与「AutonomousDriving」相关的搜索结果

On July 1, Pakistani youth influencers on the “B.R.I.D.G.E.” program rode Guiyang’s driverless robobus on the "Wonder Loop". Blogger Ali Mujeeb called it "a revolution," witnessing Guizhou's rapid development in recent years. #ChinaPakistan# #BRIDGE# #PIX# #AutonomousDriving#

This is the capital of robotics! 🌁 Silicon Valley is home to so many physical AI companies that you could spend a month visiting them and still not see even 10% of them (trust me, I tried). It took me 3x to create this map as it did to create any other. And the truth is, it's still incomplete. Let’s see why this is the case. So, the Bay Area is the world's leading ecosystem for robotics startups, bringing together top AI talent, top universities, experienced founders, and unmatched access to capital. The region is anchored by Stanford University and University of California, Berkeley, two of the world's top universities for AI and robotics. They produce a constant stream of researchers, founders, and breakthrough technologies. The Bay Area is also home to many of the companies shaping the future of robotics and AI, including @Figure_robot, @physical_int , and major AI labs such as @OpenAI. This concentration of talent makes it easy for startups to recruit experienced engineers and collaborate with leaders in embodied AI. Not mentioning that it  is also home to leaders such as @NVIDIARobotics , whose headquarters and leadership in AI chips power much of today's robotics revolution, and @Tesla, whose work on autonomous driving and humanoid robots has created a deep pool of robotics, AI, and manufacturing talent. Perhaps its biggest advantage is access to capital and ambition. The Bay Area has the world's deepest network of venture capital firms, serial entrepreneurs, and technical leaders who are willing to fund bold, long-term robotics companies. In the comments I'll post the companies from the ecosystem. ‼️ Note that Bay Area has >300 robotics companies, research labs, and innovation hubs, so this is a curated selection of the notable product companies, not an exhaustive census! P.S. I'm constantly working on improving these maps, so if your company is missing, please DM me with basic info about the co, and I will include it in the next release. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

The Port of Felixstowe is expanding its autonomous fleet to 100 trucks, demonstrating how AI and autonomous driving are supporting safer, smarter and more efficient terminal operations at scale. Discover the next step in smart port innovation.

🚀 Tencent Cloud Data Platform — The Unified Data Foundation for AI Built for the most demanding AI workloads—from AI Agents, multimodal intelligence, and data lakes to autonomous driving, and embodied intelligence—Tencent Cloud Data Platform provides a high-performance, cost-efficient, and unified data infrastructure that enables enterprises to accelerate AI innovation across the entire lifecycle, from data preparation and model training to intelligent applications.

Just some public market read through from Chinese private VC markets: Institutions are pouring funds into physical AI and world models. 1. Large models / LLMs: ~$23.56B 2. AI infrastructure + technical layer: ~$15.74B 3. Embodied intelligence / physical AI: ~$13.36B 4. AIGC applications: ~$8.79B 5. Autonomous driving + other Top-20 cluster: ~$3.82B, but not apples-to-apples with the above. Some notes: - "Early-stage pure foundation-model funding is basically closed". Looks like more funding is just being put into existing leaders and going into World Model companies. My guess is that we'll likely see the same in the US with Anthorpic/OpenAI consolidation. - "World models have become the biggest consensus in early-stage investment." I said months ago 4D AI/World Models would be the most interesting moving forward, and called out $AEVA as potential exposure. But there's not exactly any pure play exposure. But probably next we'll wait for the next IPOs here in this sector maybe H1 next year. - AIGC application sector is the most mature for AI technology commercialization "Artificial Intelligence Generated Content commercialization is mature but no clear winner yet". Makes sense. in the US there's stuff like Grok Imagine, Google Nano Banana, etc. no clear winner too. especially for video. _ TLDR: Continued funding into AI infrastructure/semiconductor supply chains. Huge capital rotation influx into physical AI / embodied brain / humanoids + world models from capital inflow. Consolidation around leading frontier model companies. Personally just validated what I've been focusing on with Agility Robotics and physical AI players (eg. leaderdrive, harmonic, etc) in public markets... As new potential opportunities in terms of capital rotation. But sadly no world model pure play exposure yet.

VLA 2.0 goes global, locked in. This week, the UN WP.29 Contracting Parties approved: DCAS UNR 171 Series 02, covering urban NGP functionality regulations UNR ADS, covering L3 to L5 autonomous driving regulations DCAS 171 Series 02 will take effect as mandatory EU regulation in six months, meaning autonomous driving can legally enter the global market starting from late 2026. UNR ADS is still a framework regulation for now, but it will help accelerate Robotaxi (L4) approvals and deployment across different markets. Stay tuned for XPENG's VLA and VLM rollout overseas in 2027, where you'll be able to talk to and control your car in a mix of Chinese and local languages.😉

Micron will be a $3,000 stock within a few years and Jensen Huang just spent a week in Korea telling the world exactly why (Save this). Jensen announced four new products at the Korea event and every single one of them has memory at the center of its architecture. Vera Rubin, the next generation AI supercomputer, needs massive quantities of HBM. The new Vera CPU needs large amounts of LPDDR5. RTX Spark, the first major PC reinvention in 40 years according to Jensen, needs a lot of LPDDR5. And Nvidia's new robotics and autonomous driving platforms are being built in deep partnership with the Korean memory and electronics ecosystem. Every single growth vector for Nvidia in 2026 and 2027 runs directly through memory and Micron is the only US based company that manufactures all of it. Here is what the numbers look like right now. Fiscal Q2 2026 revenue came in at $23.86 billion, up 196% year over year, with 75% gross margins and $6.9 billion in free cash flow, a quarterly record. Management guided Q3 revenue to $33.5 billion at roughly 81% gross margins, with EPS of $19.15. These are not the numbers of a cyclical memory company but rather the numbers of a company that has been structurally repriced by the largest demand supercycle in the history of the semiconductor industry. The reason the bull case reaches $3,000 comes down to three things that have never been true at the same time in Micron's history. First, the entire 2026 HBM supply is already sold out under multi-year contracts. CEO Sanjay Mehrotra told analysts that Micron can currently only fulfill 50% to two thirds of key customers' HBM demand at any price. Second, Micron has begun volume shipment of HBM4 12-Hi specifically for Nvidia's Vera Rubin platform, the exact product Jensen was talking about in Korea and has signed its first five year strategic customer agreement, converting what was historically a quarterly negotiation business into something closer to a long-term recurring revenue model. Third, Wolfe Research's bull case model points to $160 billion in calendar year 2027 revenue and $80 in EPS. At even a 20x earnings multiple, modest for a company with this growth profile, that is a $1,600 stock. UBS has already tripled its price target to $1,625. The path to $3,000 requires HBM4 to ramp smoothly, supply constraints to persist into 2027 as Mehrotra says they will, and hyperscaler AI capex to continue growing at its current trajectory, all three of which Jensen Huang just confirmed in Seoul. The HBM total addressable market alone is projected to reach $100 billion by 2028, a forecast Micron itself already pulled forward two years ahead of schedule because demand arrived faster than anyone modeled. Micron trades at roughly 9x forward earnings today. That is cheaper than a grocery chain, for a company growing revenue at 196% year over year, with its entire production sold out, supplying the infrastructure for the most important technology buildout in history. Come join Milk Road Pro for our full breakdown of the Micron bull case how we think about the HBM4 transition timeline, what multi-year customer contracts mean for Micron's valuation multiple expansion, and our entire AI thesis. Link below!

🇭🇰 WeRide joins the Hong Kong Stock Connect program (effective June 4), enabling eligible mainland Chinese investors to trade stocks listed on @HKEXGroup. This milestone enhances access, liquidity, and capital market connectivity as we scale autonomous driving globally. $WRD