Oliver Koo

Want a preview of what I'm going to be talking about in my keynote for RubyConf? You can catch a glimpse of it here!

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𝗔𝗿𝗲 𝘆𝗼𝘂 𝗹𝗼𝘀𝗶𝗻𝗴 𝘀𝗹𝗲𝗲𝗽 💤 ? because you can't pinpoint your CI bottlenecks or spot problematic trends? At Pinterest, we faced the same challenges—but we’ve found a solution. 🌟 In our latest Pinterest Engineering blog post 🔗 https://lnkd.in/eJJ_GpGW We share how we’re leveraging honeycomb.io to identify CI root causes through cross-data correlations. Discover our innovative approach for categorizing CI failures in real-time using job log analysis. Learn how to segment CI jobs by agent wait time, script execution, specific Bazel targets, or any other level of detail tailored to your needs. Our enhanced CI observability metrics have let us improve CI stability and boost developer productivity—and they could do the same for you! Check out the blog for the full breakdown and see what’s possible when data-driven decisions guide your CI workflows. 🚀 Let’s make CI faster and more reliable together! #DevOps #DevX #CICD #honeycomb #observability #engineering #softwareengineer

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Leverage StarCoder 2, a powerful LLM for code generation, completion, summarization, and documentation. Try the now available NVIDIA-hosted StarCoder 2 API, packaged as NIM inference microservice for free from the NVIDIA API catalog. https://bit.ly/3y8fyvB

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This morning I've got a guest post on Google's Open Source Programs Office blog: what to do when your open source contribution stalls out. There are posts and posts about how to improve contributor experiences from the maintainer side, but I couldn't find much about how to push through a rough contribution process from the contributor side. Turns out you, as a contributor, actually have quite a lot of power here! I wrote down some of the strategies that have worked for me and my team as we contribute to the Git project; they apply for open source work, but also for any kind of decision stalling out. https://lnkd.in/g3eD6W4N

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🕶️ Google's XR comeback, Waymo's rise, and Netflix's parental leave plot twist – oh my! Just wrapped up the latest edition of The Compiler, and it's a wild ride through tech town. Here's what caught my eye: 1. Google's dusting off its AR/VR playbook with Android XR. It's like they saw Apple's Vision Pro and said, "Hold my Pixel." Will it be Google Glass 2.0 or an actual contender? Place your bets! 🎰 2. Waymo's robotaxis are dominating SF faster than sourdough trends. Human drivers, it might be time to learn to code... or befriend our new robot overlords. 🤖🚕 3. Netflix just hit "skip intro" on its unlimited parental leave policy. Guess "Netflix and chill" doesn't apply to new parents anymore. Is this the end of their cool workplace culture, or just adulting kicking in? 👶💼 Plus, OpenAI's Sora is making Hollywood nervous, Reddit's cutting out Google as the middleman, and GM's Cruise is hitting the brakes on robotaxis. Curious about the juicy details and my hot takes? Check out the full newsletter here: https://lnkd.in/dge-C7-p What do you think? Is Google's XR push too little, too late? Are robotaxis the future or a fancy pipe dream? Let's chat in the comments! 💬 #TechNews #AI #FutureOfWork #TheCompiler

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Imagine a world where the boundaries of Machine Learning are pushed beyond imagination. 🌍✨💥 A world where large-scale models like LLMs, Stable Diffusion, and Vision Transformers are optimized to their fullest potential, revolutionizing industries and changing lives. At AWS Neuron, we're not just imagining – we're making it a reality. And we want you to be a part of this extraordinary journey. As a member of our team, you'll be a trailblazer, developing and optimizing distributed training solutions for these cutting-edge models on AWS Inferentia and Trainium, cloud-scale Machine Learning accelerators. Your expertise will be instrumental in building distributed training support into PyTorch, TensorFlow with XLA, and the Neuron compiler/runtime stacks, and tuning these models for optimal performance on AWS custom silicon. But it's not just about the work – it's about the journey. You'll be part of a team that values work-life balance, mentorship, career growth, and an inclusive culture, where your ideas and contributions are celebrated. 🌟💪🏼 🌈 Together, we'll push the boundaries of what's possible and shape the future of Machine Learning. Are you ready to unleash your potential and join us on this incredible adventure? Apply now and be a part of the AWS Neuron team. #annapuralabs #neuron #AWS #MachineLearning #DistributedTraining #LLM #StableDiffusion #VisionTransformers #PyTorch #TensorFlow #CloudComputing #Innovation #CareerGrowth #InclusiveCulture https://lnkd.in/gD7dDhgb

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This is a huge development but not for everyone. An interface that is smart and can control your computer via conversational inputs is useful for a large number of people, but not for everyone. Additionally, we are bringing electronic interfaces in new areas (no physical menus but online digital menus for example). And with smart intermediaries like AI, a lot more systems can become “conversational” controlled. Code generation is perhaps the most compelling use case of GenAI and English can become the most useful DSL across applications and domains.

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Observation: 9/10 SWE's quit at “reading the docs”. Cut through the BS with this easy trick: Take action and build. Writing code is 100x easier than the docs make it sound. “Reading the docs” gave me crazy imposter syndrome: -Git -WPF -Kafka -OAuth -Angular -GraphQL -RabbitMQ -Kubernetes In ALL cases, I conquered my fears by building. Except for WPF. I gave up on that. And Kafka, that's for another day. Forcing yourself to build/code/deploy melts analysis paralysis. Then you'll say "oh that was pretty easy". Trust me, we aren't building rockets. Practice AND Study build true mastery.

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It’s no secret—I’m obsessed with humanoid robots. Why? Because they’re cool—they’re revolutionizing manufacturing, reshaping the labor force, and pushing humanity forward in ways we’re only beginning to imagine. (and maybe I just need more help in life. Obviously). Here’s what’s happening in the world of my favorite humie heroes: 🤖🚘 Figure has teamed up with BMW, putting their humanoid robots to work in auto manufacturing. 🤖 📦Agility Robotics has introduced Digit, their incredible bot that’s already lending a hand in Amazon warehouses. And of course, there’s 🤖 🎁Tesla’s Optimus, aiming to wrap our Christmas presents (or take over other tedious tasks) by 2025. This article dives deeper into these robotic trailblazers—and my favorite “humies.” Which one’s your favorite? I can't decide, but hopefully you'll weigh in.

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First blog post in a long time! I started writing a post ~2 years ago on adventures counting 130M U.S. buildings by zipcode and finally circled back to write it up properly. Everybody is a winner really, but DuckDB, Ibis, Apache Arrow, and GeoParquet were absolutely essential for getting the data into and out of all of the various engines. Give it a read and let me know what I missed! https://lnkd.in/evgVe3vD

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Come join us tomorrow in SF to learn more about the latest updates to run AI workloads on Google Cloud!

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Project update! My application tracking extension is now doing fuzzier matching and injecting new information into LinkedIn (and other sites) to keep me from doubling up on applications. Next up: local storage and bulk import/export operations...

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I've been working on scaling Reddit's re-ranking of queries in Solr using ML with the Learning to Rank plugin and we ran into some issues running it that I talk about in a new blog post "Bringing Learning to Rank to Reddit Search - Operating with Filter Queries"

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🌶🌶🌶 Hot take… Old problem: if we put more devs on the project, we can deliver it sooner. Same thinking, new manifestation: we can hire more overseas devs for less total money to produce the same result as our US staff. Flaw in that thinking: product development is not an assembly line. Devs are not “interchangeable”. Software is as much an art as it is science. It’s a team sport. The people on your team matters. #tech #staffing #management #hiring #jobs #layoffs #software #startup #teamleadership

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The difference between a decision and a data-driven decision is like the difference between a shot in the dark and a carefully aimed arrow. Which decision do you want to make?

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What does it feel like to be an engineering manager at Amazon: Since the RTO announcement it became popular to write shit about Amazon, but it's still one of the best companies around the world. A few weeks ago, Gilad Naor shared with the 'Leading Developers' readers 3 lessons from his time as an engineering manager at Amazon. Here is the first one, read the full article here: https://lnkd.in/dHBxv2Ha 𝟭. 𝗦𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝘄𝗶𝘁𝗵 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺𝘀 My first meeting at Amazon was baffling. I entered a room with about a dozen Software Development Managers (SDMs) and Product Managers (PMs). Everyone sat in silence and looked at their laptops or the printed papers they had before them. It was my second day at Amazon, and I picked up one of the extra sheets and started reading. After those first ten awkward minutes, everyone finished reading and the meeting began. Why do Amazon meetings always start this way? This is a specific example of how Amazon approaches problem-solving. It is the "Good Intentions Don't Matter" approach. In a famous internal video, Jeff Bezos talks about why good intentions are irrelevant. When things don't work, it does not matter what people wanted. All that matters is fixing the problems with mechanisms. For example, many busy managers come to meetings without first reading the prep material. They all intended to read the 6-Pager before the meeting. They just got sidetracked by the latest emergency. Scolding the managers won't solve the problem. A mechanism will. This is why all Amazon meetings start with a study period. The remaining meeting time is then spent on high-quality decision-making. Meta solves the same problem by creating cultural norms. I can't count the number of times that I heard a senior leader cut off the presenter: "Stop, assume that everyone here already read the slides. Let's get to the point." This is a culture-first approach. I have seen this work well in some teams, and not work at all in other teams. At Amazon, the solution is part of the company's "operating system". ------------------------- Anton here - by now everyone is familiar with the 6-pager concept, but that "operating system" thinking can be used almost anywhere. Think about something annoying that your developers do, and how can you solve it. For example, I remember being annoyed that people don’t update the Jira tickets. Finally, after requesting multiple times, now we just take 20 seconds from the standup to update them.

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sharpening writing skill is one of killer skill!

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