According to Sawyer Merritt, Elon Musk said AI could drive 90% of distance within 10 years and detailed Tesla’s unsupervised robotaxi rollout.

According to SawyerMerritt, Elon Musk discussed Tesla’s unsupervised robotaxi rollout, Starship V3, and Neuralink at Israel’s Smart Mobility Summit.

According to Sawyer Merritt, Uber criticized Waymo’s robotaxi scale-up and tech strategy, signaling partner strain and diverging AV go-to-market models.

According to FoxNewsAI, a robotaxi left an airport with a passenger’s suitcase, raising autonomy safety and handoff procedure concerns, per Fox News.

According to The Rundown AI, Figure showcases bed-making robots, Korea taps Boston Dynamics, Uber partner faces crashes, and Rocket Lab buys a Mars arm.

According to Sawyer Merritt, Piper Sandler’s Alex Potter says at $400 TSLA, investors get Optimus for free and FSD and robotaxi metrics now matter most.

According to SawyerMerritt, Tesla's Unsupervised Model Y robotaxi fleet totals 29 across Austin, Houston, and Dallas, per RtaxiTracker data.

According to SawyerMerritt, Tesla added unsupervised Model Y robotaxis in Dallas and Houston, signaling wider pilot expansion and autonomy validation.

According to SawyerMerritt, California will ticket robotaxis for traffic violations from July 1, 2026, raising compliance and liability stakes for AV firms.

According to TheRundownAI, humanoids load airport bags, SoftBank launches a $100B robotics firm, China halts robotaxi permits, and Harvard advances swarm bots.

According to Sawyer Merritt, China paused new robotaxi licenses after Baidu Apollo Go cars stalled in Wuhan, stranding riders and blocking traffic.

According to Sawyer Merritt, Tesla is expanding FSD V14.3.2 to more owners, signaling broader access and feature stability.

According to Sawyer Merritt on X, Tesla published a new factory video showing Cybercabs without steering wheels leaving the production line and autonomously driving themselves to the outbound lot, indicating a production-intent robotaxi form factor and in-plant self-driving workflow. As reported by Sawyer Merritt, the footage suggests Tesla is validating end-of-line autonomous driving for logistics, a key step for commercial robotaxi readiness and safety validation pipelines. According to the X post, the vehicles operate hands-free on factory grounds, signaling progress toward a purpose-built autonomy stack integrated with manufacturing and fleet operations. For AI vendors and mobility platforms, this highlights opportunities in perception model optimization for low-speed industrial domains, high-reliability vision-only stacks, and fleet orchestration systems aligned to autonomous yard movements, as reported by Sawyer Merritt.

According to Sawyer Merritt on X and Tesla’s 10-Q, Tesla reported 456,000 active monthly Full Self-Driving subscribers generating over $45 million in recurring revenue per month, signaling accelerating software margins and subscription scale (according to Sawyer Merritt; as reported in Tesla’s 10-Q). According to Sawyer Merritt, Tesla’s fleet now averages 28.8 million FSD miles per day, up 100% in three months, expanding real-world reinforcement data for model training and enhancing long-tail autonomy performance. As reported by Sawyer Merritt, Tesla will nearly double GPU training capacity in Q2 2026, indicating a major ramp in AI training infrastructure for end-to-end autonomy and video foundation models. According to Tesla’s 10-Q cited by Sawyer Merritt, Tesla entered an agreement to acquire an AI hardware company for up to $2 billion, with about $1.8 billion contingent on service and performance milestones, highlighting a strategic push into vertically integrated AI hardware. According to Sawyer Merritt, FSD v15 will run on AI4 and the Cybercab will not be capped by the 2,500 autonomous vehicle annual limit, suggesting broader commercial robotaxi deployment potential pending regulatory approval. As reported by Sawyer Merritt, Tesla will raise Model Y output at Giga Berlin by 20% from July and hire 1,000 staff, while ending Q1 with the highest first-quarter order backlog in over two years—supporting near-term delivery growth that can fund AI investment.

According to Sawyer Merritt on X, Tesla updated its Full Self-Driving (FSD) miles tracker to reflect a larger fleet and higher utilization, reporting an average of 28.8 million FSD miles per day, up from 14.4 million a few months ago, equivalent to roughly 1,000 miles every 3 seconds. As reported by Sawyer Merritt, this doubling of daily FSD miles materially expands Tesla’s real‑world driving dataset, which is critical for training end‑to‑end neural networks and improving long‑tail reliability. According to the same source, the scale-up indicates stronger user engagement with FSD, creating opportunities for faster model iteration, regional feature rollout, and potential progress toward supervised autonomy services that could precede broader robotaxi deployment.

According to Sawyer Merritt on X, Tesla has begun rolling out FSD v14.3.2 to early access users, and the release notes state Tesla has unified the driving model across Actually Smart Summon, FSD, and Robotaxi to enable more capable and reliable behavior. As reported by Sawyer Merritt, this model convergence suggests a single end to end network spanning low speed parking maneuvers through on road autonomy and future ride hailing operations, which can streamline training data reuse and inference optimization. According to the same source, a unified stack could reduce edge case fragmentation, speed iteration cycles, and lower per mile inference costs—key advantages for scaling a Robotaxi service and improving Smart Summon consistency in complex parking lots. For developers and fleet operators, this indicates potential API and telemetry harmonization, simplified validation, and improved transfer learning efficiency that could translate into faster feature deployment and broader geographic rollouts.

According to Sawyer Merritt on X, Tesla’s Q1 report beat expectations on revenue, EPS, gross margin, free cash flow, and net income, while posting record new Full Self-Driving (FSD) subscriptions and confirming that its next-gen AI training stack, Cortex 2, is already training; Optimus factory construction has begun at Giga Texas and Cybercab production has started (as reported by Sawyer Merritt, citing Tesla’s Q1 disclosures). From an AI-industry perspective, these updates signal accelerated end-to-end autonomy development and vertical integration: record FSD subscriptions validate product-market fit for subscription-based autonomy, expanding high-margin recurring revenue; Cortex 2 training implies larger, more efficient perception and planning models for supervised autonomy, potentially reducing edge-case intervention; Optimus factory progress indicates scaling humanoid robotics with on-device inference; and Cybercab production suggests a path toward robotaxi services leveraging Tesla’s in-house datasets, Dojo-class compute, and fleet learning (according to Sawyer Merritt and Tesla’s Q1 materials). For businesses, the near-term opportunities include AI data pipeline tooling, simulation and evaluation frameworks for autonomy, and component ecosystems for edge inference in robotics; enterprise partners may benefit from integration with Tesla’s mapping, telematics, and charging networks if Tesla opens APIs or partnerships, while investors should watch FSD take rates, AI training efficiency metrics, and unit economics of autonomy services as leading indicators (as reported by Sawyer Merritt referencing Tesla’s Q1 update).

According to Sawyer Merritt, Tesla says they continue to make progress on Full Self-Driving (FSD) approval in China. As reported by Sawyer Merritt on X, the update signals ongoing engagement with Chinese regulators on autonomous driving permissions and data compliance. According to prior reporting from Reuters and China’s MIIT disclosures, foreign autonomous features must meet on‑vehicle data localization, high‑precision mapping, and safety validation requirements, indicating Tesla’s pathway likely involves partnerships for mapping and adherence to China’s data security law. For businesses, this could unlock new revenue via FSD subscriptions and robotaxi pilots in key cities once approvals are granted, as reported by Reuters’ earlier coverage of China’s draft rules for intelligent connected vehicles. The near-term implication is a phased rollout focused on urban pilot zones and over-the-air updates tailored to local regulations, according to industry analyses cited by Chinese regulatory briefings.

According to Sawyer Merritt on Twitter, Tesla reported that paid Robotaxi miles nearly doubled sequentially in Q1 and outlined plans for Cybercab to replace the existing Model Y fleet over time, becoming the largest-volume vehicle in the fleet (as reported by Sawyer Merritt citing Tesla). According to Tesla’s statement shared by Merritt, the company expanded its unsupervised operation area in Austin and launched unsupervised rides in Dallas and Houston in April, while advancing testing and permitting to quickly open additional major U.S. metros. For the AI industry, this signals accelerating real-world deployment of Tesla’s end-to-end autonomy stack and data engine, creating opportunities in fleet-scale inference optimization, safety validation tooling, city-level operations orchestration, and mobility-as-a-service unit economics, according to the same source.

According to Sawyer Merritt on X, Tesla’s unsupervised Model Y robotaxi was observed operating in rainy conditions, supported by a user video credited to @RonitL14; as reported by Merritt’s post, the footage suggests Tesla’s Full Self-Driving stack is handling low-visibility and reduced-traction scenarios without human supervision. According to Merritt’s X post, the rain test highlights perception robustness across cameras and occupancy networks that are critical for robotaxi reliability, and signals iterative progress toward Tesla’s planned robotaxi launch timeline. As reported by the public X post, this real-world rainy-weather operation implies potential improvements in sensor fusion, planning, and control under adverse weather, which are essential for regulatory validation and commercial fleet uptime. According to the cited X source, if sustained across cities and weather, fleet economics could improve via higher utilization rates and lower disengagements, creating business opportunities in autonomous ride-hailing, logistics, and nighttime operations.