Tesla’s (TSLA) Artificial Intelligence (AI) day is fast approaching. And while CEO Elon Musk insists the date will be focused on recruiting “the best talent” to boost its machine-learning capabilities, investors hope it will bring much more than that – if not during the event, then in coming months.
“There could be an announcement on how they plan to use AI to improve autonomous or full self driving (FSD),” said Jane Edmondson, who runs ETF consultancy and index provider EQM Indexes, adding that Wall Street is anxiously awaiting such feedback to help prove the electric vehicle (EV) maker’s FSD software is safe. “A lot of people don’t necessarily feel confident handing over the wheel to a computer but if there is more AI integration that’s better than human intelligence, then you can make the argument that [autonomous driving] it’s safe.”
Edmondson expects the event (slated for August 19) will go beyond receiving applications from engineering and computer-science geeks and include presentations on how Tesla plans to lead the fast-growing, $62.3 billion AI industry, at least when it comes to sustainable transport and energy.
“Last year, during their Battery Day, they had a presentation on their plan to be self-sufficient with their lithium sourcing; that was the big takeaway,” Edmondson said, adding that AI Day will likely feature similar insights for FSD.
Analysts expect Tesla’s AI boss Andrej Karpathy to host the occasion – or at least make an appearance – and talk about the latest developments and how new talent can help hasten the rollout of real-world AI applications.
Regarding Robotaxis, which Tesla is widely expected to launch (though Musk has been mostly quiet about when and how), investors are eager to hear something new about how it will take on rivals such as Argos AI or Waymo to launch autonomous ride-hailing services. In that vein, Edmondson hopes Musk will provide guidance about plans to launch autonomous trucks and/or buses, which she sees as a “very logical use for self-driving.”
“Being a bus driver is not a great job, so autonomous buses are a good way to implement this technology, as well as for long-distance trucking,” she noted.
Other analysts said “green lithium,” or lithium extracted through environmentally-friendly mining, may also be on the agenda as the EV pioneer looks for alternative ways to power its batteries beyond polluting metals such as cobalt or nickel.
During Battery Day last September, Musk said the company had secured rights to 10,000 acres in Nevada to churn out lithium from clay deposits using a proprietary method to make it ecological, potentially becoming the world’s first to use such a method.
“There could be some announcements on green lithium mining,” said one expert requesting anonymity. “They want to increase lithium-ion cell production as well as iron to get rid of polluting nickel and cobalt.”
Machine learning is also being employed to streamline manufacturing at Tesla’s factories around the world, which use giant robots to assemble vehicles at ever-rising speeds. Guidance on how machine learning will boost that process would also be welcome.
“AI can tell you where metals and other components are being sourced,” added Edmondson. “It can be very powerful in managing the supply chain, especially now that manufacturers are facing chip shortages.”
David Barse, CEO of investment firm Xout Capital, hopes Tesla will provide information about how it will use its big data to accelerate FSD growth and bolster revenues. He said, “Tesla has access to real-time data from every driver in its cars. This data gives them a big advantage over most other manufacturers that have to manually test their cars. What are they doing with this data? How are they going to combine it with AI to improve performance?”
The ability to instantly merge big data [such as vehicle performance] with AI algorithms and provide over-the-air (OTA) updates to elevate the customer experience is the holy grail of Tesla’s competitive edge over traditional rivals, said Bryan Reimer, a transport and logistics researcher at MIT.
However, he noted Tesla is lacking innovation when it comes to FSD safety, which must be drastically improved though better monitoring devices such as in-vehicle cameras. While the firm recently deployed such devices in some models, critics say they are not effective enough to avoid accidents and that Tesla should deploy in-car driver monitoring systems to ensure eyes stay on the road.
“Driver attention is critical,” Reimer said, adding he'd like to see new updates from Tesla in this regard. “Driver monitoring cameras and much more robust monitoring systems are needed to ensure attentiveness to the road.” GM’s Super Cruise system is leading the industry in this regard and many rivals are rushing to emulate it, according to Reimer.
Ultimately, however, everyone agrees that Tesla’s ability to build FSD vehicles at scale will be the next catalyst for its stock to move higher, potentially reaching $1,000 target this year or even $3,000 by 2025, as star investor Cathie Wood has forecast.
Tesla needs to get to the point where “it’s okay to get in your car and push a destination button and just close your eyes,” said Barse, adding that a cultural shift will also be needed for that world to materialize. “The younger generation will be okay with it but for people who have been driving cars for years, it will be difficult.”
For now, Musk is working hard to ensure FSD becomes a near-term reality, releasing the latest update of its beta FSD V9.1 software over the weekend with drivers tweeting about how it’s “so good” and much better than the previous, 8.2 version.
Getting FSD right is “an insanely hard problem…,” the billionaire entrepreneur, who has a double physics and economics degree, told Twitter followers last Thursday, just before Tesla’s shares began a gradual ascent that saw them gain 4% to close at $714 on Monday. “Self-driving requires solving a major part of real-world AI but Tesla is getting it done. AI Day will be great,” he concluded.
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