@clarkcashes Agree with you. I did that almost 2 years ago. Didn’t have anything was getting laid off and didn’t have a car or stable job. Now I have 2 new teslas in a span of 2 years and a stable job, and a house I’m paying off. Life is good now.
A US fighter jet pilot rescued by special forces after being shot down over Iran in April described a shocking sight before ejecting from his aircraft: multiple Iranian drones hovering in the air, moving as one, in a formation that resembled a jellyfish, according to four sources familiar with the matter.
https://t.co/LcaqH5LTOb
@TiredOfDaReight@BeastOfTruth@asha_shar Can’t I say that for Xbox ? It’s also a control scheme since I bought it for games back in the day (Xbox), and to play Xbox exclusives day 1 like forza horizon 6.
State of Play returned with realm-shaking announces, ferocious new gameplay, and more including updates on:
✋ God of War Laufey
🔷 Marathon
🟢 MARVEL Tōkon: Fighting Souls
🟡 Marvel's Wolverine
🦖 Tomb Raider: Legacy of Atlantis
⚔️ Phantom Blade Zero
🏎️ Stuntman: Hollywood
🦋 Until Dawn 2
Catch up on the full show: https://t.co/MxqV8owYCz
LEGO Shrek & Donkey with Puss in Boots set is real, up for preorder at the LEGO Store for $129.99 with a June 1. SomeBODY... https://t.co/Xrsb4arDHQ #ad
New release of FSD Supervised now starting to roll out
This update brings 20% faster reaction time to further increase safety, among many other improvements
Full release notes below
Full Self-Driving (Supervised) v14.3 includes
- Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios.
- Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding.
- Rewrote the AI compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed.
- Mitigated unnecessary lane biasing and minor tailgating behaviors.
- Increased decisiveness of parking spot selection and maneuvering.
- Improved parking location pin prediction, now shown on a map with a (P) icon.
- Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles.
- Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety.
- Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping – driven by training on hard RL examples sourced from the Tesla fleet.
- Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet.
- Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements.
Upcoming Improvements
- Expand reasoning to all behaviors beyond destination handling.
- Add pothole avoidance.
- Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.