Tesla Elon Musk: Latest Updates and Analysis
Elon Musk ‘cancels’ Tesla engineer for complaining about the CEO’s behavior
Elon Musk has reportedly ‘canceled’ a Tesla engineer for complaining about the CEO’s behaviors on social media.
As we lately reported, Tesla insiders are finally starting to speak out against Elon Musk over his increasingly unhinged social media presence.
For example, just today, he called CNN legal analyst Norm Eisen’s family a “crime family” because someone wrongly claimed that his daughter received millions of dollars from USAID when it was just someone with the same last name.
However, it looks like Musk and Tesla are actively suppressing employees speaking out.
Tesla has fired Jared Ottmann, a manager of battery thermal supplier industrialization engineering, over his complaints about Musk.
Ottmann, who has been at Tesla for 6 years, says that he has been raising concerns internally about Musk’s use of social media for the last 3 years, but he ramped up his effort last month after Musk’s salute at the Trump inauguration.
The engineer specifically took offense to a tweet that Musk posted in the aftermath of the inauguration. Instead of apologizing and saying that he didn’t mean to make a Nazi salute, Musk decided to attack the media for even suggesting that the gesture was a Sieg Heiland tweeted this:
This post by Tesla’s current CEO name drops genocidal assholes as a joke and has 308,000 likes.
The engineer says that he raised the issue with Tesla and while he gets “personally support”, he says the corporation remains silent about Musk’s behavior:
Starting in 2022 and especially the last week I’ve raised the issue internally multiple times, with managers, HR, legal compliance, investor relations. And while overwhelmingly people offer personal support, Tesla as a enterprise has remained silent.
Ottmann, who has been promoted 4 times in 6 years at Tesla, has now been let go.
For a guy who calls himself a “free speech absolutist” and “anti-cancel culture”, he canceled this engineer pretty quickly when he didn’t like how he was exercising his free speech.
This is obviously an attempt at scaring other Tesla employees from speaking out at Tesla.
It’s one of my main concerns about the automaker: it’s not a meritocracy that attracts top engineering talent anymore. One of the main criteria to work at Tesla now is to support its CEO, who is off the deep end.
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Tesla applies for ride-hailing service in California, but with human drivers
Tesla has applied for a permit to operate a ride-hailing service in California, but it will be using human drivers rather than the promised robotaxi.
Last year, Tesla CEO Elon Musk claimed that Tesla would launch “unsupervised self-driving in Texas and California in Q2 2025.”.
However, we suspected that this would not be “unsupervised self-driving’ in customer vehicles like Tesla has been promising since 2016, but an internal fleet with teleoperation support in a geo-fenced area for ride-hailing services, much like Waymo has been doing for years.
Sure enough, Musk confirmed last month that this was the plan for Austin in June. We describe this as a “moving of the goal post” for Tesla.
With the focus on Austin in June, Tesla stopped talking about California, which was unveiled to happen at the same time as Texas last year.
Now, Tesla has applied for a ride-hailing permit in California:
The electric vehicle manufacturer applied late last year for what’s known as a transportation charter-party carrier permit from the California Public Utilities Commission, . That classification means Tesla would own and control the fleet of vehicles.
But this application is for a regular ride-hailing service, like Uber, albeit for an internal fleet rather than vehicles operated by clients.
Tesla has yet to apply for a permit to operate driverless vehicles:
In its communications with California officials, Tesla discussed driver’s license information and drug-testing coordination, suggesting the business intends to use human drivers, at least initially. Tesla is applying for the same type of permit used by Waymo, Alphabet Inc.’s robotaxi business. While Tesla has approval to test autonomous vehicles with a safety driver in California, it doesn’t have, nor has applied for, a driverless testing or deployment permit from the state’s Department of Motor Vehicles, .
Musk claimed that he believes Tesla will be able to achieve “unsupervised self-driving” in California by “the end of the year”, but he has claimed that every year for the past decade.
The latest available data presents that Tesla’s Full Self-Driving system is achieving about 500 miles between critical disengagement. Tesla has stated that it believes it needs to reach 700,000 miles between critical disengagement to be safer than humans.
This is just a step for Tesla to test ride-hailing services ahead of autonomy. A nothing burger, really, since ride-hailing has obviously been solved already by several companies, Lyft, Uber, Didi, etc.
What needs to be solved is autonomous driving.
As I have been saying for the last year, I am sure Tesla will be able to launch an internal fleet with teleoperation support in a geo-fenced area for a ride-hailing service in California later this year like it plans to do in Austin in June, but that’s nowhere near what Tesla promised since 2016.
It’s a moving of the goal post, and it’s basically just proving that Tesla is able to do something similar to Waymo – 5 years later.
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Tesla can already deliver new Model Y orders within 2 weeks in China – demand problem?
Tesla says it can deliver new orders for the refreshed Model Y within two weeks in China. Is the automaker already experiencing a demand problem with the new Model Y?
Last month, Tesla launched the new Model Y in China. The vehicle functions an updated design and new functions that bring it closer to the lately refreshed Model 3.
Tesla has now started delivering the Long Range AWD updated Model Y in China this week.
But along with the start of deliveries, Tesla also opened orders for the non-Launch edition and the Standard Range RWD:
There were rumors coming from China that Tesla managed to get hundreds of thousands of orders for the new Model Y, which is not impossible since it would be just a few months of production for the best-selling EVs, but now Tesla’s updated configurator raised questions about these rumors.
Tesla says it can deliver a new Model Y RWD order placed today in “2 to 4 weeks” in China.
The Long Range AWD Model Y takes a bit longer at “6-10 weeks” for new orders.
Based on insurance data, Tesla’s deliveries in 2025 are currently down about 7,000 units compared to the same period last year.
There’s no doubt that the Model Y changeover is going to hurt Tesla in Q1. The question is, by how much?
I am surprised to see that you can place an order right now and get on in just 2-4 weeks. It does point to soft demand for the RWD version, at least.
It’s going to be interesting to track deliveries through March. Tesla will need to deliver over 50,000 vehicles next month to arrive at similar levels as it did last year.
It looks like the production ramp is going well, so demand might be the bigger factor.
As for the Model 3, Tesla is already pulling all the demand levers in order for the sedan to contribute, but everything points to the new Model Y being the different maker.
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Market Impact Analysis
Market Growth Trend
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| 8.3% | 10.0% | 10.5% | 11.6% | 12.3% | 12.7% | 12.8% |
Quarterly Growth Rate
| Q1 2024 | Q2 2024 | Q3 2024 | Q4 2024 |
|---|---|---|---|
| 10.9% | 11.7% | 12.4% | 12.8% |
Market Segments and Growth Drivers
| Segment | Market Share | Growth Rate |
|---|---|---|
| Connected Cars | 35% | 14.2% |
| Autonomous Driving | 22% | 18.5% |
| EV Technology | 28% | 21.9% |
| Telematics | 10% | 9.7% |
| Other Automotive Tech | 5% | 6.3% |
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity:
Competitive Landscape Analysis
| Company | Market Share |
|---|---|
| Tesla | 16.9% |
| Waymo | 12.3% |
| NVIDIA DRIVE | 10.7% |
| Bosch | 9.5% |
| Continental | 7.8% |
Future Outlook and Predictions
The Tesla Elon Musk landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:
Year-by-Year Technology Evolution
Based on current trajectory and expert analyses, we can project the following development timeline:
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:
Innovation Trigger
- Generative AI for specialized domains
- Blockchain for supply chain verification
Peak of Inflated Expectations
- Digital twins for business processes
- Quantum-resistant cryptography
Trough of Disillusionment
- Consumer AR/VR applications
- General-purpose blockchain
Slope of Enlightenment
- AI-driven analytics
- Edge computing
Plateau of Productivity
- Cloud infrastructure
- Mobile applications
Technology Evolution Timeline
- Technology adoption accelerating across industries
- digital transformation initiatives becoming mainstream
- Significant transformation of business processes through advanced technologies
- new digital business models emerging
- Fundamental shifts in how technology integrates with business and society
- emergence of new technology paradigms
Expert Perspectives
Leading experts in the automotive tech sector provide diverse perspectives on how the landscape will evolve over the coming years:
"Technology transformation will continue to accelerate, creating both challenges and opportunities."
— Industry Expert
"Organizations must balance innovation with practical implementation to achieve meaningful results."
— Technology Analyst
"The most successful adopters will focus on business outcomes rather than technology for its own sake."
— Research Director
Areas of Expert Consensus
- Acceleration of Innovation: The pace of technological evolution will continue to increase
- Practical Integration: Focus will shift from proof-of-concept to operational deployment
- Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
- Regulatory Influence: Regulatory frameworks will increasingly shape technology development
Short-Term Outlook (1-2 Years)
In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing automotive tech challenges:
- Technology adoption accelerating across industries
- digital transformation initiatives becoming mainstream
These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.
Mid-Term Outlook (3-5 Years)
As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:
- Significant transformation of business processes through advanced technologies
- new digital business models emerging
This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.
Long-Term Outlook (5+ Years)
Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:
- Fundamental shifts in how technology integrates with business and society
- emergence of new technology paradigms
These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.
Key Risk Factors and Uncertainties
Several critical factors could significantly impact the trajectory of automotive tech evolution:
Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.
Alternative Future Scenarios
The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:
Optimistic Scenario
Rapid adoption of advanced technologies with significant business impact
Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.
Probability: 25-30%
Base Case Scenario
Measured implementation with incremental improvements
Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.
Probability: 50-60%
Conservative Scenario
Technical and organizational barriers limiting effective adoption
Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.
Probability: 15-20%
Scenario Comparison Matrix
| Factor | Optimistic | Base Case | Conservative |
|---|---|---|---|
| Implementation Timeline | Accelerated | Steady | Delayed |
| Market Adoption | Widespread | Selective | Limited |
| Technology Evolution | Rapid | Progressive | Incremental |
| Regulatory Environment | Supportive | Balanced | Restrictive |
| Business Impact | Transformative | Significant | Modest |
Transformational Impact
Technology becoming increasingly embedded in all aspects of business operations. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.
The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.
Implementation Challenges
Technical complexity and organizational readiness remain key challenges. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.
Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.
Key Innovations to Watch
Artificial intelligence, distributed systems, and automation technologies leading innovation. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.
Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.
Technical Glossary
Key technical terms and definitions to help understand the technologies discussed in this article.
Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.
autonomous driving intermediate
electric vehicle intermediate
platform intermediate
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