Brainside

Software Engineer • Future #Tesla owner • #TeamElon #TeamTesla #TeamSpaceX •
Tesla Referral Code:

[Justine Moore @venturetwins]

Incredible clip on how @karpathy uses OpenClaw to run his house via texts.

You can ask agents to find connected hardware at your home (like Sonos speaker), and they'll search the network + hack in for you 🤯

You can control music, lights, HVAC, security...w/o writing any code.

[Philip Johnston @PhilipJohnston]

Brb… cancelling all AI subscriptions 👀

[Sawyer Merritt @SawyerMerritt]

Vision-only Tesla Model Y robotaxi running FSD Unsupervised dodges a Waymo robotaxi, which uses radar, lidar, and cameras, after it incorrectly crosses the yellow line.

[Dennis Hong @DennisHongRobot]

So many humanoid robots at CES2026! 😆🤖🫶

[Andrej Karpathy @karpathy]

The first 100% autonomous coast-to-coast drive on Tesla FSD V14.2! 2 days 20 hours, 2732 miles, zero interventions.

This one is special because the coast-to-coast drive was a major goal for the autopilot team from the start. A lot of hours were spent in marathon clip review sessions late into the night looking over interventions as we attempted legs of the drive over time - triaging, categorizing, planning out all the projects to close the gap and bring the number of interventions to zero.

Amazing to see the system actually get there and huge congrats to the team!

[FSD Pilot (Unsupervised) 🛩🇺🇸 @jchybow]

@rohanpaul_ai

[Rohan Paul @rohanpaul_ai]

Robots in China are doing it all now, even dancing on stage like pros.

Here Unitree robots doing Webster flips and are performing at Chinese-American singer Wang Leehom’s concert in Chengdu.

[Richard Burton @Ricburton]

You have to hand it to Elon 🤟

[Sawyer Merritt @SawyerMerritt]

Tesla has released a new video of their Optimus humanoid robot showing off its new running capabilities.

[Sawyer Merritt @SawyerMerritt]

Here is Ron Baron's full interview with @elonmusk at the annual Baron Investment Conference.

They talk about Tesla, Optimus, Tesla's AI5 chip, Neuralink, xAI, Grok 5, FSD, buying Twitter, AI, Tesla maybe building its own chip fab, their friendship and more.

I've cut out the waiting period at the beginning of the stream.

[Adam Berg @AdamBerg4680]

Tesla FSD in crazy 🇪🇺 streets (Prague) for the FIRST https://t.co/pEvJC2YyiI. TL;DR Unofficially version is basically working! @Tesla @teslaeurope

[Andrej Karpathy @karpathy]

I took delivery of a beautiful new shiny HW4 Tesla Model X today, so I immediately took it out for an FSD test drive, a bit like I used to do almost daily for 5 years. Basically... I'm amazed - it drives really, really well, smooth, confident, noticeably better than what I'm used to on HW3 (my previous car) and eons ahead of the version I remember driving up highway 280 on my first day at Tesla ~9 years ago, where I had to intervene every time the road mildly curved or sloped. (note this is v13, my car hasn't been offered the latest v14 yet)

On the highway, I felt like a passenger in some super high tech Maglev train pod - the car is locked in the center of the lane while I'm looking out from Model X's higher vantage point and its panoramic front window, listening to the (incredible) sound system, or chatting with Grok. On city streets, the car casually handled a number of tricky scenarios that I remember losing sleep over just a few years ago. It negotiated incoming cars in tight lanes, it gracefully went around construction and temporarily in-lane stationary cars, it correctly timed tricky left turns with incoming traffic from both sides, it gracefully gave way to the car that went out of order in the 4-way stop sign, it found a way to squeeze into a bumper to bumper traffic to make its turn, it overtook the bus that was loading passengers but still stopped for the stop sign that was blocked by the bus, and at the end of the route it circled around a parking lot, found a spot and... parked. Basically a flawless drive.

For context, I'm used to going out for a brief test drive around the neighborhood to return with 20 clips of things that could be improved. It's new for me to do just that and exactly like I used to, but come back with nothing. Perfect drive, no notes. I expect there's still more work for the team in the long march of 9s, but it's just so cool to see that we're beyond finding issues on any individual ~1 hour drive around the neighborhood, you actually have to go to the fleet and mine them. Back then, I processed the incredible promise of vehicle autonomy at scale (in the fully scaleable, vision only, end-to-end Tesla way) only intellectually, but now it is possible to feel it intuitively too if you just go out for a drive. Wait, of course surround video stream at 60Hz processed by a fully dedicated "driving brain" neural net will work, and it will be so much better and safer than a human driver. Did anyone else think otherwise?

I also watched @aelluswamy 's new ICCV25 talk last week (https://t.co/RdaM23kvez) that hints at some of the recent under the hood technical components driving this progress. Sensor streams (videos, maps, kinematics, audio, ...) over long contexts (e.g. ~30 seconds) go into a big neural net, steering/acceleration comes out, optionally with visualization auxiliary data. This is the dream of the complete Software 1.0 -> Software 2.0 re-write that scales fully with data streaming from millions of cars in the fleet and the compute capacity of your chip, not some engineer's clever new DoubleParkedCarHandler C++ abstraction with undefined test-time characteristics of memory and runtime. There's a lot more hints in the video on where things are going with the emerging "robotics+AI at scale stack". World reconstructors, world simulators "dreaming" dynamics, RL, all of these components general, foundational, neural net based, how the car is really just one kind of robot... are people getting this yet?

Huge congrats to the team - you're building magic objects of the future, you rock! And I love my car <3.

[Ashok Elluswamy @aelluswamy]

Full video of the ICCV '25 presentation

[Jonas DM. @dm_jns]

Release Tesla Full Self Driving Supervised in Europe - Sign the Petition! https://t.co/SP6PP46SDl via @Change

[Alex @alex_avoigt]

If you want to understand why Tesla's approach to full autonomy is successful, read this article carefully and try to understand it.

If you don't, but pretend that any other company is even close, you don't know what you're talking about and better shut up.

[Sawyer Merritt @SawyerMerritt]

A new 30-minute presentation from @aelluswamy, Tesla’s VP of AI, has been released, where he talks about FSD, AI and the team’s latest progress.

Highlight from the presentation:
• Tesla's vehicle fleet can provide 500 years of driving data every single day.

Curse of Dimensionality:
• 8 cameras at high frame rate = billions of tokens per 30 seconds of driving context.
• Tesla must compress and extract the right correlations between sensory input and control actions.

Data Advantage:
• Tesla has access to a “Niagara Falls of data” — hundreds of years’ worth of collective fleet driving.
• Uses smart data triggers to capture rare corner cases (e.g., complex intersections, unpredictable behavior).

Quality and Efficiency:
• Extracts only the essential data needed to train models efficiently.

Debugging and Interpretability:
• Even though the system is end-to-end, Tesla can still prompt the model to output interpretable data:
3D occupancy, road boundaries, objects, signs, traffic lights, etc.
• Natural language querying: ask the model why it made a certain decision.
• These auxiliary predictions don’t drive the car but help engineers debug and ensure safety.

Tesla’s Advanced Gaussian Splatting (3D Scene Modeling):
• Tesla developed a custom, ultra-fast Gaussian splatting system to reconstruct 3D scenes from limited camera views.
• Produces crisp, accurate 3D renderings even from few camera angles — far better than standard NeRF/splatting approaches.
• Enables rapid visual debugging of the driving environment in 3D.

Evaluation & World Models:
• Evaluation is the hardest challenge: models may perform well offline but fail in real-world conditions.
• Tesla builds balanced, diverse evaluation datasets focusing on edge cases — not just easy highway driving.

Introduced a learned world simulator (neural network-generated video engine):
• Can simulate 8 Tesla camera feeds simultaneously — fully synthetic.
• Used for testing, training, and reinforcement learning.
• Allows adversarial event injection (e.g., adding a pedestrian or vehicle cutting in).
• Enables replaying past failures to verify new model improvements.
• Can run in near real-time, letting testers ���drive” inside a simulated world.

What’s Next:
• Scale robotaxi service globally.
• Unlock full autonomy across the entire Tesla fleet.
• Cybercab: next-gen 2-seat vehicle designed specifically for robotaxi use, targeting lowest transportation cost (cheaper than public transit).
• Same neural networks will power Optimus humanoid robot.
• The same video generation system is now being applied to Optimus.
• The system can simulate and plan movement for robots, adapting easily to new forms.

via the International Conference on Computer Vision (ICCV).

Full presentation: https://t.co/Mdswdz4oqh

[ΛI DRIVR @AIDRIVR]

Tesla FSD 14 handles a MANIAC

[Whole Mars Catalog @wholemars]

Your personal bodyguard

[DogeDesigner @cb_doge]

As @elonmusk says, we’re in a simulation.

[Ken Synopsis @TeslaSynopsis]

Optimus helping humanity