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#

In December 2015, during my first year at Stanford GSB, I chose to intern at a top hedge fund. Researching advanced driver assistance systems (ADAS) and autonomous driving, I saw a new growth opportunity for GPUs beyond gaming. The only stock I pitched during my internship was NVDA—then worth roughly $18 billion, trading around $0.80 a share, split-adjusted. The fund took a large position (and still hold today), and I bought some too. I didn’t hold it all the way to its peak, but I’m grateful of the returns from the investment. @JensenHuang has created tremendous value for shareholders. Pushing him out is a mistake. After 33 years building NVIDIA, his leadership is still central to its future. NVIDIA and the broader AI developer community still need his leadership and spirit of innovation. (Back then no AI to help on stock research, have to learn those terminologies in this old fashion…😂) Look at the impact Jensen has created to the world, unbelievable. Still can’t believe what just happened. We need a prediction market on this: when will Jensen be back?

Elon, you might have a once-in-a-generation opportunity here: > Hire Jensen (if NVIDIA fires him). > Put Jensen in charge of Terafab. > Give him the resources to build a world-class semiconductor powerhouse. > Challenge the dominance of TSMC, NVIDIA, and other semiconductor giants. > Accelerate Tesla’s AI, robotics, and autonomous driving ambitions. Imagine Elon and Jensen building the next semiconductor empire together! The most entertaining outcome is the most likely.

Cut your AI ad production costs without cutting quality. 🔥 Use Seedance 2.5 on ToAPIs and save 30–60% compared to other API providers. Seedance 2.5 isn’t just for creative videos — it’s built for serious production workflows too. From industrial manufacturing and robotics to autonomous driving, generate high-quality synthetic video for simulation, training, testing, and product demonstrations. In this example, a simple clay render becomes a high-end photorealistic car assembly sequence — preserving the camera work, structure, motion, materials, lighting, and reflections. More production. Lower API cost. See pricing ↓

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.😉