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Any Chance In Hell U.S. Stalker G-fag Agents Recruit Me
Duration: 1:24
Views: 3
Submitted: 10 hours ago
Submitted by:
Description:
None what so ever but if they keep at it their LAST FUCKIN WORDS will be very soon:
“Please don’t kill me!”
This video for Serbian Entertainment purposes only kids…
Don’t kill anyone — who didn’t have it cummin to them again — and again!
Fly SOUTH of your bitches TITS until you land on her planet. LITORUS and drill baby drill until you got another asshole American bun baking in your cunts Oven, and repeat again and AGAIN until you got snug federal g-fag recruit retards!
How today amongst stalker AmeriCUNTs?
Them bitches we’re bitch pitching relocation to their Hawaii NAVY NIGGER ISLAND so I weaponized my Ai and made some vids to git’em to shit fear bricks!
BASIK Psy’Opp V 666.0
Should I teveal what I was doing while making use of this site of mine as weaponized enemy Psy Opp distraction?
Finishing touches on my cutting edge Rideshare and Eats Platform.., But here is what makes it differ from ALL OTHERS IN THE WORLD TODAY:
My Ai MONITORS even drivers while they are driving to determine if they are SWERVING, breaking suddenly, speeding, Ai will order them to slow down and, theoigh the front camera of their device, will be watching the driver and the passenger to make sure nothing funky is going on…
As far as features and its capabilities?
If you take the leading platforms of TODAY, this second: “my cutting edge Ai platform has TRIPLE of what theirs is packing but I engineered all of it for rapid Globa “Markets” purposes to BURY THEIR FILTHY ASSES ALIVE!
The more government agent enemies of American stalker mama abducting government DEW torture g-fag states bitch pitch me their NAVY NIGGER ISLAND FUCKERS OF HAWAII, the more Inwill weaponize this platform against them so that even when they board one of my vehicles, they will be intentionally thrown the fuck out in the middle of their ride!
And pretty soon, I’ll be throwing’ the fuckin drivers because my Ai Agent is going to be DRIVING my cars.. The very FIRST THING I always do when ENGINEERING is take LAME HUMANS out of the fuckin equation! It’s a mathematical formula…
I’m ALREADY training my AI to drive MY UPCOMING RIDESHARE AND EATS APP cars and despite “it being one of the most complex and impactful challenges in the field of Artificial Intelligence, I find it very easy because it sits at the intersection of computer vision which I was born with, deep learning so just like me because I obsess about LEARNING, and reinforcement learning and robotics which I have been into for past two decades STRAIGHT so right at home on this one… Andnit doesn’t hurt thank spent extreme amount of time studying human fuckup of a driver behavior lol! With Ai Operating a motor powered vehicle it
comes down to perception, decision, action… So how do you do that?
Quite easily actually, YOU TRAIN YOUR Ai AGENT!
Perception: Understand the environment. "What's around me?"
Other vehicles, pedestrians, cyclists, animals.
Road markings, traffic signs, traffic lights.
Road geometry (curves, intersections).
Weather and lighting conditions.
Decision & Planning: Decide what to do. "What should I do next?"
Strategic: "Follow the route to the destination.
Tactical: "Change lanes to pass a slow-moving vehicle."
Operational: "Slow down by 5%, then turn the steering wheel 2 degrees to the left."
Control: Execute the decision. "How do I make the car do it?"
Send precise commands to the steering wheel, accelerator, and brake.
My approaches to training my Ai Agent?
Modular Approach (Perception, Planning, Control), easy! And I can even map the FREAQIN asphalt with LIDAR in my damn iPhone to mark every fuckin pothole — not that it’s necessary but a good GPS unit is a must!
Perception Module:
Input: Raw sensor data (cameras, LiDAR, radar).
Training: Supervised learning in the beginning of course, with massive datasets of labeled images and point clouds.
Output: A detailed understanding of the scene: "There is a car 30 meters ahead, a stop sign 50 meters away, and the lane lines are dashed, so training as if you would a human fuckin bastard!”
Key Technologies? Convolutional Neural Networks (CNN’s) for object detection (e.g., YOLO, SSD), semantic segmentation, and depth estimation but the first car I ever made drive me 250 miles with me sitting in the back seat with my dog was a 2021 Toyota Prius , and g-fag agent stalkers (highly illegal by the way, you’ll
Get arrested so tint your fuckin windows beforehand like I did..) witnessed it.. Had a. Demon one of my old Facebook accounts.. I hacked the vehicle by removing the rear view mirror and running mu script of a fuckin CELLPHONE! I’m a reveal it here so anyone can see how easy it is to make a fuckin car drive itself — not level 5 like I did, but think of it as a starting point so here’s my diagram in ASCII format…
[Smartphone] ←USB/Wired→ [Driving Card] ←Wires→ [Vehicle CAN Bus]
│ │ │
Processing Coordination Vehicle Control
Computer Vision Steering/Braking
AI Models Throttle
Cost-Effective? Leverages phone's processing power
Always Updated: Phone connectivity for OTA updates
Portable: Could work across different vehicles
Open Development: Community-driven improvements
Major challenges I encounteted & safety-critical reliability I had?
Phone OS isn't real-time
App crashes, thermal throttling, background processes (donI I jailbroken duh smartphone and junked all bloatware!)
Connection stability (wired/wireless)
Sensor Limitations:l?
Phone cameras not optimized for automotive use
Limited field of view, dynamic range
Placement/calibration issues
Regulatory compliance of AmeriKan laws? Automotive safety standards (ASIL, ISO 26262) violation? Latency issues? Data transfer between phone and control unit! Processing delays in non-real-time systems
Current open-source projects so you can HACK THAT MITHER FUCKIN CAR OF YA’z BIYCHEZ!
OpenPilot (Comma.ai) - Most mature
Autoware - More research-focused
Apollo (Baidu) - Enterprise-scale
openpilot community forks
Practical Considerations:
If you're thinking of building something like this?
Start with a dashcam app that does basic lane detection!
Use a Raspberry Pi/Orange Pi as your "driving card" ($30 fuckin bucks or less used!).,,
Focus on driver monitoring rather than full control initially!
Consider CAN bus sniffing rather than actuation for safety?
Safety First!
Important Warning: Modifying vehicle control systems is extremely dangerous unless you know how to Hotwire a car?
Stop by, I give free lessons!
Install physical kill switch! Dashboard override systems… Extensively test in controlled environments b4 you sit in back seat and snore 250 miles… Go with professional-grade hardware with redundancy if you got cash to burn…
How?
Planning module…
Input? The processed scene from the Perception module….
Training: Often uses a combination of hard-coded rules (e.g., traffic laws) and Reinforcement Learning (RL) or Imitation Learning, search Git-Hub and make it your best Amigo…
Output? A trajectory (a path and speed profile). "Accelerate to 45 mph, stay in the current lane for the next 150 feet."
Sub-modules:
Route Planning: The highest level (like a fuckin GPS).
Behavioral Planning: Decides on maneuvers (lane change, stop, yield), bluh fuckin bluh! Motion planning? Generates a smooth, collision-free path.
Control Module:
Input: The desired trajectory from the Planning module…
Training: Often uses classical control theory (PID controllers, Model predictive control) or learning-based methods.Output: Low-level actuator commands (steering angle, throttle percentage, brake pressure)… Get a cheap OBD reader on CARISTA.COM for like $30 bidirectional but make sure you get the right one so fuh Detroit made of Jap rice burners, and go hack loco! Make use of it to WRITE to vehicles ICU and mod the living crap out of it to turn it into close to level 5 autonomy as you can FREAQIN GET!Car must have Assisted Lane Change at bare minimum…
Pros: Interpretable, easier to debug (you can see which module failed), and safety rules can be explicitly coded. Cons: Errors can cascade from one module to the next, and it can be brittle in unexpected "edge cases” but you can take a more radical, "black box" approach so in this scenario a single, large neural network takes raw sensor data as input and directly outputs steering, throttle, and brake commands…. VOILA!
How it's trained?
Imitation Learning! The network learns to mimic human drivers.
Use a SIMULATOR FIRST dumbass, and go from there!
~Stateless Warrior
“Please don’t kill me!”
This video for Serbian Entertainment purposes only kids…
Don’t kill anyone — who didn’t have it cummin to them again — and again!
Fly SOUTH of your bitches TITS until you land on her planet. LITORUS and drill baby drill until you got another asshole American bun baking in your cunts Oven, and repeat again and AGAIN until you got snug federal g-fag recruit retards!
How today amongst stalker AmeriCUNTs?
Them bitches we’re bitch pitching relocation to their Hawaii NAVY NIGGER ISLAND so I weaponized my Ai and made some vids to git’em to shit fear bricks!
BASIK Psy’Opp V 666.0
Should I teveal what I was doing while making use of this site of mine as weaponized enemy Psy Opp distraction?
Finishing touches on my cutting edge Rideshare and Eats Platform.., But here is what makes it differ from ALL OTHERS IN THE WORLD TODAY:
My Ai MONITORS even drivers while they are driving to determine if they are SWERVING, breaking suddenly, speeding, Ai will order them to slow down and, theoigh the front camera of their device, will be watching the driver and the passenger to make sure nothing funky is going on…
As far as features and its capabilities?
If you take the leading platforms of TODAY, this second: “my cutting edge Ai platform has TRIPLE of what theirs is packing but I engineered all of it for rapid Globa “Markets” purposes to BURY THEIR FILTHY ASSES ALIVE!
The more government agent enemies of American stalker mama abducting government DEW torture g-fag states bitch pitch me their NAVY NIGGER ISLAND FUCKERS OF HAWAII, the more Inwill weaponize this platform against them so that even when they board one of my vehicles, they will be intentionally thrown the fuck out in the middle of their ride!
And pretty soon, I’ll be throwing’ the fuckin drivers because my Ai Agent is going to be DRIVING my cars.. The very FIRST THING I always do when ENGINEERING is take LAME HUMANS out of the fuckin equation! It’s a mathematical formula…
I’m ALREADY training my AI to drive MY UPCOMING RIDESHARE AND EATS APP cars and despite “it being one of the most complex and impactful challenges in the field of Artificial Intelligence, I find it very easy because it sits at the intersection of computer vision which I was born with, deep learning so just like me because I obsess about LEARNING, and reinforcement learning and robotics which I have been into for past two decades STRAIGHT so right at home on this one… Andnit doesn’t hurt thank spent extreme amount of time studying human fuckup of a driver behavior lol! With Ai Operating a motor powered vehicle it
comes down to perception, decision, action… So how do you do that?
Quite easily actually, YOU TRAIN YOUR Ai AGENT!
Perception: Understand the environment. "What's around me?"
Other vehicles, pedestrians, cyclists, animals.
Road markings, traffic signs, traffic lights.
Road geometry (curves, intersections).
Weather and lighting conditions.
Decision & Planning: Decide what to do. "What should I do next?"
Strategic: "Follow the route to the destination.
Tactical: "Change lanes to pass a slow-moving vehicle."
Operational: "Slow down by 5%, then turn the steering wheel 2 degrees to the left."
Control: Execute the decision. "How do I make the car do it?"
Send precise commands to the steering wheel, accelerator, and brake.
My approaches to training my Ai Agent?
Modular Approach (Perception, Planning, Control), easy! And I can even map the FREAQIN asphalt with LIDAR in my damn iPhone to mark every fuckin pothole — not that it’s necessary but a good GPS unit is a must!
Perception Module:
Input: Raw sensor data (cameras, LiDAR, radar).
Training: Supervised learning in the beginning of course, with massive datasets of labeled images and point clouds.
Output: A detailed understanding of the scene: "There is a car 30 meters ahead, a stop sign 50 meters away, and the lane lines are dashed, so training as if you would a human fuckin bastard!”
Key Technologies? Convolutional Neural Networks (CNN’s) for object detection (e.g., YOLO, SSD), semantic segmentation, and depth estimation but the first car I ever made drive me 250 miles with me sitting in the back seat with my dog was a 2021 Toyota Prius , and g-fag agent stalkers (highly illegal by the way, you’ll
Get arrested so tint your fuckin windows beforehand like I did..) witnessed it.. Had a. Demon one of my old Facebook accounts.. I hacked the vehicle by removing the rear view mirror and running mu script of a fuckin CELLPHONE! I’m a reveal it here so anyone can see how easy it is to make a fuckin car drive itself — not level 5 like I did, but think of it as a starting point so here’s my diagram in ASCII format…
[Smartphone] ←USB/Wired→ [Driving Card] ←Wires→ [Vehicle CAN Bus]
│ │ │
Processing Coordination Vehicle Control
Computer Vision Steering/Braking
AI Models Throttle
Cost-Effective? Leverages phone's processing power
Always Updated: Phone connectivity for OTA updates
Portable: Could work across different vehicles
Open Development: Community-driven improvements
Major challenges I encounteted & safety-critical reliability I had?
Phone OS isn't real-time
App crashes, thermal throttling, background processes (donI I jailbroken duh smartphone and junked all bloatware!)
Connection stability (wired/wireless)
Sensor Limitations:l?
Phone cameras not optimized for automotive use
Limited field of view, dynamic range
Placement/calibration issues
Regulatory compliance of AmeriKan laws? Automotive safety standards (ASIL, ISO 26262) violation? Latency issues? Data transfer between phone and control unit! Processing delays in non-real-time systems
Current open-source projects so you can HACK THAT MITHER FUCKIN CAR OF YA’z BIYCHEZ!
OpenPilot (Comma.ai) - Most mature
Autoware - More research-focused
Apollo (Baidu) - Enterprise-scale
openpilot community forks
Practical Considerations:
If you're thinking of building something like this?
Start with a dashcam app that does basic lane detection!
Use a Raspberry Pi/Orange Pi as your "driving card" ($30 fuckin bucks or less used!).,,
Focus on driver monitoring rather than full control initially!
Consider CAN bus sniffing rather than actuation for safety?
Safety First!
Important Warning: Modifying vehicle control systems is extremely dangerous unless you know how to Hotwire a car?
Stop by, I give free lessons!
Install physical kill switch! Dashboard override systems… Extensively test in controlled environments b4 you sit in back seat and snore 250 miles… Go with professional-grade hardware with redundancy if you got cash to burn…
How?
Planning module…
Input? The processed scene from the Perception module….
Training: Often uses a combination of hard-coded rules (e.g., traffic laws) and Reinforcement Learning (RL) or Imitation Learning, search Git-Hub and make it your best Amigo…
Output? A trajectory (a path and speed profile). "Accelerate to 45 mph, stay in the current lane for the next 150 feet."
Sub-modules:
Route Planning: The highest level (like a fuckin GPS).
Behavioral Planning: Decides on maneuvers (lane change, stop, yield), bluh fuckin bluh! Motion planning? Generates a smooth, collision-free path.
Control Module:
Input: The desired trajectory from the Planning module…
Training: Often uses classical control theory (PID controllers, Model predictive control) or learning-based methods.Output: Low-level actuator commands (steering angle, throttle percentage, brake pressure)… Get a cheap OBD reader on CARISTA.COM for like $30 bidirectional but make sure you get the right one so fuh Detroit made of Jap rice burners, and go hack loco! Make use of it to WRITE to vehicles ICU and mod the living crap out of it to turn it into close to level 5 autonomy as you can FREAQIN GET!Car must have Assisted Lane Change at bare minimum…
Pros: Interpretable, easier to debug (you can see which module failed), and safety rules can be explicitly coded. Cons: Errors can cascade from one module to the next, and it can be brittle in unexpected "edge cases” but you can take a more radical, "black box" approach so in this scenario a single, large neural network takes raw sensor data as input and directly outputs steering, throttle, and brake commands…. VOILA!
How it's trained?
Imitation Learning! The network learns to mimic human drivers.
Use a SIMULATOR FIRST dumbass, and go from there!
~Stateless Warrior
