Morgan Stanley Keeps Overweight on Tesla, $430 Price Target

Morgan Stanley analyst Adam Jonas reiterated an Overweight rating and $430 price target on Tesla (NASDAQ: TSLA).

“Why does DeepSeek matter? Advancement in genAI/LLMs directly impacts the advancement of foundation model training for robotics (AVs, eVTOL, AMRs, humanoids, etc).

More than any other factor, the growing investor interest in embodied AI has been driven by recent advancements in genAI/supercomputing. – Direction of travel will ultimately get physical.

Just as chatbots need textual data to train LLM foundation models, physical robots need vision data to train their VLA (vision, language, actuation) foundation models.

As computing architecture (inference, training, simulation) continues to proliferate in size and improve in efficiency, we anticipate a global scramble for passive optical data to create a hyper realistic digital twin of the physical world. – China is making rapid headway in embodied AI.

Supported by government backed industrial initiatives, The PRC is making rapid progress in the development of physical AI including autonomous cars (AVs), drones/eVTOLs and humanoids.

Advantages in localization of mass production of key enabling components such as actuators, sensors, batteries, encoders, bearings, gears, harmonic reducers and critical up-stream supply chain is complemented by an aggressive testing and commercialization efforts. – What the Future of Tesla’s business in China?

Autonomous cars must avoid objects. Autonomous weapons systems (AWS) target objects.

Experts in autonomy have long suggested the civilian environment of city streets is more complex (with less room for error) than a military theater.

The dual purpose element of embodied AI carries obvious national security sensitivities. – EVs are the ‘sockets’ for the forthcoming physical (’embodied’) AI.

In our opinion, if the US wants to be a leader in autonomy, it must ultimately embrace electric mobility.

In a future where geopolitical rivals demonstrate increasing competency/rate-of-change we would expect to see an acceleration of government/lawmaker and investor attention on the embodied theme.

In our view, this could enhance the market’s appreciation for what Tesla brings to the table beyond the EV market. – Tesla’s expanding inference swarm.

We estimate Tesla ended FY24 with just under 7mm software defined semi-autonomous vehicles on the road.

By 2030, we forecast this combined fleet number to reach 24mm units, rising to 50mm by 2035 and 84mm units by 2040.

Keeping Tesla’s hardware 4 FSD computer capability unchanged (up to 50 TOPS) would imply 4,200 exaFLOPS of aggregate inference capacity in the road vehicle fleet by 2040. – TSLA as a robotics/AI portfolio.

While we continue to view Tesla as sort of an embodied AI ‘portfolio’ and well positioned due to the underpinnings of our DREAMS framework, we note that we do not currently ascribe any value to Tesla for embodied AI in our $430 price target or $800 bull case.”

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