Asif Haque

This is f*cking hilarious: TuSimple's pivot from self-driving trucks to AI animation and gaming! 🤖🎮 Right now, everyone’s betting on humanoid and general-purpose robotics startups. But after 5 years in self-driving tech and building Kopernikus Auto, here’s the reality: most humanoid robotics companies will be dead. In the self-driving world, we’ve only seen a few real winners: Tesla, Waymo, and Comma.ai. Why?  - Humanoid robotics isn’t a hardware problem; it’s a software problem. - You either have infinite data, cash, talent, or a clear use case—or you won’t make it, no matter how much you raise. From over 100 companies, almost all in self-driving tech are dead or miles away from profitability. ✨ Don’t get distracted by the appeal of humanoids. Focus on real problems you can actually solve. What are you focusing on? 👇

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Great story from Fred Grier, Business San Diego, covering the progress of Xiaodi Hou at Bot Auto, and former Founder of TuSimple. Xiaodi Hou, we look forward to your impact on building resilient supply chains in Texas and the nation. Great quote: “We came to Texas because we feel that we need the technology team to be very close to the day-to-day operation of the trucks, . . . it was clear that Texas is the leader in autonomous trucking and is also home to some of the most central freight routes in the U.S., including the I-45 corridor." Texas is leading with autonomous systems deployments - shuttles, cars, trucks, vans, rovers, drones, lawnmowers, construction, . . . . National sovereignty and global productivity will go to the nation that deploys the INTELLIGENT INFRASTRUCTURE enabling Industry 4.0 - impacting the $100 trillion physical world: https://lnkd.in/exXzcJSt Logistics moves the world, and INTELLIGENT INFRASTRUCTURE (the foundation of ARPA-I) will refactor the North American Supply Chain - Canada - USA - Texas - Mexico. Texas is executing large-scale Intelligent Infrastructure deployments to Build a Stronger and More Connected Texas, the State of the Future.  https://lnkd.in/gCiDhbzk The Federal Infrastructure Bank and infrastructure investors are mobilizing $billions in private capital to underwrite Intelligent Infrastructure Economic Zones, which is revitalizing infrastructure in the United States. https://lnkd.in/gWnJD877 Building the Infrastructure for the Next 100 Years. Autonomy Institute https://lnkd.in/gK4-J8qF #infrastructure  #future #supplychains #autonomous #autonomy #transportation  #arpa-i #arpax  #jobs  #bank  #digital  #innovation  #data  #people  #visionzero  #continuumofcapital  #dataexchange  #partnerships  #digitaltwin #privacy #investment #p3programs

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$2 H100s: How the GPU Bubble Burst Last year, H100s were $8/hr if you could get them. Today, there's 7 different resale markets selling them under $2. What happened? The market has flipped from shortage ($8/hr) to oversupplied ($2/hr), because of reserved compute resales, open model finetuning, and decline in new foundation model co’s. Rent instead. https://lnkd.in/gpQEidmC

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🪄✨🤖 Magical AI Experiences 🪄✨🤖 In yesterday’s Stratechery Daily Update, Ben Thompson describes his magical first ride with Waymo: “The ride itself was, on any objective basis, pretty uneventful…What was really surprising to me, though, was how I felt about the entire thing. After Waymo greeted me by name, explained the process (which only happens on your first ride), and dropped me off with a cheery “Happy Friday”, I felt a twinge of — what is this?! — sadness as it drove away. I felt like I had just made a new friend, and now my friend was driving away after too short a time together.” Later in the update, he comments, “What was the most striking was how this experience made me think about Google: I felt a genuine surge of affection for the Internet giant.” ^^This is what we strive for at OfOne (YC W23). With voice AI, restaurant brands have a unique opportunity to rethink and deliver a differentiated brand experiences. When done correctly, AI can be delightful and immersive. We’re working really hard every day to enable our partners to provide this to their customers. The technology is there, and it's getting better every day. The brands that lean in and execute on this well will win customers hearts. Link to article below. If you aren’t yet a subscriber, you should be!

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We’re in the transition phase from value creation through human labour to value creation through machine labour — labour being the key word. The jobs that’ll be replaced first are the most laborious. Three areas stand out: 1. Movement of People & Goods Autonomous vehicles. Wayve, Tesla, Waymo. 2. Movement of Parts Warehousing and robotics. Figure, Tesla. 3. Movement of Information AI agents. OpenAI, Anthropic. My back-of-the-napkin calculation suggests that over 250 billion human hours are spent each year in these areas. From delivering packages to component fabrication or intra-company accounting, we’re headed toward a future where over a billion people will need to rethink how they spend their working time. What’s interesting is that training for these laborious roles is incredibly skill-specific, making them particularly vulnerable to automation. In a way, they’re very non-human tasks, requiring situational awareness within the capabilities of today’s machines. This suggests a stark truth: each year, 250 billion hours of human life are spent enduring non-human behaviours to make a living. The issue? Many adjacent roles face a similar risk, pushing unprepared workers into potentially major career shifts. I think we’re dropping the ball when it comes to preparing today’s workforce for this shift. And we’re certainly failing the workforce of the future through outdated education. The shift to machine labour is happening. It’s glacial — slow, unstoppable, and world-changing. On balance, I think it’s a net positive. Fewer laborious, non-human jobs being done by people. But we need much greater emphasis on preparing people for that change.

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If you think compute scaling will plateau, think again. We are in the baby states of inference time compute. VLLMs coupled with computer tools, reward learning and RL can leverage orders of magnitude more inference time compute than what we have seen with foundation models. Here’s a concrete training architecture (replace \pi with a large pre-trained vLLM and add it to the reward learner too, \R is the space of all computer tools)

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NEW: Ex-TuSimple CEO and cofounder launches a new robot truck startup Xiaodi Hou, the cofounder and CTO behind the failed startup TuSimple, is making another attempt to master robotic trucking. His new company just raised $20 million from venture investors and aims to launch commercial operations next year. Houston-based Bot Auto plans to operate autonomous semis on highway routes in Texas, hauling freight between warehouses and logistics facilities in Houston and San Antonio. Unlike San Diego-based TuSimple, which delisted shares early this year after a major implosion, the new company will own and operate its trucks directly rather than provide autonomous cargo-hauling technology as a service, Hou said. #selfdriving #trucking

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This week I rode in a Waymo for the first time and it immediately made me think of the parallels between autonomous vehicles and smart home technology. Both are about taking complex and inefficient systems, removing friction, and creating a seamless experience for the user. With Waymo there’s no driver to guide the car yet everything feels intuitive and effortless. In smart home tech it’s the same goal: to give people solutions that simplify their lives—whether it’s automating temperature control, streamlining access, energy efficiency or customization. What excites me most is how these technologies are evolving to not just meet expectations but exceed them. The common thread is efficiency and time—freeing people to focus on the things that matter most. It’s amazing to see how these innovations are redefining industries and how much potential there is ahead. Smart tech isn’t just about convenience—it’s about creating a better way to live.

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***The Future of Mobility is Here! 🚖 Waymo, Alphabet's self-driving unit, has just secured $5.6 billion in funding Exciting news in the world of autonomous vehicles! Waymo, Alphabet's self-driving unit, has just secured $5.6 billion in funding to supercharge its robotaxi services across the United States. This investment marks a significant leap forward in the race to revolutionize urban transportation. With this funding, Waymo aims to expand its operations beyond its current markets of Los Angeles, San Francisco, and Phoenix, bringing its innovative ride-hailing service to new cities like Austin and Atlanta. Co-CEOs Tekedra Mawakana and Dmitri Dolgov are committed to advancing their technology, ensuring that more riders can experience the convenience and safety of Waymo's autonomous vehicles. As the only company operating a commercial robotaxi service in major metro areas, Waymo is setting the standard for the future of mobility. With over 100,000 weekly trips already being conducted, the demand for safe, reliable, and efficient transportation is clear. This funding will not only enhance their fleet but also improve the Waymo Driver technology, making it even more robust for business applications. The Robotaxi race is heating up, and Waymo is leading the charge! As we witness this transformation in transportation, it's an exciting time to be part of the tech and mobility sectors. Let's embrace the future of travel and the possibilities that autonomous vehicles bring to our cities!

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YC put together a great video on how OpenAI’s o1 chain of thought works. Now that o1 is out of preview and in full prod, it’s a good time to understand more about what’s going on under-the-hood. Reasoning models change everything when it comes to using LLMs. Everything you learned about prompting to-date has changed. That being said, I’m no expert, and I don’t have any special course or guidebook for you. But safe to say there are a zillion people out there now selling courses, guides, etc. so take your pick! Link to YC’s video in the comment section below 🎥 🍿 ⬇️

My cofounder Saumil goes on the Stack Overflow Podcast to deep dive on AI Agents! He goes into detail how we leverage AI agents to power automated workflows to accomplish the most complex tasks. Including agents firing off tasks to other agents to tackle the details. Need an agent to verify your work? No problem. Give it a listen and let us know what you think!

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AI is reshaping how enterprise software delivers—and prices—value. Companies like Zendesk, Intercom, and Forethought are shifting to outcome-based pricing, charging only when AI autonomously resolves issues. I've been investing in AI for over a decade. The shift to outcome-based pricing in enterprise software is a seismic change. As I told Jon Victor at The Information, software companies now face a critical decision: Does a company decide to change business models at the expense of losing revenue? It's a necessary risk. With cheap access to LLMs, businesses can build their own enterprise apps. Adapt or die. Why this pricing shift matters: → Vendor success ties directly to customer outcomes → Short-term revenue risks enable long-term market expansion → Industry faces widespread pressure to demonstrate measurable value Pitching AI-powered automation software as a clear cost-reduction tool could ultimately lead to greater revenue for vendors. This is because customers may view AI solutions as fundamentally different from traditional enterprise apps, whose business value is often harder to quantify directly. It's a huge market expansion opportunity. Vendors that nail outcome-based pricing could see massive growth as AI transforms enterprise operations. Those that don't? 😬🫣 How do you see this impacting sectors beyond customer support? Leave a comment. And if you're building in this space, send me a message.

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I spent over half a decade working with driverless cars. I see massive potential for these vehicles to reshape NYC real estate. Waymo recently raised $5.6 billion in a Series C round led by Alphabet and supported by many other leading companies. Meaning the future of this technology feels closer than ever. These are the biggest Opportunities & Challenges Driverless cars present in the NYC market: 1. Reduced need for parking could free up valuable urban space, converting parking lots into housing, retail, or green areas. 2. Easier commutes may drive up outer borough property values, balancing Manhattan and other more densely populated areas of the City 3. NYC’s notorious traffic, pushback from unions on automation, unpredictable weather, and high foot traffic require advanced tech and regulatory adaptation. The next steps will be crucial as real estate, tech, and policy leaders navigate how driverless cars might reimagine our cities. How do you think driverless tech will impact real estate in NYC? P.S This is me in a driverless car back in 2017

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Alphabet committed another $5 billion recently to Waymo's self-driving cars. A renewed vow of confidence. Per my post yesterday, fast growing additional compute and better AI architectures are changing self driving cars rapidly. Notably, some traditional car manufacturers pulled out investments in full self-driving cars. It didn't think the tech was going to be ready for decades to come, if ever. I think it may be a mistake given AI and compute grow exponentially, not linearly. As an example, it may take 20-40 years to achieve 1% of progress, then just 5-10 years for the remaining 99% (instead of 1,000s of years per our intuition) link in comments #AI #Transformers #waymo

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"AI is powerful, but without the right data foundation, it’s just noise." In the latest Tech Teams Today podcast episode, I had a great conversation with Yongsheng Wu, VP of Engineering at Granica, about why a solid data foundation is crucial for AI success. Here are the top insights from the episode: 1️⃣ Data Foundations Matter: Before diving into AI, ensure your data systems are robust. Solid pipelines & data integrity are critical for meaningful insights. 2️⃣ AI as an Enhancer: AI and ML should optimize existing processes, not solve undefined problems. 3️⃣ Data Quality is King: Curating and labeling data accurately is vital for effective AI models. The better the data, the better the outcomes. 4️⃣ Efficiency & Cost-Effectiveness: Successful AI solutions balance effectiveness with cost efficiency, especially as models scale. Catch the full episode on all major podcast platforms or watch it on YouTube: https://lnkd.in/dbkE__JC #AI #EngineeringLeadership #DataScience #MachineLearning #TechTeamsToday

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Having worked at Cruise and Waymo on self-driving taught me many things. I hope to bring some of these learnings to healthcare so it too can soon have the magical, "no-driver-at-the-wheel" moment. Here's a short conversation I had with Louie Cai, MD on this topic!

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