Jean-Mathieu Chabas

During yesterday's LibreQoS APNIC webinar, I posed the question: won't more bandwidth solve these problems? As Herbert Wolverson said, yes, more bandwidth is good, but, still these problems remain if queueing is done incorrectly. Here's my take on why bandwidth alone is not as good as bandwidth + good queueing policies: Generally it was believed that 'data is important, so don't throw it away; hang on to it and send it later'. In practice, this has proven to be suboptimal as two issues may emerge: 1) latency increases for some flows due to heavy demand from other flows using the same bottleneck link, 2) even a single flow can have excessive latency due to aspects of typical TCP behavior (referred to bufferbloat) when the buffers grew large enough that the data being buffered was retransmitted anyway. It turns out that not all data is equally important. Active Queue Management is the art of deciding priorities, both in deciding what data to throw away, but also in allowing some later arriving data to be transmitted ahead of data in another connection that arrived before it. These problems have been studied, and good solutions have been found by using certain queueing policies in routers and switches, referred to as “fq_codel’ and “cake”. These track the different flows not by classifying the data, but by watching the behavior. Flows that send relatively little data (DNS lookups), or at a measured pace (video chat) have priority over flows that send a lot of data as quickly as possible (App and System updates, Video and ISO downloads).

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"Editors note: Welcome to issue #2 of Transcriptions. Today, we’d like to present a conversation between Qasar Younis of Applied Intuition, and Bilal Zuberi of Lux Capital. We discovered Qasar recently, and find his focus and clarity of thinking to be admirable. What follows is a lightly edited transcript of their talk, first held at the Paklaunch forum." Link to transcipt: https://lnkd.in/gH4uBmPE

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Instacart is a market leader when it comes to leveraging AI tools to boost productivity at work. I had an amazing conversation with JJ Zhuang, Instacart’s Chief Architect, who has shepherded over 50 AI-driven initiatives to market across the org. We explored what catapulted Instacart to the forefront of AI integration, supporting radically diverse use cases across various functional areas. One striking insight (echoed by Ethan Mollick and others elsewhere) is that you often don't need specialized tools for specialized work. Frontier models like GPT-4 can seamlessly adapt to a wide range of functions and use cases. They're not just for engineers; they're incredibly versatile tools used by marketing, comms, and legal teams. From generating code to proofreading and ideation, GPT-4 empowers every department to leverage AI for enhanced productivity and innovation. By integrating LLM’s like GPT-4 into their workflows, teams can streamline processes, automate repetitive tasks, and unlock bandwidth for new creative possibilities. How can you harness the power of AI in your own work to boost productivity? Share your thoughts below 👇 Want to hear more insights from JJ? Check out the full podcast episode by clicking the link in the comments.

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Ever since we launched SHAKTI, every quarter we write a letter to our LPs = Each letter includes an update on the portfolios, the GP's (our) view on the zeitgeist, an interview with a portfolio CEO and an interview with a TITAN = So far, we have 16 such letters = it's been on our "to do" list to share these publicly (i am lazy) = then Google comes along to save lazy people like me (thank you NotebookLLM) = here's a 10 min podcast summarizing our journey since Dec/2020 with the 16 LP letters as source = if you wanted to know what we are about, this is a pretty good place to start = https://lnkd.in/db7K2TrT cc SHAKTI

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Loved bringing together a group of research-centric, product-minded technologists building the future of AI tonight in the 🅱️🍎, incl. product / eng leadership @ NVIDIA, Pinecone, Datadog; founding eng @ Abnormal Security, Modal, Counsel Health; applied AI @ OpenAI, Anthropic; research eng @ Meta (FAIR), Harvey, Google DeepMind; founders @ Sapien and some of NYC's greatest stealth AI co's ☄ We covered a lot of ground over 4 hours - some of the recurring themes in our conversations: - Agents:🕴Model inference is getting so much faster, which will unlock AI agents' potential. That said, agents should be trained to handle very narrow tasks, reliably, first vs. an open-ended approach many startups are attempting today - Robotics: 🤖 While the science is not there yet, the robotics market and its impact will be much bigger than LLM. The introduction of humanoids will fundamentally change how we live. That said, the U.S. is in a vulnerable position due to lack of supply chain independence, compared to rivals like China - Value creation: ✨ AI personalization is overrated as consumers mostly care about status (i.e., ‘whatever is the best’) vs. what's tailored to them. Delivering great UX is still hugely undervalued, for both enterprise and consumer use cases. Cost and reliability remain enterprise buyers' front-and-center priorities. AI can preserve endangered rare languages by documenting and creating digital archives / databases cc: our amazing sponsor Arc (Brendan Bettencourt, Erika Bricky, Eric Lo), Visible Ventures

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Today, I was reminded of two remarkably prescient 1997 ACM, Association for Computing Machinery presentations: the first by Nathan Myhrvold and the second by Bran Ferran. If you are not a member of the ACM - I highly recommend joining. Nathan Myhrvold The future of software, the software industry, and Windows '47 https://lnkd.in/egMwYty Bran Ferran How IT will transform the experience of telling and listening to stories https://lnkd.in/gqF7C7TK

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I've been thinking a lot about how Tesla's vehicle infrastructure can leverage inference compute, distributing computational load and reducing data center energy usage. Dr. John Gibb does a nice job of summarizing these concepts in his video (Starting around 8:10). Inference Arbitrage: A Game Changer for AI Compute As AI continues to evolve, the demand for computational power is skyrocketing. Giants like OpenAI, Meta, and Google are pouring billions into training and inference compute, facing looming shortages of transformers and electricity. Here's where inference arbitrage, a novel concept leveraging Tesla's infrastructure, comes into play. The Challenge: Soaring AI Compute Costs Leading AI companies are investing billions to power their AI programs. However, the energy and computational needs are outpacing infrastructure capabilities. This bottleneck isn't just financial; it's physical. The growing demand for AI services could soon exceed available power and hardware. The Solution: Inference on the Edge xAI, in collaboration with Tesla, offers a groundbreaking solution: using Tesla vehicles for AI inference tasks. Tesla's fleet, equipped with powerful hardware and large batteries, can perform AI inference during idle times (about 90% of the time), reducing strain on central data centers How Inference Arbitrage Works Distributed Computing: Instead of relying solely on massive, centralized compute farms, inference requests (e.g., generating an email or image) are processed by idle Tesla vehicles. This distributed approach taps into the existing infrastructure efficiently. Energy Optimization: Tesla vehicles can perform inference tasks using their batteries during peak electricity demand times, avoiding high energy costs. At off-peak times, they recharge at lower costs, ensuring energy-efficient operations. Commercial Benefits: This model allows Tesla owners to earn money by utilizing their vehicle's idle time for AI computations. Tesla benefits from additional revenue streams with minimal overhead, and xAI gains a scalable, cost-effective solution for AI service delivery. Impact on the AI Industry By integrating AI inference with Tesla's distributed compute network, xAI can deliver services faster and more economically than competitors. This innovative use of existing resources not only addresses the infrastructure bottleneck but also offers a sustainable path forward for AI growth. Conclusion Inference arbitrage provides a strategic edge for xAI and Tesla, combining AI innovation with smart energy use. As the demand for AI compute continues to rise, this approach could redefine the landscape, positioning xAI and Tesla as leaders in efficient, scalable AI service delivery. Stay tuned as this exciting development unfolds and reshapes the future of AI. #ElectricVehicles #InferenceCompute #DataCenters #Electrification #AI #FrontierTechnology #FutureFrontier

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DeepCast shipped a number of really cool new features recently in advance of a broad outreach push to podcast listeners. One new feature is our new Daily DeepDigest tool that sends you a concise daily email including any new episodes from the trailing 24 hours from any podcasts you Subscribe to (on DeepCast). Think daily podcast cliff notes or podcast news ticker tape, with a hint of Morning Brew various brews or PitchBook News—it's increasing information throughput when you're pressed for time. And this feature is rapidly evolving to distill other key extractions from shows you're already interested in, but also exposing you to other shows you might be unfamiliar with that also have nuggets to share—and thus increasing your aperture yet still conscious of your time. Want to go deeper on any given episode? Click the episode detail and you're off to an episode on DeepCast, where you can subsequently read a longer form distillation of that episode or go straight to the source and listen to the episode. (And podcaster friends, these pages are definitely increasing indexing and thus Google entry points to your shows!) I'm loving this feature as a user, personally. Can't wait to see what others think! #BuildingInPublic #Podcasts #AllTheWorldsInformation #HowYouWantIt

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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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I'm always happy and proud to hear our early investors at REFASHIOND Ventures: The Industrial Transformation Fund talk about the work they are doing. Each of them is having real impact in building supply chains for tomorrow. In this podcast Zac talks about the underlying infrastructure for what what I describe as Information and Data Supply Chains. This is worth listening to if you want to get into some of the issues that will determine the future of Physical Supply Chains. #TWSCF #TNYSCM | The past ran on supply chains. The present runs on supply chains. The future will run on supply chains. The world is a supply chain.®

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Super helpful article and accompanying doc with a #Startup #Equity Calculator to determine the equity for early hires, thanks to Pear VC head of talent Matt Birnbaum! Thanks for sharing Pejman Nozad! 🙏🏼 You can read more here How to structure startup equity for early hires: https://lnkd.in/ggmpT5-Y Google Doc: https://lnkd.in/gjsvths6

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This is quite a piece on accusations of unethical pay-to-play within the #cyber #VC ecosystem. -Guaranteed first-year sales for portfolio companies -Formal loyalty program for CISOs -Points awarded within the program for CISO commitment level to portfolio companies (meetings, PoCs, product purchases) -Share of GP fees for CISOs in the loyalty program https://lnkd.in/gDta7Gp7

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I’m excited to share this one! Redactive has raised a $11.5M seed round -- their mission is to become the trusted GenAI engineer for enterprise teams. Blackbird co-led this round alongside Felicis with participation from Atlassian Ventures and Zapier. Andrew, Alexander and Lucas are working to solve an urgent problem hidden in plain sight – empowering GenAI applications to meet their promise of "magic" in an enterprise setting. GenAI applications are only as useful as the data that they have access to, and for most enterprises, the most valuable data is sensitive and permissioned. We all want a chatbot (“ChatGPT for…”) at work that can search the data that we share in private Slack conversations or store in private folders on Sharepoint but first, we need to trust that our data will be kept safe – from prying eyes and accidental disclosure to others in the organisation who should not see it. Redactive keeps your sensitive data safe, giving developers the trust to connect it to GenAI applications and build products that you will love. Here's to the next decade. https://lnkd.in/gPuEAFvW

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How companies purchase software is rapidly evolving, with cloud marketplaces expected to reach $100B in 2026, up from $15B in 2023. Simply put, if you are building and selling cloud software today, it's imperative that you can sell through a cloud marketplace. The journey, however, can be a little confusing, and management can be even harder. With 3x growth last year and 3/4th of our business now flowing through a cloud marketplace, CloudZero switched to Clazar earlier this year to handle our rapid growth, and I couldn't be more thrilled. Trunal B. and Aayush Bahuguna have a big vision for how cloud marketplaces will evolve and how software will be bought and sold in the future. No matter where you are on your journey, learning from them what's coming next is worth your time.

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Let's finally get rid off the "VC alphabet song" and redo the system to become more founder friendly. "The benchmarks set by funding stages are often arbitrary and not necessarily aligned with the actual development needs of individual startups." #vc #venturecapital #founder #fundraising #startups #fundingstages #funding #fundingrounds #pitchbook

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🧙‍♂️ My friend Gandalf dropping some real SaaS wisdom in his latest podcast episode: Took the new Runway ACT-1 for a little test drive yesterday. What do you think? 😃 Steps: 1. Open Runway Act-1 2. Record or upload a reference video of yourself 3. Create or upload a reference image (used Midjourney) 4. Click "Generate" (no prompt needed) 5. Final video edits with VEED.IO

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Here are the Top 10 SaaS funding rounds of the past week (Seed to A) Starting at number 1... 🥇 Emergence, $97.2mm Seed 🤯 Emergence is developing an AI "agent-based" system that automates tasks typically performed by knowledge workers. Founded by Satya Nitta. 💸 Investors: Learn 🔗 https://bit.ly/3XSitTA 🟠🟠🟠 🥈 Formic, $27.4mm Series A Formic enables manufacturers to scale faster by making it easy to deploy robotic automations, like packing and palletizing. Founded by Misa Ilkhechi and Saman Farid. 💸 Investors: Blackhorn Ventures, FJ Labs, and more 🔗 https://bit.ly/3XGzEYr 🟠🟠🟠 🥉 normai, $27mm Series A Norm Ai is automating compliance processes, making them more efficient, cost-effective, and accurate via (you guessed it) AI. Founded by John Nay. 💸 Investors: Coatue, Bain Capital Ventures, and more 🔗 https://bit.ly/4ckpNft 🟠🟠🟠 🎖️ 4. ORA, $20mm Series A Ora is a blockchain project incorporating AI into dapps. Founded by Kartin Wong. 💸 Investors: Polychain Labs, HF0, and more 🔗 https://bit.ly/3zpW7Ph 🟠🟠🟠 🎖️ 5. Payabli, $20mm Series A Payabli builds the infrastructure that allows companies, specifically software companies, to embed and facilitate payments through APIs. Founded by Joseph Elias Phillips and William Corbera. 💸 Investors: QED Investors, Bling Capital, and more 🔗 https://bit.ly/4bwkGHE 🟠🟠🟠 🎖️ 6. Sift, $17.5mm Series A Sift develops tools to accelerate the development and ensure the reliability of complex machines (think Spacecrafts). Founded by Austin Spiegel and Karthik Gollapudi. 💸 Investors: GV (Google Ventures) 🔗 https://bit.ly/3L7zlyk 🟠🟠🟠 🎖️ 7. Ario, $16mm Seed Ario is an AI-powered assistant for parents that helps with daily tasks, from meal planning to scheduling playdates. Founded by Sumit Agarwal. 💸 Investors: Wing Venture Capital, Floodgate, and more 🔗 https://bit.ly/4eEjeG9 🟠🟠🟠 🎖️ 8. MagicSchool AI, $15mm Series A MagicSchool provides lesson-planning solutions for teachers to fight burnout. Founded by Adeel Khan. 💸 Investors: Bain Capital Ventures, Adobe Ventures and more 🔗 https://bit.ly/3RQt5Pn 🟠🟠🟠 🎖️ 9. AuthZed, $12mm Series A Authzed makes it easier for developers to build permissions in their applications. Founded by Jacob Moshenko and Jimmy Zelinskie. 💸 Investors: General Catalyst, Work-Bench, and more 🔗 https://bit.ly/4bqkh9B 🟠🟠🟠 🎖️ 10. SLUSHY.com, $10.2mm Seed SLUSHY is a creator monetization platform. Founded by David Gross and Fred Sprivock. 💸 Investors: Mantis Venture Capital, Jon Oringer, and more 🔗 https://bit.ly/4eN9Boi ⚫⚫⚫ I'm Gyan, Head of Community at Venture House. I create tools, guides, and other free resources for Junior VCs and founders. If you found this helpful, check out the Venture House website for more 👇 https://venturehouse.xyz/ #startups #venturecapital #funding #saas

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Day 13: Case Study: The Analog Ecosystem Powering Dynamic Neural Networks Imagine a supply chain that organizes itself, aligned to shared goals in real-time. That’s what we accomplished in the Australian fresh produce industry—a system once weighed down by inefficiencies, waste, and unpredictability. It was fragmented, reactive, and out of sync. The challenge was clear: How do we fix it? The solution wasn’t just to tweak the system, but to reimagine it completely. We stopped thinking of it as a traditional supply chain and envisioned it as a living ecosystem. An analog ecosystem powered by collaboration. We introduced ‘One Touch,’ a simple yet revolutionary system that connected growers, manufacturers, wholesalers, and retailers in real-time. They could see exactly what was happening in the supply chain, at every moment. Inventory, demand, availability—all dynamically adjusting, like neurons responding to live data. The impact? Over a billion dollars saved. Waste slashed. Inventory moved faster. What was once a broken system is now self-organizing, adapting, and thriving. This is the power of thinking differently. When you create an ecosystem that evolves with the world, it transforms how we live, work, and trade. Now, we’ve taken that analog ecosystem and digitally twinned it with a Dynamic Neural Network. And this is just the beginning of what’s possible. #SupplyChain #Sustainability #Innovation #ai #machine #NeuralNetworks #BalancedEcosystemScorecard

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Founderville believes one of the most significant opportunities is emerging in legacy system applications. We look for manual tasks to leverage AI for efficient automation. Rather than chasing massive TAM, which will be addressed by larger VCs, we focus on smaller market domains that won't be chased as hard. Think of "boring" processes that require human intervention or manualized tasks. Those are opportunities. Keep your eyes open if you have deep domain expertise in a non-automated and fragmented industry. #entrepreneurs #venturecapital #startups #saas

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