Tesla gets Top Pick Upgrade from Morgan Stanley on Dojo Supercomputer Boost

Category Technology

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Morgan Stanley raised their target on Tesla to $400, upgrading their rating to "overweight" after releasing a 66-page report. Tesla has created Dojo, a purpose-built supercomputer, to enhance and train its Full Self-Driving system. While it is difficult to validate the many claioms Tesla's makes, the full suite of acquisitions and investments made over the past few years makes a powerful case for an ambitious effort in hardware/software integration in autonomy.


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Morgan Stanley raised their target on Tesla to $400. Details of Morgan Stanley's 66-page upgrade report for Tesla to now "overweight" with a Price Target of $400 (from $250): .

- Catalyst: Dojo, V12 of FSD and next AI day (early 2024) .

- Dojo (purpose-built super computer to train FSD) can add up to $500bn of value, through faster adoption of robotaxi and SaaS. Emphasizes 3 core capabilities: speed, performance and cost.

Dojo was designed to meet Tesla's challenge of collecting, processing and scaling vast amounts of real-world data from its vehicles for enhancing the efficacy of its FSD system

- In the near term, Dojo can accelerate the development and monetization of Tesla's software and service business. Longer term, we see scope for Dojo to provide avenues for Tesla's software and hardware capabilities to extend well beyond the auto industry.

- Tesla cars are sensor encrusted robots making life and death decisions in highly unpredictable environments and driving situations.

- Tesla has built a custom AI ASIC chip which can operate more efficiently than any chip on the market and at a fraction of the cost.

Tesla's advanced supercomputing architecture is set to give them an asymmetrical advantage in a $10 trillion TAM

- Tesla has a unique longtime experience with advanced driver assist systems with a world-class design team.

- Tesla's vertical integration helps to diversify away from overreliance on 3rd party suppliers.

- Report dives into the world of custom silicon at exaFLOP scale solving some of the world's most challenging problems (autonomy) offering a gateway into vast untapped commercial potential.

The more Morgan Stanley looked at Dojo, the more they realized the potential for underappreciated value in the stock and believes Tesla can reasonably test it's ATH of $400 over the next 12 months.

Tesla's recent acquisitions and investments are indicative of an ambitious effort in hardware/software integration for autonomy

Tesla rallies 5.5% on Monday mornoing as Morgan Stanley upgrades to Top Pick on Dojo supercomputer boost. Tesla (TSLA) rallies as Morgan Stanley upgrades to Top Pick on Dojo supercomputer boost.

"Tesla has developed an advanced supercomputing architecture that pushes new boundaries in custom silicon and may put Tesla at an asymmetric advantage in a $10trn TAM," the analysts wrote in a client note.

They liken Tesla to Amazon (NASDAQ:AMZN) after the e-commerce titan’s AWS was able to reach 70% of the company’s total EBIT.

"We believe that Dojo can add up to $500bn to Tesla's enterprise value, expressed through a faster adoption rate in Mobility (robotaxi) and Network Services (SaaS)," they added.

Tesla has created Dojo, a dedicated supercomputer, to enhance and train its Full Self-Driving (FSD) system. Tesla's vehicles are equipped with numerous sensors and must make critical real-time decisions in unpredictable driving conditions.

To improve the FSD system's efficacy, Tesla needs to address challenges related to data collection, processing power, speed, efficiency, and scalability. Dojo is designed to meet these challenges by providing the computational power necessary to process extensive real-world data from Tesla's vehicles. This enables Tesla to accelerate the development of its autonomous driving technology, a critical step toward achieving Full Self-Driving capabilities and enhancing road safety.

"While it is difficult to explicitly validate the many claioms Tesla's makes, the full suite of acquisitions and investments made over the past few years makes a powerful case for an ambitious effort in hardware/software integration in autonomy." .


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