SPRINGFIELD — Illinois rideshare drivers could soon collectively bargain with Uber and Lyft after the state General Assembly passed legislation early Monday outlining a path toward unionization. Meanwhile, a separate bill that would have authorized autonomous vehicle pilot programs in the state failed to advance before the end of the legislative session. The rideshare bill, which still needs Gov. JB Pritzker’s signature, passed with backing from SEIU Local 1, IAM machinists union Local 701 and Uber, supporters said. It would give more than 100,000 rideshare drivers in Illinois a way to form a union. “We’re excited to hit the road and let everybody know that they’re going to be able to join a union,” said Giovanni Suarez, a Chicago-based full-time rideshare driver who stayed in the Capitol past 2 a.m. to watch the bill pass in the state House. The Illinois model is similar to one approved by voters in Massachusetts, the first state where rideshare drivers won the right to bargain as independent contractors in 2024. Just days ago, Massachusetts also became the first state to formally recognize a union for ride-hailing app drivers, a certification covering roughly 70,000 workers that labor leaders described as the largest private-sector organizing win since Ford autoworkers unionized in 1941, according to The Associated Press. Illinois Republicans raised concerns during floor debate about the feasibility of organizing workers who are not classified as employees. “What I’m trying to understand is how do we unionize people who aren’t employees, people who are their own independent contractors? They run themselves as their own business,” said GOP state Rep. Dan Ugaste of Geneva. That tension was at the heart of the bill. Rideshare companies and other employers in the so-called gig economy have long maintained that their drivers and other workers are not their direct employees.
Jun 1, 2026 · via chicagotribune.com
Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what’s happening in their world, predict what’s likely to happen next, and generate actions for specific environments, embodiments, and tasks. NVIDIA Cosmos 3 is a frontier foundation model for physical AI that combines physical reasoning, world generation, and action generation within a single open model. NVIDIA is open sourcing Cosmos 3 models, training scripts, deployment tools, and datasets to make physical AI development more open and reproducible. This blog post covers the fundamentals of Cosmos 3, highlights key concepts from the technical report, guides through technical workflows and shows how teamsrobotic manipulation systems, autonomous vehicles, and warehouse monitoring solutions can get started. Key highlights of this release include: - NVIDIA Cosmos 3 Nano and NVIDIA Cosmos 3 Super model checkpoints on Hugging Face with code on GitHub. - Open datasets for physical AI applications like robotics and autonomous driving. - Open post-training scripts for adapting Cosmos 3 to your domain. - Cosmos NIM microservices for easy, optimized deployment on NVIDIA GPUs. What’s new in Cosmos 3 Previous Cosmos releases separated world generation, physical understanding, and controlled scene generation into different models and workflows. This release unifies those capabilities with a Mixture-of-Transformers (MoT) architecture built around two towers. - Reasoner tower: A vision-language model (VLM) that interprets multimodal observations like images, videos, and text. This tower uses an autoregressive architecture to interpret the input and understand motion, object interactions, and other physical context. This serves as the ‘brain’ that reasons about the world before any generation happens. - Generator tower: Generates future observations and action sequences. This tower uses a diffusion-based process to generate physics-aware video and action outputs that are conditioned on the reasoner tower’s understanding. The
Jun 1, 2026 · via developer.nvidia.com
VINFAST AND AUTOBRAINS LAUNCH FIRST AGENTIC AI L4 PROGRAM FOR SOUTHEAST ASIA WITH NVIDIA Rhea-AI Summary VinFast (NASDAQ: VFS), Autobrains, and NVIDIA announced a strategic collaboration to develop a next-generation Level 4 autonomous driving program for Southeast Asia, built on NVIDIA DRIVE Hyperion 10 and Autobrains' Agentic AI. The goal is scalable, cost-efficient autonomy suited to the region's complex traffic. AI-generated analysis. Not financial advice. Positive - None. Negative - None. Key Figures Market Reality Check Peers on Argus VFS was down 1.97% while key EV peers were mixed: LCID and NIO showed gains, ZK was nearly flat, and PSNY/PSNYW declined. The negative move contrasts with several rising peers, pointing to a stock-specific reaction rather than a broad sector move. Historical Context | Date | Event | Sentiment | Move | Catalyst | |---|---|---|---|---| | May 21 | VF 9 positioning | Positive | +0.3% | Highlights VF 9 as premium yet cost-efficient 7-seat electric SUV. | | May 21 | New VF 8 launch | Positive | +0.3% | Introduces new-generation VF 8 with upgrades and Vietnam pre-order details. | | Apr 22 | Q1 2026 deliveries | Positive | -1.4% | Reports strong YoY growth in global EV and two-wheeler deliveries. | | Apr 16 | VF 8 Eco promo | Positive | -1.2% | Promotes VF 8 Eco value proposition, specs, and financing offers. | | Apr 14 | Canada EV benefits | Positive | +0.0% | Showcases Canadian EV appeal amid higher fuel costs and warranty support. | Positive product and growth news has not consistently translated into gains; several upbeat releases coincided with flat or negative next-day performance. Over recent months, VinFast has focused on product positioning and volume growth. Releases on the VF 9 and new-generation VF 8 highlighted premium features, pricing, and user-experience
Jun 1, 2026 · via stocktitan.net
- Combining Autobrains' Agentic AI with NVIDIA DRIVE Hyperion - Developing VinFast's level 4 to drive safely in real-world conditions - Advancing autonomous driving without the premium cost that has stalled others TAIPEI, June 1, 2026 /PRNewswire/ -- VinFast (NASDAQ: VFS), and Autobrains announced at NVIDIA GTC Taipei at COMPUTEX 2026 today a strategic collaboration for a next-generation level 4 program for Southeast Asia built on NVIDIA DRIVE Hyperion. The collaboration marks a new step in VinFast's roadmap to make advanced autonomous driving technology more accessible at a reasonable cost, while opening a more practical approach to autonomous mobility solutions in the region's highly complex traffic environments. Built on NVIDIA DRIVE Hyperion 10 compute and powered by Autobrains' Agentic AI software for autonomous driving capabilities, VinFast is developing the level 4 platform for Southeast Asia. With dense traffic, diverse road behavior, and highly dynamic urban environments, Southeast Asia presents a demanding validation ground for autonomous driving. The three-way collaboration comes at a time when autonomous driving has stalled on three persistent barriers: system complexity, compute cost, and brittle performance outside controlled environments. To address these challenges, VinFast, NVIDIA, and Autobrains are developing a modular architecture, pairing vehicle integration, high-performance compute, and Agentic AI software. Unlike traditional end-to-end approachs, Autobrains' Agentic AI deploys specialized AI agents that activate only when the driving task demands them. This approach delivers sharper real-world reasoning, lower compute overhead, and a scalable, cost-efficient path to autonomy. For VinFast, the program provides a path to bring advanced autonomous capability to market without the premium cost structure that has limited wider deployment. NVIDIA DRIVE Hyperion gives VinFast a validated hardware and software foundation, reducing the integration work that typically adds years to autonomous vehicle programs. Prof.-Dr. Duong Nguyen, Deputy CEO of ADAS at VinFast Global, said: "Advanced mobility
Jun 1, 2026 · via prnewswire.com
Autobrains and Uber to Launch Agentic AI Robotaxi Program in Munich built on NVIDIA DRIVE Hyperion Key Terms agentic ai technical robotaxi technical autonomous driving technical software-defined technical - Combining Uber’s mobility network, Autobrains’ Agentic AI, and NVIDIA DRIVE Hyperion - Launching a Munich robotaxi service designed to scale into a fully autonomous fleet - Creating an OEM-agnostic model for autonomous ride-hailing across vehicle platforms Pending regulatory approval, Autonomy has often depended on custom vehicles, heavy sensor stacks, and compute architectures that are much harder to commercialize at scale. Autobrains’ Agentic AI is designed to change that - enabling robust, real-time decision-making on standard automotive sensor configurations and efficient, accelerated compute, with the flexibility to deploy across OEM platforms. The collaboration combines three essential layers for scalable robotaxi deployment: Autobrains’ Agentic AI autonomous driving technology, the NVIDIA DRIVE Hyperion platform, and Uber’s global mobility network and operational experience. Together, they establish an OEM-agnostic model to move autonomous ride-hailing from isolated deployments to repeatable, scalable fleet infrastructure. Autobrains’ Agentic AI represents a new path to autonomy. Rather than relying on a single, monolithic end-to-end model to handle the full driving task, Autobrains decomposes driving into specialized agents, each focused on a specific driving context or decision dimension. These agents continuously evaluate context, reason across multiple possible actions, and select responses in real time. This enables more robust behavior in complex, unpredictable environments, while maintaining the efficiency needed to deploy across fleets and OEM platforms. The program is designed to integrate across vehicle platforms and operate within Uber’s ride-hailing ecosystem. For automakers, it creates a practical path to participate in autonomous ride-hailing by combining vehicle platforms with autonomous technology, marketplace access, and fleet operations. “Autonomous driving will not scale by relying on a single model to solve every driving scenario,” said Igal
Jun 1, 2026 · via stocktitan.net
Self-driving cars aren’t science fiction anymore. They’re already on public roads, navigating intersections, merging onto highways, and making thousands of micro-decisions every single minute. But here’s something most people don’t think about: the real magic isn’t in the sensors or the cameras. It’s in where and how fast the data from those sensors gets processed. That’s where edge computing comes in, and honestly, it doesn’t get nearly enough attention. Sending data to a remote server, waiting for analysis, and receiving a response take precious milliseconds that a vehicle traveling at 70 mph simply cannot afford. That is precisely why edge computing in autonomous vehicles has emerged as the cornerstone of modern self-driving systems. By relocating data processing to the vehicle itself or nearby infrastructure, this technology enables real-time, life-saving decisions without the bottleneck of cloud dependency. This blog explores how the technology works, why it matters, and the challenges ahead as it continues to scale across global transportation networks. Strip away the jargon, and it’s pretty simple. Instead of sending data to a remote server and waiting for a response, edge computing processes everything right there on the vehicle itself or at nearby roadside infrastructure. No round-trips to the cloud. No waiting. Why does that matter? Because a modern autonomous vehicle isn’t just a car. It’s basically a rolling data center. LiDAR, radar, cameras, ultrasonic sensors, GPS all running simultaneously. Together, they can generate somewhere between 1 TB and 5 TB of data every single hour. Try routing that through the internet in real time and see how far you get. The vehicles handling this today use onboard processors like NVIDIA’s DRIVE platform or Qualcomm’s Snapdragon Ride. These units handle the heavy lifting: AI inference, sensor fusion, and route planning without ever needing a Wi-Fi signal. Beyond the car itself,
Jun 1, 2026 · via securityjournalamericas.com
News Summary: TAIPEI, Taiwan, June 01, 2026 (GLOBE NEWSWIRE) -- NVIDIA GTC Taipei -- NVIDIA today introduced NVIDIA Alpamayo 2 Super, a 32-billion-parameter reasoning‑based vision language action (VLA) model that extends the NVIDIA Alpamayo family of open AI models, simulation frameworks and physical AI datasets for safe, level 4 robotaxi development. Alongside the model, the company announced new tools, models and agent skills that complete the pipeline from real-world data capture to closed-loop training and in-vehicle deployment, including NVIDIA AlpaGym, NVIDIA OmniDreams and new NVIDIA Omniverse NuRec models. Alpamayo 2 Super helps accelerate autonomous vehicle (AV) development by eliminating the need to build key autonomy infrastructure from scratch. It enables humanlike perception, reasoning and action, and provides the interpretability needed for safety validation and regulatory collaboration. To better train models for on-road deployment, the AlpaGym framework provides a platform for closed-loop reinforcement learning (RL). The NVIDIA OmniDreams generative world model for photorealistic closed-loop AV scenario generation enables developers to simulate rare and long-tail driving scenarios at scale. To amplify developer productivity, NVIDIA is providing physical AI agent skills for all of its AV development tools. For example, the Neural Reconstruction skill powered by NVIDIA Omniverse NuRec uses real-world fleet driving scenarios for simulation and generates synthetic training data at scale. “Alpamayo is the moment cars begin to safely reason, not just drive,” said Jensen Huang, founder and CEO of NVIDIA. “Only NVIDIA makes available open models, simulation, real-world data and agent skills so the entire global robotaxi ecosystem can develop level 4 capabilities that understand edge cases, explain decisions, earn trust and scale safely to millions of vehicles.” Alpamayo 2 Super, Now Available for Reasoning-Based AVs The NVIDIA Alpamayo family now scales from 10 billion to 32 billion parameters with Alpamayo 2 Super — going beyond trajectory generation to reason,
Jun 1, 2026 · via markets.businessinsider.com
Grab, the Singapore-based superapp, plans to explore pilot programs for autonomous vehicles and delivery robots in Vietnam, said Chin Yin Ong, Chief Organization Capability Officer at Grab. The executive made the statement at a meeting with Vietnam’s General Secretary and President To Lam on Sunday, during the latter’s state visit to the Philippines, according to the Vietnam News Agency and Ong’s personal LinkedIn post. Ong also pledged continued long-term investment in Vietnam and Grab’s activities in Vietnam, including digital transformation, sustainable growth, and smart mobility. On sustainability, Grab is accelerating the transition to electric vehicles and has proposed investing in a nationwide network of 6,000 shared charging points by 2027. On smart mobility, Grab is working to integrate public transport with its app to promote multimodal connectivity. Ong added that the group currently operates across Vietnam with ride-hailing service GrabBike, food delivery GrabFood, and taxi service GrabTaxi. Grab strives to support multimodal transport connectivity, urban public transport, and green vehicle infrastructure, and to promote Vietnam’s prestige across the region, she emphasized. For his part, General Secretary and President To Lam encouraged Grab to advance research and investment in smart city development and autonomous vehicles, and to invest in green and intelligent public transport systems and the promotion of Vietnamese tourism and cuisine on the Grab platform. Grab‘s revenue in 2025 grew 20 percent year on year, reaching a record $3.37 billion. Grab generated $1.04 billion in revenue from Malaysia, the only market exceeding $1 billion. Other leading markets were Singapore with $727 million, Indonesia with $715 million, the Philippines with $316 million, followed by Thailand and Vietnam with $288 million and $255 million, respectively. Grab’s record quarter signals growing shift In Southeast Asian food retail – BMI
Jun 1, 2026 · via technode.global
NVIDIA Releases Major Collection of Open Source Agent Tools and Skills for Physical AI News Summary: - NVIDIA releases a major open source collection of physical AI agent skills and tools spanning NVIDIA Omniverse, Cosmos, Alpamayo and Metropolis for robotics, autonomous vehicles, vision AI and industrial digital twins. - New physical AI skills turn complex physical AI training, evaluation and deployment workflows into repeatable, optimized and agent-executable instructions. - Industry leaders including Agile Robots, Cadence, Dassault Systèmes, Delta Electronics, Foxconn, Pegatron, PTC, Siemens, Synopsys and TSMC are using NVIDIA physical AI tools to accelerate physical AI development. TAIPEI, Taiwan, June 01, 2026 (GLOBE NEWSWIRE) -- NVIDIA GTC Taipei -- NVIDIA today announced a major collection of open source physical AI skills and tools that help developers turn complex robotics, autonomous vehicle (AV), vision AI and industrial digital twin workflows into agent-executable tasks — reducing the costs, time and complexity of building physical AI workflows at scale. As AI agents move from writing code to orchestrating entire development tasks, physical AI is the next frontier. NVIDIA physical AI skills, available as part of NVIDIA Agent Toolkit, let agents use NVIDIA libraries, models and frameworks to speed the data generation, simulation, training, evaluation and deployment pipelines behind robots, AVs, factories and labs. “AI agents are revolutionizing software development, and that shift is now coming to physical AI, extending into the systems that will transform transportation, manufacturing, healthcare and robotics,” said Jensen Huang, founder and CEO of NVIDIA. “When agents can directly use NVIDIA libraries, models and frameworks, physical AI development will move faster, enabling developers to build the robots, autonomous vehicles and industrial systems of the future at an incredible pace.” Agent-Ready Tools and Skills for Physical AI Development NVIDIA is optimizing its entire physical AI stack for agents by turning libraries,
Jun 1, 2026 · via theglobeandmail.com
Chinese electric vehicle maker BYD is intensifying its push into the autonomous driving market through its advanced driver assistance system (ADAS) platform "God's Eye," while introducing an aggressive policy that covers accident compensation and even protects drivers from higher insurance premiums when crashes occur during autonomous driving functions. At its "Intelligent Strategy Event" held in Shenzhen on May 28, BYD unveiled a new service package aimed at expanding use of its God's Eye ADAS platform. The core policy is that BYD will directly handle repairs and compensation if accidents occur while using the system's City Navigation feature. The company also said users' insurance premiums for the following year would not increase. BYD had previously announced compensation coverage for accidents caused by algorithm errors or system defects in its autonomous parking system, including vehicle repairs, third-party property damage and personal injury compensation. At the May 28 event, the company expanded the policy to include accidents caused by errors in its city navigation assistance function. However, the compensation applies only to the higher-tier A and B versions of the three-tier God's Eye system lineup. The God's Eye ADAS platform is divided into three systems: the flagship A version, the upper-mid-tier B version and the entry-level C version. The entry-level C system provides Level 2 assistance features including automated highway entry and exit, lane keeping, adaptive cruise control, automatic lane changes, obstacle avoidance, automatic emergency braking, remote parking and autonomous parking after passengers exit the vehicle. The system uses a vision-centered architecture without lidar, equipped with 12 cameras — three front-facing cameras, five panoramic cameras and four surround-view cameras — along with five millimeter-wave radars and 12 ultrasonic radars. The God's Eye B system includes lidar and high-performance computing chips while offering more advanced capabilities such as city navigation assistance, handling complex intersections
Jun 1, 2026 · via thelec.net
Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can reason over more complex driving scenes and produce richer intermediate reasoning are predominantly trained in open-loop, where model outputs are directly compared to ground-truth behaviors without considering their effect on the environment. In deployment, however, a driving policy runs in closed-loop, where every braking, steering, and navigation decision affects the environment, and small errors can compound over time. A systematic means to address this challenge is provided by NVIDIA Alpamayo, an open portfolio of AI models, simulation frameworks, and physical AI datasets for AV development. Alpamayo includes the AlpaSim AV simulation platform and the AlpaGym closed-loop training framework (coming soon). This post explains how to train AV models in closed-loop with NVIDIA Alpamayo. Specifically, it walks through how to: - Install and configure AlpaGym - Define closed-loop rewards - Launch closed-loop training - Export the post-trained checkpoint for downstream use Closed-loop post-training with AlpaGym extends AV training workflows by turning AlpaSim rollouts into training experience. Rather than treating simulation only as a final evaluation stage, AlpaGym connects simulator feedback directly to the policy training loop. How to use AlpaGym for closed-loop reinforcement learning Reinforcement learning (RL) can be used to improve a policy that was initially trained in open-loop. Instead of optimizing only against logged expert trajectories, the model can now learn from the consequences of its own actions in simulation. This shift is critical for AV development, where small prediction or planning errors can compound over time. In closed-loop training, each braking, steering, and navigation decision affects the next state of the environment, revealing failure modes that static datasets or open-loop evaluation may miss. However, enabling closed-loop RL comes with its own challenges. Model inference, running simulation, training models, syncing
Jun 1, 2026 · via developer.nvidia.com
News Summary: - NVIDIA’s most powerful open reasoning model to date, NVIDIA Alpamayo 2 Super is an open 32-billion-parameter reasoning VLA model that reasons, plans and acts across the full driving stack for safer, scalable level 4 development. - NVIDIA AlpaGym is a new high-throughput, closed-loop reinforcement learning framework that trains AV models on the consequences of their driving decisions in simulation before road deployment. - NVIDIA OmniDreams is a new generative world model for photorealistic closed-loop AV scenario generation, enabling developers to simulate rare and long-tail driving scenarios at scale. - NVIDIA physical AI agent skills for AV development include Neural Reconstruction powered by NVIDIA Omniverse NuRec, enabling developers to reconstruct real-world fleet data into photorealistic 3D scenes and adapt them across vehicle sensor configurations. NVIDIA GTC Taipei—NVIDIA today introduced NVIDIA Alpamayo 2 Super, a 32-billion-parameter reasoning‑based vision language action (VLA) model that extends the NVIDIA Alpamayo family of open AI models, simulation frameworks and physical AI datasets for safe, level 4 robotaxi development. Alongside the model, the company announced new tools, models and agent skills that complete the pipeline from real-world data capture to closed-loop training and in-vehicle deployment, including NVIDIA AlpaGym, NVIDIA OmniDreams and new NVIDIA Omniverse NuRec models. Alpamayo 2 Super helps accelerate autonomous vehicle (AV) development by eliminating the need to build key autonomy infrastructure from scratch. It enables humanlike perception, reasoning and action, and provides the interpretability needed for safety validation and regulatory collaboration. To better train models for on-road deployment, the AlpaGym framework provides a platform for closed-loop reinforcement learning (RL). The NVIDIA OmniDreams generative world model for photorealistic closed-loop AV scenario generation enables developers to simulate rare and long-tail driving scenarios at scale. To amplify developer productivity, NVIDIA is providing physical AI agent skills for all of its AV development tools. For
Jun 1, 2026 · via nvidianews.nvidia.com
Samsung Electronics tops automotive memory chip market in 2025: report SEOUL, May 31 (Yonhap) -- Samsung Electronics Co. became the world's leading supplier of automotive memory chips last year, surpassing U.S. chipmaker Micron, an industry report showed Sunday. Samsung's share of the global automotive memory chip market rose to 40 percent last year from 35 percent in 2024, according to a report by S&P Global Mobility. Over the same period, Micron's market share fell to 36 percent from 40 percent, placing it at No. 2. Samsung's gains were driven in part by its expanding presence in China, one of the world's fastest-growing automotive markets. Market watchers said Samsung Electronics benefited from growing demand for advanced memory chips as autonomous driving systems become more widespread and as in-vehicle infotainment systems grow increasingly sophisticated across the board. The South Korean chipmaker is known to supply automotive memory chips to major customers, including Qualcomm, Bosch, Tesla and Denso. ejkim@yna.co.kr (END) - (3rd LD) Court acquits ex-President Yoon of perjury over testimony at ex-PM's trial - BTS shows in N. America draw 840,000 concertgoers: agency - Zombie thriller 'Colony' breaks 2 mln admissions - Foreign ministers of S. Korea, Croatia discuss arms, energy cooperation - Justice ministry recoups 139.6 bln won in criminal proceeds in 2025 - Shinsegae chairman to apologize again over Starbucks Korea's 'Tank Day' event - (5th LD) Iran-linked missiles behind attack on S. Korean vessel in Hormuz: foreign ministry - Culture minister says seeks 400 tln-won 'K-culture' market by 2030 - (URGENT) Hegseth calls for 'balanced' OPCON transfer where U.S. military plans, roles are 'honored' - Zombie thriller 'Colony' breaks 2 mln admissions - Seoul conveys position to Washington on USFK chief's 'dagger' remarks - S. Korea rout Trinidad and Tobago 5-0 in pre-World Cup friendly - (News Focus) Lee's
May 31, 2026 · via en.yna.co.kr
Estonia becomes third EU country to allow self-driving cars on its roads Estonia has become the third country in Europe to allow cars with self-driving systems on its roads, following the Netherlands and Lithuania. Within the next few months, drivers of newer Tesla electric cars in Estonia will be able to install a self-driving software update. "It is still a driver-assistance system, where the driver is responsible for the vehicle's entire driving behavior and safety and must take over the vehicle when necessary," explained Jürgo Vahtra, head of the Vehicle Technical Department at the Transport Administration. "At the same time, Tesla itself monitors whether the driver is engaging in unrelated activities or looking elsewhere. If not, it alerts that the driver is not paying attention to traffic. Therefore, this does not really affect current laws, because ultimately the driver remains responsible," he added. Geenius editor-in-chief Kuldar Kullasepp took a test drive in a self-driving car in Finland and said it handled all conditions perfectly and that, at times, the drive was even boring. "There are about eight cameras in the car that continuously send images to a computer. The computer constructs a picture of the world around it and then makes its decisions based on the experience it has gained from millions and millions of kilometers of driving. So it should be safer, it is certainly smoother, meaning there is no nervous road user," Kullasepp described. Pavel Nikolajev, whose family owns two Teslas, is eagerly awaiting the software update. He said it could help improve Estonia's driving culture. "When the car drives itself, it looks everywhere around it, and maybe they will also drive a little more slowly and properly, and then other cars will observe that and take it as an example," Nikolajev told Saturday's "Aktuaalne kaamera" evening news
May 31, 2026 · via news.err.ee
New episodes of State of Texas are on KXAN or the KXAN+ app every Sunday at 8:30 a.m. Don’t want to wait? Scroll down to continue watching this week’s segments now. AUSTIN (Nexstar) – Texas voters will elect a new U.S. senator this November. Attorney General Ken Paxton won Tuesday’s Republican runoff, defeating incumbent John Cornyn. The victory sets the stage for a November showdown with Democratic nominee James Talarico. “We just proved that this senate seat doesn’t belong to Washington, it belongs to you, the hardworking men and women of this state,” said Paxton in his victory speech. “No matter who you supported in this race…I want to earn your support. Tonight is the beginning of the fight to preserve every value we hold dear.” Paxton then shifted his attention to Talarico. He called him a “radical democrat,” claiming Talarico “is a threat to our security and our safety” and “to our prosperity and Texas economy”. “He wants boys and girls sports, gender mutilation surgery performed on kids. And when asked what he loved outside of his family and friends, his first answer was trans kids.” Paxton said to the crowd of supporters. He then listed off a series of derogatory nicknames for his opponent, drawing laughter and applause from the crowd of supportrers. The list included “six gender Jimmy,” in response to Talarico saying in a House committee meeting that there were six genders, “Tofu Talarico,” playing off allegations that he is vegan, and “Talafreako.” Talarico launched attacks of his own, starting minutes after Paxton secured the Republican nomination. In a social media post, Talarico called Paxton “the most corrupt politician in America.” “Three years ago, Ken Paxton was impeached by his own party for using his public office to enrich himself and his donors at the expense
May 31, 2026 · via ktsm.com
Innoviz Technologies Sees Lidar Momentum Rebounding as Defense, Physical AI Demand Grows Innoviz Technologies INVZ Chief Financial Officer Eldar Cegla said the lidar industry is seeing renewed momentum in automotive applications and growing demand in non-automotive markets tied to “Physical AI,” during a fireside chat at TD Cowen’s TMT Conference. Speaking with TD Cowen analyst Itay Michaeli, Cegla described Physical AI as systems that must interact with the real world in real time and therefore require strong perception capabilities. He said cameras remain widely used, but 3D sensors such as lidar can provide an AI system with a more detailed view of its surroundings by pinpointing objects in the environment. Cegla said the automotive lidar market has gone through a hype cycle and a subsequent slowdown, but is now in a more mature phase. He said the industry has a better understanding of the sensors required to support safe autonomous driving, with companies such as Mobileye and NVIDIA providing computing platforms that use sensor data to make driving decisions. Defense and Security Seen as Near-Term Growth Areas Cegla said Innoviz began expanding its market focus beyond automotive more than a year ago, initially exploring areas such as smart cities, intelligent transportation systems and construction. More recently, he said the company has seen growing demand from security and defense applications, including situational awareness, perimeter security and automated systems that must navigate their environments. “We see that there is a real sense of urgency in these kinds of applications and an actual missing link or sensory level, which is not accommodated for by cameras and radars because they have certain shortcomings,” Cegla said. In non-automotive markets, Cegla said Innoviz does not intend to act as a Tier 1 supplier as it does in automotive programs. Instead, the company expects to supply lidar
May 31, 2026 · via tradingview.com
A group of consumers has filed a class-action lawsuit against Tesla (TSLA) seeking over 3.95M yuan ($583K) in damages, alleging that the EV maker fraudulently marketed its Full SelfâDriving feature, The Beijing News reported.
The litigation filed by 10 Chinese
May 30, 2026 · via seekingalpha.com
Tesla is marching toward its goal of global vehicle autonomy, slowly but surely rolling out its advanced driver assistance features across multiple international markets. What started as an exclusive, experimental software trial in the United States has quickly expanded into a worldwide deployment. By systematically checking off regional regulatory requirements, Tesla is turning its neural network framework into a scalable solution. FSD now allows a Tesla to navigate complex city streets, handle busy intersections, execute protected or unprotected turns, and manage high-speed lane changes on its own. It accomplishes this by leveraging an end-to-end neural network trained on more than 10 billion miles of real-world driving data. FSD even serves as the foundation of Tesla’s autonomous Robotaxi service. The latest iteration of the software at the time of writing is version 14.3.3, which started rolling out earlier this month, delivering a smoother, more refined experience with reduced driver monitoring. As Tesla continues to expand FSD availability, the hardware limitations and launch conditions vary by territory. Let's take an intensive, market-by-market look at the current state of Tesla's global autonomous footprint. United States The U.S. serves as the testbed and epicenter of Tesla's autonomous development. The original FSD Beta officially launched to its first private consumer testers back in October 2020, running on Hardware 3 (HW3). Today, the U.S. remains the first market in the world to receive the latest FSD software iterations. While the software continues to support millions of older legacy vehicles, the most advanced neural network builds and newest features now only roll out to more modern vehicles with Hardware 4 (AI4). Canada Canada was the first international expansion territory for the driver assist program, officially introducing FSD in March 2022 on HW3-equipped vehicles. Because Canadian vehicles have to deal with intense winter conditions, more country roads, and
May 30, 2026 · via notateslaapp.com
Elon Musk has shared new footage on X showcasing the Cybercab driving itself out of Giga Texas. The brief clip captures a couple of the gold-painted robotaxis exiting the factory doors, navigating the outdoor logistics lots while following street signs, executing tight turns, and blending into active factory traffic — all entirely unassisted. Cybercab driving itself out of the GigaTexas factory pic.twitter.com/EwAMVVDjYy — Elon Musk (@elonmusk) May 28, 2026 Responding to Musk's post, Tesla’s AI chief, Ashok Elluswamy, teased that the Cybercab could begin commercial Robotaxi operations very soon. He even revealed where these purpose-built autonomous vehicles are heading first, writing, "Soon it’ll be driving itself in to Austin city, reporting for duty!" Elluswamy's comments indicate that Tesla is not only closing in on Cybercab deployment but that Austin will likely be the debut market where the next-gen vehicle will officially join the fleet. Factory Automation: Built Into Tesla's DNA While seeing an unmanned Cybercab cruise out of a factory is exciting, this functionality builds directly on previous automation that Tesla has already established at its facilities. Tesla is building the Cybercab at Gigafactory Texas, where Model Ys have been driving themselves off the production line for quite some time now. In fact, the company already achieved a world-first by autonomously delivering a Model Y from Giga Texas straight to a local customer's doorstep last year. Tesla has also achieved similar automation internationally; vehicles also drive themselves off the line at Giga Berlin. The progression to the Cybercab shows how Tesla’s autonomy-first fleet is designed to manage its own physical distribution right from birth. Production Ramps Up as Regulatory Paths Clear This video drops at a critical operational moment in the Cybercab’s life. Tesla officially kicked off mass production last month, and we've already seen fleets of Cybercab units sitting
May 30, 2026 · via notateslaapp.com
Huawei-GAC’s Aistaland GT7 electric shooting brake opens pre-sales with over 10,000 pre-orders in 5 hours Aistaland (Qijing), the premium intelligent new energy vehicle brand jointly established by GAC Group and Huawei, officially opened pre-sales for its inaugural model, the GT7, on May 29, 2026. The mid-to-large pure electric shooting brake secured over 10,000 orders within the first five hours of its launch. Blind orders for this model opened in March this year, and the interior was revealed two weeks ago. The GT7 is available in four configurations, with a pre-sale price range of 219,900 yuan (32,300 USD) to 309,900 yuan (45,600 USD). The vehicle is scheduled to officially hit the market in June 2026. Performance and engineering Built on an 800V high-voltage architecture, the GT7 features a chassis equipped with a closed-loop dual-chamber air suspension and continuously adjustable damping. The top-tier Ultra three-motor all-wheel-drive version delivers a combined output of 768 hp, enabling a 0-100 km/h acceleration time of 2.98 seconds. The entry-level model is powered by a single-motor rear-wheel-drive system producing 253 kW (340 hp), achieving a 0-100 km/h sprint in 5.9 seconds. The vehicle offers two battery options customised by CATL: an 86.111 kWh pack and a 102.768 kWh Qilin battery that supports 6C fast charging, providing a maximum CLTC range of 900 km. Dimensions and design The GT7 measures 5,050 mm in length, 1,980 mm in width, and 1,470 mm in height, with a wheelbase of 3,000 mm. Its design emphasises aerodynamics and utility, featuring a “shooting brake” silhouette that offers a trunk capacity of 647 litres, expandable to 1,606 litres with the rear seats folded, alongside a 215-litre waterproof front trunk. Intelligent technology As the first vehicle to feature the Huawei Qiankun ADS 5.0 intelligent driving system, the GT7 is hardware-ready for L3 autonomous driving. The
May 30, 2026 · via carnewschina.com