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Real-time traffic analysis using Ultralytics YOLO26 🚗 Traffic analysis sounds simple: detect cars, count them, done. But in reality, it’s messy. Cars overlap at signals. Tracking breaks for a few frames. Multiple camera streams don’t scale easily. And suddenly, your “traffic insights” aren’t that reliable. 👉 Why this matters:... show more

Muhammad Rizwan Munawar

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11,375 views • 5 months ago •via X (Twitter)

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🚀 Introducing Atlas Miner: Autonomous DePIN Driving Networks. 🔹 1,200 pre-orders: We are overwhelmed by the demand for Atlas NAVI Miners. 1,200 drivers joined the whitelist and the first 100 can buy it NOW, with more to come each week as we increase our capacities progressively. Order your Atlas Miner here: 🔹 First of its kind: Custom-built by Atlas Navi, Atlas Miner is a hardware device seamlessly integrated into our decentralized physical infrastructure network (DePIN) communicating with other Atlas Navi drivers in real time. 🔹 Connects to any dash camera: Plug & play with almost any aftermarket dash camera – even inexpensive ones (Note: Doesn't work with factory-installed cameras yet.) 🔹 AI-powered real-time analysis: Using the latest computer vision machine learning algorithms, Atlas Miner detects traffic incidents, roadblocks, lane closures, heavy traffic, police vehicles, and more. Alerts drivers in real-time via the Atlas Navi ecosystem. 🔹 Benefits for miners (Drivers using the Atlas Miner): Generate rewards for contributing data. Other drivers get vital traffic info without using an app – just plug it in and go. 🔹 For fleet managers: Reliable income and essential driver monitoring. Access GPS data, trip history, and driving behavior through our upcoming Fleet Management Dashboard. 🔹 For smart cities: Anonymized and aggregated data becomes invaluable, creating revenue opportunities with $NAVI tokens through the upcoming Traffic Dashboard. Join us in transforming the driving experience and paving the way for smarter cities! 🌍🚗💡 #AtlasMiner #DePIN #NAVI #AI #SmartCities #FleetManagement #TrafficTech

🚀 Introducing Atlas Miner: Autonomous DePIN Driving Networks. 🔹 1,200 pre-orders: We are overwhelmed by the demand for Atlas NAVI Miners. 1,200 drivers joined the whitelist and the first 100 can buy it NOW, with more to come each week as we increase our capacities progressively. Order your Atlas Miner here: 🔹 First of its kind: Custom-built by Atlas Navi, Atlas Miner is a hardware device seamlessly integrated into our decentralized physical infrastructure network (DePIN) communicating with other Atlas Navi drivers in real time. 🔹 Connects to any dash camera: Plug & play with almost any aftermarket dash camera – even inexpensive ones (Note: Doesn't work with factory-installed cameras yet.) 🔹 AI-powered real-time analysis: Using the latest computer vision machine learning algorithms, Atlas Miner detects traffic incidents, roadblocks, lane closures, heavy traffic, police vehicles, and more. Alerts drivers in real-time via the Atlas Navi ecosystem. 🔹 Benefits for miners (Drivers using the Atlas Miner): Generate rewards for contributing data. Other drivers get vital traffic info without using an app – just plug it in and go. 🔹 For fleet managers: Reliable income and essential driver monitoring. Access GPS data, trip history, and driving behavior through our upcoming Fleet Management Dashboard. 🔹 For smart cities: Anonymized and aggregated data becomes invaluable, creating revenue opportunities with $NAVI tokens through the upcoming Traffic Dashboard. Join us in transforming the driving experience and paving the way for smarter cities! 🌍🚗💡 #AtlasMiner #DePIN #NAVI #AI #SmartCities #FleetManagement #TrafficTech

ATLAS NAVI | AI Navigation APP with 1M Downloads

359,404 views • 1 year ago

🔴 FREE Tool - Watch Over 145,000+ Live Cameras You don’t always need satellite imagery or paid feeds to monitor an area in real time. This is one of the first tools I check when I need a quick look at what’s happening on the ground. A lot of roads, highways, and city streets already have public traffic cameras. puts many of them in one place. It pulls from 145,000+ live traffic cameras, including official sources like Caltrans, TxDOT, FDOT, 511NY, and hundreds of other state and local feeds. What I use it for 👇 🚗 Checking highway and street cameras across the US 📍 Looking at conditions near an address or route 🕵️‍♂️ Seeing whether a road or location is active, blocked, or congested 📡 Getting a quick visual They can help confirm basic details like weather, traffic, road conditions, and visible landmarks from your desk. ⚠️ Important note: camera refresh rates vary, and coverage is uneven from state to state. Treat this as one source, not the final answer. 🔗 Tool link: __________ P.S. ♻️ Repost if you found this useful.

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CyberSudo

28,549 views • 1 month ago

Inside the Quant AI Ecosystem Where Intelligence Meets Markets The crypto and financial landscape is evolving fast, but one problem has remained constant: fragmentation. Traders and users are forced to jump between tools, charts, news feeds, analytics dashboards, sentiment trackers, just to answer one simple question: What’s actually happening in the market right now? This is exactly the gap the Quant AI ecosystem is stepping into. A unified intelligence layer for markets Quant AI is building an ecosystem where market interaction becomes simple, conversational, and accessible. Instead of navigating multiple platforms, users can interact directly with markets using chat and voice. That means: ➠ Asking for real-time market insights in plain language ➠ Tracking smart money movements across assets ➠ Understanding trends in crypto, stocks, and commodities in one place ➠ Acting faster with clearer, AI-driven context It’s not just another analytics tool, it’s an attempt to reshape how information flows in trading environments. Why the ecosystem approach matters Most platforms solve isolated problems: One for charts. One for signals. One for news. But Quant AI is moving toward something broader, an ecosystem where intelligence is centralized, and decision-making becomes faster and more intuitive. The goal is simple: Reduce complexity. Increase clarity. Improve execution. And in markets where speed and information matter, that shift is significant. Start here:👇 Quant AI #QuantAIPioneers

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The Agentic Alpha

16,825 views • 3 months ago

I wouldn't usually post this here, as this is normally about classic cars and the journey of ownership, but I've just spent the day at the ITAI (Institute of Traffic Accident) Crash Test and Research Day, and considering that if you're seeing this you probably drive cars or have an interest in them, that it might be pertinent to see what it looks like when it all goes wrong. These were all set up in a safe environment with no one harmed, to gather more information to assist collision investigators in real world investigations. The reason for me posting is that even though I'm very used to seeing broken or crashed cars, the X-Type involved in the first part of this video really did surprise me at how poorly it performed. It was struck by the Vauxhall at 60mph, with the Jaguar stationary and the Astra T-Boning it. After that, you'll see a BMW 5-series (fear not, it had a cracked block), impacting a Ford Focus CC at 73mph, which appears to fare better thanks to its reinforced floor pan, though the reality is the passenger cell is still greatly affected. Just some food for thought for the next time you get in the car.

I wouldn't usually post this here, as this is normally about classic cars and the journey of ownership, but I've just spent the day at the ITAI (Institute of Traffic Accident) Crash Test and Research Day, and considering that if you're seeing this you probably drive cars or have an interest in them, that it might be pertinent to see what it looks like when it all goes wrong. These were all set up in a safe environment with no one harmed, to gather more information to assist collision investigators in real world investigations. The reason for me posting is that even though I'm very used to seeing broken or crashed cars, the X-Type involved in the first part of this video really did surprise me at how poorly it performed. It was struck by the Vauxhall at 60mph, with the Jaguar stationary and the Astra T-Boning it. After that, you'll see a BMW 5-series (fear not, it had a cracked block), impacting a Ford Focus CC at 73mph, which appears to fare better thanks to its reinforced floor pan, though the reality is the passenger cell is still greatly affected. Just some food for thought for the next time you get in the car.

LUDEN Automotive

24,781 views • 3 months ago

Should officers give someone extra patience in a situation like this… or immediately take control once the driver becomes confrontational? The ending of video is the best… A SIMPLE TRAFFIC TICKET… OR A SITUATION ABOUT TO EXPLODE? What should have been a routine traffic stop suddenly turned into a tense roadside confrontation. Officers pulled a woman over for a violation and issued her a citation. Normally, the process is simple…explain the ticket, have the driver sign it, and everyone moves on. But that’s not what happened. The woman suddenly insisted she had no idea her license was suspended. Her frustration quickly turned into anger. Voices rose. She refused to accept what officers were telling her and the stop began spiraling out of control. Now the officers faced a dilemma. Do they keep trying to calmly explain the situation and risk the scene escalating even more? Or do they move quickly to detain her for driving on a suspended license before the roadside argument turns into something dangerous? Every second the tension grew. A stop that should have taken two minutes had now turned into a confrontation on the side of the road… with passing traffic, emotions running high, and officers forced to make a decision in real time. One small ticket. One angry driver. And suddenly… a routine stop becomes a situation where every move matters. If you truly didn’t know your license was suspended, would you still be responsible once you’re behind the wheel? At what point does arguing during a traffic stop turn from frustration into interfering with law enforcement?

Should officers give someone extra patience in a situation like this… or immediately take control once the driver becomes confrontational? The ending of video is the best… A SIMPLE TRAFFIC TICKET… OR A SITUATION ABOUT TO EXPLODE? What should have been a routine traffic stop suddenly turned into a tense roadside confrontation. Officers pulled a woman over for a violation and issued her a citation. Normally, the process is simple…explain the ticket, have the driver sign it, and everyone moves on. But that’s not what happened. The woman suddenly insisted she had no idea her license was suspended. Her frustration quickly turned into anger. Voices rose. She refused to accept what officers were telling her and the stop began spiraling out of control. Now the officers faced a dilemma. Do they keep trying to calmly explain the situation and risk the scene escalating even more? Or do they move quickly to detain her for driving on a suspended license before the roadside argument turns into something dangerous? Every second the tension grew. A stop that should have taken two minutes had now turned into a confrontation on the side of the road… with passing traffic, emotions running high, and officers forced to make a decision in real time. One small ticket. One angry driver. And suddenly… a routine stop becomes a situation where every move matters. If you truly didn’t know your license was suspended, would you still be responsible once you’re behind the wheel? At what point does arguing during a traffic stop turn from frustration into interfering with law enforcement?

𝐌𝐑. 𝐖𝐇𝐈𝐓𝐄 ™

39,449 views • 6 months ago

Blogging used to be simple. Write something helpful, rank on Google, and wake up to traffic. That worked for a long time. Then AI got good at summarizing it. A recent study tracked 100 once-successful blogs. The median one lost 85% of its Google traffic. But the split is what matters. The blogs getting destroyed right now are mostly describing things “best budgeting apps,” “how to start a podcast,” “top tools in 2026.” The ones still growing? They’re proving something. They didn’t write another roundup. They built the thing, tested it for real, spent the money, made the mistake, and showed what actually happened. That’s the new filter. Before you create your next piece of content, look at what people are searching for using then you can create content for what people actually want to know about. Then ask yourself one question: Can AI answer this without me? If the answer is yes, you’re writing something a machine can already summarize better and faster than you. If the answer is no, if it requires your experience, your specific results, your data, or your actual outcome that’s where the opportunity is. The future of content isn’t more articles. It’s proof that can’t be faked.

Blogging used to be simple. Write something helpful, rank on Google, and wake up to traffic. That worked for a long time. Then AI got good at summarizing it. A recent study tracked 100 once-successful blogs. The median one lost 85% of its Google traffic. But the split is what matters. The blogs getting destroyed right now are mostly describing things “best budgeting apps,” “how to start a podcast,” “top tools in 2026.” The ones still growing? They’re proving something. They didn’t write another roundup. They built the thing, tested it for real, spent the money, made the mistake, and showed what actually happened. That’s the new filter. Before you create your next piece of content, look at what people are searching for using then you can create content for what people actually want to know about. Then ask yourself one question: Can AI answer this without me? If the answer is yes, you’re writing something a machine can already summarize better and faster than you. If the answer is no, if it requires your experience, your specific results, your data, or your actual outcome that’s where the opportunity is. The future of content isn’t more articles. It’s proof that can’t be faked.

Neil Patel

11,696 views • 2 months ago

They really want y’all to believe this is just about “traffic” 🤔 Bike lanes everywhere. Bus lanes everywhere. Streets turning into outdoor lounges. Pay just to ENTER Manhattan. Now they talking about charging you to park near your own home… And if that’s not enough? Lower speed limits. Cameras everywhere 24/7. More rules for drivers… Less enforcement for bikes… But yeah… nothing to see here, right? 😭 Then they hit you with the “environment” angle… “Less cars = less pollution” Cool. But at what cost? Because when you make driving: More expensive… More stressful… More restricted… Of course people gonna stop driving. That’s not a coincidence. That’s strategy. More tolls. More cameras. Lower speeds. Less space for cars. And next up… more meters. Call it whatever you want… But don’t act like this isn’t a car phase-out in real time. Pay attention. Agree or I’m bugging? 👇 Follow me—because I’m breaking all of this down piece by piece. #nyc #mta #fyp #ny

They really want y’all to believe this is just about “traffic” 🤔 Bike lanes everywhere. Bus lanes everywhere. Streets turning into outdoor lounges. Pay just to ENTER Manhattan. Now they talking about charging you to park near your own home… And if that’s not enough? Lower speed limits. Cameras everywhere 24/7. More rules for drivers… Less enforcement for bikes… But yeah… nothing to see here, right? 😭 Then they hit you with the “environment” angle… “Less cars = less pollution” Cool. But at what cost? Because when you make driving: More expensive… More stressful… More restricted… Of course people gonna stop driving. That’s not a coincidence. That’s strategy. More tolls. More cameras. Lower speeds. Less space for cars. And next up… more meters. Call it whatever you want… But don’t act like this isn’t a car phase-out in real time. Pay attention. Agree or I’m bugging? 👇 Follow me—because I’m breaking all of this down piece by piece. #nyc #mta #fyp #ny

Tramell Thompson

218,921 views • 6 months ago

WATCH IT TO BELIEVE IT 📽️ The render distance on the FSD visualization is absolutely mind-blowing when you actually pinch to zoom out 🔥 We spend so much time focusing on how the car handles the immediate space around it, but this clip shows the sheer scale of the environment Tesla Vision is mapping in real-time 🔥 Even while crawling in stop-and-go traffic under 15mph, the system isn't just locked onto the lead vehicle. It's holding stable bounding boxes for dozens of cars and accurately tracking a semi-truck way down the road 🔥 This macro-level tracking is what allows the stack to be predictive instead of just reactive. By analyzing the broader traffic flow, the car can anticipate stops and optimize efficiency long before a human driver would even tap the brakes. The inference required to maintain object permanence and spatial awareness at this massive distance purely from photon-in to control-out shows the raw power of the FSD compute 🔥 And the craziest part is that all of these capabilities are happening right now on current AI4 hardware. As the stack eventually evolves toward AI5, the fidelity of this distant mapping is only going to get crazier 🔥

WATCH IT TO BELIEVE IT 📽️ The render distance on the FSD visualization is absolutely mind-blowing when you actually pinch to zoom out 🔥 We spend so much time focusing on how the car handles the immediate space around it, but this clip shows the sheer scale of the environment Tesla Vision is mapping in real-time 🔥 Even while crawling in stop-and-go traffic under 15mph, the system isn't just locked onto the lead vehicle. It's holding stable bounding boxes for dozens of cars and accurately tracking a semi-truck way down the road 🔥 This macro-level tracking is what allows the stack to be predictive instead of just reactive. By analyzing the broader traffic flow, the car can anticipate stops and optimize efficiency long before a human driver would even tap the brakes. The inference required to maintain object permanence and spatial awareness at this massive distance purely from photon-in to control-out shows the raw power of the FSD compute 🔥 And the craziest part is that all of these capabilities are happening right now on current AI4 hardware. As the stack eventually evolves toward AI5, the fidelity of this distant mapping is only going to get crazier 🔥

Ming

64,537 views • 5 months ago

FOUR “BAD GIRLS” TOOK OVER THE DANCE FLOOR FOR 30 SECONDS. AND THE OPERATOR BEHIND THEM IS MAKING $17,200/MONTH. Dark club. Red and black dresses. One girl in latex, one in red satin, two more filling the frame from behind. They move like they own the room, lock eyes, press closer, and for 30 seconds the whole place feels like it revolves around them. That is exactly why the clip works. But here is the part most people miss: they are AI girls. No nightlife shoot. No real models. No promoter table. No camera crew. Just one operator building the characters, generating the clips, and pushing them through a content pipeline designed to farm attention. And it is not just “pretty girls dancing.” It is social proof compressed into half a minute. One girl can look staged. Four AI girls dancing together in a packed club looks like status, chaos, and instant curiosity. The viewer’s brain reads it as: something is happening here. That half-second pause is what stops the scroll, and once people stop, the algorithm does the rest. The funnel is simple. Short club clips go out on Instagram, TikTok, and repost pages built for reach. The best ones drive traffic into a paid page where subscriptions sit between $12.99 and $19.99 a month, with extra money coming from DMs, PPV drops, and upsells. One AI girl can make money. Four in one clip creates more tension, more replay value, and way more comments. The math is why creators keep doing it. At around 1.2M+ monthly views, a setup like this can convert enough traffic to clear $17,200 a month from subs, PPV, and retention. The production only looks expensive. In reality, once the pipeline is locked, the marginal cost of each new clip is almost nothing. That is the deeper lesson. The girls are not the business. The format is. Group energy. Club lighting. Tight framing. The feeling that everyone in the room is watching them. That is what sells the fantasy. The fact that they are AI only makes the model more scalable. So the real play is not just “make an AI girl.” It is: make AI girls that feel like they are at the center of a moment people want to step into. Attention first. Curiosity second. Money after that.

FOUR “BAD GIRLS” TOOK OVER THE DANCE FLOOR FOR 30 SECONDS. AND THE OPERATOR BEHIND THEM IS MAKING $17,200/MONTH. Dark club. Red and black dresses. One girl in latex, one in red satin, two more filling the frame from behind. They move like they own the room, lock eyes, press closer, and for 30 seconds the whole place feels like it revolves around them. That is exactly why the clip works. But here is the part most people miss: they are AI girls. No nightlife shoot. No real models. No promoter table. No camera crew. Just one operator building the characters, generating the clips, and pushing them through a content pipeline designed to farm attention. And it is not just “pretty girls dancing.” It is social proof compressed into half a minute. One girl can look staged. Four AI girls dancing together in a packed club looks like status, chaos, and instant curiosity. The viewer’s brain reads it as: something is happening here. That half-second pause is what stops the scroll, and once people stop, the algorithm does the rest. The funnel is simple. Short club clips go out on Instagram, TikTok, and repost pages built for reach. The best ones drive traffic into a paid page where subscriptions sit between $12.99 and $19.99 a month, with extra money coming from DMs, PPV drops, and upsells. One AI girl can make money. Four in one clip creates more tension, more replay value, and way more comments. The math is why creators keep doing it. At around 1.2M+ monthly views, a setup like this can convert enough traffic to clear $17,200 a month from subs, PPV, and retention. The production only looks expensive. In reality, once the pipeline is locked, the marginal cost of each new clip is almost nothing. That is the deeper lesson. The girls are not the business. The format is. Group energy. Club lighting. Tight framing. The feeling that everyone in the room is watching them. That is what sells the fantasy. The fact that they are AI only makes the model more scalable. So the real play is not just “make an AI girl.” It is: make AI girls that feel like they are at the center of a moment people want to step into. Attention first. Curiosity second. Money after that.

Rimi

19,265 views • 13 days ago

Generative AI is cool and all, but procedural 3D modeling just hits different. Check out this Houdini setup by Pepe Buendia. Why this is cool: Instead of manually placing every building and car, this system generates an NYC-style city that builds itself -- automatically spawning buildings with unique variations, plus a traffic system where cars actually obey traffic lights and avoid crashing into each other (all orchestrated through houdini VEX code). Each car knows exactly which road it's on and makes real-time decisions about navigation. The whole thing runs on custom algorithms that handle everything from road directions to building placement. If you did this with generative AI, even approaches to conditioning and taming the chaos -- you'd still get a ton of variance which might be an issue for visual and spatial consistency. To me this is procedural modeling at its finest - precise control meets infinite scalability. Immensely useful for media & entertainment, but also synthetic training data for robotics and augmented reality. I of course can't wait until multimodal LLMs to have the spatial understanding to write these kind of controllable 3D worlds for us. Claude counting 2D pixels on a screen is a step in this direction. Soon they'll be able to manipulate 2D ortho viewports, and eventually spawn procedural 3D worlds.

Generative AI is cool and all, but procedural 3D modeling just hits different. Check out this Houdini setup by Pepe Buendia. Why this is cool: Instead of manually placing every building and car, this system generates an NYC-style city that builds itself -- automatically spawning buildings with unique variations, plus a traffic system where cars actually obey traffic lights and avoid crashing into each other (all orchestrated through houdini VEX code). Each car knows exactly which road it's on and makes real-time decisions about navigation. The whole thing runs on custom algorithms that handle everything from road directions to building placement. If you did this with generative AI, even approaches to conditioning and taming the chaos -- you'd still get a ton of variance which might be an issue for visual and spatial consistency. To me this is procedural modeling at its finest - precise control meets infinite scalability. Immensely useful for media & entertainment, but also synthetic training data for robotics and augmented reality. I of course can't wait until multimodal LLMs to have the spatial understanding to write these kind of controllable 3D worlds for us. Claude counting 2D pixels on a screen is a step in this direction. Soon they'll be able to manipulate 2D ortho viewports, and eventually spawn procedural 3D worlds.

Bilawal Sidhu

527,814 views • 1 year ago

Wow, since the last post blew up, here is another fascinating insight from my years working with car-on-demand companies and more traditional automakers. Most people still think the entire automotive business is about selling or leasing vehicles. But there is a new market emerging that is absolutely massive: data Modern cars are packed with sensors and constantly collect real-time information. And this data is quickly becoming one of the most valuable revenue streams in the industry. Companies like Tesla, with their autonomous, sensor-rich fleets, are positioned to benefit enormously, but the same applies to many newer connected vehicles across all brands. What makes this so powerful is how diverse the use cases are. Cities, for example, can tap into aggregated vehicle data to understand exactly where they need to intervene. If thousands of cars detect the same irregular bump on the road, you instantly know there is a pothole at a precise location. Scale that across a whole city and you have a live map of infrastructure issues before residents even complain. The same data can help optimize traffic flow, identify congestion patterns in real time, or highlight zones where drivers consistently brake or accelerate suddenly, revealing potential safety problems. Automakers can also use this information to better understand how people actually drive in the real world, which directly influences design, durability testing, and product evolution And then there is the insurance angle. As driving behavior becomes measurable at scale, dynamic insurance pricing emerge. Acceleration habits, braking patterns, cornering, speed consistency, environmental context all of this will feed into future scoring models What we are seeing right now is only the beginning. With cars full of electronics, sensors, and especially autonomous vision systems, data is becoming one of the largest and most predictable revenue lines for automakers and mobility companies. Even traditional vehicles are now connected and constantly transmitting information that can be analyzed or monetized in multiple ways We are still just scratching the surface, but the shift is already underway. The value is no longer just in the vehicle itself. It is also in the billions of data points it generates every single day

Wow, since the last post blew up, here is another fascinating insight from my years working with car-on-demand companies and more traditional automakers. Most people still think the entire automotive business is about selling or leasing vehicles. But there is a new market emerging that is absolutely massive: data Modern cars are packed with sensors and constantly collect real-time information. And this data is quickly becoming one of the most valuable revenue streams in the industry. Companies like Tesla, with their autonomous, sensor-rich fleets, are positioned to benefit enormously, but the same applies to many newer connected vehicles across all brands. What makes this so powerful is how diverse the use cases are. Cities, for example, can tap into aggregated vehicle data to understand exactly where they need to intervene. If thousands of cars detect the same irregular bump on the road, you instantly know there is a pothole at a precise location. Scale that across a whole city and you have a live map of infrastructure issues before residents even complain. The same data can help optimize traffic flow, identify congestion patterns in real time, or highlight zones where drivers consistently brake or accelerate suddenly, revealing potential safety problems. Automakers can also use this information to better understand how people actually drive in the real world, which directly influences design, durability testing, and product evolution And then there is the insurance angle. As driving behavior becomes measurable at scale, dynamic insurance pricing emerge. Acceleration habits, braking patterns, cornering, speed consistency, environmental context all of this will feed into future scoring models What we are seeing right now is only the beginning. With cars full of electronics, sensors, and especially autonomous vision systems, data is becoming one of the largest and most predictable revenue lines for automakers and mobility companies. Even traditional vehicles are now connected and constantly transmitting information that can be analyzed or monetized in multiple ways We are still just scratching the surface, but the shift is already underway. The value is no longer just in the vehicle itself. It is also in the billions of data points it generates every single day

Aurelien

72,062 views • 9 months ago

🚨 UVA Law Pays Anne Coughlin $375,700 to Flinch at “Police” and Hype Abolitionists as “The More the Merrier” UVA Law professor Anne Coughlin made $375,700 in 2024. Watch how she treats the word “police” like it’s radioactive: “I don’t wanna use the word police… some of you may be abolitionists… that’s fine, the more the merrier.” Then she turns a law school classroom into a policy shop: “You can insist that you get police out of traffic enforcement.” “You are going to convince your legislators, your city councils, your police that they should cut this out. They should no longer have police in traffic enforcement.” And she frames freedom as “being protected against the police.” Then she tells on herself: “I’m assuming everyone violates the traffic code all the time because I do,” and says the police tell her she’s “not a threat,” which “kind of upsets” her because she wants “to be scary.” Then comes the racial generalization: “My students of color say to me, ‘You violate the traffic laws all the time because you’re a white woman.’” This is not training lawyers. It’s training activists. A law school professor’s job is to teach students how to argue both sides, not hand them a preloaded ideology and call it “education.” And yes, there’s another side she skips. Traffic enforcement is one of the main ways serious crime gets caught in real time: DUI, stolen vehicles, illegal guns, warrants, missing persons, and suspects. Stops and crashes can turn volatile fast, and civilian “ticketing” units don’t have the authority or capacity to detain, investigate, arrest, and control chaotic scenes end-to-end. Reform is fair game, but “no police in traffic enforcement” ignores deterrence, escalation, and the evidentiary work that actually delivers public safety and justice. And notice the move: “the court has said,” then “Justice Thomas has indicated,” so one justice’s views get treated as the Supreme Court. If UVA Law wants to be an activist academy, say so. If it wants to be a law school, start acting like one. Next: the UVA professor targeted by colleagues for taking a Supreme Court case that went 9–0.

🚨 UVA Law Pays Anne Coughlin $375,700 to Flinch at “Police” and Hype Abolitionists as “The More the Merrier” UVA Law professor Anne Coughlin made $375,700 in 2024. Watch how she treats the word “police” like it’s radioactive: “I don’t wanna use the word police… some of you may be abolitionists… that’s fine, the more the merrier.” Then she turns a law school classroom into a policy shop: “You can insist that you get police out of traffic enforcement.” “You are going to convince your legislators, your city councils, your police that they should cut this out. They should no longer have police in traffic enforcement.” And she frames freedom as “being protected against the police.” Then she tells on herself: “I’m assuming everyone violates the traffic code all the time because I do,” and says the police tell her she’s “not a threat,” which “kind of upsets” her because she wants “to be scary.” Then comes the racial generalization: “My students of color say to me, ‘You violate the traffic laws all the time because you’re a white woman.’” This is not training lawyers. It’s training activists. A law school professor’s job is to teach students how to argue both sides, not hand them a preloaded ideology and call it “education.” And yes, there’s another side she skips. Traffic enforcement is one of the main ways serious crime gets caught in real time: DUI, stolen vehicles, illegal guns, warrants, missing persons, and suspects. Stops and crashes can turn volatile fast, and civilian “ticketing” units don’t have the authority or capacity to detain, investigate, arrest, and control chaotic scenes end-to-end. Reform is fair game, but “no police in traffic enforcement” ignores deterrence, escalation, and the evidentiary work that actually delivers public safety and justice. And notice the move: “the court has said,” then “Justice Thomas has indicated,” so one justice’s views get treated as the Supreme Court. If UVA Law wants to be an activist academy, say so. If it wants to be a law school, start acting like one. Next: the UVA professor targeted by colleagues for taking a Supreme Court case that went 9–0.

Stu Smith

516,283 views • 9 months ago

The Atlas Miner is finally here and Drive2Earn 2.0 is rolling out with an excellent explanation given by Chico Crypto-"The Most Trustless Name in News" in his 5 minute video. This is how the Atlas Miner works: 1. Dedicated DePIN + AI hardware device 2. Connects to any dash camera 3. Collects driving footage, which is anonymized and shared with vehicle manufacturers to train their self driving vehicles (we have such a vehicle for testing already). 4. Uses custom A.I. computer vision algorithms to detect traffic issues (accidents, congestion, road closures, road work, potholes, police cars) and sends these detections to other drivers on the Atlas Navi app rerouting them to avoid those areas 5. Price $300 + shipping, payable in $NAVI only. 6. Get paid for every beneficial data point you collect. This data is very valuable to drivers using Atlas Navi, to car manufacturers and smart cities. Owners of Atlas Miner are rewarded for every mile driven on top of regular NFT rewards. The Autonomous Driving market is expected to reach $6T within the next eight years and we aim to be the main provider of driving data for training these algorithms and real time traffic notification / routing for such vehicles. We are opening the whitelist for a limited quantity of Atlas Miners. Sign up to the whitelist and get rewarded for every mile driven: #NAVI #DePIN #AtlasMiner

The Atlas Miner is finally here and Drive2Earn 2.0 is rolling out with an excellent explanation given by Chico Crypto-"The Most Trustless Name in News" in his 5 minute video. This is how the Atlas Miner works: 1. Dedicated DePIN + AI hardware device 2. Connects to any dash camera 3. Collects driving footage, which is anonymized and shared with vehicle manufacturers to train their self driving vehicles (we have such a vehicle for testing already). 4. Uses custom A.I. computer vision algorithms to detect traffic issues (accidents, congestion, road closures, road work, potholes, police cars) and sends these detections to other drivers on the Atlas Navi app rerouting them to avoid those areas 5. Price $300 + shipping, payable in $NAVI only. 6. Get paid for every beneficial data point you collect. This data is very valuable to drivers using Atlas Navi, to car manufacturers and smart cities. Owners of Atlas Miner are rewarded for every mile driven on top of regular NFT rewards. The Autonomous Driving market is expected to reach $6T within the next eight years and we aim to be the main provider of driving data for training these algorithms and real time traffic notification / routing for such vehicles. We are opening the whitelist for a limited quantity of Atlas Miners. Sign up to the whitelist and get rewarded for every mile driven: #NAVI #DePIN #AtlasMiner

ATLAS NAVI | AI Navigation APP with 1M Downloads

360,334 views • 2 years ago

Stanley Druckenmiller, who has relied heavily on technical analysis during his career, recently said: “I can unequivocally tell you that technical analysis is about 20% as effective today as it was 30 years ago, because no one was using it. But when everybody’s using it, it doesn’t work anymore because you don’t have a unique thing to act against.” If even Druckenmiller says this, it reinforces a simple idea: What really matters is buying great companies and avoiding overpaying for them. As Peter Lynch used to say, in the long run the price of a stock will follow the company’s economic results — regardless of the “drawings” on a chart. “If charts could really predict the future, technical analysts would all be billionaires.” Technical analysis is more of a distraction than anything else. The real edge isn’t drawing lines. It’s understanding businesses.

Stanley Druckenmiller, who has relied heavily on technical analysis during his career, recently said: “I can unequivocally tell you that technical analysis is about 20% as effective today as it was 30 years ago, because no one was using it. But when everybody’s using it, it doesn’t work anymore because you don’t have a unique thing to act against.” If even Druckenmiller says this, it reinforces a simple idea: What really matters is buying great companies and avoiding overpaying for them. As Peter Lynch used to say, in the long run the price of a stock will follow the company’s economic results — regardless of the “drawings” on a chart. “If charts could really predict the future, technical analysts would all be billionaires.” Technical analysis is more of a distraction than anything else. The real edge isn’t drawing lines. It’s understanding businesses.

Daniel

489,106 views • 6 months ago

🚨NYC Shutting Down Another Traffic Lane – Causing More Gridlock and Making You Pay for It !! 🚨 I’ve been investigating the streets of New York City for a long time. As a NYC driver, I see firsthand how congestion and traffic aren’t just happening by accident—they’re being created by the city’s own bad street designs. And now, they expect us to pay for it with congestion pricing, draining the wallets of middle- and lower-class New Yorkers. Last month alone, the city made over $50 million from congestion pricing—money taken straight from the pockets of hardworking New Yorkers who have no choice but to drive. And instead of fixing the streets, they’re making things even worse. Now, the city is rolling out a new street design that will shut down another traffic lane on Sixth Avenue to make way for a double-wide bike lane. This means fewer lanes for cars, leading to even more gridlock in one of the busiest parts of Manhattan. Sixth Avenue is already packed with delivery trucks, taxis, rideshares, buses, and regular commuters—now the city is making it worse by cutting down road space even further. What do they think is going to happen when they remove a lane of traffic from one of the most congested streets in Midtown? Traffic will back up even more, drivers will be forced to sit in gridlock for longer periods, and emergency vehicles will struggle to get through. This isn't about making the streets better—this is about making it impossible to drive in NYC, forcing people to give up their cars and rely on an already broken public transit system. Meanwhile, bike lanes keep getting expanded while the city ignores the real traffic problems. The reality is, bike lanes aren’t being used nearly as much as the city wants you to believe. Most of the time, they sit empty, while cars and buses are crammed into fewer and fewer lanes. This isn’t about safety—it’s about forcing an anti-car agenda on the people who actually need to drive. And what’s their solution? They want to force you onto the subway—a transit system that’s more dangerous than ever. Over the past few months, we’ve all seen the rise in subway violence—stabbings, robberies, and assaults happening daily. The same politicians who created this mess, like Governor Hochul and the MTA, expect us to just accept it. Instead of making the trains safer, they’re making driving impossible. And let’s talk about the MTA—New York’s never-ending money pit. Billions of dollars pour into the system every year, and yet we never see any real improvements. Trains still break down, stations are filthy, service is unreliable, and crime is out of control. The MTA always claims they need more funding, yet no one ever asks where all the money is actually going. Meanwhile, the people who rely on the subway are stuck dealing with fare hikes, delays, and dangerous conditions. But the damage doesn’t stop there. I’ve been speaking with business owners throughout New York City, and they all tell me the same thing—sales are down since congestion pricing rolled out. With fewer people driving into the city, foot traffic has dropped, and small businesses are suffering. Shops, restaurants, and other local businesses that rely on a steady flow of customers are now seeing empty stores and struggling to stay afloat. Business owners have told me the city just isn’t the same anymore. This isn’t about reducing congestion—it’s about punishing drivers, killing small businesses, and squeezing more money out of the people who can least afford it. New York City is no longer a place for the working class. The politicians and bureaucrats behind this mess don’t care—because they’re not the ones stuck in traffic, struggling to run a business, or riding the subways in fear. We are.

🚨NYC Shutting Down Another Traffic Lane – Causing More Gridlock and Making You Pay for It !! 🚨 I’ve been investigating the streets of New York City for a long time. As a NYC driver, I see firsthand how congestion and traffic aren’t just happening by accident—they’re being created by the city’s own bad street designs. And now, they expect us to pay for it with congestion pricing, draining the wallets of middle- and lower-class New Yorkers. Last month alone, the city made over $50 million from congestion pricing—money taken straight from the pockets of hardworking New Yorkers who have no choice but to drive. And instead of fixing the streets, they’re making things even worse. Now, the city is rolling out a new street design that will shut down another traffic lane on Sixth Avenue to make way for a double-wide bike lane. This means fewer lanes for cars, leading to even more gridlock in one of the busiest parts of Manhattan. Sixth Avenue is already packed with delivery trucks, taxis, rideshares, buses, and regular commuters—now the city is making it worse by cutting down road space even further. What do they think is going to happen when they remove a lane of traffic from one of the most congested streets in Midtown? Traffic will back up even more, drivers will be forced to sit in gridlock for longer periods, and emergency vehicles will struggle to get through. This isn't about making the streets better—this is about making it impossible to drive in NYC, forcing people to give up their cars and rely on an already broken public transit system. Meanwhile, bike lanes keep getting expanded while the city ignores the real traffic problems. The reality is, bike lanes aren’t being used nearly as much as the city wants you to believe. Most of the time, they sit empty, while cars and buses are crammed into fewer and fewer lanes. This isn’t about safety—it’s about forcing an anti-car agenda on the people who actually need to drive. And what’s their solution? They want to force you onto the subway—a transit system that’s more dangerous than ever. Over the past few months, we’ve all seen the rise in subway violence—stabbings, robberies, and assaults happening daily. The same politicians who created this mess, like Governor Hochul and the MTA, expect us to just accept it. Instead of making the trains safer, they’re making driving impossible. And let’s talk about the MTA—New York’s never-ending money pit. Billions of dollars pour into the system every year, and yet we never see any real improvements. Trains still break down, stations are filthy, service is unreliable, and crime is out of control. The MTA always claims they need more funding, yet no one ever asks where all the money is actually going. Meanwhile, the people who rely on the subway are stuck dealing with fare hikes, delays, and dangerous conditions. But the damage doesn’t stop there. I’ve been speaking with business owners throughout New York City, and they all tell me the same thing—sales are down since congestion pricing rolled out. With fewer people driving into the city, foot traffic has dropped, and small businesses are suffering. Shops, restaurants, and other local businesses that rely on a steady flow of customers are now seeing empty stores and struggling to stay afloat. Business owners have told me the city just isn’t the same anymore. This isn’t about reducing congestion—it’s about punishing drivers, killing small businesses, and squeezing more money out of the people who can least afford it. New York City is no longer a place for the working class. The politicians and bureaucrats behind this mess don’t care—because they’re not the ones stuck in traffic, struggling to run a business, or riding the subways in fear. We are.

Viral News NYC

149,961 views • 1 year ago

I just published a new tutorial on how to build a directory using AI and no-code tools. Directories are the ultimate MVP. They let you validate an idea, build traffic, and then pivot into something bigger—like SaaS or a marketplace. Remember when Yahoo and DMOZ ruled the internet? Okay, maybe you don’t, but they did. They curated the web back when search engines were clunky and unreliable. Fast forward to today—directories are making a quiet comeback. And it’s not about nostalgia. The 5 step playbook that we go through: 1. Niche first, features later Use Google Keyword Planner to find high-volume, low-competition keywords. Lock in a matching domain. 2. Build fast No-code tools + AI = rapid setup. Let AI generate the initial content and structure for you. 3. Promote smart Share on Reddit, list your directory in other directories, and engage on Twitter. 4. SEO from day one Start with 10 high-quality articles and solid internal linking. 5. Monetize as you grow Affiliate links, premium listings, B2B sponsorships. It’s all on the table. A directory can be a side hustle that pulls in $5K MRR. Then, once you’ve got traffic, you can scale into SaaS or a marketplace. It literallyyyyy pays to have traffic for your software startup. Why aren’t more people talking about this? Huge shoutout to John Rush for giving us a free masterclass on this exact strategy. Legend. You’ll want to watch to this episode on directories. I respond to all comments and appreciate them. Audio is over here if you prefer listening: Directories are cool - it’s the perfect foundation for something much bigger. Was this interesting? Well, reply to me with if it was and what you'd like to learn next on The Startup ideas Podcast. People like to gate this type of content. I won't. I live to serve and will continue sharing this info for free.

I just published a new tutorial on how to build a directory using AI and no-code tools. Directories are the ultimate MVP. They let you validate an idea, build traffic, and then pivot into something bigger—like SaaS or a marketplace. Remember when Yahoo and DMOZ ruled the internet? Okay, maybe you don’t, but they did. They curated the web back when search engines were clunky and unreliable. Fast forward to today—directories are making a quiet comeback. And it’s not about nostalgia. The 5 step playbook that we go through: 1. Niche first, features later Use Google Keyword Planner to find high-volume, low-competition keywords. Lock in a matching domain. 2. Build fast No-code tools + AI = rapid setup. Let AI generate the initial content and structure for you. 3. Promote smart Share on Reddit, list your directory in other directories, and engage on Twitter. 4. SEO from day one Start with 10 high-quality articles and solid internal linking. 5. Monetize as you grow Affiliate links, premium listings, B2B sponsorships. It’s all on the table. A directory can be a side hustle that pulls in $5K MRR. Then, once you’ve got traffic, you can scale into SaaS or a marketplace. It literallyyyyy pays to have traffic for your software startup. Why aren’t more people talking about this? Huge shoutout to John Rush for giving us a free masterclass on this exact strategy. Legend. You’ll want to watch to this episode on directories. I respond to all comments and appreciate them. Audio is over here if you prefer listening: Directories are cool - it’s the perfect foundation for something much bigger. Was this interesting? Well, reply to me with if it was and what you'd like to learn next on The Startup ideas Podcast. People like to gate this type of content. I won't. I live to serve and will continue sharing this info for free.

GREG ISENBERG

120,737 views • 1 year ago

Joe Biden can’t help this guy… Foreigner wants to FAFO…and he does.. If a driver tells officers they have a gun and then reaches for it, do police have any other option besides using force? What started as a routine traffic stop suddenly turned into a life or death situation in seconds. Bodycam footage shows officers pulling over a driver after noticing something wasn’t right. At first, it looked like a normal stop. But the driver quickly became extremely aggressive. According to the footage, the man began shouting at officers, telling them to “go back to your car, sit there, and leave.” Instead of calming down, the situation escalated. The driver reportedly told officers he had a gun and continued refusing commands. At one point, he even insisted he would call President Joe Biden to excuse the situation, while continuing to argue and ignore the officers. Moments later, the situation reached a critical point. Officers say the man reached toward his firearm, forcing them to make a split-second decision to protect themselves and everyone around them. Within seconds, the confrontation was over. What began as a simple traffic stop quickly turned into a dangerous encounter where officers had to react immediately once a weapon entered the situation. Do incidents like this show how quickly a few bad decisions can escalate a routine stop into tragedy?

Joe Biden can’t help this guy… Foreigner wants to FAFO…and he does.. If a driver tells officers they have a gun and then reaches for it, do police have any other option besides using force? What started as a routine traffic stop suddenly turned into a life or death situation in seconds. Bodycam footage shows officers pulling over a driver after noticing something wasn’t right. At first, it looked like a normal stop. But the driver quickly became extremely aggressive. According to the footage, the man began shouting at officers, telling them to “go back to your car, sit there, and leave.” Instead of calming down, the situation escalated. The driver reportedly told officers he had a gun and continued refusing commands. At one point, he even insisted he would call President Joe Biden to excuse the situation, while continuing to argue and ignore the officers. Moments later, the situation reached a critical point. Officers say the man reached toward his firearm, forcing them to make a split-second decision to protect themselves and everyone around them. Within seconds, the confrontation was over. What began as a simple traffic stop quickly turned into a dangerous encounter where officers had to react immediately once a weapon entered the situation. Do incidents like this show how quickly a few bad decisions can escalate a routine stop into tragedy?

𝐌𝐑. 𝐖𝐇𝐈𝐓𝐄 ™

26,729 views • 6 months ago

I just press a button… and my Tesla takes me to my destination. No stress, no constant steering, no thinking about every little turn. It just drives me safely there. And honestly, it’s hard to explain this feeling to someone who hasn’t experienced the latest software yet. It’s freakin 2026... If your car isn’t electric and can’t take you from parking lot to parking lot by itself, it's like using a flip phone with a keyboard… or riding a horse in this era. That might sound dramatic, but once you see what’s actually happening behind the scenes, it starts to make sense. When I activate Tesla’s Full Self-Driving, the car is doing far more than simple cruise control that other car companies show off... it's really funny when I see them advertise it tbh. My Tesla is literally watching the world around it with eight cameras that give it a full 360° view. All that video feeds into the onboard AI computer inside the car, which is constantly analyzing everything around it like cars, lanes, pedestrians, traffic lights, construction zones, and making decisions in real time. Tesla has millions of cars on the road, and every single one is helping train the system. Even when people are driving manually, the AI is running quietly in the background predicting what it would do in that situation. And when something unusual happens, a weird intersection, a sudden obstacle, an unexpected move from another driver, that short clip gets sent back to Tesla’s data systems. Engineers then use those clips to train the next version of the driving AI. And that updated AI then gets pushed back to every Tesla through a software update. So literally overnight, your car wakes up smarter. This is what we call the Tesla’s AI flywheel. The more cars on the road, the more data the system learns from. The more it learns, the better the driving gets. The better the driving gets, the more people use it. And that cycle just keeps spinning faster. At this point the fleet has driven billions of miles using FSD, which means the system has already experienced situations that no single human driver could ever see in a lifetime. That’s why when you press that button, the car is running a massive neural network that learned from millions of real drivers and billions of miles on real roads. And the result is something that honestly feels like the future. You literally just press a button… then you arrive at your destination. I really don't know how anyone in their right mind would choose anything other than a Tesla.

I just press a button… and my Tesla takes me to my destination. No stress, no constant steering, no thinking about every little turn. It just drives me safely there. And honestly, it’s hard to explain this feeling to someone who hasn’t experienced the latest software yet. It’s freakin 2026... If your car isn’t electric and can’t take you from parking lot to parking lot by itself, it's like using a flip phone with a keyboard… or riding a horse in this era. That might sound dramatic, but once you see what’s actually happening behind the scenes, it starts to make sense. When I activate Tesla’s Full Self-Driving, the car is doing far more than simple cruise control that other car companies show off... it's really funny when I see them advertise it tbh. My Tesla is literally watching the world around it with eight cameras that give it a full 360° view. All that video feeds into the onboard AI computer inside the car, which is constantly analyzing everything around it like cars, lanes, pedestrians, traffic lights, construction zones, and making decisions in real time. Tesla has millions of cars on the road, and every single one is helping train the system. Even when people are driving manually, the AI is running quietly in the background predicting what it would do in that situation. And when something unusual happens, a weird intersection, a sudden obstacle, an unexpected move from another driver, that short clip gets sent back to Tesla’s data systems. Engineers then use those clips to train the next version of the driving AI. And that updated AI then gets pushed back to every Tesla through a software update. So literally overnight, your car wakes up smarter. This is what we call the Tesla’s AI flywheel. The more cars on the road, the more data the system learns from. The more it learns, the better the driving gets. The better the driving gets, the more people use it. And that cycle just keeps spinning faster. At this point the fleet has driven billions of miles using FSD, which means the system has already experienced situations that no single human driver could ever see in a lifetime. That’s why when you press that button, the car is running a massive neural network that learned from millions of real drivers and billions of miles on real roads. And the result is something that honestly feels like the future. You literally just press a button… then you arrive at your destination. I really don't know how anyone in their right mind would choose anything other than a Tesla.

Teslaconomics

19,059 views • 6 months ago