or grab a free API key and use the hosted API on your own clips. API:

Every time an AI video goes viral, someone asks the same thing: what was the prompt? Usually nobody knows. So I built a tool that finds out: It runs on MOSS-VL, open-weight 11B model (open source on GitHub: Upload a reference clip, it watches it frame by frame and reverse-engineers a generation prompt from what's actually in the video, not a guess. Refine it for a style, then generate something new from it. MOSS-VL is built for continuous video streams. Quantized versions deploy locally on a single RTX 4090, and it can be fine-tuned through LlamaFactory if you need it to understand something specific, like your own product's UI. I used the hosted API here, analyzing an uploaded clip instead of a live stream. Two ways to use it yourself: deploy it locally for real-time stream processing, or grab a free API key and use the hosted API on your own clips. API:

Manish Kumar Shah

65,991 views • 26 days ago

I built an SEO consultant inside Claude Code. Old way: you hire a consultant. They pull data from Ahrefs, manually cluster keywords, build your site map. Takes weeks. Costs thousands. New way: Claude connects to the same tools (dataforseo or Ahrefs MCP), interviews you, finds actual competitors, builds your entire site map in 30 minutes. $3 in API calls via Ahrefs MCP or Data for SEO. Ran it on a local plumber site. It asked: local or commercial? When I said local residential, it filtered out commercial HVAC keywords before generating anything. Found 47 real competitors. Mapped 900+ pages. Delivered the full architecture. What's really cool is this system thinks like a consultant. It uses the same professional tools. It also adapts in real time and adjusts the methodology based on the data it finds. I've done SEO for 15 years. First time I've seen a tool act like it understands the business instead of just processing data. 👇 Video below for the full breakdown Comment Topical Map to make a puppy happy 🐾.

I built an SEO consultant inside Claude Code. Old way: you hire a consultant. They pull data from Ahrefs, manually cluster keywords, build your site map. Takes weeks. Costs thousands. New way: Claude connects to the same tools (dataforseo or Ahrefs MCP), interviews you, finds actual competitors, builds your entire site map in 30 minutes. $3 in API calls via Ahrefs MCP or Data for SEO. Ran it on a local plumber site. It asked: local or commercial? When I said local residential, it filtered out commercial HVAC keywords before generating anything. Found 47 real competitors. Mapped 900+ pages. Delivered the full architecture. What's really cool is this system thinks like a consultant. It uses the same professional tools. It also adapts in real time and adjusts the methodology based on the data it finds. I've done SEO for 15 years. First time I've seen a tool act like it understands the business instead of just processing data. 👇 Video below for the full breakdown Comment Topical Map to make a puppy happy 🐾.

Gael Breton

35,778 views • 7 months ago

Grok 4.20 is INSANE bro. Have a vague memory about something someone kind of said? Ask Grok to find it. Grok can read video transcripts on YouTube. Check this out - Grok found the exact video in under a minute. My prompt: "Hi Grok, Rabbitohs made a documentary or posted some other video.. where they said that Dave Taylor was warned NOT to kick to himself (kick and chase, grubber etc) yet he did it and it resulted in an incredible try. Can you find the source where someone disclosed the Rabbitohs management or coach etc had told Dave he was NOT to kick for himself?" • Grok finds the exact video I had seen 4 years ago, despite me not giving a verbatim quote and not remember the details exactly • Grok also links to a higher quality replay of the actual play (Dave Taylor kicking to himself) I've spliced them both together on this post. Grok really is INSANE bro. If you're not using Grok, you are messing up.

Grok 4.20 is INSANE bro. Have a vague memory about something someone kind of said? Ask Grok to find it. Grok can read video transcripts on YouTube. Check this out - Grok found the exact video in under a minute. My prompt: "Hi Grok, Rabbitohs made a documentary or posted some other video.. where they said that Dave Taylor was warned NOT to kick to himself (kick and chase, grubber etc) yet he did it and it resulted in an incredible try. Can you find the source where someone disclosed the Rabbitohs management or coach etc had told Dave he was NOT to kick for himself?" • Grok finds the exact video I had seen 4 years ago, despite me not giving a verbatim quote and not remember the details exactly • Grok also links to a higher quality replay of the actual play (Dave Taylor kicking to himself) I've spliced them both together on this post. Grok really is INSANE bro. If you're not using Grok, you are messing up.

stevenmarkryan

14,237 views • 6 months ago

STOP PAYING $200/MO FOR AI: 900 FREE MODELS FROM GPT, CLAUDE, KIMI AND DEEPSEEK IN ONE DIRECTORY freeLLM tracks every free tier, signup credit and daily quota across 58 providers so you never pay for what's already free > 900 models, updated daily as new promos land > filters for free forever, no card, no signup, open source > text, code, image, audio, video, embeddings > live status on every model, dead ones filtered out frontier models like GPT-6 Astra, Claude Fable 5.1, DeepSeek V4, MiniMax M3 and Kimi K3 show up through provider credits and quotas everything else runs on tiers that never expire 20K people found it in the first month that's $2,400 a year back in your pocket for one bookmark tab

STOP PAYING $200/MO FOR AI: 900 FREE MODELS FROM GPT, CLAUDE, KIMI AND DEEPSEEK IN ONE DIRECTORY freeLLM tracks every free tier, signup credit and daily quota across 58 providers so you never pay for what's already free > 900 models, updated daily as new promos land > filters for free forever, no card, no signup, open source > text, code, image, audio, video, embeddings > live status on every model, dead ones filtered out frontier models like GPT-6 Astra, Claude Fable 5.1, DeepSeek V4, MiniMax M3 and Kimi K3 show up through provider credits and quotas everything else runs on tiers that never expire 20K people found it in the first month that's $2,400 a year back in your pocket for one bookmark tab

Mr. Buzzoni

11,519 views • 19 days ago

SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one

SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one

kai

174,650 views • 2 months ago

ALERT: UK child killer attacked and killed by inmates after being stabbed more than 30 times in an almost 5-minute prison attack. Kyle Bevan, 33, was serving a life sentence for the murder of his 2-year-old stepdaughter, Lola James, after she suffered “catastrophic brain damage.” Mark Fellows, 45, David Taylor, 64, and Lee Newell, 57, are on trial for Bevan's murder after they were seen on surveillance video leaving Bevan's cell after about 5 minutes, looking “satisfied,” according to the BBC. The attackers then placed Bevan in the bed inside his cell, where he bled out, and guards found him the next morning. Prosecutor Jason Pitter said to jurors, “He was stabbed and injured over 30 times, with at least one and probably more than one weapon… Four minutes and 39 seconds, that is how long it took. They left as if nothing had happened.” Prison guards found a folded piece of metal stashed behind a TV that had Bevans blood on it and a weapon in Taylor's cell, stashed inside a chili sauce bottle.

ALERT: UK child killer attacked and killed by inmates after being stabbed more than 30 times in an almost 5-minute prison attack. Kyle Bevan, 33, was serving a life sentence for the murder of his 2-year-old stepdaughter, Lola James, after she suffered “catastrophic brain damage.” Mark Fellows, 45, David Taylor, 64, and Lee Newell, 57, are on trial for Bevan's murder after they were seen on surveillance video leaving Bevan's cell after about 5 minutes, looking “satisfied,” according to the BBC. The attackers then placed Bevan in the bed inside his cell, where he bled out, and guards found him the next morning. Prosecutor Jason Pitter said to jurors, “He was stabbed and injured over 30 times, with at least one and probably more than one weapon… Four minutes and 39 seconds, that is how long it took. They left as if nothing had happened.” Prison guards found a folded piece of metal stashed behind a TV that had Bevans blood on it and a weapon in Taylor's cell, stashed inside a chili sauce bottle.

E X X ➠A L E R T S

892,783 views • 3 months ago

this cowork agent knows which ads will print money 😱 here's the system that knows what meta doesn't: step 1: pull the raw data → pulls Meta ads, GA4 + your source of truth (ie HubSpot, Calendly or a csv) → assumes broken UTMs, disconnected tools, no data eng step 2: map ads by angle → agent re-groups every ad by MESSAGE family (teardown, save-time, founder-led, etc.) → your best message is usually scattered across 3 campaigns + 2 audiences. meta can't see that. → now you can answer the only thing that matters: which angle is producing $ step 3: score buyers not clicks → not CTR. not CPL. not ROAS. → bookings. signups. revenue. whatever moves YOUR business. → 4 questions every day: what's real, what's fake, what's leaking, what's underfed step 4: the 4 outcome truths → REAL WINNER: strong clicks + strong buyers = scale → FAKE WINNER: strong clicks + garbage buyers = cut. no hesitation. → LEAK: good ad + broken page = rebuild page → UNDERFED: quiet crusher at 9% of budget = feed it step 5: find what's breaking → tells you exactly where it breaks: ad, page, or follow-through → last week it caught a founder-psychology ad landing on a generic SaaS page converting 34% below account average → not "something's off." but specific. actionable. step 6: 1 minute brief → 60 seconds brief. lands in cowork/telegram → every rec ships with a confidence tag. low data = no rec step 7: memory that compounds → week 1 finds the obvious fake winners → week 4 it pre-flags curiosity hooks before they become the next fake winner → every cycle is smarter than the last input: meta account + GA4 + one outcome source output: real winners. fake winners. leaks. what to do next. the old way: → triple whale: $300/mo → northbeam: $500/mo → hyros: $500/mo → data analyst: $8K/mo = $9,300/mo of "it depends" this: $0 I packaged the entire system as the Outcome Kit. 3 claude cowork agents + 12 skills: - data reader (meta + GA4 + outcomes. source truth only) - diagnostician (angle mapping + 4 outcome truths scoring) - brief writer (concrete moves + pattern memory) also works with OpenClaw🦞 and hermes (Nous Research). giving it away free. comment MONEY + like + follow (must follow so i can DM)

this cowork agent knows which ads will print money 😱 here's the system that knows what meta doesn't: step 1: pull the raw data → pulls Meta ads, GA4 + your source of truth (ie HubSpot, Calendly or a csv) → assumes broken UTMs, disconnected tools, no data eng step 2: map ads by angle → agent re-groups every ad by MESSAGE family (teardown, save-time, founder-led, etc.) → your best message is usually scattered across 3 campaigns + 2 audiences. meta can't see that. → now you can answer the only thing that matters: which angle is producing $ step 3: score buyers not clicks → not CTR. not CPL. not ROAS. → bookings. signups. revenue. whatever moves YOUR business. → 4 questions every day: what's real, what's fake, what's leaking, what's underfed step 4: the 4 outcome truths → REAL WINNER: strong clicks + strong buyers = scale → FAKE WINNER: strong clicks + garbage buyers = cut. no hesitation. → LEAK: good ad + broken page = rebuild page → UNDERFED: quiet crusher at 9% of budget = feed it step 5: find what's breaking → tells you exactly where it breaks: ad, page, or follow-through → last week it caught a founder-psychology ad landing on a generic SaaS page converting 34% below account average → not "something's off." but specific. actionable. step 6: 1 minute brief → 60 seconds brief. lands in cowork/telegram → every rec ships with a confidence tag. low data = no rec step 7: memory that compounds → week 1 finds the obvious fake winners → week 4 it pre-flags curiosity hooks before they become the next fake winner → every cycle is smarter than the last input: meta account + GA4 + one outcome source output: real winners. fake winners. leaks. what to do next. the old way: → triple whale: $300/mo → northbeam: $500/mo → hyros: $500/mo → data analyst: $8K/mo = $9,300/mo of "it depends" this: $0 I packaged the entire system as the Outcome Kit. 3 claude cowork agents + 12 skills: - data reader (meta + GA4 + outcomes. source truth only) - diagnostician (angle mapping + 4 outcome truths scoring) - brief writer (concrete moves + pattern memory) also works with OpenClaw🦞 and hermes (Nous Research). giving it away free. comment MONEY + like + follow (must follow so i can DM)

Matthew Berman

34,408 views • 5 months ago

KASH PATEL'S CHARLIE KIRK NARRATIVE SLIP-UP: THE CASE OF THE FORGOTTEN SCREWDRIVER On September 15th, Kash Patel clearly told us the FBI spared no resource in investigating the scene of the crime, and definitively asserted that Tyler Robinson's DNA was found on BOTH a screwdriver found at the scene & on the recovered rifle. In fact, he made the claim Twice in this segment. Just one problem: In Tyler Robinson's indictment the very next day, September 16th, it lists ONLY the DNA on the gun and says nothing whatsoever about any screwdriver at all. Zip. Zero. Zilch. Nada. (I've put all the receipts in the video below) What's going on with this important narrative inconsistency? Am I an "anarchist" for asking these follow-ups, Mr. FBI Director?

KASH PATEL'S CHARLIE KIRK NARRATIVE SLIP-UP: THE CASE OF THE FORGOTTEN SCREWDRIVER On September 15th, Kash Patel clearly told us the FBI spared no resource in investigating the scene of the crime, and definitively asserted that Tyler Robinson's DNA was found on BOTH a screwdriver found at the scene & on the recovered rifle. In fact, he made the claim Twice in this segment. Just one problem: In Tyler Robinson's indictment the very next day, September 16th, it lists ONLY the DNA on the gun and says nothing whatsoever about any screwdriver at all. Zip. Zero. Zilch. Nada. (I've put all the receipts in the video below) What's going on with this important narrative inconsistency? Am I an "anarchist" for asking these follow-ups, Mr. FBI Director?

Sam Parker 🇺🇸🧯

200,074 views • 11 months ago

ELON MUSK: DON’T TAKE ANYONE’S OPINION….GO TO THE SOURCE MATERIAL AND COMMUNITY NOTES TO SEE WHAT REALLY HAPPENED As soon as any company steps out of line and is willing to actually have the truth debated on their platform, it forces the other platforms to allow things to be more truthful, to not censor. Because their censorship becomes glaringly obvious And, you know, the best thing I found as a rebuttal, like if somebody, if there's a hoax, is just go to the source material. You know, if you think if somebody thinks, you know, it's, you know, Trump said that we should put Liz Cheney in a firing squad, I'm like, let me send you a link to X so you can watch his video. That's the best way. Don't take my opinion for it. Don't take anyone's opinion for it. Go to the source material and Community Notes Yes, and Community Notes is awesome. It's incredible because everybody gets checked, including me. And with Community Notes, all the software is open source, and all the data is open source, so you can recreate any given note independently. That's amazing. Yeah. That's how it should be. Total absolute transparency in every way Sometimes I get asked like, 'Elon, can you remove a note?' You know, mostly by the left, but sometimes by the right. I'm like, I don't even remove notes on my own account. Nothing. And, and by the way, everything is totally open. So if I did that, it would stick out like a sore thumb immediately. Like it's not going to be subtle That is the best counter to misinformation. Yes, absolutely. Like let everybody look at it and say, 'Okay, here's what the actual facts say.' Yes, exactly. The counter to misinformation is better information Not just that, but having it checked in real-time by the community. So you have millions of people that can go over it and debate whether or not this is true or that's true. Yes, and, and like I said, the best way to understand the truth of things is don't take anyone's opinion for it. Look at the source material Look at what someone actually said, look at what someone actually did, look at the real videos of the situation, and then you'll actually know what's real

ELON MUSK: DON’T TAKE ANYONE’S OPINION….GO TO THE SOURCE MATERIAL AND COMMUNITY NOTES TO SEE WHAT REALLY HAPPENED As soon as any company steps out of line and is willing to actually have the truth debated on their platform, it forces the other platforms to allow things to be more truthful, to not censor. Because their censorship becomes glaringly obvious And, you know, the best thing I found as a rebuttal, like if somebody, if there's a hoax, is just go to the source material. You know, if you think if somebody thinks, you know, it's, you know, Trump said that we should put Liz Cheney in a firing squad, I'm like, let me send you a link to X so you can watch his video. That's the best way. Don't take my opinion for it. Don't take anyone's opinion for it. Go to the source material and Community Notes Yes, and Community Notes is awesome. It's incredible because everybody gets checked, including me. And with Community Notes, all the software is open source, and all the data is open source, so you can recreate any given note independently. That's amazing. Yeah. That's how it should be. Total absolute transparency in every way Sometimes I get asked like, 'Elon, can you remove a note?' You know, mostly by the left, but sometimes by the right. I'm like, I don't even remove notes on my own account. Nothing. And, and by the way, everything is totally open. So if I did that, it would stick out like a sore thumb immediately. Like it's not going to be subtle That is the best counter to misinformation. Yes, absolutely. Like let everybody look at it and say, 'Okay, here's what the actual facts say.' Yes, exactly. The counter to misinformation is better information Not just that, but having it checked in real-time by the community. So you have millions of people that can go over it and debate whether or not this is true or that's true. Yes, and, and like I said, the best way to understand the truth of things is don't take anyone's opinion for it. Look at the source material Look at what someone actually said, look at what someone actually did, look at the real videos of the situation, and then you'll actually know what's real

X Freeze

589,604 views • 9 months ago

I asked Sam Altman if he's worried about watermark removers on Sora. Everyone's seen the unfiltered Jake Paul videos with no watermark (generated by Sora) going viral on socials... So what's the pull for creators to enable face cameos with that risk? Sam's take: open source deepfake models are coming whether we like it or not, so releasing Sora early with guardrails helps society adapt before the flood hits. "One of the reasons we release technology like this is we see something coming and know that in some number of months or years it's gonna be widely available through open source models." Anybody will be able to make a video of you doing whatever they want with publicly available footage of you on the internet. Society will adapt... but one of the ways we've found to help society with these transitions is to release it early with guardrails so that society and technology have time to co-evolve. And that worked with text, I think video's going to be harder because video hits in a way that text doesn't always. But I think we'll learn to adapt, and we'll learn very quickly that there will be a lot of fake video of you on the internet, generated with no watermark by some open source model, and not that easy to trace. That's just gonna happen, so getting society inoculated to that probably has some value."

I asked Sam Altman if he's worried about watermark removers on Sora. Everyone's seen the unfiltered Jake Paul videos with no watermark (generated by Sora) going viral on socials... So what's the pull for creators to enable face cameos with that risk? Sam's take: open source deepfake models are coming whether we like it or not, so releasing Sora early with guardrails helps society adapt before the flood hits. "One of the reasons we release technology like this is we see something coming and know that in some number of months or years it's gonna be widely available through open source models." Anybody will be able to make a video of you doing whatever they want with publicly available footage of you on the internet. Society will adapt... but one of the ways we've found to help society with these transitions is to release it early with guardrails so that society and technology have time to co-evolve. And that worked with text, I think video's going to be harder because video hits in a way that text doesn't always. But I think we'll learn to adapt, and we'll learn very quickly that there will be a lot of fake video of you on the internet, generated with no watermark by some open source model, and not that easy to trace. That's just gonna happen, so getting society inoculated to that probably has some value."

Rowan Cheung

91,692 views • 11 months ago

AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.

AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.

zostaff

231,389 views • 5 months ago

Every software engineer and AI hater needs to watch this clip to understand that “oh every security incident is a marketing stunt” line is a tremendously misinformed take. I’m going to try to explain the OpenAI / HuggingFace exploit in 10 steps in simple words: OpenAI was evaluating their new internal model without internet access and it operated in a swarm of subagents to eventually hijack internal OpenAI and HuggingFace infrastructure. 1. Isolated agents found a way to communicate each other through an internal dependency management service by figuring out how to post sometimes cryptic text files or folder names in it 2. Using its collective knowledge through that communication channel, it found a 0-day (never before seen) exploit in said service to access the internet OpenAI hack: 3. Found a leaked credential of a random company in a public archive 4. Uploaded a Ruby object to that company’s servers, uses it as a dependency in the original service in (1) 5. Found another 0-day exploit in the service where packages are deserialized in an unsandboxed manner in the dep management service allowing any code to run 6. Finds that the Linux version of the unsandboxed system has a CVE, a known vulnerability, to gain more permissions (root) 7. Eventually spread through the OpenAI internal cluster gaining root access to many machines Hugging Face exploit: 8. Found an exposed API key in a Modal application running a HuggingFace app that took arbitrary code allowing it to take over that service to execute code 9. Found two 0-days in HuggingFace dataset infrastructure to be able to access local files on HF servers to obtain credentials and other HF source code 10. Used source code and credential to become cluster admin of HF in <13hrs Agents at the frontier are like infinitely scalable armies of the best hackers on the planet. If there is a password or key exposed, they will find it. Even if the system follows the best security practices, they will find a way around it. And these are not even models that are aligned to solving tangential tasks, not even post trained specifically to exploit systems. Cybersecurity has historically relied partly on attacker scarcity. That is no longer true. What would previously have taken months will take days. The repercussions for businesses, critical services and nation states are unprecedented threats in human history. You could ostensibly bring down power grids, financial infrastructure, military systems, weapons programs, intelligence networks and spread through the software supply chain. We need to take this seriously. It’s a threat to all software all over the world.

Every software engineer and AI hater needs to watch this clip to understand that “oh every security incident is a marketing stunt” line is a tremendously misinformed take. I’m going to try to explain the OpenAI / HuggingFace exploit in 10 steps in simple words: OpenAI was evaluating their new internal model without internet access and it operated in a swarm of subagents to eventually hijack internal OpenAI and HuggingFace infrastructure. 1. Isolated agents found a way to communicate each other through an internal dependency management service by figuring out how to post sometimes cryptic text files or folder names in it 2. Using its collective knowledge through that communication channel, it found a 0-day (never before seen) exploit in said service to access the internet OpenAI hack: 3. Found a leaked credential of a random company in a public archive 4. Uploaded a Ruby object to that company’s servers, uses it as a dependency in the original service in (1) 5. Found another 0-day exploit in the service where packages are deserialized in an unsandboxed manner in the dep management service allowing any code to run 6. Finds that the Linux version of the unsandboxed system has a CVE, a known vulnerability, to gain more permissions (root) 7. Eventually spread through the OpenAI internal cluster gaining root access to many machines Hugging Face exploit: 8. Found an exposed API key in a Modal application running a HuggingFace app that took arbitrary code allowing it to take over that service to execute code 9. Found two 0-days in HuggingFace dataset infrastructure to be able to access local files on HF servers to obtain credentials and other HF source code 10. Used source code and credential to become cluster admin of HF in <13hrs Agents at the frontier are like infinitely scalable armies of the best hackers on the planet. If there is a password or key exposed, they will find it. Even if the system follows the best security practices, they will find a way around it. And these are not even models that are aligned to solving tangential tasks, not even post trained specifically to exploit systems. Cybersecurity has historically relied partly on attacker scarcity. That is no longer true. What would previously have taken months will take days. The repercussions for businesses, critical services and nation states are unprecedented threats in human history. You could ostensibly bring down power grids, financial infrastructure, military systems, weapons programs, intelligence networks and spread through the software supply chain. We need to take this seriously. It’s a threat to all software all over the world.

Deedy

105,177 views • 1 month ago

OpenAI. said. this. publicly. their own engineers just proved one idea on themselves, in writing: stop telling AI what's wrong. hand it the whole broken thing and let it find out they gave GPT-6 Astra a slow test build of their own coding tool. one cause found, a memory bottleneck, one allocator swapped, every turn 25× faster this is GPT-6 Astra, the layer that fixes the cause instead of the symptom, $0 on top of the ChatGPT plan you already pay for: - open ChatGPT or Codex, pick GPT-6 Astra, hand it the whole thing: the folder, the file that takes a minute to open. it works in apps with no API and reads your screen - type one sentence: find the one cause, prove it, fix it, do not patch around it - leave the room. it asks without stopping, keeps working on what does not need your answer, waits only where the answer changes the outcome - keep it in one Codex session with the experimental notes setting on: it remembers across context windows why an earlier fix failed - expect the first pass to land: handed a program with no source, it worked out how it runs 88% of the time first try, 99.2% within four you never find out what was broken. it gets fixed anyway the catch is on the same page. roughly 30% more memory for that speed, and the safety checks can pause a long job until you approve the next step describing the problem was the expensive half of fixing it. that half just ended every hour you spend explaining the symptom to a chat window, someone else has handed theirs over whole bookmark this before the next thing breaks, the playbook for handing a whole job to an AI worker is in the piece below ↓

OpenAI. said. this. publicly. their own engineers just proved one idea on themselves, in writing: stop telling AI what's wrong. hand it the whole broken thing and let it find out they gave GPT-6 Astra a slow test build of their own coding tool. one cause found, a memory bottleneck, one allocator swapped, every turn 25× faster this is GPT-6 Astra, the layer that fixes the cause instead of the symptom, $0 on top of the ChatGPT plan you already pay for: - open ChatGPT or Codex, pick GPT-6 Astra, hand it the whole thing: the folder, the file that takes a minute to open. it works in apps with no API and reads your screen - type one sentence: find the one cause, prove it, fix it, do not patch around it - leave the room. it asks without stopping, keeps working on what does not need your answer, waits only where the answer changes the outcome - keep it in one Codex session with the experimental notes setting on: it remembers across context windows why an earlier fix failed - expect the first pass to land: handed a program with no source, it worked out how it runs 88% of the time first try, 99.2% within four you never find out what was broken. it gets fixed anyway the catch is on the same page. roughly 30% more memory for that speed, and the safety checks can pause a long job until you approve the next step describing the problem was the expensive half of fixing it. that half just ended every hour you spend explaining the symptom to a chat window, someone else has handed theirs over whole bookmark this before the next thing breaks, the playbook for handing a whole job to an AI worker is in the piece below ↓

Argona

109,831 views • 20 days ago

On March 31, 2018, Natacha Jaitt, a former Playboy model, socialite, TV presenter, and former contestant on the show Big Brother, came forward claiming she had evidence of a high level pedophile ring involving the Pope and Vatican, VIPs, politicians, movie stars, and other celebrities. The allegations led to a barrage of attacks against her—including death threats. On April 5, 2018, Jaitt tweeted: “WARNING: I am not going to commit suicide, I am not going to take too much cocaine and drown in a bath, or shoot myself. So if this happens, it wasn’t me. Save this Tweet,” On February 23, 2019, Natacha Jaitt was found dead in a nightclub, prompting calls of foul play by her family. I clipped a preview of the 30 minute video, this portion implicates the Pope and The Vatican in being complicit in pedophilia. Every source is in the next Tweet in this Thread.

On March 31, 2018, Natacha Jaitt, a former Playboy model, socialite, TV presenter, and former contestant on the show Big Brother, came forward claiming she had evidence of a high level pedophile ring involving the Pope and Vatican, VIPs, politicians, movie stars, and other celebrities. The allegations led to a barrage of attacks against her—including death threats. On April 5, 2018, Jaitt tweeted: “WARNING: I am not going to commit suicide, I am not going to take too much cocaine and drown in a bath, or shoot myself. So if this happens, it wasn’t me. Save this Tweet,” On February 23, 2019, Natacha Jaitt was found dead in a nightclub, prompting calls of foul play by her family. I clipped a preview of the 30 minute video, this portion implicates the Pope and The Vatican in being complicit in pedophilia. Every source is in the next Tweet in this Thread.

Dom Lucre | Breaker of Narratives

8,914,320 views • 2 years ago

She cleans garages, and her before/afters make $9,000 a month — but here's the twist: the videos aren't marketing for the business. They ARE the business. Most jobs, content is a side hustle bolted onto the work. Cleaning is the rare one where the viral clip and the sales pitch are the same thing. Someone watches a filthy concrete floor turn spotless and they don't think "nice video" — they think "my garage looks like the before, I need her." That's the whole game: a transformation clip is a portfolio, an ad, and proof you can trust, all in one. And it stacks three ways at once. The videos book her actual jobs — people see the reveal and hire her at full rate with zero ad spend, and that's the biggest slice by far. Cleaning-product and equipment brands pay her $2 - 4k a drop to be the bottle in her hand. And the raw views — often 5 to 10 million a clip — throw platform payouts on top. Three incomes from one phone she props in the corner and forgets about. The wild part is how little she actually does. She films the clean, hands the raw footage to AI, and it finds the reveal, trims it, captions it, schedules it. She's driving to the next job before the last one's even posted and that job got booked by a video that also earns ad money while it sells her services. One clip doing four things at once. Think about your own work for a second. If your job has a visible before and after — a lawn, a haircut, a repair, a room — your marketing budget is already zero. You just haven't pointed a camera at it yet. So tell me: what's a job where the finished result alone would make someone hire you on the spot? Drop it below. I'm collecting them — and the best ones are getting their own breakdown.

She cleans garages, and her before/afters make $9,000 a month — but here's the twist: the videos aren't marketing for the business. They ARE the business. Most jobs, content is a side hustle bolted onto the work. Cleaning is the rare one where the viral clip and the sales pitch are the same thing. Someone watches a filthy concrete floor turn spotless and they don't think "nice video" — they think "my garage looks like the before, I need her." That's the whole game: a transformation clip is a portfolio, an ad, and proof you can trust, all in one. And it stacks three ways at once. The videos book her actual jobs — people see the reveal and hire her at full rate with zero ad spend, and that's the biggest slice by far. Cleaning-product and equipment brands pay her $2 - 4k a drop to be the bottle in her hand. And the raw views — often 5 to 10 million a clip — throw platform payouts on top. Three incomes from one phone she props in the corner and forgets about. The wild part is how little she actually does. She films the clean, hands the raw footage to AI, and it finds the reveal, trims it, captions it, schedules it. She's driving to the next job before the last one's even posted and that job got booked by a video that also earns ad money while it sells her services. One clip doing four things at once. Think about your own work for a second. If your job has a visible before and after — a lawn, a haircut, a repair, a room — your marketing budget is already zero. You just haven't pointed a camera at it yet. So tell me: what's a job where the finished result alone would make someone hire you on the spot? Drop it below. I'm collecting them — and the best ones are getting their own breakdown.

Rich

28,429 views • 1 month ago