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Xiaopeng vs Tesla FSD: Same scenario, big difference ⚡ Top: Xiaopeng autonomous driving nearly crashes, forcing takeover. Bottom: FSD glides through smoothly, no issues. Tesla's edge in real-world autonomy is clear.

Tesla Aaron L

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144,564 просмотров • 4 месяцев назад •via X (Twitter)

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🚨 Tesla FSD faces a no-win scenario Tesla on FSD at 47 mph on a rural two-lane road • Dog steps into the path as oncoming traffic fills the opposite lane •No shoulder available and no time to stop The system’s decision • Held its lane • Protected the people in both vehicles • Dog was hit Why it matters • Classic real-world trolley problem • Safety rule: never trade an animal for a human collision • Humans often swerve and cause worse crashes Hard to watch. This is what maturing autonomous judgment looks like.

🚨 Tesla FSD faces a no-win scenario Tesla on FSD at 47 mph on a rural two-lane road • Dog steps into the path as oncoming traffic fills the opposite lane •No shoulder available and no time to stop The system’s decision • Held its lane • Protected the people in both vehicles • Dog was hit Why it matters • Classic real-world trolley problem • Safety rule: never trade an animal for a human collision • Humans often swerve and cause worse crashes Hard to watch. This is what maturing autonomous judgment looks like.

Joe Hansen

396,774 просмотров • 10 дней назад

FSD 14.3.3 is another reminder that Tesla owners are basically beta-testing the future in public. The latest update now tracks intervention-free driving distance and your longest no-takeover streak directly inside the app. People can literally watch the AI getting better over time through real-world driving stats. Every time a driver intervenes? Tesla now asks why, feeding more training data back into the system. The car is learning from millions of humans simultaneously. Tesla

FSD 14.3.3 is another reminder that Tesla owners are basically beta-testing the future in public. The latest update now tracks intervention-free driving distance and your longest no-takeover streak directly inside the app. People can literally watch the AI getting better over time through real-world driving stats. Every time a driver intervenes? Tesla now asks why, feeding more training data back into the system. The car is learning from millions of humans simultaneously. Tesla

Mario Nawfal

65,679 просмотров • 2 месяцев назад

Europe is ready. FSD has proven itself. Millions of kilometers of real-world driving data. Continuous improvements through software updates. Now we wait. Hopefully March 20 will bring approval from the RDW so this technology can finally move forward in Europe. Europe is ready. 💪 $TSLA #FSD Elon Musk Tesla Europe, Middle East & Africa 👇🏻

Europe is ready. FSD has proven itself. Millions of kilometers of real-world driving data. Continuous improvements through software updates. Now we wait. Hopefully March 20 will bring approval from the RDW so this technology can finally move forward in Europe. Europe is ready. 💪 $TSLA #FSD Elon Musk Tesla Europe, Middle East & Africa 👇🏻

Tesla Inside

13,470 просмотров • 5 месяцев назад

At CES, major Chinese legacy automaker Great Wall Motors (GWM) showcases its autonomous driving system HPilot, powered by its proprietary end-to-end VLA training model designed to handle all road scenarios the way a human driver would. To understand Tesla’s autonomous capabilities, one of GWM executives traveled nearly 700 miles from the Bay Area to Las Vegas using Tesla FSD. Over a 12-hour drive, there was not a single takeover. Why are Western automakers so comfortable with the status quo when it comes to autonomy while Chinese legacy automakers are moving in that direction with urgency? The tide is turning, and those who hesitate risk being left behind.

At CES, major Chinese legacy automaker Great Wall Motors (GWM) showcases its autonomous driving system HPilot, powered by its proprietary end-to-end VLA training model designed to handle all road scenarios the way a human driver would. To understand Tesla’s autonomous capabilities, one of GWM executives traveled nearly 700 miles from the Bay Area to Las Vegas using Tesla FSD. Over a 12-hour drive, there was not a single takeover. Why are Western automakers so comfortable with the status quo when it comes to autonomy while Chinese legacy automakers are moving in that direction with urgency? The tide is turning, and those who hesitate risk being left behind.

Ray

27,520 просмотров • 6 месяцев назад

Here is why I disengaged FSD 14.3.3. Before this clip starts, I could see a semi coming down the on ramp and saw that it had some momentum. FSD did not slow down but the truck in the right lane would have ran into the other semi and either had to brake real hard or switch lanes. I took over to make it clear to the semi driver that I would let them over. No big deal, would be nice, if FSD could have seen that coming and facilitated that move. Tesla AI

Here is why I disengaged FSD 14.3.3. Before this clip starts, I could see a semi coming down the on ramp and saw that it had some momentum. FSD did not slow down but the truck in the right lane would have ran into the other semi and either had to brake real hard or switch lanes. I took over to make it clear to the semi driver that I would let them over. No big deal, would be nice, if FSD could have seen that coming and facilitated that move. Tesla AI

Andy ze German

32,632 просмотров • 1 месяц назад

We knew this was going to happen at some point, somewhere. We now have politicians officially trying to dictate what hardware autonomous companies like Tesla need to use (lol) Sen. Andrew Zwicker: "At this point, I don't think the evidence is sufficient that a single sensor with software can handle situations that humans can." Apparently Tesla's nearly 12B real world miles on FSD and Unsupervised Robotaxi operations in four cities with cameras only isn't enough evidence? This will surely not be the last time this happens Be sure to oppose this ridiculous bill with Tesla at the link below $TSLA

We knew this was going to happen at some point, somewhere. We now have politicians officially trying to dictate what hardware autonomous companies like Tesla need to use (lol) Sen. Andrew Zwicker: "At this point, I don't think the evidence is sufficient that a single sensor with software can handle situations that humans can." Apparently Tesla's nearly 12B real world miles on FSD and Unsupervised Robotaxi operations in four cities with cameras only isn't enough evidence? This will surely not be the last time this happens Be sure to oppose this ridiculous bill with Tesla at the link below $TSLA

Dillon Loomis

300,219 просмотров • 25 дней назад

Tesla cars, especially with FSD, are the safest ever built and nothing else comes close Every Tesla carries a top-notch 5-star NHTSA rating Even the starting model doesn't have any compromises on this part Now Pair that with FSD Supervised and you're looking at a system ~9x safer than the average U.S. driver - 5-Star NHTSA ratings across every model - FSD Supervised: ~9x safer than the avg. U.S. driver (1 crash per 6.36M miles, Q3 2025) - Euro NCAP Best-in-Class 2025 - Model 3 & Model Y - Model Y: Highest Euro NCAP score ever recorded (362 pts) Engineered to protect everyone inside and outside the car There are real-life incidents where people have walked away unharmed from crashes so severe they would have been fatal in any other car. Tesla's safety is not just numbers on paper; it saves lives every day The safest cars ever built and getting safer every day Tesla did not just raise the bar. It inspired the entire industry to follow

Tesla cars, especially with FSD, are the safest ever built and nothing else comes close Every Tesla carries a top-notch 5-star NHTSA rating Even the starting model doesn't have any compromises on this part Now Pair that with FSD Supervised and you're looking at a system ~9x safer than the average U.S. driver - 5-Star NHTSA ratings across every model - FSD Supervised: ~9x safer than the avg. U.S. driver (1 crash per 6.36M miles, Q3 2025) - Euro NCAP Best-in-Class 2025 - Model 3 & Model Y - Model Y: Highest Euro NCAP score ever recorded (362 pts) Engineered to protect everyone inside and outside the car There are real-life incidents where people have walked away unharmed from crashes so severe they would have been fatal in any other car. Tesla's safety is not just numbers on paper; it saves lives every day The safest cars ever built and getting safer every day Tesla did not just raise the bar. It inspired the entire industry to follow

X Freeze

18,612 просмотров • 4 месяцев назад

Life update: It’s been kinda hard the past two weeks. I’ve been trying to live normally but honestly it’s still hard. Been in and out of hospitals, figuring out surgery (keeps getting delayed), trying to work (hard to focus and sleep), travel for conferences, run Touchdown (was supposed to start fundraising two weeks ago). I’m very lucky to be alive, I was worried I was gonna go blind in my left eye. I was a passenger and FSD was on, so it’s honestly just made me really curious. How does perception actually work? How does the car identify and classify objects? Is all the inference done on the vehicle? Imma always support Elon Musk and I’ll always have tremendous respect for everyone at Tesla and Tesla_AI pushing the boundaries of engineering to help humanity. Engineering is extremely hard and no matter how hard you try you can’t get all edge cases. But I genuinely want to understand the engineering challenges behind FSD and autonomous driving. Is there anyone at Tesla_AI or Tesla I can talk to go thru this? I want to see how I can help make autonomous driving safer.

Life update: It’s been kinda hard the past two weeks. I’ve been trying to live normally but honestly it’s still hard. Been in and out of hospitals, figuring out surgery (keeps getting delayed), trying to work (hard to focus and sleep), travel for conferences, run Touchdown (was supposed to start fundraising two weeks ago). I’m very lucky to be alive, I was worried I was gonna go blind in my left eye. I was a passenger and FSD was on, so it’s honestly just made me really curious. How does perception actually work? How does the car identify and classify objects? Is all the inference done on the vehicle? Imma always support Elon Musk and I’ll always have tremendous respect for everyone at Tesla and Tesla_AI pushing the boundaries of engineering to help humanity. Engineering is extremely hard and no matter how hard you try you can’t get all edge cases. But I genuinely want to understand the engineering challenges behind FSD and autonomous driving. Is there anyone at Tesla_AI or Tesla I can talk to go thru this? I want to see how I can help make autonomous driving safer.

William Chen

964,054 просмотров • 13 часов назад

BREAKING: Tesla FSD V14.1 is downloading on my Model Y right now! This is the first major FSD update in nearly a year. FSD(Supervised) v14.1 includes: • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside. • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances). • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours. • Added additional Speed Profile to further customize driving style preference. • Improved handling for static and dynamic gates. • Improved offsetting for road debris (e.g. tires, tree branches, boxes). • Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses. Improved FSD's ability to manage system faults and recover smoothly from degraded operation for enhanced reliability. • Added automatic narrow field washing to provide rapid and efficient front camera self-cleaning, and optimize aerodynamics wash at higher vehicle speed. • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning! Upcoming Improvements: • Overall smoothness and sentience • Parking spot selection and parking quality

Sawyer Merritt

624,782 просмотров • 10 месяцев назад

My 7-year-old son thinks it’s completely normal for me to play chess with him while Tesla FSD drives us. But the more I think about this… it hit me. To him, Tesla FSD may not look like some amazing piece of technology... to him it’s just normal life. He never experienced a world where every second in a car required the driver to be fully focused on steering, braking, and navigating. For him, he sees a car that safely handles the driving while Dad spends that time talking with him, teaching him, laughing with him, or playing a game of chess. That’s a pretty big shift when you really think about it. Every generation grows up taking for granted things that once seemed impossible. The internet. Smartphones. Video calls. Now we’re watching the beginning of that same transition with autonomy. For many adults, FSD still feels futuristic. For kids growing up today, it’s become the way cars work. What’s fascinating is that the biggest change is what people do with the time it gives back. Instead of staring at the road for hours, families can spend more time together, learn, work, relax, or simply enjoy the ride. My son doesn’t see autonomy as a breakthrough, like me. He sees this as normal. And that’s how I know the future is here.

My 7-year-old son thinks it’s completely normal for me to play chess with him while Tesla FSD drives us. But the more I think about this… it hit me. To him, Tesla FSD may not look like some amazing piece of technology... to him it’s just normal life. He never experienced a world where every second in a car required the driver to be fully focused on steering, braking, and navigating. For him, he sees a car that safely handles the driving while Dad spends that time talking with him, teaching him, laughing with him, or playing a game of chess. That’s a pretty big shift when you really think about it. Every generation grows up taking for granted things that once seemed impossible. The internet. Smartphones. Video calls. Now we’re watching the beginning of that same transition with autonomy. For many adults, FSD still feels futuristic. For kids growing up today, it’s become the way cars work. What’s fascinating is that the biggest change is what people do with the time it gives back. Instead of staring at the road for hours, families can spend more time together, learn, work, relax, or simply enjoy the ride. My son doesn’t see autonomy as a breakthrough, like me. He sees this as normal. And that’s how I know the future is here.

Teslaconomics

45,087 просмотров • 1 месяц назад

TESLA SEMI: THE FUTURE OF TRUCKING IS ELECTRIC, EFFICIENT & AUTONOMOUS The Tesla Semi isn’t just another truck—it’s a complete redefinition of long-haul trucking. With production ramping up and deliveries accelerating, it’s already proving why electric Class 8 semis will dominate the industry. Why the Tesla Semi is critically important: •Unmatched efficiency & cost savings ~1.7 kWh/mile energy consumption (real-world data from PepsiCo & early fleets) — far lower than diesel equivalents. Operating costs drop dramatically with electricity vs. diesel, plus massive reductions in maintenance (no oil changes, fewer brake replacements thanks to regenerative braking). •Insane performance 0–60 mph in ~20 seconds fully loaded (500-mile range version), 0–60 in under 10 seconds in lighter configs. Instant torque makes hills and merging effortless—safer and faster than diesel trucks. •500+ mile range on a single charge Real-world highway range exceeds 500 miles even with heavy loads, eliminating most range anxiety for long-haul routes. Megachargers add hundreds of miles in ~30 minutes. •Autonomy-ready platform Built on Tesla’s Full Self-Driving hardware and software stack. Future unsupervised FSD will eliminate driver fatigue, reduce accidents (94% of which involve human error), and enable 24/7 operation—transforming driver economics and safety. •Environmental & regulatory edge Zero tailpipe emissions, helping fleets meet tightening emissions standards (California, EU, etc.). Lower noise pollution for urban deliveries and night operations. •Fleet economics revolution Lower TCO (total cost of ownership) than diesel trucks over the vehicle life. When combined with solar + Megapack charging depots, operating costs approach near-zero marginal energy cost. The Tesla Semi isn’t competing in trucking—it’s redefining the entire category. From PepsiCo’s early fleet to upcoming high-volume production, it’s the truck that makes electric long-haul not just possible, but inevitable 🚛⚡

TESLA SEMI: THE FUTURE OF TRUCKING IS ELECTRIC, EFFICIENT & AUTONOMOUS The Tesla Semi isn’t just another truck—it’s a complete redefinition of long-haul trucking. With production ramping up and deliveries accelerating, it’s already proving why electric Class 8 semis will dominate the industry. Why the Tesla Semi is critically important: •Unmatched efficiency & cost savings ~1.7 kWh/mile energy consumption (real-world data from PepsiCo & early fleets) — far lower than diesel equivalents. Operating costs drop dramatically with electricity vs. diesel, plus massive reductions in maintenance (no oil changes, fewer brake replacements thanks to regenerative braking). •Insane performance 0–60 mph in ~20 seconds fully loaded (500-mile range version), 0–60 in under 10 seconds in lighter configs. Instant torque makes hills and merging effortless—safer and faster than diesel trucks. •500+ mile range on a single charge Real-world highway range exceeds 500 miles even with heavy loads, eliminating most range anxiety for long-haul routes. Megachargers add hundreds of miles in ~30 minutes. •Autonomy-ready platform Built on Tesla’s Full Self-Driving hardware and software stack. Future unsupervised FSD will eliminate driver fatigue, reduce accidents (94% of which involve human error), and enable 24/7 operation—transforming driver economics and safety. •Environmental & regulatory edge Zero tailpipe emissions, helping fleets meet tightening emissions standards (California, EU, etc.). Lower noise pollution for urban deliveries and night operations. •Fleet economics revolution Lower TCO (total cost of ownership) than diesel trucks over the vehicle life. When combined with solar + Megapack charging depots, operating costs approach near-zero marginal energy cost. The Tesla Semi isn’t competing in trucking—it’s redefining the entire category. From PepsiCo’s early fleet to upcoming high-volume production, it’s the truck that makes electric long-haul not just possible, but inevitable 🚛⚡

Tesla Owners Silicon Valley

15,161 просмотров • 5 месяцев назад

Today I had my first demo drive in a Tesla. It was also my first time ever sitting in one. This was the first car I’ve ever sat in the driver’s seat of where I didn’t touch the steering wheel for over 20 miles. Before I even got to the car, the people who had demoed it before me were an older married couple who were absolutely euphoric. They thought it was so cool that the car could drive itself. The Tesla employee told me this happens all the time. People come back from demo drives and tell the next test driver that they’re about to have an amazing experience. Little did I know, I’d end up carrying on the torch to the next couple demoing it after me. There was a ton of construction where I demoed the car, and FSD handled the entire drive extremely well. And yes, it can go through a drive-thru and stop at each window. The only thing I had to do was tap the pedal because it wouldn’t leave on its own, but it was still wild seeing the AI stop perfectly at the second window and wait. There are a million things I could write about why a Tesla feels like a better car and how much more it offers compared to a regular car. But for now, I’ll stick to FSD. There were only two moments that made me a little uneasy. The first was pretty minor. The car slightly hesitated going up a driveway, but quickly made up its mind. The second was more noticeable. I didn’t realize the car was nagging me. Once I touched the steering wheel, nothing happened, so I pulled it right a little harder, then let go. After that, the car turned left and crossed a double yellow on a backroad. (and yes I know you can sue the volume knob) I’m not totally sure if it was trying to pull over or what it was doing. I wanted to see how it would handle the situation, but there were cars coming, so I took over and corrected it. One of the coolest moments was when I thought FSD was glitching because it came to a complete stop in the middle of a busy road. Then I looked around and realized why. On the right side, there was a bicyclist waiting at a yellow crosswalk. The cars behind me didn’t honk, and the Tesla stopping actually incentivized another car in the right lane to stop and let him pass. The car is almost too nice to pedestrians, because 99.999% of humans would’ve blown through that, especially with no flashing light. For 99.9% of the drive, the car navigated confidently and smoothly. It was a real “feel the AGI” moment. Please do not let the media, the general public, or anyone else convince you that this technology is just some kind of auto assist or glorified cruise control. This is undoubtedly getting extremely close to feeling superhuman. You still have to pay attention to the road, but after experiencing it myself, I’d be shocked if HW4 Teslas aren’t unsupervised within the next couple years. The car was extremely smooth. There was no harsh braking, and it even avoided something in the road that I didn’t see. Driving with FSD made me realize I probably wasn’t driving as well as I could be. Hopefully, eventually, everyone’s car can be as mindful as a Tesla. I’ve never seen a brand so far removed from the public’s sentiment. I’m so happy I ordered one.

Chris

18,722 просмотров • 1 месяц назад

FSD 14.3.5 Down Under initial review Let me start right at the top by saying that in my 2.5 hour drive, I had 2 instances of a critical issue which I'm sad to say, in my opinion is a blocker to any wide roll-out of this build. The issue is shown in the clip below, which I'm calling the "Wiggle of Death". Half way through the roundabout you can see the steering wheel start wiggling from left to right as the car heads straight for the curb. Had I not intervened, it could have resulted in an impact. The other instance was the same behaviour, only towards a curb while turning right in a car park. Sorry guys, but it is what it is. It's what early access testing is for. On a more positive note, several major issues have been addressed in this build: FIXED: 🎉110km/h zones - they work perfectly now! Locked in at 115 in hurry, 112 in standard and 109 in chill. We don't talk about sloth on this account 😆 🎉 Follow distance / tailgating is resolved. Hurry now feels super comfortable and standard sits just a little further back again. 🎉 Lane changes were not a problem the entire drive. Every single one felt natural. I never really had many issues on 14.3.3 though tbh INCONCLUSIVE Speed sign recognition - I didn't have any instances today of it misreading a speed sign, however I didn't pass any 90 signs this time which have been most problematic on 14.3.3 - need more testing to confirm either way Exits on freeways - Didn't have any instances of it trying to take incorrect exits on freeways, though this had only happened a couple of times to me on 14.3.3 so need more data to confirm either way UNRESOLVED School zones - same issue occurred near my house where the car goes 40 regardless whether school zone is active or not and did not read the END SCHOOL ZONE sign to signal it to return to the speed limit. Didn't test during school zone hours though. Brake jabbing / hard braking due to indecisiveness at roundabouts - still had several occurrences of this tonight. Not particularly unsafe, but still uncomfortable. REGRESSION Noticed a couple of random slowdowns on the highway for no apparent reason. Nothing major, just strange. CONSLUSION A real shame about the Wiggle of Death, because other than that it's a really solid build and has fixed the major usability issues from 14.3.3. I'm hoping for a quick fix from the Tesla AI team. I logged lots of snapshots and some disengagements for them to review.

FSD 14.3.5 Down Under initial review Let me start right at the top by saying that in my 2.5 hour drive, I had 2 instances of a critical issue which I'm sad to say, in my opinion is a blocker to any wide roll-out of this build. The issue is shown in the clip below, which I'm calling the "Wiggle of Death". Half way through the roundabout you can see the steering wheel start wiggling from left to right as the car heads straight for the curb. Had I not intervened, it could have resulted in an impact. The other instance was the same behaviour, only towards a curb while turning right in a car park. Sorry guys, but it is what it is. It's what early access testing is for. On a more positive note, several major issues have been addressed in this build: FIXED: 🎉110km/h zones - they work perfectly now! Locked in at 115 in hurry, 112 in standard and 109 in chill. We don't talk about sloth on this account 😆 🎉 Follow distance / tailgating is resolved. Hurry now feels super comfortable and standard sits just a little further back again. 🎉 Lane changes were not a problem the entire drive. Every single one felt natural. I never really had many issues on 14.3.3 though tbh INCONCLUSIVE Speed sign recognition - I didn't have any instances today of it misreading a speed sign, however I didn't pass any 90 signs this time which have been most problematic on 14.3.3 - need more testing to confirm either way Exits on freeways - Didn't have any instances of it trying to take incorrect exits on freeways, though this had only happened a couple of times to me on 14.3.3 so need more data to confirm either way UNRESOLVED School zones - same issue occurred near my house where the car goes 40 regardless whether school zone is active or not and did not read the END SCHOOL ZONE sign to signal it to return to the speed limit. Didn't test during school zone hours though. Brake jabbing / hard braking due to indecisiveness at roundabouts - still had several occurrences of this tonight. Not particularly unsafe, but still uncomfortable. REGRESSION Noticed a couple of random slowdowns on the highway for no apparent reason. Nothing major, just strange. CONSLUSION A real shame about the Wiggle of Death, because other than that it's a really solid build and has fixed the major usability issues from 14.3.3. I'm hoping for a quick fix from the Tesla AI team. I logged lots of snapshots and some disengagements for them to review.

Rob Grieves 🇦🇺

18,027 просмотров • 5 дней назад

how to build Polymarket "always buy NO" bot +$200-400/day PnL if you pick the right markets everyone overcomplicates this. the "NO-maxi bot" strategy is literally: buy NO on outcomes that are structurally overpriced, wait for reality to catch up. the part that matters isn't "genius insight", it's picking the right markets plus execution. where the +$200-400/day comes from it's not betting "no" everywhere. it's selectively loading up NO on multi-outcome ladders (FDV ranges, price targets, user metrics) where the top brackets are CT dreams priced way too rich. if you're consistently capturing 5-15% edge per cycle across 20-30 outcomes and actually getting fills, +$200-400/day is just position sizing plus discipline. first, the edge (why this isn't a meme) polytrackhq research shows $40M+ arb profits from 86M trades came from exploiting pricing errors. "NO-maxi" is the retail version of the same logic on overhyped brackets. so the goal is simple: find multi-outcome markets with fat tails, skip the base case, load NO on the fantasy brackets, let time and reality work. what you actually need (minimal) Python plus official py-clob-client (standard for Polymarket orders). Telegram bot for alerts (don't stare at screen). VPS so it runs 24/7 (don't run from laptop). where people mess up: they try "always NO" on everything and get wrecked by the one outcome that hits. pick markets with obvious "dream vs reality" skew. the bot loop (in plain English) Pull multi-outcome markets (FDV ladders, price targets). For each outcome: check if YES price exceeds realistic probability. Buy NO on 3-5 fattest tails (skip base case). Log market, outcomes, expected edge, fills. Repeat on new ladders. that's it. no AI, no news scraping, no predictions. just "overhype vs fundamentals". where to get real references (not vibes) PolyTrackHQ arb guide. exact logic for multi-outcome pricing errors. py-clob-client PyPI. official client (no wrappers). Polymarket Agents GitHub. framework for outcome looping plus orders. r/arbitragebetting Reddit. discussions on non-atomic multi-order risk. two real-world gotchas (that decide profit vs loss) Outcome blowout: one crazy top bracket hitting wipes the basket. always skip the most likely 1-2 outcomes. Resolution risk: ambiguous wording equals instant edge killer. read rules before loading up. how to make it feel "pro" fast Run only on high-volume ladders (FDV, price targets). fills matter more than theory. Start with $50-100 per outcome until logs prove fills work, then scale. Use official libs only. treat GitHub bots as hostile until audited.

how to build Polymarket "always buy NO" bot +$200-400/day PnL if you pick the right markets everyone overcomplicates this. the "NO-maxi bot" strategy is literally: buy NO on outcomes that are structurally overpriced, wait for reality to catch up. the part that matters isn't "genius insight", it's picking the right markets plus execution. where the +$200-400/day comes from it's not betting "no" everywhere. it's selectively loading up NO on multi-outcome ladders (FDV ranges, price targets, user metrics) where the top brackets are CT dreams priced way too rich. if you're consistently capturing 5-15% edge per cycle across 20-30 outcomes and actually getting fills, +$200-400/day is just position sizing plus discipline. first, the edge (why this isn't a meme) polytrackhq research shows $40M+ arb profits from 86M trades came from exploiting pricing errors. "NO-maxi" is the retail version of the same logic on overhyped brackets. so the goal is simple: find multi-outcome markets with fat tails, skip the base case, load NO on the fantasy brackets, let time and reality work. what you actually need (minimal) Python plus official py-clob-client (standard for Polymarket orders). Telegram bot for alerts (don't stare at screen). VPS so it runs 24/7 (don't run from laptop). where people mess up: they try "always NO" on everything and get wrecked by the one outcome that hits. pick markets with obvious "dream vs reality" skew. the bot loop (in plain English) Pull multi-outcome markets (FDV ladders, price targets). For each outcome: check if YES price exceeds realistic probability. Buy NO on 3-5 fattest tails (skip base case). Log market, outcomes, expected edge, fills. Repeat on new ladders. that's it. no AI, no news scraping, no predictions. just "overhype vs fundamentals". where to get real references (not vibes) PolyTrackHQ arb guide. exact logic for multi-outcome pricing errors. py-clob-client PyPI. official client (no wrappers). Polymarket Agents GitHub. framework for outcome looping plus orders. r/arbitragebetting Reddit. discussions on non-atomic multi-order risk. two real-world gotchas (that decide profit vs loss) Outcome blowout: one crazy top bracket hitting wipes the basket. always skip the most likely 1-2 outcomes. Resolution risk: ambiguous wording equals instant edge killer. read rules before loading up. how to make it feel "pro" fast Run only on high-volume ladders (FDV, price targets). fills matter more than theory. Start with $50-100 per outcome until logs prove fills work, then scale. Use official libs only. treat GitHub bots as hostile until audited.

0xCryptoGirl

22,686 просмотров • 6 месяцев назад

🚨BREAKING… the top-performing 5m & 15m Polymarket Clawdbot setup just became public Sounds insane? 100%. Unreal? NOT at all. If you’re active on Polymarket, this should have your FULL attention. A random late night turned into a small wallet launching a fully automated machine that expanded into ~$1.6M in profit No insider access No affiliation with the Polymarket team Just a developer operating a bot directly connected to Polymarket Profile → Copytrade → I monitored this wallet for weeks and honestly, it barely looked real No narrative setups No discretionary decisions Zero manual execution Everything is fully automated His FULL strategy: 1. 5 & 15-minute BTC & ETH latency arbitrage The bot trades ultra-short Bitcoin and Ethereum markets with 5 & 15-minute expirations - and similar logic applies to fast 5m markets often associated with Clawdbot-style execution. When BTC moves on Binance, Polymarket pricing reacts slower. For around 30 seconds, odds reflect stale data. The system enters during that gap, when YES + NO combined is below $1, waits for repricing, and exits the moment the market corrects. No predictions, no bias - just harvesting mispriced odds 2. Automation over reaction When volatility spikes, humans pause. The system doesn’t. It triggers instantly when the window opens. No emotion, no hesitation, no missed fills. By the time manual traders click, the inefficiency has already disappeared 3. Scale through repetition Each trade earns small spreads, not headline wins. But automation allows continuous execution at scale, every 15 minutes - and on faster 5m rotations running 24/7 without burnout Scale is the edge 19,021 trades placed - irrelevant on their own. Together, they compounded into $1,624,305 in profit, with a largest single gain of $48K and an equity curve that trends almost vertically Bottom line Bots are already competing in a quiet arms race on Polymarket, especially across 5m and 15m markets where Clawdbot-style systems dominate Most traders try to forecast what’s next These systems monetize inefficiencies in real time And as long as latency and structural gaps exist, autonomous bots will continue extracting value

Shelpid.WI3M

225,724 просмотров • 5 месяцев назад

Uber is Dead, my reflections on Waymo I’ve been in San Francisco for just over a week, during which I’ve taken 7 rides with Waymo, a similar number with Uber, and a few with FSD Teslas. My journey to SFO via Uber was alarming—the driver veered out of the lane multiple times and nearly crashed on a ramp, seemingly vying for a one-star rating or to genuinely scare me. Conversely, my experiences with Waymo were virtually flawless, if you don’t consider overly cautious driving a fault. I experienced a minor hiccup when we got stuck behind parked cars because the vehicle thought they were queuing at a red light. It quickly resolved the confusion and moved on, which was rather amusing. Waymo, and other Level 5 autonomous vehicles, are poised to revolutionize the movement of people and goods. The most apt analogy I can think of is that Waymo is transforming the real world into an automated Amazon warehouse, with people as the goods and Waymo vehicles as the robots shuttling them around. With the advent of personal transportation becoming incredibly affordable, sending anything from point A to point B using a self-driving electric vehicle will soon be within easy reach. One of Waymo’s standout features is privacy. Riding in an Uber often means being subjected to the driver’s loud group chats on some app, making the journey neither quiet nor private. In contrast, Waymo offers a fully private experience, allowing you to have confidential phone conversations or chat freely with fellow passengers without distraction. Waymo also reimagines the concept of a car. Without the need for a driver, we can eliminate the front console, reduce weight, and remove the steering wheel. This opens up possibilities for passenger seats to be reoriented, perhaps facing backwards, or for the vehicle to become a mobile living room. Tomorrow’s vehicle designs will differ drastically from today’s. Destinations that are currently expensive and logistically complicated to reach via Taxi/Uber, often lying outside public transport routes, can be simplified to a single “Waymo” journey. This could shift the current model of “Uber + public transport + Uber” to a more streamlined experience. As more cars become self-driving, we could see a reduction in the amount of time cars are parked—from 99% of their lifetime to perhaps just 25%. This not only improves unit economics but could also decrease the number of cars on the road. This transition represents one of the most significant shifts for Generation X. In conclusion, the future is autonomous, electric, and efficient. Uber, as we know it, is dead.

Uber is Dead, my reflections on Waymo I’ve been in San Francisco for just over a week, during which I’ve taken 7 rides with Waymo, a similar number with Uber, and a few with FSD Teslas. My journey to SFO via Uber was alarming—the driver veered out of the lane multiple times and nearly crashed on a ramp, seemingly vying for a one-star rating or to genuinely scare me. Conversely, my experiences with Waymo were virtually flawless, if you don’t consider overly cautious driving a fault. I experienced a minor hiccup when we got stuck behind parked cars because the vehicle thought they were queuing at a red light. It quickly resolved the confusion and moved on, which was rather amusing. Waymo, and other Level 5 autonomous vehicles, are poised to revolutionize the movement of people and goods. The most apt analogy I can think of is that Waymo is transforming the real world into an automated Amazon warehouse, with people as the goods and Waymo vehicles as the robots shuttling them around. With the advent of personal transportation becoming incredibly affordable, sending anything from point A to point B using a self-driving electric vehicle will soon be within easy reach. One of Waymo’s standout features is privacy. Riding in an Uber often means being subjected to the driver’s loud group chats on some app, making the journey neither quiet nor private. In contrast, Waymo offers a fully private experience, allowing you to have confidential phone conversations or chat freely with fellow passengers without distraction. Waymo also reimagines the concept of a car. Without the need for a driver, we can eliminate the front console, reduce weight, and remove the steering wheel. This opens up possibilities for passenger seats to be reoriented, perhaps facing backwards, or for the vehicle to become a mobile living room. Tomorrow’s vehicle designs will differ drastically from today’s. Destinations that are currently expensive and logistically complicated to reach via Taxi/Uber, often lying outside public transport routes, can be simplified to a single “Waymo” journey. This could shift the current model of “Uber + public transport + Uber” to a more streamlined experience. As more cars become self-driving, we could see a reduction in the amount of time cars are parked—from 99% of their lifetime to perhaps just 25%. This not only improves unit economics but could also decrease the number of cars on the road. This transition represents one of the most significant shifts for Generation X. In conclusion, the future is autonomous, electric, and efficient. Uber, as we know it, is dead.

Linus ✦ Ekenstam

6,100,720 просмотров • 2 лет назад

This trader reportedly generated $4M in profit trading on Polymarket with ClawdBot Starting with just $1,000, the script scaled up to millions through automated trading If you trade on Polymarket, be sure to read this to simplify your trading with ClawdBot Without any insider connections or 10 years of programming experience, this trader wrote the script and connected Moltbot (Clawdbot) directly to Polymarket Profile → Copy trading → After reviewing the code, it was surprising how simple the core idea looked The bot runs fully autonomously, without constant human involvement Here is the strategy 1. 15-minute BTC & ETH micro-arbitrage The strategy focuses on very short-term Bitcoin and Ethereum markets with 15-minute contracts. In these rapid markets, brief pricing gaps often appear where the combined cost of YES and NO is below $1. A bot connected directly to Polymarket detects and exploits these gaps instantly, it doesn’t try to predict direction or analyze trends, it simply reacts to pricing inefficiencies. 2. Speed over hesitation During volatile moments, human traders often pause or second-guess. An automated system doesn’t. Orders are executed automatically: no hesitation, no emotional bias, no lag in response. By the time a person evaluates the situation, the opportunity usually no longer exists. 3. Automation enables scale The gains per trade are tiny, often just cents. But constant, uninterrupted execution allows the system to repeat the same edge thousands of times without fatigue, turning small margins into meaningful totals over time. Scale becomes the real edge Nearly 6,000 trades were executed. Individually they seemed minor. Collectively they resulted in close to $100K in net profit. Conclusion A quiet bot race already seems to be happening on Polymarket While people debate entries and opinions, automated systems profit from mechanics and speed. As long as structural inefficiencies remain in the market, autonomous setups will likely continue extracting value quietly and consistently. I’m watching this space closely Follow if you want signal, not noise

winkle.

36,628 просмотров • 5 месяцев назад

Just finished a one-week trip to China. I've now "survived" all the major (~20) L2 self-driving and robotaxi vehicles in both the US and China. Some thoughts & observations: ▶️L2 self-driving I tested major brands like $Huawei, $Li, $NIO, $Xpeng, and $Xiaomi. Overall, they exceeded my expectations. The rides were not overly cautious and handled complex situations (yes, road conditions in China are very challenging!) quite well. Nothing compares to $Tsla's approach. I see imitation learning/end-to-end as the only effective approach for self-driving. While Chinese peers perform well on main roads, they struggle on frontage roads due to reliance on high-precision maps and rule-based methods (e.g. cars stopped in the middle of the road where there was no clear white lining). Chinese EVs' self-driving capabilities are far ahead of those from US and EU brands. I doubt any Chinese players can profit from L2 self-driving, not because it’s not useful, but because it’s hard to differentiate, and price wars dominate the market in China. Chinese consumers and regulators seem much more receptive to self-driving. Even with a 5/10 self-driving capability, cars are practically *hands-free(!)* Insurance-wise, for L3+ cars, OEMs bear responsibility for incidents, so OEMs avoid labeling cars as L3+. ▶️Robotaxi I tested major brands like $Didi, and $Bidu. I'd rate equal to $Waymo, and it's ahead of other peers. However, the same issue applies here: user experience is nearly perfect (in Yizhuang, Beijing), but expansion is the real question. Chinese robotaxi companies are very sophisticated. While the rest of the world focuses on technology, Chinese peers treat it as a product, considering unit economics, operations, mass production, etc. Interestingly, most companies expressed a preference NOT to operate fleets themselves. They aim to be asset-light and let fleet managers handle operations. Policy Support: China has a very clear approval process, driven by data (autonomous driving distance, fully driverless distance, intervention rate, passenger ratings, etc.). ▶️Chinese EVs In major cities like Beijing or Shanghai, EV adoption (green license plates vs. gas cars with blue license plates) seems to be 40%+. If 40% of cars on the road are EVs, then EV penetration (defined as the % of new car sales) must already be over 50%. In shopping malls, the ground floor is filled with EV showrooms—easily 10+ brands, many of which are unfamiliar Chinese brands. It appears almost too easy to make an electric car, which is a stark contrast to the US. $Xiaomi, for example, can achieve a 10% gross profit margin in its first year of operation, compared to $RIVN's -45%. Additionally, $Xiaomi cars are priced at 30% of $RIVN's price. It's fascinating to see how China transitioned from "couldn't make their own gas cars at all (only JVs)" to "dominating EVs globally." The government deserves credit for setting the direction and executing effectively. China now controls the entire supply chain, with $CATL holding 40% of the global market share. 🔹How did it happen? The success of the industry Incentives were set just right: the government provided incentives early on to make EVs and gas cars have comparable MSRPs, allowing consumers to choose based on functionality. This approach differs from how the IRA offers incentives... Perfectly competitive market: $TSLA was brought in, and competition was welcomed, unlike the US, which has a 100% import tax on Chinese EVs. Strategic regulations: License plate restrictions were used effectively; for example, taxis and minivans are required to be EVs. 🔹The challenges Despite the success, the industry faces challenges with low-margin companies and struggling stocks. The intense competition shows no sign of ending. Well-funded global OEMs and Chinese state-owned car companies continue to subsidize, leading to new EV brands emerging annually. The natural tendency in China is to race to the bottom. I think this ties back to China's history as the "world’s factory," where manufacturers price products at "cost plus" versus the US and developing countries, which price based on "affordability/value creation." 🔹The wow EV feature >Software features that surprised me the most: - Everything in the car can be voice-controlled. Not just simple tasks like playing music; users can adjust the height of the steering wheel and set the temperature easily. - Self-parking, which $Tsla has yet to release to all FSD users, is already a table stake in China (I'd rate the quality as 10/10). >Other fun hardware features: - Mini fridges in the car - Infotainment systems - IoT: remote access the car/home via cellphone - all connected together - Heads-up displays - UV-protected glass roofs: $Xiaomi took $Tsla's design, but the glass roof of the $Xiaomi car is made of double layers with silver, blocking 99.9% of UV and infrared rays...as a result, heat is no longer a problem inside the car

Just finished a one-week trip to China. I've now "survived" all the major (~20) L2 self-driving and robotaxi vehicles in both the US and China. Some thoughts & observations: ▶️L2 self-driving I tested major brands like $Huawei, $Li, $NIO, $Xpeng, and $Xiaomi. Overall, they exceeded my expectations. The rides were not overly cautious and handled complex situations (yes, road conditions in China are very challenging!) quite well. Nothing compares to $Tsla's approach. I see imitation learning/end-to-end as the only effective approach for self-driving. While Chinese peers perform well on main roads, they struggle on frontage roads due to reliance on high-precision maps and rule-based methods (e.g. cars stopped in the middle of the road where there was no clear white lining). Chinese EVs' self-driving capabilities are far ahead of those from US and EU brands. I doubt any Chinese players can profit from L2 self-driving, not because it’s not useful, but because it’s hard to differentiate, and price wars dominate the market in China. Chinese consumers and regulators seem much more receptive to self-driving. Even with a 5/10 self-driving capability, cars are practically hands-free(!) Insurance-wise, for L3+ cars, OEMs bear responsibility for incidents, so OEMs avoid labeling cars as L3+. ▶️Robotaxi I tested major brands like $Didi, and $Bidu. I'd rate equal to $Waymo, and it's ahead of other peers. However, the same issue applies here: user experience is nearly perfect (in Yizhuang, Beijing), but expansion is the real question. Chinese robotaxi companies are very sophisticated. While the rest of the world focuses on technology, Chinese peers treat it as a product, considering unit economics, operations, mass production, etc. Interestingly, most companies expressed a preference NOT to operate fleets themselves. They aim to be asset-light and let fleet managers handle operations. Policy Support: China has a very clear approval process, driven by data (autonomous driving distance, fully driverless distance, intervention rate, passenger ratings, etc.). ▶️Chinese EVs In major cities like Beijing or Shanghai, EV adoption (green license plates vs. gas cars with blue license plates) seems to be 40%+. If 40% of cars on the road are EVs, then EV penetration (defined as the % of new car sales) must already be over 50%. In shopping malls, the ground floor is filled with EV showrooms—easily 10+ brands, many of which are unfamiliar Chinese brands. It appears almost too easy to make an electric car, which is a stark contrast to the US. $Xiaomi, for example, can achieve a 10% gross profit margin in its first year of operation, compared to $RIVN's -45%. Additionally, $Xiaomi cars are priced at 30% of $RIVN's price. It's fascinating to see how China transitioned from "couldn't make their own gas cars at all (only JVs)" to "dominating EVs globally." The government deserves credit for setting the direction and executing effectively. China now controls the entire supply chain, with $CATL holding 40% of the global market share. 🔹How did it happen? The success of the industry Incentives were set just right: the government provided incentives early on to make EVs and gas cars have comparable MSRPs, allowing consumers to choose based on functionality. This approach differs from how the IRA offers incentives... Perfectly competitive market: $TSLA was brought in, and competition was welcomed, unlike the US, which has a 100% import tax on Chinese EVs. Strategic regulations: License plate restrictions were used effectively; for example, taxis and minivans are required to be EVs. 🔹The challenges Despite the success, the industry faces challenges with low-margin companies and struggling stocks. The intense competition shows no sign of ending. Well-funded global OEMs and Chinese state-owned car companies continue to subsidize, leading to new EV brands emerging annually. The natural tendency in China is to race to the bottom. I think this ties back to China's history as the "world’s factory," where manufacturers price products at "cost plus" versus the US and developing countries, which price based on "affordability/value creation." 🔹The wow EV feature >Software features that surprised me the most: - Everything in the car can be voice-controlled. Not just simple tasks like playing music; users can adjust the height of the steering wheel and set the temperature easily. - Self-parking, which $Tsla has yet to release to all FSD users, is already a table stake in China (I'd rate the quality as 10/10). >Other fun hardware features: - Mini fridges in the car - Infotainment systems - IoT: remote access the car/home via cellphone - all connected together - Heads-up displays - UV-protected glass roofs: $Xiaomi took $Tsla's design, but the glass roof of the $Xiaomi car is made of double layers with silver, blocking 99.9% of UV and infrared rays...as a result, heat is no longer a problem inside the car

Freda Duan

399,004 просмотров • 2 лет назад

From sofa to stadium in a single leap. From living room to world-class stadium in seconds. Argentina vs Brazil, one magical run, one unstoppable strike, and a celebration heard around the world. Create your World Cup moment with SeaArt, earn free Credits and win an iPhone 17. #SeaArtWorldCup Made with Seedance Credit: SeaArt.Ai🐋 SeaArt Creator Lab Prompt: First-person POV from a comfortable reclining armchair in a cozy modern living room. From the very first frame, a large television mounted on the wall directly ahead is already showing a live Argentina vs Brazil football match in full swing. Soft afternoon sunlight streams through the windows, creating a relaxed match-day atmosphere. The viewer's legs are stretched out comfortably while wearing casual shorts, enjoying the game from a resting position. Authentic British football commentary and crowd noise play naturally from the television. At 0:02, a young woman wearing an appealing lavender-purple casual shorts outfit and a stylish half-French braid hairstyle enters from the right side of frame. She is a neutral football fan, not supporting either team. Drawn into the excitement of the match, she glances at the television, smiles, then accelerates into a sprint across the living room. At 0:04, she runs directly toward the television. The camera remains first-person and perfectly stable. At 0:05, she leaps into the TV screen in one continuous motion. No cuts, no scene jumps, no transitions breaking continuity. As she reaches the screen, the living room seamlessly dissolves away and transforms into a massive international football stadium hosting Argentina vs Brazil. Television audio smoothly expands into a deafening live stadium atmosphere. The transformation happens organically around the camera while preserving one uninterrupted shot. At 0:06, she lands smoothly on the pitch, still wearing the exact same lavender outfit and half-French braid. A single football rolls naturally toward her. IMPORTANT: Only one football exists throughout the entire video. The football must maintain perfect object permanence. The same ball remains continuously visible and physically consistent from first touch to goal. No duplication, replacement, morphing, teleportation, flickering, frame-to-frame jumps, texture changes, scaling changes, disappearing ball, floating ball, or AI artefacts. Realistic football physics only. At 0:07, she controls the football with a clean first touch. At 0:08–0:11, she dribbles continuously between Argentina and Brazil players. Every touch follows realistic momentum, spacing, and foot-to-ball contact. Defenders react naturally. No clipping, collision errors, or unnatural movements. At 0:11, she approaches the edge of the penalty area. At 0:12, she unleashes a powerful strike using the same football. The camera clearly tracks the football's entire flight path from her foot to the goal in one uninterrupted motion. Realistic spin, realistic speed, realistic trajectory. At 0:13, the football smashes into the top corner of the net. The net deforms naturally and ripples realistically. The crowd explodes with excitement. Authentic British football commentator shouts: "What a strike! Absolutely sensational!" At 0:14, she turns and sprints toward the corner flag as the camera follows closely. For the final second, she leaps high into the air and performs the iconic Siuuu celebration, rotating and landing with feet apart and arms extended downward while facing the roaring crowd. Her half-French braid swings dramatically behind her. Stadium lights illuminate the scene as thousands of fans celebrate. One continuous unbroken shot, no cuts, no scene resets, seamless living-room-to-stadium transformation, cinematic football commercial quality, authentic British football commentary, realistic player movement, physically accurate football physics, strict ball continuity, stable camera motion, premium sports broadcast visuals, dramatic stadium atmosphere, crowd chants, sprinting footsteps, grass impact sounds, powerful strike, realistic net ripple, ultra-realistic visuals, 15-second duration, 16:9 horizontal format, no logos, no text overlays, no subtitles, no watermark, no flickering objects, no AI artefacts, no visual glitches.

From sofa to stadium in a single leap. From living room to world-class stadium in seconds. Argentina vs Brazil, one magical run, one unstoppable strike, and a celebration heard around the world. Create your World Cup moment with SeaArt, earn free Credits and win an iPhone 17. #SeaArtWorldCup Made with Seedance Credit: SeaArt.Ai🐋 SeaArt Creator Lab Prompt: First-person POV from a comfortable reclining armchair in a cozy modern living room. From the very first frame, a large television mounted on the wall directly ahead is already showing a live Argentina vs Brazil football match in full swing. Soft afternoon sunlight streams through the windows, creating a relaxed match-day atmosphere. The viewer's legs are stretched out comfortably while wearing casual shorts, enjoying the game from a resting position. Authentic British football commentary and crowd noise play naturally from the television. At 0:02, a young woman wearing an appealing lavender-purple casual shorts outfit and a stylish half-French braid hairstyle enters from the right side of frame. She is a neutral football fan, not supporting either team. Drawn into the excitement of the match, she glances at the television, smiles, then accelerates into a sprint across the living room. At 0:04, she runs directly toward the television. The camera remains first-person and perfectly stable. At 0:05, she leaps into the TV screen in one continuous motion. No cuts, no scene jumps, no transitions breaking continuity. As she reaches the screen, the living room seamlessly dissolves away and transforms into a massive international football stadium hosting Argentina vs Brazil. Television audio smoothly expands into a deafening live stadium atmosphere. The transformation happens organically around the camera while preserving one uninterrupted shot. At 0:06, she lands smoothly on the pitch, still wearing the exact same lavender outfit and half-French braid. A single football rolls naturally toward her. IMPORTANT: Only one football exists throughout the entire video. The football must maintain perfect object permanence. The same ball remains continuously visible and physically consistent from first touch to goal. No duplication, replacement, morphing, teleportation, flickering, frame-to-frame jumps, texture changes, scaling changes, disappearing ball, floating ball, or AI artefacts. Realistic football physics only. At 0:07, she controls the football with a clean first touch. At 0:08–0:11, she dribbles continuously between Argentina and Brazil players. Every touch follows realistic momentum, spacing, and foot-to-ball contact. Defenders react naturally. No clipping, collision errors, or unnatural movements. At 0:11, she approaches the edge of the penalty area. At 0:12, she unleashes a powerful strike using the same football. The camera clearly tracks the football's entire flight path from her foot to the goal in one uninterrupted motion. Realistic spin, realistic speed, realistic trajectory. At 0:13, the football smashes into the top corner of the net. The net deforms naturally and ripples realistically. The crowd explodes with excitement. Authentic British football commentator shouts: "What a strike! Absolutely sensational!" At 0:14, she turns and sprints toward the corner flag as the camera follows closely. For the final second, she leaps high into the air and performs the iconic Siuuu celebration, rotating and landing with feet apart and arms extended downward while facing the roaring crowd. Her half-French braid swings dramatically behind her. Stadium lights illuminate the scene as thousands of fans celebrate. One continuous unbroken shot, no cuts, no scene resets, seamless living-room-to-stadium transformation, cinematic football commercial quality, authentic British football commentary, realistic player movement, physically accurate football physics, strict ball continuity, stable camera motion, premium sports broadcast visuals, dramatic stadium atmosphere, crowd chants, sprinting footsteps, grass impact sounds, powerful strike, realistic net ripple, ultra-realistic visuals, 15-second duration, 16:9 horizontal format, no logos, no text overlays, no subtitles, no watermark, no flickering objects, no AI artefacts, no visual glitches.

Jessica Collins

32,264 просмотров • 1 месяц назад

JUST IN: Bank of America just told its clients to take profits. About 70% of its bear-market signals are flashing, a level it typically reaches only near market tops. Weeks earlier, BofA's own fund manager survey showed the largest one-month jump into stocks ever recorded, with cash down to 3.9%, under the 4% line the bank treats as a sell signal. Read those together. Investors made their biggest dash into equities in the survey's history at almost the exact moment BofA's own indicators say the top is near. But the number that should actually stop you is buried in the note, and almost nobody is quoting it. The companies driving this entire rally, the AI hyperscalers, are on track to spend nearly 100% of their operating cash flow on capex by year-end. In 2023 that figure was 40%. Sit with that. Big tech used to throw off cash and hand it back through buybacks, which lifted the stocks. Now it is pouring almost every dollar it generates into chips and data centers. BofA notes buybacks have slowed and cash conversion has flat-lined. The engine of the rally is consuming the fuel that powered the stocks. It is the same $725 billion build that companies are now blaming for layoffs. The whole market is priced on one bet, and that bet has grown large enough to eat the cash that used to support the share prices. This is not a crash call. BofA's year-end target is 7,100, about 4% below today, and the median outcome after this cash signal since 2011 has been a 1% dip, not a collapse. The posts screaming sell everything are wrong. The real message is quieter. You are being paid less and less to stay, while the engine runs hotter and hotter.

JUST IN: Bank of America just told its clients to take profits. About 70% of its bear-market signals are flashing, a level it typically reaches only near market tops. Weeks earlier, BofA's own fund manager survey showed the largest one-month jump into stocks ever recorded, with cash down to 3.9%, under the 4% line the bank treats as a sell signal. Read those together. Investors made their biggest dash into equities in the survey's history at almost the exact moment BofA's own indicators say the top is near. But the number that should actually stop you is buried in the note, and almost nobody is quoting it. The companies driving this entire rally, the AI hyperscalers, are on track to spend nearly 100% of their operating cash flow on capex by year-end. In 2023 that figure was 40%. Sit with that. Big tech used to throw off cash and hand it back through buybacks, which lifted the stocks. Now it is pouring almost every dollar it generates into chips and data centers. BofA notes buybacks have slowed and cash conversion has flat-lined. The engine of the rally is consuming the fuel that powered the stocks. It is the same $725 billion build that companies are now blaming for layoffs. The whole market is priced on one bet, and that bet has grown large enough to eat the cash that used to support the share prices. This is not a crash call. BofA's year-end target is 7,100, about 4% below today, and the median outcome after this cash signal since 2011 has been a 1% dip, not a collapse. The posts screaming sell everything are wrong. The real message is quieter. You are being paid less and less to stay, while the engine runs hotter and hotter.

Shanaka Anslem Perera ⚡

17,235 просмотров • 1 месяц назад