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Showing posts with label tesla. Show all posts
Showing posts with label tesla. Show all posts

Saturday, June 14, 2025

Tesla's Attempted Reinvention: Has The Train Left The Station?

How Elon Musk Is Reinventing Tesla’s Strategy CEO’s embrace of AI is a shift from days when company used off-the-shelf technology for electric car



Tesla is undergoing a fundamental transformation—from an electric vehicle manufacturer to a robotics and AI company. CEO Elon Musk is increasingly positioning Tesla as a leader in autonomous driving technology, driven by the belief that a fleet-wide neural network can enable fully driverless cars. Tesla aims to launch up to one million robotaxis by the end of 2026 and recently began limited public testing in Austin, Texas (wsj.com, wsj.com). 

Key highlights:

  • Strategic pivot: Tesla’s future is being anchored in robotics and AI, building on its acclaimed electric vehicle platform .

  • Robotaxi rollout: Musk has tentatively set June 22, 2025, as the start date for a pilot robotaxi service with 10–20 Model Y vehicles—software-upgraded, driverless on public roads in Austin (wsj.com).

  • Camera-based autonomy: In contrast to competitors like Waymo and Cruise that use lidar, Tesla relies solely on cameras and its proprietary AI, processing fleet data via its Dojo supercomputer (wsj.com).

  • Tech and valuation edge: Goldman Sachs praises Tesla’s scalable, cost-effective autonomy setup—claiming robotaxis could run at just $0.40 per mile—though they remain cautious on widespread deployment timelines (investopedia.com).

  • Commercial challenges: Tesla’s EV sales are softening, with lower Q1 2025 revenue and profit. The bold shift toward autonomy is seen as essential—but still fraught with safety, regulatory, and technological risk .

  • Competitive landscape: Tesla faces established players like Waymo, which already operates hundreds of robotaxis with strong safety credentials (nypost.com).

Bottom line: Tesla is doubling down on AI and robotics as its defining identity—transitioning from “electric car maker” to “robotics-first company.” Success hinges on executing a safe, reliable roll-out of driverless fleet vehicles by 2026. While the ambition remains massive, Tesla still needs to overcome significant hurdles in trust, regulation, and tech refinement.




Tesla's Fork in the Road: Visions, Realities, and the Race Tesla Can’t Afford to Lose

Tesla was once the undisputed pioneer of electric vehicles, riding a first-mover advantage that stunned the global auto industry into rethinking its future. But that dominance is being tested on multiple fronts—price, vision, competition, and execution. As Elon Musk increasingly leans into AI and robotics as Tesla’s identity, there’s a growing sense that the detour he took through Washington, D.C., and the FSD moonshot have cost the company something more valuable than capital: time.

Tesla's decision to open-source its early EV patents was seen as an altruistic move. And perhaps it was. But there was also a strategic undertone—create a dependence ecosystem that would eventually pull legacy automakers into Tesla’s Full Self-Driving (FSD) orbit. That bet hasn’t paid off. Other automakers—especially BYD—aren’t just resisting the pull; they’re surging ahead with their own platforms. BYD isn’t waiting in line for Tesla’s elusive autonomy package. In China, regulators even forced a name change: from “Full Self Driving” to the more honest “Advanced Assisted Driving.”

Tesla now faces price pressure that it can't dismiss with software updates or brand prestige. BYD is undercutting Tesla significantly and is only kept at bay in the U.S. due to geopolitical restrictions. That buffer won’t last forever. If Tesla is serious about competing globally, it must either meet the price challenge or offer capabilities that clearly justify the premium.

And that brings us to the bigger vision—robotaxis, humanoids, and Dojo-powered autonomy. These are ambitious and potentially trillion-dollar opportunities. But they are not today’s lifeline. Today’s battle is about affordable, scalable EVs. Humanoids are exciting, but they won’t save Tesla from losing the middle-class market. Most useful robots don’t walk on two legs. They sit in warehouses, factories, or hospitals and perform repetitive tasks with reliability—not flair. The edge Tesla seeks here will be hard-fought against Chinese manufacturers who already excel in robotics-driven production and supply chain dominance.

The missing piece is a credible, phased roadmap to FSD. Not just a vision. Not “two years away” forever. Think electric buses with driverless tech on pre-mapped, camera-assisted fixed routes. Think scalable autonomy where the environment helps the vehicle—not total, raw AI bravado. Tesla can lead here—if it gets practical.

Tesla doesn’t need to skip the car market to evolve. But it does need to stop pretending the old rules don’t apply. Price matters. Product timing matters. Execution matters. And right now, Tesla must win the EV war before it can lead the AI arms race. The vision may still be bold. But it must also be grounded.

The road to the future starts with keeping your wheels on the ground.




YC Is the New IBM — And That’s the Problem
Elon Musk's Leadership Mistakes At Tesla
Is Tesla Really a $25 Trillion Company Because of Optimus? A Deep Dive into Elon's Claim
Figure vs. Tesla: Who Is Ahead in Robotics and Humanoids?
Why Can't Tesla Match BYD Inside China On Prices?
Waymo, Tesla Robotaxi, Cost Per Mile, And Public Transit
Tesla Self Driving, BYD Assisted Driving
The Tesla Robotaxi Rollout
Self-Driving Showdown: Tesla vs BYD vs Waymo — Who’s Winning the Autonomy Race?
Just Like BYD Beat Tesla in EVs, Chinese Companies Are Poised to Win the Robot Race
Tesla's Chances Of Licensing Its Full Self-Driving Software
Why Has Tesla’s Full Self-Driving Had So Many False Starts?
What If the U.S. Let BYD In? Free Trade Meets the EV Disruptor
Why Tesla's Only Path to Survival Runs Through India
BYD, Tesla, And Self-Driving
Tesla: From EVs to AI-Powered Robotics

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Friday, June 06, 2025

Figure vs. Tesla: Who Is Ahead in Robotics and Humanoids?

 

Determining which company is "ahead" in robotics and humanoids, such as Figure or Tesla, and assessing the broader landscape, including China's role, requires examining multiple factors: technological advancements, deployment progress, funding, partnerships, and market strategies. Below, we will analyze Figure and Tesla, highlight leading companies in the space, and address China’s position and the potential for a "DeepSeek moment" in robotics.

Figure vs. Tesla: Who Is Ahead in Robotics and Humanoids?
Figure
  • Overview: Figure AI is a startup focused on developing general-purpose humanoid robots to support human activities, particularly in commercial and industrial settings, with a long-term vision for home use. Founded in 2022, it’s a relatively new player but has moved quickly.
  • Progress:
    • Product: Launched Figure 01 in 2023 (31 months after incorporation) and shipped Figure 02, a more advanced model, by early 2025. Figure 02 emphasizes advanced speech-to-speech reasoning (powered by embedded AI, possibly leveraging tech similar to ChatGPT) and dexterity for manipulating objects.
    • Commercial Traction: Signed a deal with BMW in late 2024 for automotive manufacturing applications, with pilot programs underway. Announced a second major commercial partner in early 2025, speculated to be a large U.S. retailer or tech firm, with a potential to ship 100,000 robots over four years.
    • Funding: Raised $854 million, with a Series B round valuing the company at $2.6 billion. Investors include heavyweights like Microsoft, OpenAI Startup Fund, NVIDIA, Bezos Expeditions, Intel Capital, and ARK Invest.
    • Strengths:
      • Rapid product rollout: From founding to shipping robots in under three years.
      • Focus on commercial applications (e.g., manufacturing, logistics) with a dual-market strategy (commercial and home).
      • Strong AI integration for perception, language understanding, and learned control, as seen in the Helix vision-language-action (VLA) model announced in 2025.
      • Partnerships with high-capacity customers drive cost reduction and AI data collection for iterative improvements.
    • Challenges:
      • Still in early stages, with limited widespread deployment.
      • Scaling to 100,000 units is ambitious and unproven, requiring robust supply chains and cost management.
Tesla
  • Overview: Tesla, led by Elon Musk, is developing the Optimus humanoid robot to handle repetitive, dangerous, or boring tasks, initially targeting Tesla’s Gigafactories and eventually broader markets. Announced in 2021, Optimus leverages Tesla’s expertise in AI, batteries, and manufacturing.
  • Progress:
    • Product: The latest Optimus Gen 2 model (showcased in 2023) features advanced bipedal locomotion, dexterous hands, and improved balance and full-body control. Tesla plans “limited production” in 2025, with initial testing in its factories.
    • Commercial Traction: Musk claims “several thousand” units will be built in 2025, with over 1,000 or a few thousand operational in Tesla facilities. Long-term, Musk predicts Optimus’s value could surpass all other Tesla products, potentially making it a $25 trillion company.
    • Technology: Powered by Tesla’s AI, including end-to-end neural networks from its self-driving efforts, and trained with synthetic data and significant Nvidia compute power.
    • Strengths:
      • Manufacturing prowess: Tesla’s experience in scaling electric vehicles (EVs) gives it an edge in production ramp-up, cost optimization, and supply chain management.
      • AI expertise: Leverages Tensor G3 chipset and self-driving tech for robot intelligence.
      • Ambitious vision: Musk’s goal is mass deployment, with cost estimates of $20,000 per unit if scaled effectively.
    • Challenges:
      • Delays: Musk’s timelines are often optimistic; production and deployment may lag.
      • Supply chain risks: China’s restrictions on rare earth magnets (noted in May 2025) could hinder Optimus development.
      • Competition: Faces stiff rivalry from both U.S. and Chinese firms, with cost and capability gaps to close.
Comparison and Analysis
  • Technology: Both companies are advancing humanoid capabilities, but Tesla may have an edge in AI due to its self-driving expertise and access to vast compute resources (e.g., Nvidia horsepower). Figure’s Helix VLA model, however, shows innovation in unifying perception, language, and action, potentially giving it an advantage in human-robot interaction.
  • Deployment: Figure is ahead in commercial partnerships, with BMW and a second major client, while Tesla’s focus is internal testing in 2025. Figure’s pilot programs suggest faster real-world application, though Tesla’s factory integration could scale quickly if successful.
  • Scaling: Tesla’s manufacturing expertise is a significant advantage—its ability to produce EVs at scale could translate to robotics. Figure, as a startup, faces greater challenges in production ramp-up but benefits from investor backing and a focused strategy.
  • Cost: Unitree’s G1 robot from China retails at $16,000, while Tesla’s Optimus is estimated at $20,000 (if scaled) and Figure’s costs are unclear but likely higher initially. Tesla’s reliance on cost-effective Chinese components could be disrupted by tariffs or restrictions.
  • Verdict: It’s a close race. Figure leads in commercial deployment and partnerships, with a rapid pace of innovation and strong funding. Tesla has superior manufacturing and AI foundations but faces delays and geopolitical supply chain risks. If Tesla executes its 2025 production goals, it could pull ahead; otherwise, Figure’s momentum in real-world applications gives it a slight edge as of June 2025.
Leading Companies in Robotics and Humanoids
The humanoid robotics space is crowded, with key players from the U.S., China, and beyond. Here are the leaders:
  1. Figure AI (U.S.)
    • Focus: General-purpose humanoids for commercial and home use.
    • Why Leading: Rapid product rollout, major partnerships (e.g., BMW), and $854 million in funding.
  2. Tesla (U.S.)
    • Focus: Optimus for repetitive, dangerous tasks in factories and beyond.
    • Why Leading: Manufacturing scale, AI expertise, and Musk’s ambitious vision.
  3. Agility Robotics (U.S.)
    • Focus: Bipedal robot Digit for logistics and human environments.
    • Why Leading: Advanced deployments (e.g., Spanx factory), pragmatic approach, and pilot readiness. Rated highly (0 to 1 scale) for maturity.
  4. Boston Dynamics (U.S.)
    • Focus: Atlas humanoid for R&D, with impressive locomotion and agility; testing in Hyundai facilities in 2025.
    • Why Leading: Decades of expertise, but focused on R&D rather than mass commercialization.
  5. Unitree Robotics (China)
    • Focus: G1 and H1 humanoids, affordable at $16,000 (G1) and dynamic (H1 hit 7.38 mph).
    • Why Leading: Cost advantage, viral demos (e.g., Lunar New Year dance), and consumer sales via JD.com.
  6. Fourier Intelligence (China)
    • Focus: GRx series for medical, rehab, and general-purpose bipedal robots.
    • Why Leading: GR-2 offers 53 degrees of freedom, open-source compatibility (e.g., MuJoCo, NVIDIA’s Isaac Lab).
  7. Zhiyuan Robotics (Agibot) (China)
    • Focus: High-performance bipedal robots, aiming for 1,000 units by end of 2024.
    • Why Leading: Rapid scaling and alignment with China’s industrial strategy.
  8. 1X (Norway)
    • Focus: Humanoids for human environments, with AI-driven adaptability.
    • Why Leading: Emerging player with innovative designs and growing attention.
  9. Apptronik (U.S.)
    • Focus: Humanoids for industrial and service applications.
    • Why Leading: Competitive but trailing in mass-market readiness compared to Tesla or Figure.
  10. MagicLab (China)
    • Focus: MagicBot, third-generation humanoid for industrial training.
    • Why Leading: Reinforces China’s push for widespread application.
Other Notable Players: Sanctuary AI (Canada) focuses on adaptive humanoids, while Nvidia (U.S.) powers robotics with Jetson Thor and foundational models, acting as an enabler rather than a direct competitor.
China’s Role in Robotics and Humanoids
  • Current Standing:
    • Advancements: China is a major player, with companies like Unitree, Fourier Intelligence, Zhiyuan Robotics (Agibot), and MagicLab pushing boundaries. Unitree’s G1 ($16,000) undercuts Tesla’s estimated $20,000 for Optimus, and China holds ~66% of global robotics patents, leading the U.S. (5,688 vs. 1,483 over five years).
    • Government Support: China’s Ministry of Industry and Information Technology (MIIT) set a 2023 goal to be the world’s top producer of cutting-edge humanoids by 2027, backed by $1.4 billion funds from Beijing and Shanghai (2024). State-backed training facilities in Shanghai enhance robot learning.
    • Supply Chain: China dominates downstream inputs (e.g., batteries, motors), making it the global manufacturing hub. Its robots are ~80% as capable as leaders but 30% cheaper, per estimates.
    • Deployment: BYD and Geely have deployed Unitree robots in factories, and 27 humanoids debuted at Beijing’s World Robot Conference in August 2024.
    • Edge: A “fast-follower, rapid scaling” strategy leverages manufacturing expertise, cost advantages, and government subsidies. Analysts (e.g., Morgan Stanley) note China’s progress rivals the U.S., echoing its EV success.
  • Is China Ahead?:
    • Not Yet Dominant: The U.S. leads in innovation (e.g., Tesla’s AI, Boston Dynamics’ locomotion), but China’s cost, scale, and patent lead narrow the gap. Some analysts (e.g., CNBC, March 2025) argue China is ahead in production and deployment, especially for affordable models.
    • Challenges: U.S. export controls on advanced chips and semiconductor equipment limit China’s access to cutting-edge tech, though firms like DeepSeek innovate around this with efficient algorithms.
    • Verdict: China is not “far ahead” but is closing the gap rapidly, excelling in cost, scale, and industrial integration, while the U.S. retains an edge in AI and high-end tech.
  • How Did This Happen?:
    • Industrial Base: China’s dominance in manufacturing (e.g., batteries, motors) and deep supply chains enable cost-effective robot production.
    • Policy Push: MIIT’s 2023 strategy, billions in subsidies, and training facilities fuel growth.
    • Innovation: Despite chip restrictions, firms like DeepSeek and Unitree optimize algorithms and use less advanced chips (e.g., Nvidia H800) effectively.
    • Market Demand: Labor shortages and a huge consumer base drive domestic adoption, mirroring China’s EV and solar panel success.
Will Robotics See Another DeepSeek Moment?
  • What Was the DeepSeek Moment?:
    • DeepSeek, a Chinese AI startup, shocked the tech world in January 2025 by developing an AI model (R1) for $5.6 million, rivaling U.S. models costing hundreds of millions. Using 2,000 Nvidia H800 chips and efficient algorithms, it challenged U.S. dominance, integrated into sectors like automotive and telecom, and fueled national pride.
    • Labeled “AI’s Sputnik moment” by Marc Andreessen, it highlighted China’s ability to innovate under constraints.
  • Could Robotics See a Similar Moment?:
    • Likelihood: Possible but not imminent. A “DeepSeek moment” in robotics would involve a Chinese firm delivering a breakthrough humanoid—highly capable, low-cost, and scalable—disrupting global markets. Current trends suggest potential:
      • Cost Innovation: Unitree’s G1 at $16,000 and Zhiyuan Robotics’ goal of mass production under $30,000 echo DeepSeek’s low-budget approach.
      • Scale: China’s manufacturing and government backing could enable rapid production, as seen with Agibot’s 1,000-unit target for 2024.
      • AI Integration: Advances in generative AI and neural networks (e.g., Nvidia’s models, China’s use of Isaac Sim for synthetic data) mirror DeepSeek’s algorithmic edge.
    • Challenges:
      • Complexity: Robotics requires hardware (sensors, actuators, batteries) and software (AI, control systems), harder to revolutionize than AI models alone.
      • Data: Unlike DeepSeek’s use of public data, robotics needs diverse, real-world datasets (sensory, motion, interaction), which are costly and complex to collect.
      • Geopolitics: U.S. tariffs (e.g., 145% on Chinese robots) and chip export controls could slow China’s leap.
    • Verdict: Robotics may not see a singular “DeepSeek moment” soon, but China’s trajectory—combining cost, scale, and AI—could lead to a gradual, disruptive shift. A breakthrough might emerge by 2027, aligning with MIIT’s goal, especially in industrial or service applications.
Conclusion
  • Figure vs. Tesla: Figure holds a slight edge as of June 2025 due to commercial partnerships (BMW, a second major client) and rapid progress, but Tesla’s manufacturing and AI strengths could overtake if production scales in 2025. Neither is definitively “ahead,” as both excel in different areas.
  • Leading Companies: Figure, Tesla, Agility Robotics, and Boston Dynamics lead in the U.S., while Unitree, Fourier Intelligence, Zhiyuan Robotics, and MagicLab drive China’s rise. Nvidia supports the ecosystem with tech like Jetson Thor.
  • China’s Position: Not far ahead, but closing the gap with cost advantages, scale, patents, and government support, building on its manufacturing and policy strengths.
  • DeepSeek Moment in Robotics: A dramatic breakthrough is possible but faces hardware and data hurdles. China’s rapid progress suggests a strong challenge to the U.S. within 3-5 years, especially in affordable, scalable humanoids.

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