Tesla (NASDAQ: TSLA) has quietly unplugged the very project Elon Musk once touted as the company’s ticket to full self-driving supremacy. People familiar with the matter say Musk ordered the Dojo supercomputer team dissolved last week.
Unit head Peter Bannon is leaving and roughly 20 engineers have defected to a new startup, DensityAI, while the rest are being redeployed to other data-center work inside Tesla.
The reversal undercuts Tesla’s plan to build proprietary silicon and training infrastructure for its autopilot and robotics programs.
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Barely two weeks ago, Musk told fans Dojo 2 would be “operating at scale” in 2026 at the equivalent of 100,000 Nvidia H100 GPUs. That timeline is now moot. Critics point out that the billionaire’s shifting forecasts similar to Full Self-Driving and Optimus have become central to Tesla’s narrative—and valuation—just as core EV sales growth slows.
Dojo’s pitch was straightforward: purpose-built silicon would process vast video data from Tesla’s global fleet faster and cheaper than off-the-shelf GPUs, accelerating FSD progress and enabling humanoid robot “Optimus” to learn in simulation. Losing that edge now adds a hurdle for Tesla to prove it can still achieve said goals.
With Dojo shelved, Tesla appears set to lean harder on external suppliers. Just last week, Samsung Electronics inked a US$16.5 billion agreement to provide custom AI chips to the automaker. Tesla already relies on Nvidia and AMD for training clusters, and abandoning homegrown hardware may blunt capex but exposes the firm to tight supply and pricing risk in the broader AI accelerator market.
Tesla ended Q2 with roughly $22 billion in cash, but free cash flow has been lumpy as the company juggles factory expansions, the Cybertruck rollout, and now multibillion-dollar AI chip commitments.
This development notably comes after Tesla board awarded Musk a new $29 billion compensation package, even as his previous record-breaking pay deal remains tied up in Delaware courts.
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