Figure AI's humanoid robots — powered by the Helix-02 neural network — just completed a full 8-hour autonomous shift sorting packages in a factory. The company live-streamed the humanoid's sorting tasks which ran for over 14 hours. Multi-robot coordination with automatic swap-outs when batteries run low. Is this hat the future of factory work looks like? #FigureAI# #Helix02# #HumanoidRobots# #Robotics# #FactoryAutomation# #AIRobotics# #FutureOfWork# #Autonomous#

UBTECH Robotics has posted its H1 2026 financial results, highlighting rapid top-line growth driven by full-size humanoid deployments: ● Revenue: RMB 1.27B (+$188M), up 104% YoY ● Full-size humanoid revenue: Surged 1,445% YoY to RMB 590M (46.5% of total revenue) ● Volume: 921 full-size and 15,202 non-full-size units shipped ● Profitability: Net loss narrowed 23% to RMB 339M, with full-size gross margin hitting 66.8% Over 96% of full-size revenue came from industrial enterprise customization, underscoring the ongoing shift toward factory automation. Read the full breakdown:

JUST IN: RIVIAN SPINOFF MIND ROBOTICS JUST RAISED $400 MILLION, TWO MONTHS AFTER RAISING $500 MILLION The new round brings the total raised to over $1 billion in under a year and values the company at $3 billion+. The full picture, per WSJ: The new round: - $400M led by Kleiner Perkins - Additional investors include the venture arms of Volkswagen and Salesforce - Volkswagen is Rivian's partner on a software joint venture Capital raised to date: - $115M from Eclipse (2025 seed) - $500M (two months ago) - $400M (this round) - Total: $1B+ The company: - Originally known internally as "Project Synapse" - Builds industrial robotics with "human-like skills" for factory automation - Chairman: Rivian $RIVN CEO RJ Scaringe Scaringe told TechCrunch in March he created Mind Robotics because he felt other startups were not fully equipped to automate industrial work. He also spun out a separate micromobility company called Also, which has raised $300M+ to date.

Sam Altman says AI usage could grow from 100,000 tokens per month in 2020 to hundreds of billions today, creating enormous demand for the companies powering the AI economy (Save this). That would represent roughly a million fold increase in six and a half years. Tokens are a way to measure how much information an AI model processes, so this growth shows that AI is moving from occasional chatbot questions to continuous use for coding, research, customer service, and business automation. OpenAI has reportedly seen its heaviest users consume around 100 billion tokens per month. Some extreme users have processed several hundred billion tokens in just 30 days. If usage continues expanding, demand will rise across the entire AI supply chain and here is some of the stocks that will benefit from this. NVIDIA remains the clearest beneficiary because its GPUs, networking products and software are used to train and run AI models. AMD could benefit as cloud companies and enterprises look for alternatives to NVIDIA’s chips. Broadcom and Marvell are important networking and custom chip suppliers and as AI models process more data, data centers need faster connections between servers, memory, and processors. Micron benefits from demand for high-bandwidth memory, which is essential for advanced AI processors. Super Micro Computer and Dell can benefit from demand for AI servers, storage systems, and complete data-center installations. Arista Networks supplies high-speed networking equipment for data centers, while Amphenol and TE Connectivity provide connectors and other components used to connect servers, racks, and communication systems. The AI boom also requires enormous amounts of electricity and cooling. Vertiv provides data-center cooling and power-management systems. Eaton and Schneider Electric benefit from electrical distribution, backup power, automation, and data center infrastructure. GE Vernova, Constellation Energy, and Vistra could benefit from the rising electricity demand created by AI data centers. The stronger AI adoption becomes, the more power companies and utilities may need to build or expand generation capacity. Equinix and Digital Realty provide data-center space and connectivity. Their facilities can benefit as companies lease additional capacity for AI workloads. The opportunity also extends to industrial automation. Siemens and Schneider Electric provide factory automation, industrial software, sensors, and control systems. If AI moves from the cloud into factories, warehouses, and robots, these companies could benefit from the physical deployment of intelligent machines. If you enjoyed reading this, make sure to follow @MilkRoadAI for more AI infrastructure and semiconductor insights and turn on post notifications on.