Arun Chetty

Sustained ~252–291 GiB/s of HBM memory throughput on H100s under decode load — essentially hitting the hardware roofline. This matters because HBM throughput, not FLOPs, is the real bottleneck in LLM inference. By keeping memory nearly fully saturated, I’ve unlocked far higher efficiency and throughput than standard engines. The result: 0.9–1.36M tokens/sec with ~0.1 ms first-token latency  #AI #LLM #GPURouter #H100 #Inference #CostEfficiency #Innovation #DeepLearning #AIInfrastructure #HighPerformanceComputing NVIDIA AMD OpenAI Google Shilpa Kolhatkar Keith Strier a16z speedrun

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I’m lucky to work alongside colleagues like Richard Fruehauf, who constantly push my thinking. His latest piece unpacks why U.S. robotics and drone manufacturing faces uphill economics, and how public policy can help turn the tide. One key takeaway: 232 tariffs on robotics imports could help reset the economics that are holding back U.S. investment and production. It’s a sharp perspective on how policy can shape the future of advanced tech here at home. Well worth a read: https://lnkd.in/edMPTQPQ Richard Fruehauf, Robert J. Szczerba, Michael Lutzky, Edward Ovando, Karl Sanchack, Herman Herman, Jeff Legault, Phil English, Richard Fruehauf, Ryan Aument, Michael Guido, Sheila Fitzgerald Sterrett, David McCormick

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Navigating the Future of Mobility: Safety Concerns in Autonomous Technology The recent incident involving a Waymo robotaxi hitting a child near a Santa Monica elementary school underscores the critical importance of safety in the rapidly evolving autonomous vehicle sector. As stakeholders in venture capital, we must prioritize understanding the regulatory landscape and invest in companies that prioritize child and pedestrian safety. How do you think incidents like this will shape public perception and regulatory frameworks for autonomous technologies? #investing #innovation #venturecapital #entrepreneurship

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For decades, robots have been designed for narrow, repetitive tasks in highly structured environments. But as AI advances, we’re moving into an era where robots can operate in dynamic, unstructured settings, like homes, hospitals, warehouses, and beyond. That’s what makes Figure unique – they aren’t just building humanoid robots, they’re creating a scalable platform that combines cutting-edge AI with human-like form and function. By unlocking entirely new categories of safe and productive work for machines, Figure is augmenting human capability rather than replacing it. At Intel Capital we are thrilled with Figure’s progress in bridging the gap between robotics research and real-world, commercially-viable applications. Excited to continue this journey with Brett Adcock and the team.

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#AmTech Weekly Roundup: Ambience Healthcare raised $243 million in Series C funding from Oak HC/FT, Andreessen Horowitz, OpenAI, Kleiner Perkins, Optum Ventures, and Town Hall Ventures. Ambience is building AI documentation software to record patient appointments, generate comprehensive medical notes, and standardize coding/authorization workflows.   Michael Ng, Nikhil Buduma    Reveal Technology raised $30 million in Series B funding from Ballistic Ventures, Shield Capital, Booz Allen Hamilton, and others. Reveal’s two main offerings are 3D mappings generated from drone videos and mobile biometrics. They are deployed with the US Army, Special Operations Command, Marine Corps, and other NATO forces.   Garrett Smith    Prophet Security raised $30 million in Series A funding from Accel and Bain Capital Ventures. Prophet is applying agentic AI to Security Operations Centers (SOCs), or hubs for cybersecurity defenses within an organization.  Kamal Shah, Vibhav Sreekanti #VC #HealthTech #Healthcare #Defense #Cybersecurity

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You can have groundbreaking science, elegant engineering, and even early customer interest. But without this one thing, you don't have an investable business. After two decades running IP strategy projects and now leading UC Berkeley's Deep Tech Innovation Lab while building the Berkeley Gateway Accelerator, I've watched countless brilliant technologies die in the valley between breakthrough and business. The problem isn't what most technical founders think it is. It's not about having better tech. It's not about getting more funding. It's not even about finding product-market fit. The fatal flaw shows up much earlier—and it's almost always the same mistake. In my latest piece, I answer questions from a Taiwanese entrepreneur about what really separates deep tech ventures that scale from those that stall. Including one provocative suggestion for Asian ecosystems that has nothing to do with technology. Read the full conversation, linked below. #DeepTech #Innovation #Startups #IntellectualProperty #VentureCapital

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As AI workloads eat up global computing supply, DRAM prices are surging like never before—creating major challenges for teams trying to plan out their data center spend. One of my portfolio companies, Mext, is addressing the largest cost component in the datacenter: server memory (DRAM). From being on the board of Redis for the last twelve years, I’ve learned a lot about the various aspects of this problem and approaches to solving them. Mext found a breakthrough, using new AI techniques, for dramatically reducing the amount of server-DRAM required to run applications, all while maintaining performance. It intelligently manages the server’s memory, keeping hot pages (i.e., those in use by applications) in fast DRAM and offloading cold pages (i.e., those less used) to a much less expensive memory tier (e.g., NVMe Flash). Key to the approach is ensuring cold memory pages that are about to be accessed by an application are back in DRAM before the application needs them or notices that they were gone. This is done without modifications to the application or the OS – so it can run in the cloud or on-premise. Mext thus allows applications to either run using less DRAM or keep their DRAM footprint but do more with it. They're hosting a webinar along with Fred Weber (former CTO of AMD) on Jan 22nd at 10am pacific time. You can register here: https://lnkd.in/gXe9GCeE

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