Investor's Corner
Why Tesla Autopilot will ultimately prove the self-driving industry leader
Tesla took an early lead in the race to develop vehicle autonomy, and its Autopilot system remains the state of the art. However, the technology is advancing more slowly than the company predicted – Elon Musk promised a coast-to-coast driverless demo run for 2018, and we’re still waiting. Meanwhile, competitors are hard at work on their own autonomy tech – GM’s Super Cruise, is now available on the CT6 luxury sedan.
Is Tesla in danger of falling behind in the self-driving race? Trent Eady, writing in Medium, takes a detailed look at the company’s Autopilot technology, and argues that the California automaker will continue to set the pace.
Every Tesla vehicle produced since October 2016 is equipped with a hardware suite designed for Full Self-Driving, including cameras, radar, ultrasonic sensors and an upgradable onboard computer. Around 150,000 of these “Hardware 2” Teslas are currently on the road, and could theoretically be upgraded to self-driving vehicles via an over-the-air software update.
Above: In its current state, Tesla’s Autopilot requires a hands-on approach (Youtube: Tesla)
Tesla disagrees with most of the other players in the self-driving game on the subject of Lidar, a technology that calculates distances using pulses of infrared laser light. Waymo, Uber and others seem to regard lidar as a necessary component of any self-driving system. However, Tesla’s Hardware 2 sensor suite doesn’t include it, instead relying on radar and optical cameras.
Lidar’s strength is its high spatial precision – it can measure distances much more precisely than current camera technology can (Eady believes that better software could enable cameras to close the gap). Lidar’s weakness is that it functions poorly in bad weather. Heavy rain, snow or fog causes lidar’s laser pulses to refract and scatter. Radar works much better in challenging weather conditions.
According to Eady, the reason that Tesla eschews lidar may be the cost: “Autonomy-grade lidar is prohibitively expensive, so it’s not possible for Tesla to include it in its production cars. As far as I’m aware, no affordable autonomy-grade lidar product has yet been announced. It looks like that is still years away.”
If Elon Musk and his autonomy team are convinced that lidar isn’t necessary, why does everyone else seem so sure that it is? “Lidar has accrued an aura of magic in the popular imagination,” opines Mr. Eady. “It is easier to swallow the new and hard-to-believe idea of self-driving cars if you tell the story that they are largely enabled by a cool, futuristic laser technology…It is harder to swallow the idea that if you plug some regular ol’ cameras into a bunch of deep neural networks, somehow that makes a car capable of driving itself through complicated city streets.”
Those deep neural networks are the real reason that Eady believes Tesla will stay ahead of its competitors in the autonomy field. The flood of data that Tesla is gathering through the sensors of the 150,000 or so existing Hardware 2 vehicles “offers a scale of real-world testing and training that is new in the history of computer science.”
Competitor Waymo has a computer simulation that contains 25,000 virtual cars, and generates data from 8 million miles of simulated driving per day. Tesla’s real-world data is of course vastly more valuable than any simulation data could ever be, and the company uses it to feed deep neural networks, allowing it to continuously improve Autopilot’s capabilities.
A deep neural network is a type of computing system that’s loosely based on the way the human brain is organized (sounds like the kind of AI that Elon Musk is worried about, but we’ll have to trust that Tesla has this under control). Deep neural networks are good at modeling complex non-linear relationships. The more data that’s available to train the network, the better its performance will be.
“Deep neural networks started to gain popularity in 2012, after a deep neural network won the ImageNet Challenge, a computer vision contest focused on image classification,” Eady explains. “For the first time in 2015, a deep neural network slightly outperformed the human benchmark for the ImageNet Challenge…The fact that computers can outperform humans on even some visual tasks is exciting for anyone who wants computers to do things better than humans can. Things like driving.”
By the way, who was the human benchmark who was bested by a machine in the ImageNet Challenge? Andrej Karpathy, who is now Director of AI at Tesla.
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Note: Article originally published on evannex.com by Charles Morris; Source: Medium
Tesla has scheduled its Earnings Call for Q4 and Full Year 2025 for next Wednesday, January 28, at 5:30 p.m. EST, and investors are already preparing to get some answers from executives regarding a wide variety of topics.
The company accepts several questions from retail investors through the platform Say, which then allows shareholders to vote on the best questions.
Tesla does not answer anything regarding future product releases, but they are willing to shed light on current timelines, progress of certain projects, and other plans.
There are five questions that range over a variety of topics, including SpaceX, Full Self-Driving, Robotaxi, and Optimus, which are currently in the lead to be asked and potentially answered by Elon Musk and other Tesla executives:
- You once said: Loyalty deserves loyalty. Will long-term Tesla shareholders still be prioritized if SpaceX does an IPO?
- Our Take – With a lot of speculation regarding an incoming SpaceX IPO, Tesla investors, especially long-term ones, should be able to benefit from an early opportunity to purchase shares. This has been discussed endlessly over the past year, and we must be getting close to it.
- When is FSD going to be 100% unsupervised?
- Our Take – Musk said today that this is essentially a solved problem, and it could be available in the U.S. by the end of this year.
- What is the current bottleneck to increase Robotaxi deployment & personal use unsupervised FSD? The safety/performance of the most recent models or people to monitor robots, robotaxis, in-car, or remotely? Or something else?
- Our Take – The bottleneck seems to be based on data, which Musk said Tesla needs 10 billion miles of data to achieve unsupervised FSD. Once that happens, regulatory issues will be what hold things up from moving forward.
- Regarding Optimus, could you share the current number of units deployed in Tesla factories and actively performing production tasks? What specific roles or operations are they handling, and how has their integration impacted factory efficiency or output?
- Our Take – Optimus is going to have a larger role in factories moving forward, and later this year, they will have larger responsibilities.
- Can you please tie purchased FSD to our owner accounts vs. locked to the car? This will help us enjoy it in any Tesla we drive/buy and reward us for hanging in so long, some of us since 2017.
- Our Take – This is a good one and should get us some additional information on the FSD transfer plans and Subscription-only model that Tesla will adopt soon.
Tesla will have its Earnings Call on Wednesday, January 28.
Elon Musk
Tesla locks in Elon Musk’s top problem solver as it enters its most ambitious era
The generous equity award was disclosed by the electric vehicle maker in a recent regulatory filing.
Tesla has granted Senior Vice President of Automotive Tom Zhu more than 520,000 stock options, tying a significant portion of his compensation to the company’s long-term performance.
The generous equity award was disclosed by the electric vehicle maker in a recent regulatory filing.
Tesla secures top talent
According to a Form 4 filing with the U.S. Securities and Exchange Commission, Tom Zhu received 520,021 stock options with an exercise price of $435.80 per share. Since the award will not fully vest until March 5, 2031, Zhu must remain at Tesla for more than five years to realize the award’s full benefit.
Considering that Tesla shares are currently trading at around the $445 to $450 per share level, Zhu will really only see gains in his equity award if Tesla’s stock price sees a notable rise over the years, as noted in a Sina Finance report.
Still, even at today’s prices, Zhu’s stock award is already worth over $230 million. If Tesla reaches the market cap targets set forth in Elon Musk’s 2025 CEO Performance Award, Zhu would become a billionaire from this equity award alone.
Tesla’s problem solver
Zhu joined Tesla in April 2014 and initially led the company’s Supercharger rollout in China. Later that year, he assumed the leadership of Tesla’s China business, where he played a central role in Tesla’s localization efforts, including expanding retail and service networks, and later, overseeing the development of Gigafactory Shanghai.
Zhu’s efforts helped transform China into one of Tesla’s most important markets and production hubs. In 2023, Tesla promoted Zhu to Senior Vice President of Automotive, placing him among the company’s core global executives and expanding his influence beyond China. He has since garnered a reputation as the company’s problem solver, being tapped by Elon Musk to help ramp Giga Texas’s vehicle production.
With this in mind, Tesla’s recent filing seems to suggest that the company is locking in its top talent as it enters its newest, most ambitious era to date. As could be seen in the targets of Elon Musk’s 2025 pay package, Tesla is now aiming to be the world’s largest company by market cap, and it is aiming to achieve production levels that are unheard of. Zhu’s talents would definitely be of use in this stage of the company’s growth.
Tesla analyst Andrew Percoco of Morgan Stanley teased the company’s dominance in its self-driving initiative, stating that its lead over competitors is “not even close.”
Percoco recently overtook coverage of Tesla stock from Adam Jonas, who had covered the company at Morgan Stanley for years. Percoco is handling Tesla now that Jonas is covering embodied AI stocks and no longer automotive.
His first move after grabbing coverage was to adjust the price target from $410 to $425, as well as the rating from ‘Overweight’ to ‘Equal Weight.’
Percoco’s new note regarding Tesla highlights the company’s extensive lead in self-driving and autonomy projects, something that it has plenty of competition in, but has established its prowess over the past few years.
He writes:
“It’s not even close. Tesla continues to lead in autonomous driving, even as Nvidia rolls out new technology aimed at helping other automakers build driverless systems.”
Percoco’s main point regarding Tesla’s advantage is the company’s ability to collect large amounts of training data through its massive fleet, as millions of cars are driving throughout the world and gathering millions of miles of vehicle behavior on the road.
This is the main point that Percoco makes regarding Tesla’s lead in the entire autonomy sector: data is King, and Tesla has the most of it.
One big story that has hit the news over the past week is that of NVIDIA and its own self-driving suite, called Alpamayo. NVIDIA launched this open-source AI program last week, but it differs from Tesla’s in a significant fashion, especially from a hardware perspective, as it plans to use a combination of LiDAR, Radar, and Vision (Cameras) to operate.
Percoco said that NVIDIA’s announcement does not impact Morgan Stanley’s long-term opinions on Tesla and its strength or prowess in self-driving.
NVIDIA CEO Jensen Huang commends Tesla’s Elon Musk for early belief
And, for what it’s worth, NVIDIA CEO Jensen Huang even said some remarkable things about Tesla following the launch of Alpamayo:
“I think the Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-to-end AI. Whether their AI did reasoning or not is somewhat secondary to that first part.”
Percoco reiterated both the $425 price target and the ‘Equal Weight’ rating on Tesla shares.
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