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
Investor's Corner
SpaceX IPO is coming, CEO Elon Musk confirms
However, it appears Musk is ready for SpaceX to go public, as Ars Technica Senior Space Editor Eric Berger wrote an op-ed that indicated he thought SpaceX would go public soon. Musk replied, basically confirming it.
Elon Musk confirmed through a post on X that a SpaceX initial public offering (IPO) is on the way after hinting at it several times earlier this year.
It also comes one day after Bloomberg reported that SpaceX was aiming for a valuation of $1.5 trillion, adding that it wanted to raise $30 billion.
Musk has been transparent for most of the year that he wanted to try to figure out a way to get Tesla shareholders to invest in SpaceX, giving them access to the stock.
He has also recognized the issues of having a public stock, like litigation exposure, quarterly reporting pressures, and other inconveniences.
However, it appears Musk is ready for SpaceX to go public, as Ars Technica Senior Space Editor Eric Berger wrote an op-ed that indicated he thought SpaceX would go public soon.
Musk replied, basically confirming it:
As usual, Eric is accurate
— Elon Musk (@elonmusk) December 10, 2025
Berger believes the IPO would help support the need for $30 billion or more in capital needed to fund AI integration projects, such as space-based data centers and lunar satellite factories. Musk confirmed recently that SpaceX “will be doing” data centers in orbit.
AI appears to be a “key part” of SpaceX getting to Musk, Berger also wrote. When writing about whether or not Optimus is a viable project and product for the company, he says that none of that matters. Musk thinks it is, and that’s all that matters.
It seems like Musk has certainly mulled something this big for a very long time, and the idea of taking SpaceX public is not just likely; it is necessary for the company to get to Mars.
The details of when SpaceX will finally hit that public status are not known. Many of the reports that came out over the past few days indicate it would happen in 2026, so sooner rather than later.
But there are a lot of things on Musk’s plate early next year, especially with Cybercab production, the potential launch of Unsupervised Full Self-Driving, and the Roadster unveiling, all planned for Q1.
Investor's Corner
Tesla Full Self-Driving statistic impresses Wall Street firm: ‘Very close to unsupervised’
The data shows there was a significant jump in miles traveled between interventions as Tesla transitioned drivers to v14.1 back in October. The FSD Community Tracker saw a jump from 441 miles to over 9,200 miles, the most significant improvement in four years.
Tesla Full Self-Driving performance and statistics continue to impress everyone, from retail investors to Wall Street firms. However, one analyst believes Tesla’s driving suite is “very close” to achieving unsupervised self-driving.
On Tuesday, Piper Sandler analyst Alexander Potter said that Tesla’s recent launch of Full Self-Driving version 14 increased the number of miles traveled between interventions by a drastic margin, based on data compiled by a Full Self-Driving Community Tracker.
🚨 Piper Sandler reiterated its Overweight rating and $500 PT on Tesla $TSLA stock
Analyst Alexander Potter said FSD is near full autonomy and latest versions showed the largest improvement in disengagements, from 440 miles to 9,200 miles between critical interventions pic.twitter.com/u4WCLfZcA9
— TESLARATI (@Teslarati) December 9, 2025
The data shows there was a significant jump in miles traveled between interventions as Tesla transitioned drivers to v14.1 back in October. The FSD Community Tracker saw a jump from 441 miles to over 9,200 miles, the most significant improvement in four years.
Interestingly, there was a slight dip in the miles traveled between interventions with the release of v14.2. Piper Sandler said investor interest in FSD has increased.
Full Self-Driving has displayed several improvements with v14, including the introduction of Arrival Options that allow specific parking situations to be chosen by the driver prior to arriving at the destination. Owners can choose from Street Parking, Parking Garages, Parking Lots, Chargers, and Driveways.
Additionally, the overall improvements in performance from v13 have been evident through smoother operation, fewer mistakes during routine operation, and a more refined decision-making process.
Early versions of v14 exhibited stuttering and brake stabbing, but Tesla did a great job of confronting the issue and eliminating it altogether with the release of v14.2.
Tesla CEO Elon Musk also recently stated that the current v14.2 FSD suite is also less restrictive with drivers looking at their phones, which has caused some controversy within the community.
Although we tested it and found there were fewer nudges by the driver monitoring system to push eyes back to the road, we still would not recommend it due to laws and regulations.
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
With that being said, FSD is improving significantly with each larger rollout, and Musk believes the final piece of the puzzle will be unveiled with FSD v14.3, which could come later this year or early in 2026.
Piper Sandler reaffirmed its $500 price target on Tesla shares, as well as its ‘Overweight’ rating.
Tesla received a price target boost from Morgan Stanley, according to a new note on Monday morning, but there is some considerable caution also being communicated over the next year or so.
Morgan Stanley analyst Andrew Percoco took over Tesla coverage for the firm from longtime bull Adam Jonas, who appears to be focusing on embodied AI stocks and no longer automotive.
Percoco took over and immediately adjusted the price target for Tesla from $410 to $425, and changed its rating on shares from ‘Overweight’ to ‘Equal Weight.’
Percoco said he believes Tesla is the leading company in terms of electric vehicles, manufacturing, renewable energy, and real-world AI, so it deserves a premium valuation. However, he admits the high expectations for the company could provide for a “choppy trading environment” for the next year.
He wrote:
“However, high expectations on the latter have brought the stock closer to fair valuation. While it is well understood that Tesla is more than an auto manufacturer, we expect a choppy trading environment for the TSLA shares over the next 12 months, as we see downside to estimates, while the catalysts for its non-auto businesses appear priced at current levels.”
Percoco also added that if market cap hurdles are achieved, Morgan Stanley would reduce its price target by 7 percent.
Perhaps the biggest change with Percoco taking over the analysis for Jonas is how he will determine the value of each individual project. For example, he believes Optimus is worth about $60 per share of equity value.
He went on to describe the potential value of Full Self-Driving, highlighting its importance to the Tesla valuation:
“Full Self Driving (FSD) is the crown jewel of Tesla’s auto business; we believe that its leading-edge personal autonomous driving offering is a real game changer, and will remain a significant competitive advantage over its EV and non-EV peers. As Tesla continues to improve its platform with increased levels of autonomy (i.e., hands-off, eyes-off), it will revolutionize the personal driving experience. It remains to be seen if others will be able to keep pace.”
Additionally, Percoco outlined both bear and bull cases for the stock. He believes $860 per share, “which could be in play in the next 12 months if Tesla manages through the EV-downturn,” while also scaling Robotaxi, executing on unsupervised FSD, and scaling Optimus, is in play for the bull case.
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Meanwhile, the bear case is placed at $145 per share, and “assumes greater competition and margin pressure across all business lines, embedding zero value for humanoids, slowing the growth curve for Tesla’s robotaxi fleet to reflect regulatory challenges in scaling a vision-only perception stack, and lowering market share and margin profile for the autos and energy businesses.”
Currently, Tesla shares are trading at around $441.
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