According to SawyerMerritt, Tesla FSD v14.3.7 is rolling out to customer cars with unchanged release notes, signaling iterative safety and performance updates.

According to @SawyerMerritt, Tesla is testing unreleased FSD V14.3.7 on a Model Y, highlighting new autonomy tweaks with potential safety gains.

According to SawyerMerritt, Tesla begins rolling out FSD v14 Lite to US-built Model 3/Y with HW3 in South Korea, marking its first international release.

According to SawyerMerritt, Tesla launched unsupervised Model Y robotaxis in rainy Miami on day one of service, sparking questions on fleet size.

According to SawyerMerritt, Tesla launched Robotaxi in Miami, Dallas, Houston, Austin, and Bay Area with varying oversight levels, per his tweet.

According to Sawyer Merritt, Tesla launched unsupervised Robotaxi rides in Miami, but no official Tesla or regulator confirmation is available.

According to SawyerMerritt, Tesla FSD V14.3.4 completed NYC and NH round-trip drives with zero disengagements, handling tight spaces and hazards.

According to SawyerMerritt, Texas DOT’s chief saw Tesla’s Cybercab with no driver controls as Tesla runs Model Y robotaxis in Texas using FSD.

According to SawyerMerritt, The Straight Pipes praised Tesla FSD V14 for smooth city driving and obstacle response in a Model Y Performance review.

According to Sawyer Merritt, FSD v14 detected reverse lights and backed up to yield, showing real time planning benefits, as reported by X post video.

According to SawyerMerritt, Tesla Model Y units at Giga Berlin have self-driven 93,000 miles on FSD from line end to outbound, streamlining yard logistics.

According to Sawyer Merritt, NHTSA says the 2026 Tesla Model Y passed new driver-assist tests, raising industry standards and highlighting lifesaving tech.

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 Sawyer Merritt, some 2026 Model Y reviews skip FSD, despite wide autonomy claims; according to Tesla, drivers must supervise at all times.

According to Sawyer Merritt, Tesla FSD V14.3.2 slowed for a bunny, and release notes cite RL on harder examples with rewards for proactive safety.

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 has added a second Unsupervised Model Y Robotaxi to its Dallas fleet, signaling an accelerated pilot footprint for autonomous ride-hailing in a major U.S. metro. According to RtaxiTracker, the addition suggests Tesla is iterating on supervised-to-unsupervised transitions for its Full Self-Driving stack in real-world operations, potentially reducing the need for safety drivers and lowering unit economics for robotaxi deployments. As reported by the X post, scaling in Dallas indicates Tesla is testing service density, mapping coverage, and operations logistics such as charging and maintenance hubs, which are critical to commercial viability. According to industry practice cited by Tesla’s autonomy communications in prior updates, such deployments typically inform software reliability metrics, interventions per mile, and edge-case handling—key inputs for regulatory engagement and insurance underwriting.

According to Sawyer Merritt on X, citing RtaxiTracker, Tesla has added a second Model Y robotaxi to its Houston fleet, signaling expanded on‑road testing of autonomous capabilities (source: Sawyer Merritt post referencing RtaxiTracker on X). According to Sawyer Merritt, the deployment underscores Tesla’s push to validate Full Self-Driving in real-world urban operations, a prerequisite for scalable robotaxi services and potential ride-hailing revenue streams (source: Sawyer Merritt on X). As reported by RtaxiTracker via Sawyer Merritt, incremental fleet growth in one metro allows Tesla to collect diverse edge-case data, improve neural network training, and iterate on safety and reliability KPIs critical for regulatory approvals and commercial launch (source: RtaxiTracker via Sawyer Merritt on X). According to Sawyer Merritt, Houston’s expansion may enable Tesla to test pricing models, dispatch logic, and utilization metrics ahead of broader rollouts, creating near-term business opportunities in autonomous mobility and fleet management software (source: Sawyer Merritt on X).

According to Sawyer Merritt on X, every Unsupervised Model Y operating in Austin, Houston, and Dallas is running Tesla’s AI4 stack. According to Merritt’s post, this indicates Tesla has standardized its next‑gen autonomy software across key Texas pilot markets. As reported by Sawyer Merritt, broader AI4 deployment could accelerate data collection for end‑to‑end neural networks and reinforcement learning at scale, improving Full Self-Driving model iteration cycles. According to prior Tesla disclosures cited by investor reports, concentrated regional rollouts enable rapid telemetry feedback, lowering validation costs and shortening release cadences, which can translate into faster pathway to supervised-to-unsupervised transitions and potential regulatory engagement advantages. For suppliers and ecosystem partners, this AI4 footprint in Texas signals near-term opportunities in edge AI compute, high-bandwidth connectivity, and fleet data labeling operations supporting autonomy model training, as indicated by industry analyses referencing Tesla’s incremental city-by-city activation strategy.