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Tesla’s 2020 Aftermath: A look at the shorts who said 500k was ‘absurd’
Tesla’s 2020 showing has created an aftermath of reflection from bulls and bears alike. Despite the company coming off of a record year with a massive 500,000 vehicle delivery and production rate, which was considered “absurd” by some short-sellers in years past, Tesla proved the doubters wrong once again.
Everyone knows that the stock market is really an unpredictable and unfathomably tough thing to read. Some of the world’s best analysts can misread even the slightest bit of data and be miles off of what a particular stock accomplishes. Tesla, which is one of the more polarizing stocks despite its 700% climb in 2020, has had doubters since day 1. The difference between doubters of Tesla and doubters of other companies is that Tesla shorts and bears are some of the most vocal on Wall Street because the company’s momentum and hype have been talked about for nearly a decade.
2020 was easily the toughest year for the U.S. automotive market since the Great Recession of 2008. Tesla was one of the few companies that accomplished the feat of sustaining growth through the year of the COVID-19 pandemic, which crippled many industries, not just the automotive one, for most of the year. However, doubts on Tesla set in way back when the company started in 2008. Six years after Tesla built the original Roadster, analysts were still curious about the automaker’s capabilities moving forward and doubted that it would be able to scale its production to half-a-million cars by 2020. The old saying goes, “hindsight is 2020,” and as Tesla reached its goal for the year, it is easy to sit back and judge those who were wrong. However, their reasoning for not reaching 500,000 vehicles was completely flawed, and everything Tesla said it would do years ago has been accomplished.
Mark Spiegel called 500,000 cars in 2020 “absurd”
Mark Spiegel is a notable Tesla short-seller and has been bearish on the automaker’s stock for years. In 2014, Spiegel posted an article to Seeking Alpha, titled, “Why Projections For Tesla To Sell 500,000 Cars In 2020 Are Absurd.”
Spiegel used data like the compound annual growth rate to support his evidence, stating, “If Tesla sells 35,000 cars this year, 500,000 sales in 2020 would imply a six-year CAGR of 56%.” Additionally, Spiegel did not believe that Tesla could scale growth at that rate in six years because “no complex product manufacturer has ever grown that quickly from a revenue base of $3 billion or more.” But hey, there is a first time for everything.
Microsoft was able to scale its CAGR by 32.1% from 1993 to 1999, which is a six-year time span and was identical to Tesla’s outlook that was challenged in the 2014 article. While Microsoft managed a remarkable 32.1% CAGR because of the evergrowing popularity of the computer and other technology, Tesla’s overwhelming growth throughout the same timespan was due to tech developments, industry influence, proving affordability of electric cars, and a consistent growth rate that proved the company was here to stay.
Spiegel’s outlook for 2020 was 186,000 cars sold by Tesla, but the company managed to nearly accomplish this figure in Q4 alone, as it delivered 180,570 cars in the final three months of the year. Spiegel was way off in his predictions, and Tesla’s domination in 2020 was just one of many examples of analysts getting it completely wrong.
Tesla wasn’t a prime candidate for scaling its products, according to Thomas Bartman
In an April 2015 article in the Harvard Business Review, Thomas Bartman wrote an opinionated piece called, “Why Tesla Won’t Be Able to Scale.” Bartman claimed that Tesla’s EVs were “not actually disruptive, which will likely cause it to struggle to scale.” Bartman didn’t have the Model 3 to use as a benchmark at the time, but he doubted that Tesla would be able to sell a vehicle for $35,000, which it did.
“Tesla plans to launch a ‘mainstream’ luxury car, the Model 3,” Bartman wrote, “which it estimates will cost $35,000, although analysts have begun to question the feasibility of reaching that price point.” Tesla did discontinue this variant in late 2020, but the Standard Range Model 3 was available for over three years. The Standard Range+ was only $2,770 more and was more popular because of the range. Also, the SR was not listed on Tesla’s website and had to be ordered in a showroom or over the phone.
Bartman believed that Tesla had launched two good vehicles in the Model S and Model X, but legacy auto would quickly catch up after a few years. However, this has been proven wrong repeatedly, as companies like Mercedes-Benz and Audi have failed to launch effective and competitive EVs that are comparable to Tesla’s models globally. The Model 3 continues to dominate in China and the U.S., and the Model Y is gaining plenty of momentum as it nears the one-year mark since its first deliveries.
Tesla China Model Y attracts flocks of customers in local showrooms
“As Tesla attempts to scale, it’s likely to discover that its internal impediments, combined with competitor responses, make it much harder than anticipated,” Bartman said. “The symptoms of these problems will manifest as product launch delays, cost overruns, and higher than expected prices.”
The only issue is that Tesla was able to internally combat production issues, even though Elon Musk has admitted many times that Model 3 manufacturing was “production hell.” The company has effectively beaten all of its competitors to launching an effective and cost-worthy electric car by launching four of them.
Hindsight is 2020
With 2020 over (thank God), Tesla and analysts are already looking forward to the new year. 2021 has plenty in store for Tesla: Two production facilities in the U.S. and Europe are set to begin manufacturing efforts, the launch of the Cybertruck at the tail-end of the year, and a possible refresh of the Model S and Model X. Moving forward, Tesla shorts may be more cautious, especially considering their traumatic $38 billion loss this year.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
