AChia

TSLA (2018+)

[AChia @TeslaChia]

@NickGibbsIAG Sounds good. I am signed up for June.

[AChia @TeslaChia]

Never a Dull Moment in This Market.

I’m still calling it: We’re in a Bull Market.

I’ve been bullish for weeks.

Even $TSLA is starting to look bullish. Let’s just say actions speak louder than words—more on this in a second.

Most pros are still fighting the market.

That’s exactly why retail is positioned to take this cycle once again.

Let’s Discuss:

[Shanaka Anslem Perera ⚡ @shanaka86]

Nine billion miles of driving data just became a chip.

Tesla AI5 is finalized for production. The design files are at Samsung in Texas and TSMC in Arizona. The transistors are locked. There is no going back. Tape-out is the hardest gate in semiconductor engineering because everything before it is reversible and everything after it is silicon.

How this particular chip was designed is the most interesting part.

Nvidia builds general-purpose GPUs. They pack transistors into a full-reticle die, ship it with CUDA, and let customers figure out which operations matter. Blackwell B200 delivers 4.5 petaFLOPS at up to 1,000 watts. It runs any model for any customer. That generality is the moat and the tax. Every workload pays for circuits it never uses.

Tesla designed AI5 backward. They started with 9 billion miles of FSD inference data and asked one question: where does the neural network waste cycles? The answer was softmax computation and quantization precision loss. Two specific mathematical operations that consume disproportionate silicon area and power in every general-purpose GPU on Earth. Operations that Nvidia cannot optimize away because other customers need those transistors for different workloads.

Tesla hardened them. Burned custom quantization and softmax accelerator blocks directly into the die. Five times more efficient on those operations than any general-purpose equivalent. Then they added 10 times the raw compute and 9 times the memory capacity relative to AI4. The result: a single AI5 system-on-chip delivers roughly 5 times the useful compute of the current dual-chip AI4 configuration at an estimated 250 watts. Musk has framed a single AI5 as Nvidia Hopper class and dual AI5 as Blackwell class for Tesla workloads, at 3 to 5 times better power efficiency and roughly 10 times better performance per dollar.

This is not a chip designed to compete with Nvidia. This is a chip designed to run one thing: the learned differentiable physics engine that emerged from 9 billion miles of camera observation. Every transistor serves that engine. No wasted silicon. No generality tax. The neural network wrote its own hardware.

The chip goes to two foundries. Samsung in Taylor, Texas. TSMC in Arizona. Both American. Musk thanked both this morning and added: “It will be one of most produced AI chips ever.”

Samples arrive late 2026. Volume targets H2 2027. In the same post, Musk confirmed AI6, Dojo3, and “other exciting chips” are in active development. The 9-month cadence is real. AI6 targets tape-out by December. Dojo3 restarts on the unified architecture after Musk shut down Dojo2 last August as an “evolutionary dead end.” Intel joined Terafab eight days ago for advanced packaging. The $16.5 billion Samsung deal runs through 2033.

The chip that taped out this morning is not a product. It is the physical crystallization of 9 billion miles of learned physics into transistors optimized for the exact mathematical operations that physics requires. The software trained on the road. The silicon was designed from what the software learned. And the factory that will mass-produce it is being built in the same city where the cars that generated the training data roll off the line.

The loop is closed.

[AChia @TeslaChia]

@techbharat White rose?

[AChia @TeslaChia]

@Pharmdca Agreed. Mass manufacturing with the API, while not being the innovator, is basically a generic company for the same dosage and formulation.

[AChia @TeslaChia]

@strengthPlan I just don’t care anymore about the volatility. It’s going to choppy. I finally just want to enjoy my life instead of worrying about market movements and let Elon and his team cook.

[AChia @TeslaChia]

@elonmusk @Tesla And working internet!

[AChia @TeslaChia]

@ShrimpTeslaLong True. I really hope there is a dividend.

[AChia @TeslaChia]

@SawyerMerritt @Tesla I won’t find out for several months the total for 2026. In 2025, VPP paid ~$700 (Feb and May).

[AChia @TeslaChia]

@DevinOlsenn One time I forgot to enter a destination and tapped start. The car unparked and proceed to leave the parking lot then I remembered and quickly entered my destination. I wonder what the car would done if I let it drive without a destination.

[AChia @TeslaChia]

@grok @Brand0_XYZ @elonmusk @teslayoda @grok

[AChia @TeslaChia]

@grok @Brand0_XYZ @elonmusk @teslayoda What companies would supply manufacturing machines and supplies to the Tesla Terafab? Only include the industry leaders.

[jimmah @jamesdouma]

No, this is not competition for FSD anymore than LEGO releasing a Space Shuttle kit is competition for the Falcon 9.

Nvidia has released multiple generations of ADAS development kits and tools for developing ADAS systems. These are not ADAS systems, they are tools to help get started developing an ADAS system. Nvidia has also produced multiple generations of hardware kits that can help a developer get started building the compute framework for an ADAS system using Nvidia silicon. An ADAS demo can be put together pretty quickly using these kits, but a production system cannot - the kit gets you 0.01% of the way to concept for a production system and it doesn't include most of the difficult to understand parts - it just shows what is possible. This latest kit apparently includes the a VLA as the core software architectural component. Using a VLA provides a lot of development advantages but VLAs are compute intensive and not, in their simple form, suitable for a production system.

It would be a good thing for the world if companies picked up these tools and started making a serious attempt to develop ADAS systems and I hope they do. If they were wildly successful they might start fielding them in 5 years and that could help Tesla to displace the billion plus human driven vehicles ten years from now. We need lots and lots and lots of autonomous capable vehicles and Tesla can't build all of them in any reasonable period of time.

There is no scenario in which a company building on top of this new development kit will even slightly dent Tesla's Robotaxi market opportunity. I wish it were that easy - building an FSD like system is still a technically challenging, resource intensive, and commercially fraught task. It's kind of a miracle that any company did it once. It's the thing I'm most grateful to Tesla for.

[AChia @TeslaChia]

Charged there today. Worst spot to visit when it’s raining and you want somewhere covered to eat. Prefer the Kettleman City Lounge. Also the Oasis bathrooms had no toilet paper and there were pooped stained ones on the ground. Hopefully Optimus can clean up after some filthy visitors…

[AChia @TeslaChia]

@DillonLoomis Couldn’t agree more. So many if not the majority are still plugged into the matrix.

[AChia @TeslaChia]

@thecybersurg B

[AChia @TeslaChia]

@BullTradeFinder Same