Musk Drops Trove of Model 3 Production Intel in Email

  • An “internal” email written by Musk was leaked today with details around how Tesla can hit Model 3 production goals for the June quarter and measures to increase profitability and internal efficiency.
  • This makes us more confident in Tesla’s ability to ramp Model 3 production to a level that will satisfy investors in the Jun-18 quarter.
  • Tesla will be pausing Model 3 production for retooling. While this sounds bad, it’s actually a good thing.

There are 6 key takeaways from this lengthy memo:

  • Model 3 production over the past 3 weeks has been 2020, 2070, and 2250 respectively, and has increased by 10% since reporting earlier this month.
  • Production is on pause for 3-5 days for comprehensive upgrades that should result in 3-4k Model 3’s per week next month.
  • Production will pause again in May and result in capacity (not production) of 6k per week by late June.
  • The reason they’re shooting for 6k per week is to allow a margin of error towards the goal of 5k per week. We’re modeling Model 3 production of 4k per week exiting Jun-18.
  • Fremont factory is moving to 24/7 operations, but timing is unclear. To make this possible they will be hiring ~400 people per week for several weeks.
  • Musk is taking a more active role, requiring personal approval of expenses over $1m, and demanding streamlined internal communication.

Model 3 production pause sounds bad but is actually a good thing. The headline that production has been shutdown suggested that there was something wrong with the design and or production of the car. As outlined in this memo, production stoppages serve to provide time for upgrades to the line which should result in increased output. This is necessary to scale Model 3 production from its current ~100,000 cars per year rate to just over 500,000 per year during the next year and a half. Tesla has been clear that the ramp in Model 3 production will grow exponentially in a stairstep pattern, not linearly.

Why investors will likely continue to support the Tesla story. The last 6 weeks have been a wild ride for Tesla investors. Shares have declined 27% and rebounded 15% as investors digested a range of Tesla news including Model 3 production miss in the March quarter, a debt downgrade, an accident that called into question the integrity of Autopilot, the company projecting they will not need to raise capital in 2018 and now a Model 3 production pause. In total, during that period, there have been four negative stories and one positive story. Given this negativity, it begs the question, how long will investors continue to support the Tesla story. We think the answer is a long time. Core Tesla investors are less interested in the week to week news cycle and more interested in finding companies that have open-ended growth opportunities. Despite all of the hair on the Tesla story, the company remains ideally positioned for growth around the themes of renewable energy, storage, electric vehicles, and autonomous transport. We believe, given the size of Tesla’s addressable markets, that investors will remain committed in the form of holding shares and participating in future fundraising.

Disclaimer: We actively write about the themes in which we invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Posted in Tesla  • 

Seeing The Road Ahead: The Undervalued Self-Driving Asset of Data

This is the 4th in a series of notes based on our deep dive into computer perception for autonomous vehicles. Autonomy is a question of when? not if? In this series, we’ll outline our thoughts on the key components that will enable fully autonomous driving. See our previous notes (Computer Perception Outlook 2030What You Need To Know About LiDAR, The Importance of Cameras To Self-Driving Vehicles).

A self-driving car will only be as strong as the data it trains on.

The importance driving data will play in developing fully autonomous vehicles is often understated, and companies that possess large and high-quality driving data sets are much further ahead of their peers than some may think. Driving data is key because it is the core input that will train the artificial intelligence models that operate autonomous vehicles. The more data these models have, the more scenarios they can prepare for, and, in turn, the stronger the entire system becomes. However, obtaining good driving data is not an easy task, and it is virtually impossible to gather data on every single driving scenario in all types of weather conditions. Due to improvements in computer graphics technology, many are relying on simulated data to train their self-driving models.  In the paragraphs below, we dive deeper into the pros and cons of using simulated data versus real data and identify who are the data leaders among self-driving car companies.

Simulation vs. real data. We recently spoke to a computer vision expert at the University of Michigan about the difference between using simulated data versus real-world data. He believes that simulated training data is valuable because most of the data collected during on-road driving is innocuous. Real-time driving data is only very interesting when there is a critical event or an unusual scenario. Simulation data lets you test on critical events constantly. However, he also noted the AI in simulated data is still programmed by a human and those AI tend to act differently than humans on the road. All autonomous systems will train with some simulated data and will therefore require fine tuning to factor in the difference between human and machine driving styles. That said, we do not want to underestimate the value of real data and believe capturing non-programmed scenarios will play a key role in preparing AVs for all situations that may arise.

Waymo’s large data lead.  The more miles an autonomous vehicle drives, the more real data the system can capture, the more robust the system can become. Companies that are approved to test autonomous driving in California are responsible for recording and publishing the number of autonomous miles driven. As of April 1st, 52 companies have been issued permits to test autonomous vehicles in California, and as shown in the graph below, Waymo has driven 352,545 as of November 30th, 2017. As of February 2018, Waymo had announced they have driven over 5 million miles in total. This announcement came only ~3 months after they announced crossing the 4-million-mile mark. While testing takes place in many states other than California, these data points suggest that Waymo has a very large data lead over their peers, which may translate to a large lead in the race to full autonomy.

Tesla lurking in the shadows. While Tesla is one of the 52 companies approved to test autonomous vehicles in California, Tesla did not test on state roads in 2017. However, the company acknowledged in the report they filed with California DMV that Tesla conducts testing to develop autonomous vehicles via simulation, in laboratories, on test tracks, and on public roads in various locations around the world. Tesla also highlighted that they have a fleet of hundreds of thousands of customer-owned vehicles that test autonomous technology in “shadow-mode” during their normal operation. Shadow mode is a feature that runs in the background without actuating vehicle controls in order to provide data on how the features would perform in real-world and real-time conditions. This has allowed Tesla to gather billions of miles of passive real-world driving data to develop its autonomous technology. This data is extremely valuable in training autonomous vehicles to interact with the real world, and, in our eyes, makes Tesla one of the top contenders in the race for full autonomy.

Disclaimer: We actively write about the themes in which we invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Tesla Production: A Step in the Right Direction

  • While Tesla missed their original Model 3 production goal (exiting Mar-18 at 2,000 per week vs guidance of 2,500), the miss was not as severe as investors were expecting.
  •  Importantly, Tesla doubled the Model 3 production run rate in Mar-18 over Dec-17 and is now 20% of the way to its goal of 10,000 Model 3s per week, which we expect in mid-2019. We expect Model 3 production to double again in the Jun-18 quarter to 4,000 vehicles per week.
  • Tesla addressed the investor cash concern, predicting they will not need to raise money in 2018.
  • While on a bumpy road, we believe Tesla remains exceptionally positioned for the future around EV, autonomy, and sustainable energy.
  • Tesla reiterated their goal of exiting Jun-18 at a run rate of 5,000 Model 3s per week. We are modeling for 4,000 per week.
  • To factor in Mar-18’s miss, we are lowering our 2018 Model production estimate to 161k from 168k.

Perspective on expectations. Tesla continues to miss Model 3 production numbers. Mar-18 is the third out of three quarters that they have failed to meet this important target. Investors are up in arms over these misses and have lost confidence in Tesla’s production guidance. While we share some of the same frustration, this hyperfocus on missing high, self-imposed production targets causes investors to miss the bigger story, which involves the company nicely ramping production of a car that is exceptionally difficult to produce and could potentially usher in global adoption of EVs.

Changes to our numbers. The table below outlines the changes to our production estimates.

Note: given the ~20% gap between Model 3 production and delivery numbers, we are now adjusting our Model 3 estimates to be driven by deliveries. This results in a ~20% reduction in Model 3 deliveries, however, there is little change in our Model 3 production numbers. No changes to S and X modeling methodology given our model had been driven by deliveries. Link to updated model here.

Expecting Profitability in Sep-20. We continue to model for Tesla to reach profitability in ten quarters. We will publish an updated cash flow model in the next week, but conceptually, we expect the company to be cashflow positive before Sep-20.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Posted in Tesla  • 

Seeing the Road Ahead: The Importance of Cameras to Self-Driving Vehicles

This is the third in a series of notes based on our deep dive into computer perception for autonomous vehicles. Autonomy is a question of when? not if? In this series, we’ll outline our thoughts on the key components that will enable fully autonomous driving. See our previous notes (Computer Perception Outlook 2030, What You Need To Know About LiDAR).

If a human can drive a car based on vision alone, why can’t a computer?

This is the core philosophy companies such as Tesla believe and practice with their self-driving vehicle initiatives. While we believe Tesla can develop autonomous cars that “resemble human driving” primarily driven by cameras, the goal is to create a system that far exceeds human capability. For that reason, we believe more data is better, and cars will need advanced computer perception technologies such as RADAR and LiDAR to achieve a level of driving far superior than humans. However, since cameras are the only sensor technology that can capture texture, color and contrast information, they will play a key role in reaching level 4 and 5 autonomy and in-turn represent a large market opportunity.

Mono vs Stereo Cameras. Today, OEMs are testing both mono and stereo cameras. Due to their low-price point and lower computational requirements, mono-cameras are currently the primary computer vision solution for advanced driver assistance systems (ADAS). Mono-cameras can do many things reasonably well, such as identifying lanes, pedestrians, traffic signs, and other vehicles in the path of the car, all with good accuracy. The monocular system is less reliable in calculating the 3D view of the world. While stereo cameras can receive the world in 3D and provide an element of depth perception due to dual-lenses, the use of stereo cameras in autonomous vehicles could face challenges because it’s computationally difficult to find correspondences between the two images. This is where LiDAR and RADAR have an edge over cameras, and will be used for depth perception applications and creating 3D models of the car’s surroundings.

Camera Applications. We anticipate Level 2/3 and Level 4/5 autonomous passenger cars will be equipped with 6 – 8 and 10 – 12 cameras, respectively; most will be mono-cameras. These cameras will play a prominent role in providing nearly 360-degree perception and performing applications such as lane departure detection, traffic signal recognition, and park assistance.

$19B Market Opportunity. Given cameras are the primary computer perception solution for advanced driver assistance systems (ADAS), the camera market is currently the largest computer perception segment and represented a $2.3B opportunity in 2017. While growing adoption of ADAS enabled cars will continue to act a near-term catalyst, adoption of fully autonomous vehicles (Level 4/5) equipped with 10+ units per car, will be the tailwind taking this market to $19B by 2030 (18% CAGR 2017 – 2030). As displayed in the chart below, the bulk of sales will be in the form of mono-camera systems. Note our forecast is driven by our 2040 Auto Outlook and only includes passenger vehicles. Fully autonomous heavy-duty trucks will also leverage similar computer vision technology, and when factoring these sales, the total camera market could be 1.5x- 2x larger.

Disclaimer: We actively write about the themes in which we invest: virtual reality, augmented reality, artificial intelligence, and robotics. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

When It Rains It Pours; Model S Recall

  • Tesla announced a recall this afternoon on 123,000 (built before April 2016) Model S sedans over a potential power steering issue.
  • Tesla has had other recalls. In 2017 the company recalled 53,000 Model S and Model Xs over a parking brake problem, and in 2015, 90,000 Model S sedans were recalled for a bad seat belt.
  • Assuming $500 (our guess) to repair each recalled Model S, suggests the cost of the recall to be just over $60m.
  • The bigger issue is erosion of brand which impacts demand for Tesla’s and investors’ willingness to keep funding the Tesla mission.
  • We believe the size of Tesla’s opportunity, defined as accelerating the world’s adoption of renewable energy, is so large they will continue to find investors willing to back the company.
  • Our patience is being tested, but we continue to expect Tesla to be a winner in EV and AV.

Tesla is testing our patience. Today’s recall is the third negative news story related to Tesla in the past week on top of the Model X crash and Moody’s credit downgrade. We’re bracing for a fourth negative data point early next week when the company reports production and delivery numbers for the Mar-18 quarter. We’re expecting around 1,500 Model 3s per week, below the company’s target of 2,500. When we heard the recall news tonight we asked ourselves, do we still believe in the story? The answer is yes. Our support is based on a view that the company is uniquely positioned to capitalize on a dramatic shift in auto (computer on wheels), innovate in both EV and autonomy, and usher in a new paradigm of manufacturing efficiencies.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Posted in Tesla  •