Angelo Huang

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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If you are working with Docker... I highly recommend looking at the Slim toolkit. https://lnkd.in/gX_Gb9Kf Why? Slim allows developers to inspect, optimize, and debug their containers using its xray, lint, build, debug, run, images, merge, registry, vulnerability (and other) commands. It simplifies and improves your developer experience building, customizing and using containers. It makes your containers better, smaller and more secure while providing advanced visibility and improved usability working with the original and minified containers. Don't change anything in your container image; minify it by up to 30x to make it secure, too! Optimizing images isn't the only thing it can do, though. It can also help you understand and author better container images. Keep doing what you are doing. No need to change anything. Use the base image you want. Use the package manager you want. Don't worry about hand-optimizing your Dockerfile. You shouldn't have to throw away your tools and your workflow to have small container images. Node.js application images: from ubuntu:14.04 - 432MB => 14MB (minified by 30.85X) from debian:jessie - 406MB => 25.1MB (minified by 16.21X) from node:alpine - 66.7MB => 34.7MB (minified by 1.92X) from node:distroless - 72.7MB => 39.7MB (minified by 1.83X) Go application images: from golang:latest - 700MB => 1.56MB (minified by 448.76X) from ubuntu:14.04 - 531MB => 1.87MB (minified by 284.10X) from golang:alpine - 258MB => 1.56MB (minified by 165.61X) from centos:7 - 615MB => 1.87MB (minified by 329.14X) Rust application images: from rust:1.31 - 2GB => 14MB (minified by 147.16X) Java application images: from ubuntu:14.04 - 743.6 MB => 100.3 MB

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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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As I educate myself in the venture capital realm, I learn about the ups and downs of the startup world. The Lacework news is interesting because when a startup is overvalued, it means its market price is higher than its true business value. If it's later bought for much less than its inflated valuation, it indicates that the market has corrected its perception of the company's worth. This situation can be tough for the original investors and founders who may face significant financial losses, as they won't get back as much money as they expected. It can also affect the startup's reputation and the morale of its team, as such a stark adjustment in value can lead to doubts about the business’s viability and future prospects. Not sure if this is true for this situation, but I have been told it occurs more often than not. #VC #stealth #startups #cloud #cybersecurity #VentureCapital #learnNewThings

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If you are an existing Elastic customer and use Langchain for your GenAI stack, you can now use Langtrace to gain visibility into your GenAI layer by following this guide! 👇 Grateful to the GenAI Observability team at Elastic! h/t to Bahubali Shetti and Adrian Cole!

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We've had a blast at AI Engineer – the energy is electric, and the current moment is clearly such a unique time and place in software. Bullish on conferences. Nothing quite like walking through the product live, seeing that moment when it clicks in full HD. There's a certain kind of conviction that can only be built through this kind of rapid-fire, on-the-ground repetition... I'm now fully convinced that: (1) We're the first and only multi-inference API (2) We have the best programming model for building computation graphs Good design is invisible. With Substrate, you don't even realize you're building a graph. You don't have to learn any new unwieldy abstractions. You never "deploy" anything. But you get all the benefits of an advanced distributed system every time you run a graph.

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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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Exciting news for teams leveraging monorepos! Coherence now supports glob patterns for selective build configuration, bringing unprecedented efficiency to your development pipeline. 🔧 Technical Highlights: • Granular control over build and deploy processes • Intelligent file change detection • Seamless integration with existing CI/CD workflows 💡 Key Advantages: 1. Dramatic reduction in build and deploy times 2. Optimized resource allocation 3. Precision targeting of updates for changed code only 🏗️ Real-world Impact: • Accelerated development cycles • Enhanced productivity for large-scale projects • Significant cost savings on computational resources This feature empowers you to fine-tune your build process, ensuring only necessary services are built and deployed based on actual code changes. It's a game-changer for maintaining velocity in complex, multi-service architectures. Ready to supercharge your monorepo? Dive into our comprehensive documentation to implement selective builds and experience the future of efficient development.

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And that was a wrap! As #apisummit24 completes with over 10,000 attendees from the API community - making it the largest API conference by far - with dozens of awesome product and partner launches to show what we can do with *the API platform for the AI era*... one fundamental question remains open: Are you on the right side of AI? One thing we know for sure... APIs are the common language of LLMs as we build apps and transform our business with {Gen} AI. In this post, I wrote a few thoughts from my opening keynote on the API market evolution that's ahead of us. Lmk what you think!

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Big news from Cephable! This team is transforming interactions with the digital world and creating the accessible future we all deserve. There is nothing better than investing in leaders like Alexander Dunn. Congratulations Cephable and thank you for including Hyperplane in your journey! ➡️ See them in action (I still get goosebumps): https://lnkd.in/eHfCp3iD ➡️ Read the full release here: https://lnkd.in/e68MS2CP

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Okay, now this is seriously a cool event and a good idea, and you should click the link and register now. But bear with me in this AI experiment. Read on, including the comments... Hey Kafka developers! 📢 Mark your calendars for Confluent AI Day on Oct. 23 in the Bay Area. 🗓️ Dive into data streaming, Flink, and real-time Gen AI applications, including retrieval augmented generation, or RAG, architectures. Gain insights, join Q&A sessions, and explore Gen AI demo tutorials. 🚀 MongoDB and AWS will be there to guide you with vector embedding. Don't miss the hackathon with $30K in prizes! 🏆 Register now:  https://lnkd.in/gSZZVDV5 🌟 #Kafka #ConfluentAIDay #DataStreaming #Flink #GenAI #RAG #MongoDB #AWS #Hackathon #AI #Developers #TechEvent

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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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Our revamped newsletter, The Angle by Angular Ventures, officially launched today! We hope this new format will make it easier to read, share, and subscribe. Back to it, in this week's column, Gil Dibner covered the spirit of risk-taking that inspired Angular to venture into unusual spaces. While, of course, we invest in AI and SaaS, as of late, we have been investing in more and more contrarian spaces - from quantum, to spacetech, to energy, etc. in search of the supposedly impossible - the truly contrarian. Read the full column via the link.

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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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🚀🚀 We are excited to announce the integration of Langtrace with AWS Bedrock. If you are building AI apps on Amazon Web Services (AWS) Bedrock, all it takes is just 2 lines of code to setup tracing for your AI applications so you can gain deep visibility and insights. Also, you can host Langtrace on AWS in less than 10minutes because Langtrace is fully open source.

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Amazing turnout & insightful discussion for our AI x Blockchain event!! More to come

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Are we building too much supply side infrastructure for AI? Will revenue ever catch up? I discussed these questions and more with Laura Chau, partner at Canaan, in episode 452 of The Full Ratchet. Tune in today to catch our full discussion. Link to the full episode is in the comment section below.

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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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