TSLA Earnings Primer

Here’s our Tesla earnings primer for tomorrow’s results. Find our TSLA model here.

High Level Thoughts. 

  • We believe the TSLA story has the most upside in large cap tech over the next 5 years.
  • The company released Sep-17 delivery numbers on Oct 2nd, below plan for Model 3. They reiterated their goal of exiting Dec-17 quarter producing 5k Model 3’s per week, and 10k at some point in 2018.
  • There is no cannibalization yet of Model X and S from Model 3. A second part of  the October announcement was strong demand for Model X and S, which is trending inline with Street expectations of ~100k Model S and X units for 2017.
  • One downside of Sep-17 results; production outlook chips away at investor confidence in the Model 3 ramp over the next year.
  • China is an emerging opportunity, with the government’s EV goals.

Model 3 Production. 

  • Tesla last updated Model 3 net reservations on Aug 2nd, when they stood at 455K.
  • For Dec-17 quarter, we’re expecting 5.6k Model 3 deliveries (Street at ~7k).
  • For 2018, we believe the Street expects Model 3 production of 150-175K vehicles.
  • While we believe Model 3 production will largely be a guessing game over the next few quarters, and will produce future disappointments, it’s important to note by now we believe Tesla has close to 475-500k net reservations for the Model 3, and we remain confident that Model 3’s value will stoke demand for the next several years.

Upcoming Questions:

  • How realistic is the Model 3 ramp?
  • Model S & X are not being cannibalized by Model 3 today. Do they expect that to change once Model 3 gets on the road?
  • Timing on profitability?
  • Timing on autonomy?
  • Will Tesla build a China factory given the relaxed China JV requirements?
  • Competition from Chinese brands will be an emerging topic with investors, given China’s goal for EV ultimately accounting for 11% of cars in 2019 and 12% in 2020.
  • In China, will some car OEMs have to buy credits from EV sellers like Tesla, if it builds a factory in China?

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  • 

Don’t Underestimate the Importance of 3D Mapping for Autonomy

As you drive down the road, you make countless subconscious micro-decisions and calculations built on past experience. You know what 40 mph feels like by observing how fast the trees are passing by, how hard you can hit the brakes to comfortably slow down at a traffic signal, and that you should coast down a steep hill to avoid speeding. Even if you are on an unfamiliar road, driving experience has built foundational expectations and awareness, so that you are not hurdling into the unknown waiting to react to situations that arise. In the case of autonomous vehicles, however, these decisions are made by software. Simply adding sensors like LiDAR and cameras to a vehicle allow it to perceive its surroundings, but, on their own, would fail to enable a safe ride. Enter 3D maps – a critical element of autonomy that is often overlooked.

Detailed, 3-dimensional, continuously updated maps are essential to true widespread adoption of self-driving cars. This is what separates a system that needs to be overseen by a human focused on the road, and one where you can fall asleep and wake up at your destination. While it is technically possible for a car to navigate an unfamiliar setting without a digital map, the information that 3D maps provide is critical to building the trust necessary for widespread adoption of autonomy. Maps effectively teach a self-driving vehicle the rules of the road. The car’s AI can learn the mechanics of driving like a human, but the map introduces things like bike and HOV lanes, speed limits, construction zones, train tracks, and pedestrian crosswalks. Maps also ease the burden on the car’s computers by giving them foresight and adding redundancy to its understanding of the situation it faces.

Civil Maps CEO, Sravan Puttagunta explains, “Radar and cameras cannot always recognize a stop sign if pedestrians are standing in the way or the sign has been knocked down. But if the map knows there is a stop sign ahead, and the sensors just need to confirm it, the load on the sensors and processor is much lower.”

Reducing the load on the car’s computing power must be considered, because a fully autonomous vehicle could produce as much as a gigabyte of data every second. By building an accurate and up-to-date, digital representation of the world around us, a car is able to process this data in conjunction with the data created by its sensors to create a safer, smoother, and more reliable driving experience. Maps allow a vehicle to see into the future – further than human drivers can see – anticipating instead of reacting to changes in their environment.

Maps allow a vehicle to see into the future – further than human drivers can see – anticipating instead of reacting to changes in their environment.

Maps are an important aspect of vehicle-to-vehicle (V2V) communication as well. Using maps as an extension of a car’s sensors requires a reliance on other cars for input information. This presents us with the consortium conundrum that we wrote about here. In the realm of V2V communication, where it does no good to ‘out-communicate’ the competition, we believe company collaboration would be beneficial, if not a requirement. Maps that are shared through a single cloud-based platform are updated frequently, adding exponentially to their utility. The minute details of roads are constantly changing – construction zones, fallen trees, or damaged roads are all things that must be mapped and updated to reflect current conditions. This can be accomplished using the cameras and sensors on each car including some element of automated Waze-like crowd sourcing from the vehicles, too. As a vehicle drives, its sensors are constantly comparing their inputs to the map. When a discrepancy is detected, it is corroborated by other vehicles and changed in the cloud, so every car in the network is up-to-date. Take, for example, the scenario pictured below.

Here, there are three layers of safety that come from V2V and mapping. As the black car drives by the wreck, it observes a discrepancy in its map and relays that message. The cars involved in the accident share their location and that their speed is zero, and the car blindly approaching the wreck knows to avoid its current lane and switches lanes accordingly. Sensors alone, which have limited range and therefore reaction time, would not have been able to detect and prevent a collision.

Navigation apps like Google Maps provide more than enough detail to find your way from A to B, but these maps are only able to locate your car within a margin of several meters – 3D maps must be accurate within centimeters. They must show the precise location of all street signs, lane markings, curbs, and even deep potholes that should be avoided. Moreover, if we want autonomous vehicles to be able to take us anywhere, we have to have detailed maps everywhere – and there are more than 4 million miles of roads in the U.S. How do we tackle such a monumental task? This question has provoked the attention and innovative efforts of a host of companies.

Lvl5, a startup from former Tesla and iRobot engineers, aims to crowdsource mapping data with their app called Payver. While not all cars are equipped with cameras, nearly all of their drivers carry smartphones with them. By mounting your phone aiming out the windshield, you can earn between 2 and 5 cents per mile depending on whether or not the road is common or uncharted. The process, which relies heavily on machine vision to stitch together and label every fragmented video, is a logical way to build maps early on, leveraging the user base of smartphones and the sizable number of people who drive for a living for a ridesharing, delivery, or freight service.

Waymo, who has a longer history of mapping tech and a large budget thanks to parent company Google, is taking the opposite approach. In its usual ‘do everything ourselves’ fashion, Waymo is building their maps by driving around in vehicles equipped with spinning LiDAR units. LiDAR provides a much more detailed image of its surroundings than a camera, but still requires substantial human input to label each object. Labeling things like traffic lights, street signs, and buildings is tedious, but is necessary so that a car can tell the difference between a tree and a yield sign. There is also promise of automation of this process by AI tech similar to Google Lens.

Here Mapping and Mobileye have combined many of their efforts around building, maintaining, and distributing maps to become the defacto leader in the space early on. Here, owned by a consortium of German automakers, (Audi, BMW, and Mercedes-Benz) has ambitions to build a digitized version of our world that can be interpreted by autonomous vehicles and other machines with what they call an open location platform. Here has built out their maps with LiDAR-equipped vehicles and will maintain them with an extensive network of cars outfitted with Mobileye hardware. Mobileye, purchased by Intel earlier this year for $15.3B, offers a range of services for self-driving cars like sensor fusion and camera tech, but has recently been focusing on mapping. The combined result will be a comprehensive 3D map that is aggregated in the cloud and maintained in near real-time by crowdsourcing data from a network of connected cars. The maps will be sold as a service that automakers with autonomous systems can subscribe to.

Tesla has a distinct advantage stemming from the sheer number of cars they have on the road equipped with the hardware necessary to build maps (cameras, RADAR, and ultrasonic sensors). 3D mapping presents a textbook network effect and Tesla, with thousands of vehicles already in play, is in a great position to take advantage of that market force. The question will be one of communication with other cars as more automakers begin to develop and test autonomous systems.

While the method of building sufficiently detailed maps varies, their importance in the self-driving equation is almost universally agreed upon. In contrast with lively debates over the correct combination of RADAR, LiDAR, and camera sensor arrays, or countless chipmakers jockeying to provide cars with computing power, mapping seem under-appreciated and underinvested. As Mobileye co-founder Amnon Shashua suggests, there are three core elements of self-driving cars – sensing the road, mapping the road, and negotiating your position on the road. 3D maps will be a key determinant of the long-term winners in autonomy.

Thanks to Will Thompson for his work on this note.

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.

Model 3 Production Miss Sounds Bad, but Doesn’t Change the Magnitude of Opportunity

The Tesla story may feel like a waiting game. Tonight, Tesla reported Q3 deliveries and production results for the Sept-17 quarter which fell short of expectations due to a 4.8k order push out for the Model X and S into Dec-17, as well as a manufacturing bottleneck for the Model 3. These results further validate our thesis that EV and autonomy will take longer than most think, but eventually will be more impactful than most can imagine. Our optimism around Tesla’s ability to capitalize on the shift to EV, autonomy, and renewable energy has not changed.

Link to model here.

The real problem is that tonight’s results chip away at investor Model 3 production confidence. Adjusting Street models from 1.1k units in Sep-17 down to the reported 220 Model 3 production is immaterial to the model. What is material is this production miss will fuel investor concerns about the slope of the Model 3 ramp. While we believe Model 3 production will largely be a guessing game over the next few quarters, and could produce future disappointments, it’s important to note Tesla has over 500k net reservations for the Model 3, and we remain confident that Model 3’s value will stoke demand for the next several years. We expect Model 3 to have a breakout year in 2019. (We are modeling 359k deliveries in 2019, up from 300k in 2018.)

Model Changes to Model 3:  For the Dec-17 quarter, we’re now expecting 5.6k Model 3 deliveries, compared to the Street which was 15.8k. For 2018, our new numbers expect 200k (reduced by 8%) Model 3 delivers, compared to the Street which was previously at ~280k.

Model Changes to Model X and S: A second part of tonight’s announcement was demand for Model X and S, which  is trending inline with Street expectations of ~100k Model S and X units for 2017.

When Will We See Profitability? Our time to profitability estimate is unchanged. We continue to expect Tesla to show its first profit in the Dec-19 quarter and be profitable in the full year 2020.

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  • 

Tesla Semi Truck Hauls Heavy Disruptive Potential

Tesla’s announcement of an electric semi-truck is a big deal – not only does it have the potential to disrupt one the nation’s largest industries, but it marks another leap forward in making Tesla’s grand vision a reality. That said, we caution that it will take years for the Tesla Semi to come to market.

Based on Tesla’s history, the most logical go-to-market approach would be staggered: Within about 3 years, Tesla could target short haul trucking (think of UPS or Fedex trucks that return to a depot to be charged at night). Then in about 5 years, Tesla could target long haul trucking, and, in 6-10 years, offer a fleet of trucks as a service. We expect the Oct 26th event will be short on details (we don’t expect details on pricing or  delivery date) and long on the opportunity. That opportunity is ripe for Tesla’s taking, considering legacy truck manufacturers’ past struggles with innovation.

In his 2016 memo, Master Plan, Part Deux, Musk elaborates on this vision (which we detail here) and explains Tesla’s ambition to “expand to cover the major forms of terrestrial transport.” This includes heavy-duty trucks and high passenger-density urban transport, among others. By electrifying more forms of transportation (roughly 30% of our energy consumption), Tesla would advance their vision of accelerating the world’s transition to sustainable energy. Although many of the details surrounding the truck have yet to surface, the implications are clear – and they are widespread.

The trucking industry is downright massive. Upending an industry with such deep roots that touches a sizable portion of our economic activity is not a simple or a swift process, but its core elements are ripe for today’s disruptive forces. Let’s put the industry into perspective:

  • Trucks move roughly 70% of the nation’s freight by weight, and 82% of it by value.
  • It takes 54.3 billion gallons of fuel to move this freight each year.
  • It employs 7.3 million people, 6% of the U.S. working population, or 1 in 17 workers.
  • Truck driver is the most common profession in 29 of 50 states.
  • As of 2016 there were 1.5 million trucking companies in the country, 97% of which operate fewer than 20 trucks.

sources: American Trucking Association, Trucker Path

All of this equates to a massive logistics operation that is optimized down to details like tire pressure. As former GM vice chairman, Bob Lutz says, “these are people that operate by spreadsheets,” and the cost savings attainable with electrification and autonomy are too large to ignore. Fuel and driver labor make up 65% of the per mile cost of moving goods on wheels, so discounts on both fronts could have a measurable effect even on the end cost of goods.

Can Tesla pull it off? With concerns mounting about Tesla meeting its existing demand with limited manufacturing volume, many criticize the company for overextending into distracting business lines like energy storage and semi-trucks. Remember that this has been on Tesla’s to-do list since the beginning, and that this vehicle will likely not be commercially available for several years, by which time their manufacturing output will be formidable. Not to mention, Musk says the semi will be made mostly from Model 3 parts.

Further, critics of electric trucking point to range as its number one shortcoming. However, almost a third of all trips made by semi-trucks are regional outings within 100 to 200 miles. In other words, Tesla’s truck doesn’t have to go very far to access a huge market. After working closely with the trucking industry during the design process, Musk said, “they already know that it’s going to meet their needs, because they’ve told us what those needs are. So it’ll really just be a question of scaling volume to make as many as we can.”

Don’t count Tesla out of true long-haul trucking, though. While a traditional truck can travel over 1,000 miles on a single tank of diesel, the combination of electric and autonomous trucking could change routes and infrastructure if it gains traction. Tesla has filed a patent for a battery swapping mechanism that could cut recharging time well under that of filling up 300 gallons of fuel. They have also expressed interest in platooning, where autonomous trucks are synced together drafting a lead vehicle which, in addition to being safer, can also improve range.

Electric offers better performance. Medium and heavy-duty trucks account for about a quarter of all greenhouse gas emissions in the transportation sector today. Electric rigs will not only cut down drastically on emissions, but power from the grid is also cheaper (not factoring in any of Tesla’s future goals concerning energy). Furthermore, electric trucks are far more powerful than their traditional diesel counterparts. This is due to the flat torque RPM curve delivered by an electric powertrain, which offers much quicker, smoother acceleration and eliminates the need for slow and cumbersome 10 or 12-speed transmissions used today. In a recent interview, Musk said, “if you had a tug of war competition, the Tesla semi will tug the diesel semi uphill.”

The larger, longer-term opportunity is autonomy. We have written at length in the past about self-driving cars for human transport, but autonomy will not stop there. Long-haul trips on straight interstate highways – this is the low-hanging fruit of autonomous vehicles. If Tesla succeeds in enabling these trucks to drive themselves, it is easy to imagine a future where other vehicles like busses, delivery trucks, or waste collectors operate autonomously, opening up a substantial market opportunity. Trucking routes and charger networks could transform as autonomous platoons move goods faster and cheaper than ever before. Thousands of small trucking companies with fixed routes could be replaced by fleets of on-demand autonomous semis. Removing the driver also increases safety as semi trucks, while only representing 1% of traffic are involved in over 10% of fatal accidents. With a semi truck several years away and fully autonomous trucking even further down the road, the concept may seem like a dream for Tesla – but we would urge caution in betting against Musk and Co. in turning those dreams into reality.

Special Thanks to Will Thompson for his work on this note.

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.

Tesla’s Building Blocks to Reengineering the Future

Tesla is not (just) an automaker. Nor is it (just) a battery, solar, or software company. Tesla is an agent of change. Its mission is to accelerate the transition to sustainable energy – and its story is about engineering a different future. Each move the company makes lends itself to a higher-order goal, and, as you zoom out, the picture becomes clearer.

It is fairly common knowledge that Tesla does more than make cars. Though the company has garnered a powerful media presence, primarily based on its work in the electric vehicle space, we think the bulk of this attention is misguided, focusing on too narrow a scope and too short a timeframe.

The Master Plan. In a 2006 blog post entitled The Secret Tesla Motors Master Plan (just between you and me), Elon Musk outlines most of this vision. In it he writes, “the overarching purpose of Tesla Motors (and the reason I am funding the company) is to help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy, which I believe to be the primary, but not exclusive, sustainable solution.” The master plan, which was actually written as a bulleted list in the 2006 post and extended ten years later in Master Plan, Part Deux, goes something like this:

  • First – build an indisputably excellent, fast, and expensive electric sports car to kill the existing stigma around EVs (Roadster & Model S).
  • Then – use that money to create an affordable, high-volume, EV that is fundamentally better than the average consumer car (Model 3).
  • In the meantime – while demonstrating the superiority of electric vehicles, provide zero emission power generation and storage options (solar & battery) to power those vehicles and all other activity.
  • Later – widespread implementation will only be possible at a reasonable cost to consumers, so operations must be vastly scaled up to apply economies of scale (Gigafactory).
  • Eventually – help power the globe with energy that is generated from renewables and stored in batteries for optimal deployment.

Musk concludes the first post by saying, “Don’t tell anyone.” And he’s only half kidding. At least early on, Tesla seems fine with investors and the public thinking they are an automaker. Musk knows that his ambitions to manufacture electric vehicles, develop autonomous driving software, double the world’s output of lithium-ion batteries, be the largest solar panel installer in the U.S., and modernize energy production, storage, and consumption, must be executed in steps, each building on the last.

The Silicon Valley approach. Tesla, like others in technology today (e.g., Amazon), is attacking non-tech sectors with a thoughtful, albeit unconventional, commercialization plan. If your goal was to accelerate the world’s transition to sustainable energy, you might get a degree in chemistry or electrical engineering, go on to study environmental engineering or law, assert yourself as an expert in the field, create an interest group, lobby congress, get approved to test a project; you get the picture. Tesla, however, figured that most efficient way to exact the greatest change is with a consumer-facing, product-focused approach. Maybe people would drive an electric car if it were faster, safer, and sleeker than the one they owned. Maybe people would put solar roofs on their homes if they looked great and were more durable than traditional materials. People are drawn to better products; not to intangible environmental and sustainability benefits.

“The future has already arrived – it’s just not evenly distributed.” – science fiction author William Gibson. This quote applies broadly to many themes within tech, but is particularly pertinent to Tesla’s situation today. Right now, using Tesla products, you are able to consume energy in an entirely sustainable manner. With a Solar Roof and Power Wall, you can generate and store enough energy to power your home and your Model S, effectively removing you from the grid and reducing your carbon footprint to zero. Further, Tesla Energy has embarked on a handful of projects around the world. Some of these include building the world’s largest battery storage facility in South Australia, powering the entire Samoan island of Ta’u with solar and batteries, relieving the grid during peak demand in California, and several others. Unfortunately, these solutions are few and far between, and the technology is not accessible to everyone because of the upfront cost. The uneven distribution, however, is largely an issue of manufacturing scale.

A word on scale. Scaling their operations is perhaps both Tesla’s largest hurdle and the single most important determinant of their success. Their goal is not to help the rich save on their energy bill or give them a fun car to drive. In a recent interview, CTO J.B. Straubel said, “we work incredibly hard every chance we can to reduce cost. Most of our effort is focused on how do we reduce cost so that we can grow volume and reach a broader customer base.” There is no agenda or desire to sell to wealthy customers only – it is a necessary step in the economics of scaling up operations. Scale is currently Tesla’s core focus. While the Nevada Gigafactory will effectively double the world’s output of lithium-ion battery cells, Musk has said he wants to build 10 or 20 of them, and that to power the globe, we would need 100 Gigafactories (begs the question if there is enough lithium in the world to supply 100 Gigafactories). Tesla has focused on creating “the machine that builds the machine,” and thinks of the factory as a product, carefully crafting and optimizing it like they would a Model S. We suspect that people will be shocked by Tesla’s manufacturing output ability in the coming years.

From paper to practice. The concept is simple on paper; we have, as Musk says, “this handy fusion reactor in the sky called the sun,” and enough of its energy hits the earth every hour to meet the world’s energy demands for an entire year (MIT Tech Review). So how can Tesla accelerate the process of capturing, storing, and utilizing this energy?

  • Grid-scale energy storage – in our current system there is virtually no storage, so power plants that feed the grid are constantly adjusting output to perfectly meet demand. In most cases they fire up extremely dirty and expensive “peaker plants” to meet peak demand each day. By adding batteries to the grid, which are essentially an infinitely scalable, plug-and-play technology, Tesla could smooth out production and deploy stored energy as needed. This idea has come to life in several locations, most notably in Mira Loma, CA, where Tesla has installed 396 Power Packs to assist the over-stressed grid in meeting peak demand each day.
  • Renewables + batteries – energy storage enables mass adoption of renewables of all kinds because it solves a core issue; there is a disconnect between when solar and wind power is generated and when it needs to be deployed. Batteries can be charged during the day when the sun is shining, then deploy energy at peak demand and throughout the night. Tesla is currently installing a battery storage facility tied to a wind farm in South Australia that, when finished, will be the world’s largest by a factor of 3.
  • Microgrids – whether it’s a single-family home, a rural community in Brazil, or an entire Pacific island, the combination of solar and battery storage offers the unique opportunity to create smaller, self-contained power networks and spread clean energy to new areas. Rural areas will be able to leapfrog traditional infrastructure, and urban areas can reduce the burden on the existing grid. Tesla has built a microgrid in American Samoa that powers the entire island of Ta’u, able to capture and store enough solar energy to meet demand even if the sun doesn’t shine for 3 days.

The faster Tesla reaches economies of scale in its existing businesses, the sooner we could see Tesla tackle these important issues, extend its operations to their fullest potential and, most importantly, further accelerate the transition to sustainable energy.

Special thanks to Will Thompson for his work on this note.

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  •