AI (Chatgpt and Grok) were asked for near term TESLA share price catalysts and gave a list below. It was a reasonable list. However, they missed important catalysts.
Q3 earnings report in October and market reactions to updates on autonomous robo-taxi progress and margins.
Broader rollout and monetization of Full Self-Driving (FSD).
Expansion into emerging markets like India (e.g., new showrooms) and investments in carbon credits [probably no impact].
Scaling of energy storage deployments.
Regulatory or tax credit developments in key markets [Little Impact].
AI Missed Specific Aspects of AI and Specifics of Car Production and Models
Release of FSD v14 in September
Rollout of unsupervised driving by year-end.
Strong Q4 delivery numbers from China
Introduction of a compact or stripped-down Model Y variant,
Cybercab (robo-taxi vehicle) production starting as early as December or Q1 2026
Tesla Semi truck mass production

Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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Any speculation on how Tesla transitions FSD from supervised to unsupervised?
There is the gradual continuous improvement of FSD driving performance with a several metrics. Then there is the binary status of either Supervised or Unsupervised that creates a dramatic difference in functionality and value. Unsupervised no matter how safe or competent still requires 100% of the time of a human driver, unsupervised that goes away and vehicles can travel without people in them or with people who can’t drive. Unsupervised Tesla has to assume all insurance liability and price FSD accordingly. For Robotaxi FSD there may well be a gradual transition with remote drivers because one remote human might monitor more than one vehicle.
How do you think Tesla will handle transition to Unsupervised FSD?
Probably not very controversial.
There will be some threshold metrics and once they are crossed, they deploy one unsupervised vehicle, probably without passengers. If that works for x days, they deploy another batch.
Such metrics can be as simple as : x days without intervention
LLMs only parrot what they have been trained on.
The have not been trained on future developments that hasn’t happened.
Brian doesn’t have that much competition surprisingly. Considering how important the topic is, there isn’t a lot of content to train AI models on for thinking about the future and technology development.
Who is Brian?